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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1608.03464
|
Alan Paris
|
Alan Paris, George Atia, Azadeh Vosoughi, Stephen Berman
|
A New Statistical Model of Electroencephalogram Noise Spectra for
Real-time Brain-Computer Interfaces
|
Revised submission to IEEE EMBS Trans. Biomed. Eng. 12 pages, 9
figures
| null |
10.1109/TBME.2016.2606595
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
$Objective$: A characteristic of neurological signal processing is high
levels of noise from sub-cellular ion channels up to whole-brain processes. In
this paper, we propose a new model of electroencephalogram (EEG) background
periodograms, based on a family of functions which we call generalized van der
Ziel--McWhorter (GVZM) power spectral densities (PSDs). To the best of our
knowledge, the GVZM PSD function is the only EEG noise model which has
relatively few parameters, matches recorded EEG PSD's with high accuracy from 0
Hz to over 30 Hz, and has approximately $1/f^\theta$ behavior in the
mid-frequencies without infinities. $Methods$: We validate this model using
three approaches. First, we show how GVZM PSDs can arise in population of ion
channels in maximum entropy equilibrium. Second, we present a class of mixed
autoregressive models, which simulate brain background noise and whose
periodograms are asymptotic to the GVZM PSD. Third, we present two real-time
estimation algorithms for steady-state visual evoked potential (SSVEP)
frequencies, and analyze their performance statistically. $Results$: In
pairwise comparisons, the GVZM-based algorithms showed statistically
significant accuracy improvement over two well-known and widely-used SSVEP
estimators. $Conclusion$: The GVZM noise model can be a useful and reliable
technique for EEG signal processing. $Significance$: Understanding EEG noise is
essential for EEG-based neurology and applications such as real-time
brain-computer interfaces (BCIs), which must make accurate control decisions
from very short data epochs. The GVZM approach represents a successful new
paradigm for understanding and managing this neurological noise.
|
[
{
"created": "Sun, 24 Jul 2016 06:36:59 GMT",
"version": "v1"
}
] |
2016-11-17
|
[
[
"Paris",
"Alan",
""
],
[
"Atia",
"George",
""
],
[
"Vosoughi",
"Azadeh",
""
],
[
"Berman",
"Stephen",
""
]
] |
$Objective$: A characteristic of neurological signal processing is high levels of noise from sub-cellular ion channels up to whole-brain processes. In this paper, we propose a new model of electroencephalogram (EEG) background periodograms, based on a family of functions which we call generalized van der Ziel--McWhorter (GVZM) power spectral densities (PSDs). To the best of our knowledge, the GVZM PSD function is the only EEG noise model which has relatively few parameters, matches recorded EEG PSD's with high accuracy from 0 Hz to over 30 Hz, and has approximately $1/f^\theta$ behavior in the mid-frequencies without infinities. $Methods$: We validate this model using three approaches. First, we show how GVZM PSDs can arise in population of ion channels in maximum entropy equilibrium. Second, we present a class of mixed autoregressive models, which simulate brain background noise and whose periodograms are asymptotic to the GVZM PSD. Third, we present two real-time estimation algorithms for steady-state visual evoked potential (SSVEP) frequencies, and analyze their performance statistically. $Results$: In pairwise comparisons, the GVZM-based algorithms showed statistically significant accuracy improvement over two well-known and widely-used SSVEP estimators. $Conclusion$: The GVZM noise model can be a useful and reliable technique for EEG signal processing. $Significance$: Understanding EEG noise is essential for EEG-based neurology and applications such as real-time brain-computer interfaces (BCIs), which must make accurate control decisions from very short data epochs. The GVZM approach represents a successful new paradigm for understanding and managing this neurological noise.
|
1510.03224
|
Matteo Figliuzzi
|
Matteo Figliuzzi, Herv\'e Jacquier, Alexander Schug, Olivier
Tenaillon, Martin Weigt
|
Coevolutionary landscape inference and the context-dependence of
mutations in beta-lactamase TEM-1
|
14 pages, 5 figures. Supplementary files on the publisher's website:
http://mbe.oxfordjournals.org/content/early/2015/10/06/molbev.msv211.short?rss=1
|
Mol Biol Evol (2015) doi: 10.1093/molbev/msv211
|
10.1093/molbev/msv211
| null |
q-bio.QM cond-mat.stat-mech q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The quantitative characterization of mutational landscapes is a task of
outstanding importance in evolutionary and medical biology: It is, e.g., of
central importance for our understanding of the phenotypic effect of mutations
related to disease and antibiotic drug resistance. Here we develop a novel
inference scheme for mutational landscapes, which is based on the statistical
analysis of large alignments of homologs of the protein of interest. Our method
is able to capture epistatic couplings between residues, and therefore to
assess the dependence of mutational effects on the sequence context where they
appear. Compared to recent large-scale mutagenesis data of the beta-lactamase
TEM-1, a protein providing resistance against beta-lactam antibiotics, our
method leads to an increase of about 40% in explicative power as compared to
approaches neglecting epistasis. We find that the informative sequence context
extends to residues at native distances of about 20{\AA} from the mutated site,
reaching thus far beyond residues in direct physical contact.
|
[
{
"created": "Mon, 12 Oct 2015 11:05:22 GMT",
"version": "v1"
}
] |
2015-10-13
|
[
[
"Figliuzzi",
"Matteo",
""
],
[
"Jacquier",
"Hervé",
""
],
[
"Schug",
"Alexander",
""
],
[
"Tenaillon",
"Olivier",
""
],
[
"Weigt",
"Martin",
""
]
] |
The quantitative characterization of mutational landscapes is a task of outstanding importance in evolutionary and medical biology: It is, e.g., of central importance for our understanding of the phenotypic effect of mutations related to disease and antibiotic drug resistance. Here we develop a novel inference scheme for mutational landscapes, which is based on the statistical analysis of large alignments of homologs of the protein of interest. Our method is able to capture epistatic couplings between residues, and therefore to assess the dependence of mutational effects on the sequence context where they appear. Compared to recent large-scale mutagenesis data of the beta-lactamase TEM-1, a protein providing resistance against beta-lactam antibiotics, our method leads to an increase of about 40% in explicative power as compared to approaches neglecting epistasis. We find that the informative sequence context extends to residues at native distances of about 20{\AA} from the mutated site, reaching thus far beyond residues in direct physical contact.
|
0902.2404
|
Eugene Shakhnovich
|
Muyoung Heo, Louis Kang and Eugene Shakhnovich
|
Adaptation through stochastic switching into transient mutators in
finite asexual populations
| null | null | null | null |
q-bio.BM q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The importance of mutator clones in the adaptive evolution of asexual
populations is not fully understood. Here we address this problem by using an
ab initio microscopic model of living cells, whose fitness is derived directly
from their genomes using a biophysically realistic model of protein folding and
interactions in the cytoplasm. The model organisms contain replication
controlling genes (DCGs) and genes modeling the mismatch repair (MMR)
complexes. We find that adaptation occurs through the transient fixation of a
mutator phenotype, regardless of particular perturbations in the fitness
landscape. The microscopic pathway of adaptation follows a well-defined set of
events: stochastic switching to the mutator phenotype first, then mutation in
the MMR complex that hitchhikes with a beneficial mutation in the DCGs, and
finally a compensating mutation in the MMR complex returning the population to
a non-mutator phenotype. Similarity of these results to reported adaptation
events points out to robust universal physical principles of evolutionary
adaptation.
|
[
{
"created": "Fri, 13 Feb 2009 22:10:40 GMT",
"version": "v1"
}
] |
2009-02-17
|
[
[
"Heo",
"Muyoung",
""
],
[
"Kang",
"Louis",
""
],
[
"Shakhnovich",
"Eugene",
""
]
] |
The importance of mutator clones in the adaptive evolution of asexual populations is not fully understood. Here we address this problem by using an ab initio microscopic model of living cells, whose fitness is derived directly from their genomes using a biophysically realistic model of protein folding and interactions in the cytoplasm. The model organisms contain replication controlling genes (DCGs) and genes modeling the mismatch repair (MMR) complexes. We find that adaptation occurs through the transient fixation of a mutator phenotype, regardless of particular perturbations in the fitness landscape. The microscopic pathway of adaptation follows a well-defined set of events: stochastic switching to the mutator phenotype first, then mutation in the MMR complex that hitchhikes with a beneficial mutation in the DCGs, and finally a compensating mutation in the MMR complex returning the population to a non-mutator phenotype. Similarity of these results to reported adaptation events points out to robust universal physical principles of evolutionary adaptation.
|
2006.12536
|
Yannick Tchaptchie Kouakep
|
S. Y. Tchoumi, Y. T. Kouakep, D. J. Fotsa Mbogne, J. C. Kamgang, J. M.
Tchuenche
|
Optimal Control of a Malaria Model with Long-Lasting Insecticide-Treated
Nets
|
Submitted to a scientific journal
| null | null | null |
q-bio.PE math.AP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A deterministic multi-stage malaria model with a non-therapeutic control
measure, the use of mosquito bednet is formulated and analyzed. The model basic
reproduction number is derived, and analytical results show that the models
equilibria are locally and globally asymptotically stable when certain
threshold conditions are satisfied. Pontryagin's Maximum Principle with respect
to a time dependent constant is used to derive the necessary conditions for the
optimal usage of the Long-Lasting Insecticide-treated bednets(LLINs) to
mitigate the malaria transmission dynamics. This is accomplished by introducing
biologically admissible control and e-approximate sub-optimal control. The
results from this study could help public health planners and policy
decision-makers to design reachable and more practical malaria prevention
programs "close" to the optimal strategy.
|
[
{
"created": "Mon, 22 Jun 2020 18:06:57 GMT",
"version": "v1"
},
{
"created": "Sat, 18 Jul 2020 11:11:11 GMT",
"version": "v2"
}
] |
2020-07-21
|
[
[
"Tchoumi",
"S. Y.",
""
],
[
"Kouakep",
"Y. T.",
""
],
[
"Mbogne",
"D. J. Fotsa",
""
],
[
"Kamgang",
"J. C.",
""
],
[
"Tchuenche",
"J. M.",
""
]
] |
A deterministic multi-stage malaria model with a non-therapeutic control measure, the use of mosquito bednet is formulated and analyzed. The model basic reproduction number is derived, and analytical results show that the models equilibria are locally and globally asymptotically stable when certain threshold conditions are satisfied. Pontryagin's Maximum Principle with respect to a time dependent constant is used to derive the necessary conditions for the optimal usage of the Long-Lasting Insecticide-treated bednets(LLINs) to mitigate the malaria transmission dynamics. This is accomplished by introducing biologically admissible control and e-approximate sub-optimal control. The results from this study could help public health planners and policy decision-makers to design reachable and more practical malaria prevention programs "close" to the optimal strategy.
|
0906.5028
|
Mari Watanabe
|
Tomofumi Kimotsuki (Saint Louis University), Noriko Niwa (Washington
Univ. St. Louis), Martin N. Hicks (Glasgow University), Michael Dunne
(Glasgow University), Stuart M. Cobbe (Glasgow University), Mari A. Watanabe
(Saint Louis University)
|
Isoprenaline increases Excursive Restitution Slope in the Conscious
Rabbit with Ischaemic Heart Failure
|
27 pages
| null | null | null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Background: An increased QT/RR slope is hypothesized to be predictive of
sudden cardiac death after myocardial infarction. Previous studies have shown
that beta-adrenergic stimulation increases QT/RR slope, but the effects of
beta-adrenergic stimulation on QT/RR slope in heart failure are unknown.
Methods: New Zealand White rabbits underwent coronary ligation (n=15) or sham
surgery (n=11), and implantation of a pediatric pacemaker lead in the right
ventricle for chronic ECG recording. Eight weeks after surgery, unsedated
rabbits were given intravenous administrations of 0.25 to 2.0 ml of 1
micromol/l isoprenaline, while peak QRS to QRS (RR) and Q to T peak (QT)
intervals were measured. Results: Ligated rabbits (n=6) had lower LVEF than
sham rabbits (n=7, p<.0001), but similar baseline RR (269 +/- 15 vs 292 +/- 23
ms, p=.07), QT (104 +/- 17 vs 91 +/- 9 ms, p=.1) and minimum RR (204 +/- 11 vs
208 +/- 6 ms, p=.4) intervals induced by isoprenaline (0.79 +/- 0.18 vs 0.73
+/- 0.14 ml, p=.6). Hysteresis in QT vs TQ interval plots displayed biphasic
restitution and regions of negative slope. The slope of the positive slope
region was >1 in ligated rabbits (1.27 +/- 0.66) and <1 in sham rabbits (0.35
+/- 0.14, p=.004). Absolute value of the negative slope was greater in ligated
rabbits (-0.81 +/- 0.52 vs -0.35 +/- 0.14, p=.04). Conclusion: Ischaemic heart
failure produces steeper restitution slopes during beta-adrenergically induced
QT/TQ hysteresis. This could underlie the propensity of failing hearts to
arrhythmias.
|
[
{
"created": "Sat, 27 Jun 2009 02:31:20 GMT",
"version": "v1"
}
] |
2009-06-30
|
[
[
"Kimotsuki",
"Tomofumi",
"",
"Saint Louis University"
],
[
"Niwa",
"Noriko",
"",
"Washington\n Univ. St. Louis"
],
[
"Hicks",
"Martin N.",
"",
"Glasgow University"
],
[
"Dunne",
"Michael",
"",
"Glasgow University"
],
[
"Cobbe",
"Stuart M.",
"",
"Glasgow University"
],
[
"Watanabe",
"Mari A.",
"",
"Saint Louis University"
]
] |
Background: An increased QT/RR slope is hypothesized to be predictive of sudden cardiac death after myocardial infarction. Previous studies have shown that beta-adrenergic stimulation increases QT/RR slope, but the effects of beta-adrenergic stimulation on QT/RR slope in heart failure are unknown. Methods: New Zealand White rabbits underwent coronary ligation (n=15) or sham surgery (n=11), and implantation of a pediatric pacemaker lead in the right ventricle for chronic ECG recording. Eight weeks after surgery, unsedated rabbits were given intravenous administrations of 0.25 to 2.0 ml of 1 micromol/l isoprenaline, while peak QRS to QRS (RR) and Q to T peak (QT) intervals were measured. Results: Ligated rabbits (n=6) had lower LVEF than sham rabbits (n=7, p<.0001), but similar baseline RR (269 +/- 15 vs 292 +/- 23 ms, p=.07), QT (104 +/- 17 vs 91 +/- 9 ms, p=.1) and minimum RR (204 +/- 11 vs 208 +/- 6 ms, p=.4) intervals induced by isoprenaline (0.79 +/- 0.18 vs 0.73 +/- 0.14 ml, p=.6). Hysteresis in QT vs TQ interval plots displayed biphasic restitution and regions of negative slope. The slope of the positive slope region was >1 in ligated rabbits (1.27 +/- 0.66) and <1 in sham rabbits (0.35 +/- 0.14, p=.004). Absolute value of the negative slope was greater in ligated rabbits (-0.81 +/- 0.52 vs -0.35 +/- 0.14, p=.04). Conclusion: Ischaemic heart failure produces steeper restitution slopes during beta-adrenergically induced QT/TQ hysteresis. This could underlie the propensity of failing hearts to arrhythmias.
|
1301.7254
|
Michael B\"orsch
|
Nawid Zarrabi, Caterina Clausen, Monika G. Dueser, Michael Boersch
|
Manipulating freely diffusing single 20-nm particles in an Anti-Brownian
Electrokinetic Trap (ABELtrap)
|
11 pages, 6 figures
| null |
10.1117/12.2002952
| null |
q-bio.QM physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Conformational changes of individual fluorescently labeled proteins can be
followed in solution using a confocal microscope. Two fluorophores attached to
selected domains of the protein report fluctuating conformations. Based on
F\"orster resonance energy transfer (FRET) between these fluorophores on a
single protein, sequential distance changes between the dyes provide the real
time trajectories of protein conformations. However, observation times are
limited for freely diffusing biomolecules by Brownian motion through the
confocal detection volume. A. E. Cohen and W. E. Moerner have invented and
built microfluidic devices with 4 electrodes for an Anti-Brownian
Electrokinetic Trap (ABELtrap). Here we present an ABELtrap based on a laser
focus pattern generated by a pair of acousto-optical beam deflectors and
controlled by a programmable FPGA chip. Fluorescent 20-nm beads in solution
were used to mimic freely diffusing large proteins like solubilized FoF1-ATP
synthase. The ABELtrap could hold these nanobeads for about 10 seconds at the
given position. Thereby, observation times of a single particle were increased
by a factor of 1000.
|
[
{
"created": "Wed, 30 Jan 2013 15:22:13 GMT",
"version": "v1"
}
] |
2015-06-12
|
[
[
"Zarrabi",
"Nawid",
""
],
[
"Clausen",
"Caterina",
""
],
[
"Dueser",
"Monika G.",
""
],
[
"Boersch",
"Michael",
""
]
] |
Conformational changes of individual fluorescently labeled proteins can be followed in solution using a confocal microscope. Two fluorophores attached to selected domains of the protein report fluctuating conformations. Based on F\"orster resonance energy transfer (FRET) between these fluorophores on a single protein, sequential distance changes between the dyes provide the real time trajectories of protein conformations. However, observation times are limited for freely diffusing biomolecules by Brownian motion through the confocal detection volume. A. E. Cohen and W. E. Moerner have invented and built microfluidic devices with 4 electrodes for an Anti-Brownian Electrokinetic Trap (ABELtrap). Here we present an ABELtrap based on a laser focus pattern generated by a pair of acousto-optical beam deflectors and controlled by a programmable FPGA chip. Fluorescent 20-nm beads in solution were used to mimic freely diffusing large proteins like solubilized FoF1-ATP synthase. The ABELtrap could hold these nanobeads for about 10 seconds at the given position. Thereby, observation times of a single particle were increased by a factor of 1000.
|
0911.0215
|
Manuel Rivas
|
Manuel A. Rivas, Mark J. Daly, Itsik Pe'er
|
Age, Sex, and Genetic Architecture of Human Gene Expression in EBV
Transformed Cell Lines
|
27 pages, 3 figures
| null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Individual expression profiles from EBV transformed cell lines are an
emerging resource for genomic investigation. In this study we characterize the
effects of age, sex, and genetic variation on gene expression by surveying
public datasets of such profiles. We establish that the expression space of
cell lines maintains genetic as well as non-germline information, in an
individual-specific and cross-tissue manner. Age of donor is associated with
the expression of 949 genes in the derived cell line. Age-associated genes
include over-representation of immune-related genes, specifically MHC Class I
genes, a phenomenon that replicates across tissues and organisms. Sex
associated genes in these cell lines include likely candidates, such as genes
that escape X-inactivation,testis specific expressed genes, androgen and
estrogen specific genes, but also gene families previously unknown to be sex
associated such as common microRNA targets (MIR-490, V_ARP1_01, MIR-489).
Finally, we report 494 transcripts whose expression levels are associated with
a genetic variant in cis, overlapping and validating previous reports.
Incorporating age in analysis of association facilitates additional discovery
of trans-acting regulatory genetic variants. Our findings promote expression
profiling of transformed cell lines as a vehicle for understanding cellular
systems beyond the specific lines.
|
[
{
"created": "Sun, 1 Nov 2009 23:17:06 GMT",
"version": "v1"
}
] |
2009-11-03
|
[
[
"Rivas",
"Manuel A.",
""
],
[
"Daly",
"Mark J.",
""
],
[
"Pe'er",
"Itsik",
""
]
] |
Individual expression profiles from EBV transformed cell lines are an emerging resource for genomic investigation. In this study we characterize the effects of age, sex, and genetic variation on gene expression by surveying public datasets of such profiles. We establish that the expression space of cell lines maintains genetic as well as non-germline information, in an individual-specific and cross-tissue manner. Age of donor is associated with the expression of 949 genes in the derived cell line. Age-associated genes include over-representation of immune-related genes, specifically MHC Class I genes, a phenomenon that replicates across tissues and organisms. Sex associated genes in these cell lines include likely candidates, such as genes that escape X-inactivation,testis specific expressed genes, androgen and estrogen specific genes, but also gene families previously unknown to be sex associated such as common microRNA targets (MIR-490, V_ARP1_01, MIR-489). Finally, we report 494 transcripts whose expression levels are associated with a genetic variant in cis, overlapping and validating previous reports. Incorporating age in analysis of association facilitates additional discovery of trans-acting regulatory genetic variants. Our findings promote expression profiling of transformed cell lines as a vehicle for understanding cellular systems beyond the specific lines.
|
1305.7411
|
Jiapu Zhang
|
Jiapu Zhang
|
The Methicillin-Resistant Staphylococcus Aureus Infection Controls
| null |
Journal Review of Bioinformatics and Biometrics (RBB) 2(4),
pp.83-87 (2013)
| null | null |
q-bio.OT
|
http://creativecommons.org/licenses/by-nc-sa/3.0/
|
Multi-resistant organisms (MROs), the bacteria that are resistant to a number
of different antibiotics, have been very popular around the world in recent
years. They are very difficult to treat but highly infectious in humans. MRSA
(Methicillin-Resistant Staphylococcus Aureus) is one of the MROs. It is
believed that in 2007 more people died of MRSA than of AIDS worldwide. In
Australia "there are about 2000 people per year who have a bloodstream
infection with the MRSA germ and the vast majority of those get them from
health care procedure" (Nader, 2005). It is acknowledged as a significant
challenge to Australian hospitals for MRSA infection control. Nursing
professionals are in urgent need of the study of MRSA nosocomial infection
controls. This review provides insight into the hand washing and isolation
infection-control strategies for MRSA. The important technologies on those two
aspects worldwide are well surveyed, compared, contrasted, and discussed. The
review is to do a complete survey on the hand washing and isolation
technologies of infection controls for MRSA and try to provide some possible
recommendations for Australian hospitals.
|
[
{
"created": "Thu, 30 May 2013 12:33:57 GMT",
"version": "v1"
}
] |
2013-12-09
|
[
[
"Zhang",
"Jiapu",
""
]
] |
Multi-resistant organisms (MROs), the bacteria that are resistant to a number of different antibiotics, have been very popular around the world in recent years. They are very difficult to treat but highly infectious in humans. MRSA (Methicillin-Resistant Staphylococcus Aureus) is one of the MROs. It is believed that in 2007 more people died of MRSA than of AIDS worldwide. In Australia "there are about 2000 people per year who have a bloodstream infection with the MRSA germ and the vast majority of those get them from health care procedure" (Nader, 2005). It is acknowledged as a significant challenge to Australian hospitals for MRSA infection control. Nursing professionals are in urgent need of the study of MRSA nosocomial infection controls. This review provides insight into the hand washing and isolation infection-control strategies for MRSA. The important technologies on those two aspects worldwide are well surveyed, compared, contrasted, and discussed. The review is to do a complete survey on the hand washing and isolation technologies of infection controls for MRSA and try to provide some possible recommendations for Australian hospitals.
|
1509.02816
|
John Platig
|
John Platig, Peter Castaldi, Dawn DeMeo, and John Quackenbush
|
Bipartite Community Structure of eQTLs
| null | null |
10.1371/journal.pcbi.1005033
| null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Genome Wide Association Studies (GWAS) and eQTL analyses have produced a
large and growing number of genetic associations linked to a wide range of
human phenotypes. As of 2013, there were more than 11,000 SNPs associated with
a trait as reported in the NHGRI GWAS Catalog. However, interpreting the
functional roles played by these SNPs remains a challenge. Here we describe an
approach that uses the inherent bipartite structure of eQTL networks to place
SNPs into a functional context.
Using genotyping and gene expression data from 163 lung tissue samples in a
study of Chronic Obstructive Pulmonary Disease (COPD) we calculated eQTL
associations between SNPs and genes and cast significant associations (FDR $<
0.1$) as links in a bipartite network. To our surprise, we discovered that the
highly-connected "hub" SNPs within the network were devoid of
disease-associations. However, within the network we identified 35 highly
modular communities, which comprise groups of SNPs associated with groups of
genes; 13 of these communities were significantly enriched for distinct
biological functions (P $ < 5 \times 10^{-4}$) including COPD-related
functions. Further, we found that GWAS-significant SNPs were enriched at the
cores of these communities, including previously identified GWAS associations
for COPD, asthma, and pulmonary function, among others. These results speak to
our intuition: rather than single SNPs influencing single genes, we see groups
of SNPs associated with the expression of families of functionally related
genes and that disease SNPs are associated with the perturbation of those
functions. These methods are not limited in their application to COPD and can
be used in the analysis of a wide variety of disease processes and other
phenotypic traits.
|
[
{
"created": "Wed, 9 Sep 2015 15:52:09 GMT",
"version": "v1"
}
] |
2016-09-28
|
[
[
"Platig",
"John",
""
],
[
"Castaldi",
"Peter",
""
],
[
"DeMeo",
"Dawn",
""
],
[
"Quackenbush",
"John",
""
]
] |
Genome Wide Association Studies (GWAS) and eQTL analyses have produced a large and growing number of genetic associations linked to a wide range of human phenotypes. As of 2013, there were more than 11,000 SNPs associated with a trait as reported in the NHGRI GWAS Catalog. However, interpreting the functional roles played by these SNPs remains a challenge. Here we describe an approach that uses the inherent bipartite structure of eQTL networks to place SNPs into a functional context. Using genotyping and gene expression data from 163 lung tissue samples in a study of Chronic Obstructive Pulmonary Disease (COPD) we calculated eQTL associations between SNPs and genes and cast significant associations (FDR $< 0.1$) as links in a bipartite network. To our surprise, we discovered that the highly-connected "hub" SNPs within the network were devoid of disease-associations. However, within the network we identified 35 highly modular communities, which comprise groups of SNPs associated with groups of genes; 13 of these communities were significantly enriched for distinct biological functions (P $ < 5 \times 10^{-4}$) including COPD-related functions. Further, we found that GWAS-significant SNPs were enriched at the cores of these communities, including previously identified GWAS associations for COPD, asthma, and pulmonary function, among others. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.
|
1508.00613
|
Maria Kochugaeva
|
Martin Lange, Maria Kochugaeva and Anatoly B. Kolomeisky
|
Protein search for multiple targets on DNA
| null | null |
10.1063/1.4930113
| null |
q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Protein-DNA interactions are crucial for all biological processes. One of the
most important fundamental aspects of these interactions is the process of
protein searching and recognizing specific binding sites on DNA. A large number
of experimental and theoretical investigations have been devoted to uncovering
the molecular description of these phenomena, but many aspects of the
mechanisms of protein search for the targets on DNA remain not well understood.
One of the most intriguing problems is the role of multiple targets in protein
search dynamics. Using a recently developed theoretical framework we analyze
this question in detail. Our method is based on a discrete-state stochastic
approach that takes into account most relevant physical-chemical processes and
leads to fully analytical description of all dynamic properties. Specifically,
systems with two and three targets have been explicitly investigated. It is
found that multiple targets in most cases accelerate the search in comparison
with a single target situation. However, the acceleration is not always
proportional to the number of targets. Surprisingly, there are even situations
when it takes longer to find one of the multiple targets in comparison with the
single target. It depends on the spatial position of the targets, distances
between them, average scanning lengths of protein molecules on DNA, and the
total DNA lengths. Physical-chemical explanations of observed results are
presented. Our predictions are compared with experimental observations as well
as with results from a continuum theory for the protein search. Extensive Monte
Carlo computer simulations fully support our theoretical calculations.
|
[
{
"created": "Mon, 3 Aug 2015 22:21:11 GMT",
"version": "v1"
}
] |
2015-09-30
|
[
[
"Lange",
"Martin",
""
],
[
"Kochugaeva",
"Maria",
""
],
[
"Kolomeisky",
"Anatoly B.",
""
]
] |
Protein-DNA interactions are crucial for all biological processes. One of the most important fundamental aspects of these interactions is the process of protein searching and recognizing specific binding sites on DNA. A large number of experimental and theoretical investigations have been devoted to uncovering the molecular description of these phenomena, but many aspects of the mechanisms of protein search for the targets on DNA remain not well understood. One of the most intriguing problems is the role of multiple targets in protein search dynamics. Using a recently developed theoretical framework we analyze this question in detail. Our method is based on a discrete-state stochastic approach that takes into account most relevant physical-chemical processes and leads to fully analytical description of all dynamic properties. Specifically, systems with two and three targets have been explicitly investigated. It is found that multiple targets in most cases accelerate the search in comparison with a single target situation. However, the acceleration is not always proportional to the number of targets. Surprisingly, there are even situations when it takes longer to find one of the multiple targets in comparison with the single target. It depends on the spatial position of the targets, distances between them, average scanning lengths of protein molecules on DNA, and the total DNA lengths. Physical-chemical explanations of observed results are presented. Our predictions are compared with experimental observations as well as with results from a continuum theory for the protein search. Extensive Monte Carlo computer simulations fully support our theoretical calculations.
|
q-bio/0603036
|
Otger Camp\`as
|
Otger Campas, Jaume Casademunt, Ignacio Pagonabarraga
|
Dynamic stability of spindles controlled by molecular motor kinetics
|
4 pages, 3 figures
| null | null | null |
q-bio.SC physics.bio-ph
| null |
We analyze the role of the force-dependent kinetics of motor proteins in the
stability of antiparallel arrays of polar filaments, such as those in the
mitotic spindle. We determine the possible stable structures and show that
there exists an instability associated to the collective behavior of motors
that leads to the collapse of the spindle. Our analysis provides a general
framework to understand several experimental observations in eukaryotic cell
division.
|
[
{
"created": "Thu, 30 Mar 2006 19:11:43 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Campas",
"Otger",
""
],
[
"Casademunt",
"Jaume",
""
],
[
"Pagonabarraga",
"Ignacio",
""
]
] |
We analyze the role of the force-dependent kinetics of motor proteins in the stability of antiparallel arrays of polar filaments, such as those in the mitotic spindle. We determine the possible stable structures and show that there exists an instability associated to the collective behavior of motors that leads to the collapse of the spindle. Our analysis provides a general framework to understand several experimental observations in eukaryotic cell division.
|
1401.6207
|
Huisheng Liu
|
Huisheng Liu, Hua Bai, Enfu Hui, Lu Yang, Chantell Evans, Zhao Wang,
Sung Kwon, and Edwin Chapman
|
Synaptotagmin 7 Functions as a Ca2+-sensor for Synaptic Vesicle
Replenishment
|
41 pages, 17 Figures
| null |
10.7554/eLife.01524
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Synaptotagmin (syt) 7 is one of three syt isoforms found in all metazoans; it
is ubiquitously expressed, yet its function in neurons remains obscure. Here,
we resolved Ca2+-dependent and Ca2+-independent synaptic vesicle (SV)
replenishment pathways, and found that syt 7 plays a selective and critical
role in the Ca2+-dependent pathway. Mutations that disrupt Ca2+-binding to syt
7 abolish this function, suggesting that syt 7 functions as a Ca2+-sensor for
replenishment. The Ca2+-binding protein calmodulin (CaM) has also been
implicated in SV replenishment, and we found that loss of syt 7 was phenocopied
by a CaM antagonist. Moreover, we discovered that syt 7 binds to CaM in a
highly specific and Ca2+-dependent manner; this interaction requires intact
Ca2+-binding sites within syt 7. Together, these data indicate that a complex
of two conserved Ca2+-binding proteins, syt 7 and CaM, serve as a key regulator
of SV replenishment in presynaptic nerve terminals.
|
[
{
"created": "Thu, 23 Jan 2014 22:48:27 GMT",
"version": "v1"
}
] |
2014-01-27
|
[
[
"Liu",
"Huisheng",
""
],
[
"Bai",
"Hua",
""
],
[
"Hui",
"Enfu",
""
],
[
"Yang",
"Lu",
""
],
[
"Evans",
"Chantell",
""
],
[
"Wang",
"Zhao",
""
],
[
"Kwon",
"Sung",
""
],
[
"Chapman",
"Edwin",
""
]
] |
Synaptotagmin (syt) 7 is one of three syt isoforms found in all metazoans; it is ubiquitously expressed, yet its function in neurons remains obscure. Here, we resolved Ca2+-dependent and Ca2+-independent synaptic vesicle (SV) replenishment pathways, and found that syt 7 plays a selective and critical role in the Ca2+-dependent pathway. Mutations that disrupt Ca2+-binding to syt 7 abolish this function, suggesting that syt 7 functions as a Ca2+-sensor for replenishment. The Ca2+-binding protein calmodulin (CaM) has also been implicated in SV replenishment, and we found that loss of syt 7 was phenocopied by a CaM antagonist. Moreover, we discovered that syt 7 binds to CaM in a highly specific and Ca2+-dependent manner; this interaction requires intact Ca2+-binding sites within syt 7. Together, these data indicate that a complex of two conserved Ca2+-binding proteins, syt 7 and CaM, serve as a key regulator of SV replenishment in presynaptic nerve terminals.
|
2104.02881
|
Seung Ki Baek
|
Sanghun Lee, Yohsuke Murase, and Seung Ki Baek
|
Local stability of cooperation in a continuous model of indirect
reciprocity
|
13 pages, 3 figures
|
Sci. Rep. 11, 14225 (2021)
|
10.1038/s41598-021-93598-7
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Reputation is a powerful mechanism to enforce cooperation among unrelated
individuals through indirect reciprocity, but it suffers from disagreement
originating from private assessment, noise, and incomplete information. In this
work, we investigate stability of cooperation in the donation game by regarding
each player's reputation and behaviour as continuous variables. Through
perturbative calculation, we derive a condition that a social norm should
satisfy to give penalties to its close variants, provided that everyone
initially cooperates with a good reputation, and this result is supported by
numerical simulation. A crucial factor of the condition is whether a
well-reputed player's donation to an ill-reputed co-player is appreciated by
other members of the society, and the condition can be reduced to a threshold
for the benefit-cost ratio of cooperation which depends on the reputational
sensitivity to a donor's behaviour as well as on the behavioural sensitivity to
a recipient's reputation. Our continuum formulation suggests how indirect
reciprocity can work beyond the dichotomy between good and bad even in the
presence of inhomogeneity, noise, and incomplete information.
|
[
{
"created": "Wed, 7 Apr 2021 03:14:22 GMT",
"version": "v1"
},
{
"created": "Fri, 9 Jul 2021 13:18:57 GMT",
"version": "v2"
}
] |
2021-07-12
|
[
[
"Lee",
"Sanghun",
""
],
[
"Murase",
"Yohsuke",
""
],
[
"Baek",
"Seung Ki",
""
]
] |
Reputation is a powerful mechanism to enforce cooperation among unrelated individuals through indirect reciprocity, but it suffers from disagreement originating from private assessment, noise, and incomplete information. In this work, we investigate stability of cooperation in the donation game by regarding each player's reputation and behaviour as continuous variables. Through perturbative calculation, we derive a condition that a social norm should satisfy to give penalties to its close variants, provided that everyone initially cooperates with a good reputation, and this result is supported by numerical simulation. A crucial factor of the condition is whether a well-reputed player's donation to an ill-reputed co-player is appreciated by other members of the society, and the condition can be reduced to a threshold for the benefit-cost ratio of cooperation which depends on the reputational sensitivity to a donor's behaviour as well as on the behavioural sensitivity to a recipient's reputation. Our continuum formulation suggests how indirect reciprocity can work beyond the dichotomy between good and bad even in the presence of inhomogeneity, noise, and incomplete information.
|
2307.00253
|
Rahul Biswas
|
Rahul Biswas and SuryaNarayana Sripada
|
Application of Time-Aware PC algorithm to compute Causal Functional
Connectivity in Alzheimer's Disease from fMRI data
| null | null | null | null |
q-bio.NC q-bio.QM stat.AP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Functional Connectivity between brain regions is known to be altered in
Alzheimer's disease, and promises to be a biomarker for early diagnosis of the
disease. While several approaches for functional connectivity obtain an
un-directed network representing stochastic associations (correlations) between
brain regions, association does not necessarily imply causation. In contrast,
Causal Functional Connectivity is more informative, providing a directed
network representing causal relationships between brain regions. In this paper,
we obtained the causal functional connectome for the whole brain from
recordings of resting-state functional magnetic resonance imaging (rs-fMRI) for
subjects from three clinical groups: cognitively normal, mild cognitive
impairment, and Alzheimer's disease. We applied the recently developed
Time-aware PC (TPC) algorithm to infer the causal functional connectome for the
whole brain. TPC supports model-free estimation of whole brain causal
functional connectivity based on directed graphical modeling in a time series
setting. We then perform an exploratory analysis to identify the causal brain
connections between brain regions which have altered strengths between pairs of
subject groups, and over the three subject groups, based on edge-wise p-values
from statistical tests. We used the altered causal brain connections thus
obtained to compile a comprehensive list of brain regions impacted by
Alzheimer's disease according to the current data set. The brain regions thus
identified are found to be in agreement with literature on brain regions
impacted by Alzheimer's disease, published by researchers from clinical/medical
institutions.
|
[
{
"created": "Sat, 1 Jul 2023 07:20:04 GMT",
"version": "v1"
},
{
"created": "Tue, 20 Feb 2024 00:18:19 GMT",
"version": "v2"
}
] |
2024-02-21
|
[
[
"Biswas",
"Rahul",
""
],
[
"Sripada",
"SuryaNarayana",
""
]
] |
Functional Connectivity between brain regions is known to be altered in Alzheimer's disease, and promises to be a biomarker for early diagnosis of the disease. While several approaches for functional connectivity obtain an un-directed network representing stochastic associations (correlations) between brain regions, association does not necessarily imply causation. In contrast, Causal Functional Connectivity is more informative, providing a directed network representing causal relationships between brain regions. In this paper, we obtained the causal functional connectome for the whole brain from recordings of resting-state functional magnetic resonance imaging (rs-fMRI) for subjects from three clinical groups: cognitively normal, mild cognitive impairment, and Alzheimer's disease. We applied the recently developed Time-aware PC (TPC) algorithm to infer the causal functional connectome for the whole brain. TPC supports model-free estimation of whole brain causal functional connectivity based on directed graphical modeling in a time series setting. We then perform an exploratory analysis to identify the causal brain connections between brain regions which have altered strengths between pairs of subject groups, and over the three subject groups, based on edge-wise p-values from statistical tests. We used the altered causal brain connections thus obtained to compile a comprehensive list of brain regions impacted by Alzheimer's disease according to the current data set. The brain regions thus identified are found to be in agreement with literature on brain regions impacted by Alzheimer's disease, published by researchers from clinical/medical institutions.
|
q-bio/0603021
|
Ovidiu Radulescu
|
O.Radulescu, A.Siegel, E. Pecou, and S.Lagarrigue
|
A model for regulated fatty acid metabolism in liver; equilibria and
their changes
| null | null | null | null |
q-bio.CB
| null |
We build a model for the hepatic fatty acid metabolism and its metabolic and
genetic regulations. The model has two functioning modes: synthesis and
oxidation of fatty acids. We provide a sufficient condition (the strong
lipolytic condition) for the uniqueness of its equilibrium. Under this
condition, modifications of the glucose input produce equilibrium shifts, which
are gradual changes from one functioning mode to the other. We also discuss the
concentration variations of various metabolites during equilibrium shifts. The
model can explain a certain amount of experimental observations, assess the
role of poly-unsaturated fatty acids in genetic regulation, and predict the
behavior of mutants. The analysis of the model is based on block elimination of
variables and uses a modular decomposition of the system dictated by
mathematical global univalence conditions.
|
[
{
"created": "Sat, 18 Mar 2006 22:30:57 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Radulescu",
"O.",
""
],
[
"Siegel",
"A.",
""
],
[
"Pecou",
"E.",
""
],
[
"Lagarrigue",
"S.",
""
]
] |
We build a model for the hepatic fatty acid metabolism and its metabolic and genetic regulations. The model has two functioning modes: synthesis and oxidation of fatty acids. We provide a sufficient condition (the strong lipolytic condition) for the uniqueness of its equilibrium. Under this condition, modifications of the glucose input produce equilibrium shifts, which are gradual changes from one functioning mode to the other. We also discuss the concentration variations of various metabolites during equilibrium shifts. The model can explain a certain amount of experimental observations, assess the role of poly-unsaturated fatty acids in genetic regulation, and predict the behavior of mutants. The analysis of the model is based on block elimination of variables and uses a modular decomposition of the system dictated by mathematical global univalence conditions.
|
2011.08024
|
Shailaja Akella
|
Shailaja Akella, Ali Mohebi, Kiersten Riels, Andreas Keil, Karim
Oweiss, Jose C. Principe
|
Local power estimation of neuromodulations using point process modeling
|
6 pages
| null | null | null |
q-bio.NC eess.SP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Extracellular electrical potentials (EEP) recorded from the brain are an
active manifestation of all cellular processes that propagate within a volume
of brain tissue. A standard approach for their quantification are power
spectral analyses methods that reflect the global distribution of signal power
over frequency. However, these methods incorporate analysis windows to achieve
locality and therefore, are limited by the inherent trade - off between time
and frequency resolutions. In this paper, we present a novel approach to
estimate local power more precisely at a resolution as high as the sampling
frequency. Our methods are well grounded on established neurophysiology of the
bio-signals where we model EEPs as comprising of two components:
neuromodulations and background activity. A local measure of power, we call
Marked Point Process (MPP) spectrogram, is then derived as a power - weighted
intensity function of the point process for neuromodulations. We demonstrate
our results on two datasets: 1) local field potentials recorded from the
prefrontal cortex of 3 rats performing a working memory task and 2) EEPs
recorded via electroencephalography from the visual cortex of human subjects
performing a conditioned stimulus task. A detailed analysis of the power -
specific marked features of neuromodulations confirm high correlation between
power spectral density and power in neuromodulations establishing the aptness
of MPP spectrogram as a finer measure of power where it is able to track local
variations in power while preserving the global structure of signal power
distribution.
|
[
{
"created": "Mon, 16 Nov 2020 15:20:33 GMT",
"version": "v1"
}
] |
2020-11-17
|
[
[
"Akella",
"Shailaja",
""
],
[
"Mohebi",
"Ali",
""
],
[
"Riels",
"Kiersten",
""
],
[
"Keil",
"Andreas",
""
],
[
"Oweiss",
"Karim",
""
],
[
"Principe",
"Jose C.",
""
]
] |
Extracellular electrical potentials (EEP) recorded from the brain are an active manifestation of all cellular processes that propagate within a volume of brain tissue. A standard approach for their quantification are power spectral analyses methods that reflect the global distribution of signal power over frequency. However, these methods incorporate analysis windows to achieve locality and therefore, are limited by the inherent trade - off between time and frequency resolutions. In this paper, we present a novel approach to estimate local power more precisely at a resolution as high as the sampling frequency. Our methods are well grounded on established neurophysiology of the bio-signals where we model EEPs as comprising of two components: neuromodulations and background activity. A local measure of power, we call Marked Point Process (MPP) spectrogram, is then derived as a power - weighted intensity function of the point process for neuromodulations. We demonstrate our results on two datasets: 1) local field potentials recorded from the prefrontal cortex of 3 rats performing a working memory task and 2) EEPs recorded via electroencephalography from the visual cortex of human subjects performing a conditioned stimulus task. A detailed analysis of the power - specific marked features of neuromodulations confirm high correlation between power spectral density and power in neuromodulations establishing the aptness of MPP spectrogram as a finer measure of power where it is able to track local variations in power while preserving the global structure of signal power distribution.
|
0903.4491
|
Aleksandra Walczak
|
Gasper Tkacik, Aleksandra M. Walczak, and William Bialek
|
Optimizing information flow in small genetic networks. I
| null |
Phys. Rev. E 80, 031920 (2009)
|
10.1103/PhysRevE.80.031920
| null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In order to survive, reproduce and (in multicellular organisms)
differentiate, cells must control the concentrations of the myriad different
proteins that are encoded in the genome. The precision of this control is
limited by the inevitable randomness of individual molecular events. Here we
explore how cells can maximize their control power in the presence of these
physical limits; formally, we solve the theoretical problem of maximizing the
information transferred from inputs to outputs when the number of available
molecules is held fixed. We start with the simplest version of the problem, in
which a single transcription factor protein controls the readout of one or more
genes by binding to DNA. We further simplify by assuming that this regulatory
network operates in steady state, that the noise is small relative to the
available dynamic range, and that the target genes do not interact. Even in
this simple limit, we find a surprisingly rich set of optimal solutions.
Importantly, for each locally optimal regulatory network, all parameters are
determined once the physical constraints on the number of available molecules
are specified. Although we are solving an over--simplified version of the
problem facing real cells, we see parallels between the structure of these
optimal solutions and the behavior of actual genetic regulatory networks.
Subsequent papers will discuss more complete versions of the problem.
|
[
{
"created": "Thu, 26 Mar 2009 00:12:20 GMT",
"version": "v1"
},
{
"created": "Sun, 1 Nov 2009 22:39:25 GMT",
"version": "v2"
}
] |
2013-08-01
|
[
[
"Tkacik",
"Gasper",
""
],
[
"Walczak",
"Aleksandra M.",
""
],
[
"Bialek",
"William",
""
]
] |
In order to survive, reproduce and (in multicellular organisms) differentiate, cells must control the concentrations of the myriad different proteins that are encoded in the genome. The precision of this control is limited by the inevitable randomness of individual molecular events. Here we explore how cells can maximize their control power in the presence of these physical limits; formally, we solve the theoretical problem of maximizing the information transferred from inputs to outputs when the number of available molecules is held fixed. We start with the simplest version of the problem, in which a single transcription factor protein controls the readout of one or more genes by binding to DNA. We further simplify by assuming that this regulatory network operates in steady state, that the noise is small relative to the available dynamic range, and that the target genes do not interact. Even in this simple limit, we find a surprisingly rich set of optimal solutions. Importantly, for each locally optimal regulatory network, all parameters are determined once the physical constraints on the number of available molecules are specified. Although we are solving an over--simplified version of the problem facing real cells, we see parallels between the structure of these optimal solutions and the behavior of actual genetic regulatory networks. Subsequent papers will discuss more complete versions of the problem.
|
1509.08158
|
Sara Clifton
|
Sara M. Clifton, Rosemary I. Braun, Daniel M. Abrams
|
Handicap principle implies emergence of dimorphic mating displays
|
7 pages, 4 figures, supplementary information included
|
Proceedings of the Royal Society B 283, 1970: November 30 2016
|
10.1098/rspb.2016.1970
| null |
q-bio.PE math.DS nlin.AO physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Species spanning the animal kingdom have evolved extravagant and costly
ornaments to attract mating partners. Zahavi's handicap principle offers an
elegant explanation for this: ornaments signal individual quality, and must be
costly to ensure honest signalling, making mate selection more efficient. Here
we incorporate the assumptions of the handicap principle into a mathematical
model and show that they are sufficient to explain the heretofore puzzling
observation of bimodally distributed ornament sizes in a variety of species.
|
[
{
"created": "Sun, 27 Sep 2015 22:35:32 GMT",
"version": "v1"
},
{
"created": "Mon, 9 May 2016 18:20:21 GMT",
"version": "v2"
},
{
"created": "Tue, 1 Nov 2016 00:44:29 GMT",
"version": "v3"
}
] |
2016-12-02
|
[
[
"Clifton",
"Sara M.",
""
],
[
"Braun",
"Rosemary I.",
""
],
[
"Abrams",
"Daniel M.",
""
]
] |
Species spanning the animal kingdom have evolved extravagant and costly ornaments to attract mating partners. Zahavi's handicap principle offers an elegant explanation for this: ornaments signal individual quality, and must be costly to ensure honest signalling, making mate selection more efficient. Here we incorporate the assumptions of the handicap principle into a mathematical model and show that they are sufficient to explain the heretofore puzzling observation of bimodally distributed ornament sizes in a variety of species.
|
1809.02849
|
Eli Cornblath
|
Eli J. Cornblath, Arian Ashourvan, Jason Z. Kim, Richard F. Betzel,
Rastko Ciric, Azeez Adebimpe, Graham L. Baum, Xiaosong He, Kosha Ruparel,
Tyler M. Moore, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, David R.
Roalf, Theodore D. Satterthwaite, and Danielle S. Bassett
|
Temporal sequences of brain activity at rest are constrained by white
matter structure and modulated by cognitive demands
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A diverse white matter network and finely tuned neuronal membrane properties
allow the brain to transition seamlessly between cognitive states. However, it
remains unclear how static structural connections guide the temporal
progression of large-scale brain activity patterns in different cognitive
states. Here, we analyze the brain's trajectories through a high-dimensional
activity space at the level of single time point activity patterns from
functional magnetic resonance imaging data acquired during passive visual
fixation (rest) and an n-back working memory task. We find that specific state
space trajectories, which represent temporal sequences of brain activity, are
modulated by cognitive load and related to task performance. Using
diffusion-weighted imaging acquired from the same subjects, we use tools from
network control theory to show that linear spread of activity along white
matter connections constrains the brain's state space trajectories at rest.
Additionally, accounting for stimulus-driven visual inputs explains the
different trajectories taken during the n-back task. We also used models of
network rewiring to show that these findings are the result of non-trivial
geometric and topological properties of white matter architecture. Finally, we
examine associations between age and time-resolved brain state dynamics,
revealing new insights into functional changes in the default mode and
executive control networks. Overall, these results elucidate the structural
underpinnings of cognitively and developmentally relevant spatiotemporal brain
dynamics.
|
[
{
"created": "Sat, 8 Sep 2018 18:14:29 GMT",
"version": "v1"
},
{
"created": "Mon, 30 Sep 2019 23:14:02 GMT",
"version": "v2"
}
] |
2019-10-02
|
[
[
"Cornblath",
"Eli J.",
""
],
[
"Ashourvan",
"Arian",
""
],
[
"Kim",
"Jason Z.",
""
],
[
"Betzel",
"Richard F.",
""
],
[
"Ciric",
"Rastko",
""
],
[
"Adebimpe",
"Azeez",
""
],
[
"Baum",
"Graham L.",
""
],
[
"He",
"Xiaosong",
""
],
[
"Ruparel",
"Kosha",
""
],
[
"Moore",
"Tyler M.",
""
],
[
"Gur",
"Ruben C.",
""
],
[
"Gur",
"Raquel E.",
""
],
[
"Shinohara",
"Russell T.",
""
],
[
"Roalf",
"David R.",
""
],
[
"Satterthwaite",
"Theodore D.",
""
],
[
"Bassett",
"Danielle S.",
""
]
] |
A diverse white matter network and finely tuned neuronal membrane properties allow the brain to transition seamlessly between cognitive states. However, it remains unclear how static structural connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain's trajectories through a high-dimensional activity space at the level of single time point activity patterns from functional magnetic resonance imaging data acquired during passive visual fixation (rest) and an n-back working memory task. We find that specific state space trajectories, which represent temporal sequences of brain activity, are modulated by cognitive load and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we use tools from network control theory to show that linear spread of activity along white matter connections constrains the brain's state space trajectories at rest. Additionally, accounting for stimulus-driven visual inputs explains the different trajectories taken during the n-back task. We also used models of network rewiring to show that these findings are the result of non-trivial geometric and topological properties of white matter architecture. Finally, we examine associations between age and time-resolved brain state dynamics, revealing new insights into functional changes in the default mode and executive control networks. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.
|
2104.01458
|
Mar\'ia Vallet-Regi
|
M. Natividad Gomez-Cerezo, Juan Pena, Saso Ivanovski, Daniel Arcos,
Maria Vallet-Regi, Cedryck Vaquette
|
Multiscale porosity in mesoporous bioglass 3D-printed scaffolds for bone
regeneration
|
34 pages, 10 figures
|
Materials Science and Engineering: C, Volume 120, January 2021,
111706
|
10.1016/j.msec.2020.111706
| null |
q-bio.TO
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
In order to increase the bone forming ability of MBG-PCL composite scaffold,
microporosity was created in the struts of 3D-printed MBG-PCL scaffolds for the
manufacturing of a construct with a multiscale porosity consisting of meso-,
micro- and macro-pores. 3D-printing imparted macroporosity while the
microporosity was created by porogen removal from the struts, and the MBG
particles were responsible for the mesoporosity. The scaffolds were 3D-printed
using a mixture of PCL, MBG and phosphate buffered saline (PBS) particles,
subsequently leached out. Microporous-PCL (pPCL) as a negative control,
microporous MBG-PCL (pMBG-PCL) and non-microporous-MBG-PCL (MBG-PCL) were
investigated. Scanning electron microscopy, mercury intrusion porosimetry and
micro-computed tomography demonstrated that the PBS removal resulted in the
formation of micropores inside the struts with porosity of around 30% for both
pPCL and pMBG-PCL, with both constructs displaying an overall porosity of
80-90%. In contrast, the MBG-PCL group had a microporosity of 6% and an overall
porosity of 70%. Early mineralisation was found in the pMBG-PCL post-leaching
out and this resulted in the formation a more homogeneous calcium phosphate
layer when using a biomimetic mineralisation assay. Mechanical properties
ranged from 5 to 25 MPa for microporous and non-microporous specimens, hence
microporosity was the determining factor affecting compressive properties.
MC3T3-E1 metabolic activity was increased in the pMBG-PCL along with an
increased production of RUNX2. Therefore, the microporosity within a 3D-printed
bioceramic composite construct may result in additional physical and biological
benefits.
|
[
{
"created": "Sat, 3 Apr 2021 18:34:03 GMT",
"version": "v1"
}
] |
2021-04-06
|
[
[
"Gomez-Cerezo",
"M. Natividad",
""
],
[
"Pena",
"Juan",
""
],
[
"Ivanovski",
"Saso",
""
],
[
"Arcos",
"Daniel",
""
],
[
"Vallet-Regi",
"Maria",
""
],
[
"Vaquette",
"Cedryck",
""
]
] |
In order to increase the bone forming ability of MBG-PCL composite scaffold, microporosity was created in the struts of 3D-printed MBG-PCL scaffolds for the manufacturing of a construct with a multiscale porosity consisting of meso-, micro- and macro-pores. 3D-printing imparted macroporosity while the microporosity was created by porogen removal from the struts, and the MBG particles were responsible for the mesoporosity. The scaffolds were 3D-printed using a mixture of PCL, MBG and phosphate buffered saline (PBS) particles, subsequently leached out. Microporous-PCL (pPCL) as a negative control, microporous MBG-PCL (pMBG-PCL) and non-microporous-MBG-PCL (MBG-PCL) were investigated. Scanning electron microscopy, mercury intrusion porosimetry and micro-computed tomography demonstrated that the PBS removal resulted in the formation of micropores inside the struts with porosity of around 30% for both pPCL and pMBG-PCL, with both constructs displaying an overall porosity of 80-90%. In contrast, the MBG-PCL group had a microporosity of 6% and an overall porosity of 70%. Early mineralisation was found in the pMBG-PCL post-leaching out and this resulted in the formation a more homogeneous calcium phosphate layer when using a biomimetic mineralisation assay. Mechanical properties ranged from 5 to 25 MPa for microporous and non-microporous specimens, hence microporosity was the determining factor affecting compressive properties. MC3T3-E1 metabolic activity was increased in the pMBG-PCL along with an increased production of RUNX2. Therefore, the microporosity within a 3D-printed bioceramic composite construct may result in additional physical and biological benefits.
|
2408.03942
|
Davood Karimi
|
Camilo Calixto, Matheus D. Soldatelli, Bo Li, Lana Pierotich, Ali
Gholipour, Simon K. Warfield, Davood Karimi
|
White matter tract crossing and bottleneck regions in the fetal brain
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
There is a growing interest in using diffusion MRI to study the white matter
tracts and structural connectivity of the fetal brain. Recent progress in data
acquisition and processing suggests that this imaging modality has a unique
role in elucidating the normal and abnormal patterns of neurodevelopment in
utero. However, there have been no efforts to quantify the prevalence of
crossing tracts and bottleneck regions, important issues that have been
extensively researched for adult brains. In this work, we determined the brain
regions with crossing tracts and bottlenecks between 23 and 36 gestational
weeks. We performed probabilistic tractography on 59 fetal brain scans and
extracted a set of 51 distinct white tracts, which we grouped into 10 major
tract bundle groups. We analyzed the results to determine the patterns of tract
crossings and bottlenecks. Our results showed that 20-25% of the white matter
voxels included two or three crossing tracts. Bottlenecks were more prevalent.
Between 75-80% of the voxels were characterized as bottlenecks, with more than
40% of the voxels involving four or more tracts. The results of this study
highlight the challenge of fetal brain tractography and structural connectivity
assessment and call for innovative image acquisition and analysis methods to
mitigate these problems.
|
[
{
"created": "Sat, 20 Jul 2024 21:20:50 GMT",
"version": "v1"
}
] |
2024-08-09
|
[
[
"Calixto",
"Camilo",
""
],
[
"Soldatelli",
"Matheus D.",
""
],
[
"Li",
"Bo",
""
],
[
"Pierotich",
"Lana",
""
],
[
"Gholipour",
"Ali",
""
],
[
"Warfield",
"Simon K.",
""
],
[
"Karimi",
"Davood",
""
]
] |
There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been extensively researched for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 59 fetal brain scans and extracted a set of 51 distinct white tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75-80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. The results of this study highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.
|
2309.06636
|
Chaoqian Wang
|
Chaoqian Wang
|
Evolution of trust in structured populations
|
14 pages, 2 figures, accepted for publication in Applied Mathematics
and Computation
|
Applied Mathematics and Computation, Volume 471, 15 June 2024,
128595
|
10.1016/j.amc.2024.128595
| null |
q-bio.PE nlin.AO physics.soc-ph
|
http://creativecommons.org/publicdomain/zero/1.0/
|
The trust game, derived from an economics experiment, has recently attracted
interest in the field of evolutionary dynamics. In a recent version of the
evolutionary trust game, players adopt one of three strategies: investor,
trustworthy trustee, or untrustworthy trustee. Trustworthy trustees enhance and
share the investment with the investor, whereas untrustworthy trustees retain
the full amount, betraying the investor. Following this setup, we investigate a
two-player trust game, which is analytically feasible under weak selection. We
explore the evolution of trust in structured populations, factoring in four
strategy updating rules: pairwise comparison (PC), birth-death (BD), imitation
(IM), and death-birth (DB). Comparing structured populations with well-mixed
populations, we arrive at two main conclusions. First, in the absence of
untrustworthy trustees, there is a saddle point between investors and
trustworthy trustees, with collaboration thriving best in well-mixed
populations. The collaboration diminishes sequentially from DB to IM to PC/BD
updating rules in structured populations. Second, an invasion of untrustworthy
trustees makes this saddle point unstable and leads to the extinction of
investors. The 3-strategy system stabilizes at an equilibrium line where the
trustworthy and untrustworthy trustees coexist. The stability span of
trustworthy trustees is maximally extended under the PC and BD updating rules
in structured populations, while it decreases in a sequence from IM to DB
updating rules, with the well-mixed population being the least favorable. This
research thus adds an analytical lens to the evolution of trust in structured
populations.
|
[
{
"created": "Tue, 12 Sep 2023 22:54:45 GMT",
"version": "v1"
},
{
"created": "Sun, 17 Dec 2023 02:44:09 GMT",
"version": "v2"
},
{
"created": "Sat, 10 Feb 2024 03:08:42 GMT",
"version": "v3"
}
] |
2024-02-13
|
[
[
"Wang",
"Chaoqian",
""
]
] |
The trust game, derived from an economics experiment, has recently attracted interest in the field of evolutionary dynamics. In a recent version of the evolutionary trust game, players adopt one of three strategies: investor, trustworthy trustee, or untrustworthy trustee. Trustworthy trustees enhance and share the investment with the investor, whereas untrustworthy trustees retain the full amount, betraying the investor. Following this setup, we investigate a two-player trust game, which is analytically feasible under weak selection. We explore the evolution of trust in structured populations, factoring in four strategy updating rules: pairwise comparison (PC), birth-death (BD), imitation (IM), and death-birth (DB). Comparing structured populations with well-mixed populations, we arrive at two main conclusions. First, in the absence of untrustworthy trustees, there is a saddle point between investors and trustworthy trustees, with collaboration thriving best in well-mixed populations. The collaboration diminishes sequentially from DB to IM to PC/BD updating rules in structured populations. Second, an invasion of untrustworthy trustees makes this saddle point unstable and leads to the extinction of investors. The 3-strategy system stabilizes at an equilibrium line where the trustworthy and untrustworthy trustees coexist. The stability span of trustworthy trustees is maximally extended under the PC and BD updating rules in structured populations, while it decreases in a sequence from IM to DB updating rules, with the well-mixed population being the least favorable. This research thus adds an analytical lens to the evolution of trust in structured populations.
|
2201.09647
|
Alex Zhavoronkov
|
Feng Ren, Xiao Ding, Min Zheng, Mikhail Korzinkin, Xin Cai, Wei Zhu,
Alexey Mantsyzov, Alex Aliper, Vladimir Aladinskiy, Zhongying Cao, Shanshan
Kong, Xi Long, Bonnie Hei Man Liu, Yingtao Liu, Vladimir Naumov, Anastasia
Shneyderman, Ivan V. Ozerov, Ju Wang, Frank W. Pun, Alan Aspuru-Guzik,
Michael Levitt, and Alex Zhavoronkov
|
AlphaFold Accelerates Artificial Intelligence Powered Drug Discovery:
Efficient Discovery of a Novel Cyclin-dependent Kinase 20 (CDK20) Small
Molecule Inhibitor
|
9 pages, 6 figures
| null | null | null |
q-bio.BM cs.AI cs.LG q-bio.MN
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
The AlphaFold computer program predicted protein structures for the whole
human genome, which has been considered as a remarkable breakthrough both in
artificial intelligence (AI) application and structural biology. Despite the
varying confidence level, these predicted structures still could significantly
contribute to structure-based drug design of novel targets, especially the ones
with no or limited structural information. In this work, we successfully
applied AlphaFold in our end-to-end AI-powered drug discovery engines
constituted of a biocomputational platform PandaOmics and a generative
chemistry platform Chemistry42, to identify a first-in-class hit molecule of a
novel target without an experimental structure starting from target selection
towards hit identification in a cost- and time-efficient manner. PandaOmics
provided the targets of interest and Chemistry42 generated the molecules based
on the AlphaFold predicted structure, and the selected molecules were
synthesized and tested in biological assays. Through this approach, we
identified a small molecule hit compound for CDK20 with a Kd value of 8.9 +/-
1.6 uM (n = 4) within 30 days from target selection and after only synthesizing
7 compounds. Based on the available data, the second round of AI-powered
compound generation was conducted and through which, a more potent hit
molecule, ISM042-2 048, was discovered with a Kd value of 210.0 +/- 42.4 nM (n
= 2), within 30 days and after synthesizing 6 compounds from the discovery of
the first hit ISM042-2-001. To the best of our knowledge, this is the first
reported small molecule targeting CDK20 and more importantly, this work is the
first demonstration of AlphaFold application in the hit identification process
in early drug discovery.
|
[
{
"created": "Fri, 21 Jan 2022 07:35:24 GMT",
"version": "v1"
},
{
"created": "Sun, 13 Feb 2022 04:26:30 GMT",
"version": "v2"
}
] |
2022-02-15
|
[
[
"Ren",
"Feng",
""
],
[
"Ding",
"Xiao",
""
],
[
"Zheng",
"Min",
""
],
[
"Korzinkin",
"Mikhail",
""
],
[
"Cai",
"Xin",
""
],
[
"Zhu",
"Wei",
""
],
[
"Mantsyzov",
"Alexey",
""
],
[
"Aliper",
"Alex",
""
],
[
"Aladinskiy",
"Vladimir",
""
],
[
"Cao",
"Zhongying",
""
],
[
"Kong",
"Shanshan",
""
],
[
"Long",
"Xi",
""
],
[
"Liu",
"Bonnie Hei Man",
""
],
[
"Liu",
"Yingtao",
""
],
[
"Naumov",
"Vladimir",
""
],
[
"Shneyderman",
"Anastasia",
""
],
[
"Ozerov",
"Ivan V.",
""
],
[
"Wang",
"Ju",
""
],
[
"Pun",
"Frank W.",
""
],
[
"Aspuru-Guzik",
"Alan",
""
],
[
"Levitt",
"Michael",
""
],
[
"Zhavoronkov",
"Alex",
""
]
] |
The AlphaFold computer program predicted protein structures for the whole human genome, which has been considered as a remarkable breakthrough both in artificial intelligence (AI) application and structural biology. Despite the varying confidence level, these predicted structures still could significantly contribute to structure-based drug design of novel targets, especially the ones with no or limited structural information. In this work, we successfully applied AlphaFold in our end-to-end AI-powered drug discovery engines constituted of a biocomputational platform PandaOmics and a generative chemistry platform Chemistry42, to identify a first-in-class hit molecule of a novel target without an experimental structure starting from target selection towards hit identification in a cost- and time-efficient manner. PandaOmics provided the targets of interest and Chemistry42 generated the molecules based on the AlphaFold predicted structure, and the selected molecules were synthesized and tested in biological assays. Through this approach, we identified a small molecule hit compound for CDK20 with a Kd value of 8.9 +/- 1.6 uM (n = 4) within 30 days from target selection and after only synthesizing 7 compounds. Based on the available data, the second round of AI-powered compound generation was conducted and through which, a more potent hit molecule, ISM042-2 048, was discovered with a Kd value of 210.0 +/- 42.4 nM (n = 2), within 30 days and after synthesizing 6 compounds from the discovery of the first hit ISM042-2-001. To the best of our knowledge, this is the first reported small molecule targeting CDK20 and more importantly, this work is the first demonstration of AlphaFold application in the hit identification process in early drug discovery.
|
1809.08959
|
Joaquin Goni
|
Sumra Bari, Enrico Amico, Nicole Vike, Thomas M. Talavage, Joaqu\'in
Go\~ni
|
Uncovering Multi-Site Identifiability Based on Resting-State Functional
Connectomes
|
28 pages, 11 figures in main text, 5 figures in supplementary
|
NeuroImage, 2019, Vol 202, 115967
|
10.1016/j.neuroimage.2019.06.045
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Multi-site studies are becoming important to increase statistical power,
enhance generalizability, and to improve the likelihood of pooling relevant
subgroups together activities. Even with harmonized imaging sequences,
site-dependent variability can mask the advantages of these multi-site studies.
The aim of this study was to assess multi-site reproducibility in resting-state
functional connectivity fingerprints, and to improve identifiability of
functional connectomes. The individual fingerprinting of functional
connectivity profiles is promising due to its potential as a robust
neuroimaging biomarker. We evaluated, on two independent multi-site datasets,
individual fingerprints in test-retest visit pairs within and across two sites
and present a generalized framework based on principal component analysis to
improve identifiability. Those components that maximized differential
identifiability of a training dataset were used as an orthogonal connectivity
basis to reconstruct the functional connectomes of training and validation
sets. The optimally reconstructed functional connectomes showed a substantial
improvement in individual fingerprinting within and across the two sites
relative to the original data. A notable increase in ICC values for functional
edges and resting-state networks was also observed. Improvements in
identifiability were not found to be affected by global signal regression.
Post-hoc analyses assessed the effect of the number of fMRI volumes on
identifiability and showed that multi-site differential identifiability was for
all cases maximized after optimal reconstruction. The generalizability of the
optimal set of orthogonal basis of each dataset was evaluated through a
leave-one-out procedure. Overall, results demonstrate that the framework
presented in this study systematically improves identifiability in
resting-state functional connectomes in multi-site studies.
|
[
{
"created": "Mon, 24 Sep 2018 14:14:32 GMT",
"version": "v1"
},
{
"created": "Tue, 23 Apr 2019 19:06:42 GMT",
"version": "v2"
}
] |
2019-09-11
|
[
[
"Bari",
"Sumra",
""
],
[
"Amico",
"Enrico",
""
],
[
"Vike",
"Nicole",
""
],
[
"Talavage",
"Thomas M.",
""
],
[
"Goñi",
"Joaquín",
""
]
] |
Multi-site studies are becoming important to increase statistical power, enhance generalizability, and to improve the likelihood of pooling relevant subgroups together activities. Even with harmonized imaging sequences, site-dependent variability can mask the advantages of these multi-site studies. The aim of this study was to assess multi-site reproducibility in resting-state functional connectivity fingerprints, and to improve identifiability of functional connectomes. The individual fingerprinting of functional connectivity profiles is promising due to its potential as a robust neuroimaging biomarker. We evaluated, on two independent multi-site datasets, individual fingerprints in test-retest visit pairs within and across two sites and present a generalized framework based on principal component analysis to improve identifiability. Those components that maximized differential identifiability of a training dataset were used as an orthogonal connectivity basis to reconstruct the functional connectomes of training and validation sets. The optimally reconstructed functional connectomes showed a substantial improvement in individual fingerprinting within and across the two sites relative to the original data. A notable increase in ICC values for functional edges and resting-state networks was also observed. Improvements in identifiability were not found to be affected by global signal regression. Post-hoc analyses assessed the effect of the number of fMRI volumes on identifiability and showed that multi-site differential identifiability was for all cases maximized after optimal reconstruction. The generalizability of the optimal set of orthogonal basis of each dataset was evaluated through a leave-one-out procedure. Overall, results demonstrate that the framework presented in this study systematically improves identifiability in resting-state functional connectomes in multi-site studies.
|
2307.02561
|
Samuel Church
|
Samuel H. Church, Jasmine L. Mah, Casey W. Dunn
|
Unification of species, gene, and cell trees for single-cell expression
analyses
|
16 pages, 4 figures
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
Comparisons of single-cell RNA sequencing (scRNA-seq) data across species can
reveal links between cellular gene expression and the evolution of cell
functions, features, and phenotypes. These comparisons invoke evolutionary
histories, as depicted with phylogenetic trees, that define relationships
between species, genes, and cells. Here we illustrate a tree-based framework
for comparing scRNA-seq data, and contrast this framework with existing
methods. We describe how we can use trees to identify homologous and comparable
groups of genes and cells, based on their predicted relationship to genes and
cells present in the common ancestor. We advocate for mapping data to branches
of phylogenetic trees to test hypotheses about the evolution of cellular gene
expression. We describe the kinds of data that can be compared, and the types
of questions that each comparison has the potential to address. Finally, we
reconcile species phylogenies, gene phylogenies, cell phylogenies, and cell
lineages as different representations of the same concept: the tree of cellular
life. By integrating phylogenetic approaches into scRNA-seq analyses, we can
overcome challenges for building informed comparisons across species, and
robustly test hypotheses about gene and cell evolution.
|
[
{
"created": "Wed, 5 Jul 2023 18:02:17 GMT",
"version": "v1"
}
] |
2023-07-07
|
[
[
"Church",
"Samuel H.",
""
],
[
"Mah",
"Jasmine L.",
""
],
[
"Dunn",
"Casey W.",
""
]
] |
Comparisons of single-cell RNA sequencing (scRNA-seq) data across species can reveal links between cellular gene expression and the evolution of cell functions, features, and phenotypes. These comparisons invoke evolutionary histories, as depicted with phylogenetic trees, that define relationships between species, genes, and cells. Here we illustrate a tree-based framework for comparing scRNA-seq data, and contrast this framework with existing methods. We describe how we can use trees to identify homologous and comparable groups of genes and cells, based on their predicted relationship to genes and cells present in the common ancestor. We advocate for mapping data to branches of phylogenetic trees to test hypotheses about the evolution of cellular gene expression. We describe the kinds of data that can be compared, and the types of questions that each comparison has the potential to address. Finally, we reconcile species phylogenies, gene phylogenies, cell phylogenies, and cell lineages as different representations of the same concept: the tree of cellular life. By integrating phylogenetic approaches into scRNA-seq analyses, we can overcome challenges for building informed comparisons across species, and robustly test hypotheses about gene and cell evolution.
|
2004.08973
|
Gabor Vattay
|
Gabor Vattay
|
Forecasting the outcome and estimating the epidemic model parameters
from the fatality time series in COVID-19 outbreaks
| null |
Physical Biology 2020
|
10.1088/1478-3975/abac69
| null |
q-bio.PE physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In the absence of other tools, monitoring the effects of protective measures,
including social distancing and forecasting the outcome of outbreaks is of
immense interest. Real-time data is noisy and very often hampered by systematic
errors in reporting. Detailed epidemic models may contain a large number of
empirical parameters, which cannot be determined with sufficient accuracy. In
this paper, we show that the cumulative number of deaths can be regarded as a
master variable, and the parameters of the epidemic such as the basic
reproduction number, the size of the susceptible population, and the infection
rate can be determined. In the SIR model, we derive an explicit single variable
differential equation for the evolution of the cumulative number of fatalities.
We show that the epidemic in Spain, Italy, and Hubei Province, China follows
this master equation closely. We discuss the relationship with the logistic
growth model, and we show that it is a good approximation when the basic
reproduction number is less than $2.3$. This condition is valid for the
outbreak in Hubei, but not for the outbreaks in Spain, Italy, and New York. The
difference is in the shorter infectious period in China, probably due to the
separation policy of the infected. For more complex models, with more internal
variables, such as the SEIR model, the equations derived from the SIR model
remain valid approximately, due to the separation of timescales.
|
[
{
"created": "Sun, 19 Apr 2020 22:14:17 GMT",
"version": "v1"
},
{
"created": "Sat, 1 Aug 2020 09:53:57 GMT",
"version": "v2"
}
] |
2020-08-11
|
[
[
"Vattay",
"Gabor",
""
]
] |
In the absence of other tools, monitoring the effects of protective measures, including social distancing and forecasting the outcome of outbreaks is of immense interest. Real-time data is noisy and very often hampered by systematic errors in reporting. Detailed epidemic models may contain a large number of empirical parameters, which cannot be determined with sufficient accuracy. In this paper, we show that the cumulative number of deaths can be regarded as a master variable, and the parameters of the epidemic such as the basic reproduction number, the size of the susceptible population, and the infection rate can be determined. In the SIR model, we derive an explicit single variable differential equation for the evolution of the cumulative number of fatalities. We show that the epidemic in Spain, Italy, and Hubei Province, China follows this master equation closely. We discuss the relationship with the logistic growth model, and we show that it is a good approximation when the basic reproduction number is less than $2.3$. This condition is valid for the outbreak in Hubei, but not for the outbreaks in Spain, Italy, and New York. The difference is in the shorter infectious period in China, probably due to the separation policy of the infected. For more complex models, with more internal variables, such as the SEIR model, the equations derived from the SIR model remain valid approximately, due to the separation of timescales.
|
q-bio/0605005
|
Willy Valdivia-Granda
|
Willy Valdivia-Granda and Christopher Dwan
|
Microarray Data Management. An Enterprise Information Approach:
Implementations and Challenges
|
10 pages, 12 figures, To apperar in: Database Modeling in Biology:
Practices and Challenges. Ma, Zongmin; Chen, Jake (Eds.) Springer Sciences &
Business Media, Inc., New York, USA (2006). ISBN: 0-387-30238-7
| null | null | null |
q-bio.GN
| null |
The extraction of information form high-throughput experiments is a key
aspect of modern biology. Early in the development of microarray technology,
researchers recognized that the size of the datasets and the limitations of
both computational and visualization techniques restricted their ability to
find the biological meaning hidden in the data. In addition, most researchers
wanted to make their datasets accessible to others. This resulted in the
development of new and advanced data storage, analysis, and visualization tools
enabling the cross-platform validation of the experiments and the
identification of previously undetected patterns. In order to reap the benefits
of this microarray data, researchers have needed to implement database
management systems providing integration of different experiments and data
types. Moreover, it was necessary to standardize the basic data structure and
experimental techniques for the standardization of microarray platforms. In
this chapter, we introduce the reader to the major concepts related to the use
of controlled vocabularies (ontologies), the definition of Minimum Information
About a Microarray Experiment (MIAME) and provide an overview of different
microarray data management strategies in use today. We summarize the main
characteristics of microarray data storage and sharing strategies including
warehouses, datamarts, and federations. The fundamental challenges involved in
the distribution, and retrieval of microarray data are presented, along with an
overview of some emerging technologies.
|
[
{
"created": "Wed, 3 May 2006 13:51:38 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Valdivia-Granda",
"Willy",
""
],
[
"Dwan",
"Christopher",
""
]
] |
The extraction of information form high-throughput experiments is a key aspect of modern biology. Early in the development of microarray technology, researchers recognized that the size of the datasets and the limitations of both computational and visualization techniques restricted their ability to find the biological meaning hidden in the data. In addition, most researchers wanted to make their datasets accessible to others. This resulted in the development of new and advanced data storage, analysis, and visualization tools enabling the cross-platform validation of the experiments and the identification of previously undetected patterns. In order to reap the benefits of this microarray data, researchers have needed to implement database management systems providing integration of different experiments and data types. Moreover, it was necessary to standardize the basic data structure and experimental techniques for the standardization of microarray platforms. In this chapter, we introduce the reader to the major concepts related to the use of controlled vocabularies (ontologies), the definition of Minimum Information About a Microarray Experiment (MIAME) and provide an overview of different microarray data management strategies in use today. We summarize the main characteristics of microarray data storage and sharing strategies including warehouses, datamarts, and federations. The fundamental challenges involved in the distribution, and retrieval of microarray data are presented, along with an overview of some emerging technologies.
|
1903.01316
|
Romain M. Yvinec
|
Fr\'ed\'erique Cl\'ement and Fr\'ed\'erique Robin and Romain Yvinec
|
Stochastic nonlinear model for somatic cell population dynamics during
ovarian follicle activation
|
Accepted in Journal of Mathematical Biology
| null | null | null |
q-bio.CB math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In mammals, female germ cells are sheltered within somatic structures called
ovarian follicles, which remain in a quiescent state until they get activated,
all along reproductive life. We investigate the sequence of somatic cell events
occurring just after follicle activation, starting by the awakening of
precursor somatic cells, and their transformation into proliferative cells. We
introduce a nonlinear stochastic model accounting for the joint dynamics of the
two cell types, and allowing us to investigate the potential impact of a
feedback from proliferative cells onto precursor cells. To tackle the key issue
of whether cell proliferation is concomitant or posterior to cell awakening, we
assess both the time needed for all precursor cells to awake, and the
corresponding increase in the total cell number with respect to the initial
cell number. Using the probabilistic theory of first passage times, we design a
numerical scheme based on a rigorous Finite State Projection and coupling
techniques to compute the mean extinction time and the cell number at
extinction time. We find that the feedback term clearly lowers the number of
proliferative cells at the extinction time. We calibrate the model parameters
using an exact likelihood approach. We carry out a comprehensive comparison
between the initial model and a series of submodels, which helps to select the
critical cell events taking place during activation, and suggests that
awakening is prominent over proliferation.
|
[
{
"created": "Mon, 4 Mar 2019 15:48:38 GMT",
"version": "v1"
},
{
"created": "Wed, 9 Dec 2020 08:07:29 GMT",
"version": "v2"
}
] |
2020-12-10
|
[
[
"Clément",
"Frédérique",
""
],
[
"Robin",
"Frédérique",
""
],
[
"Yvinec",
"Romain",
""
]
] |
In mammals, female germ cells are sheltered within somatic structures called ovarian follicles, which remain in a quiescent state until they get activated, all along reproductive life. We investigate the sequence of somatic cell events occurring just after follicle activation, starting by the awakening of precursor somatic cells, and their transformation into proliferative cells. We introduce a nonlinear stochastic model accounting for the joint dynamics of the two cell types, and allowing us to investigate the potential impact of a feedback from proliferative cells onto precursor cells. To tackle the key issue of whether cell proliferation is concomitant or posterior to cell awakening, we assess both the time needed for all precursor cells to awake, and the corresponding increase in the total cell number with respect to the initial cell number. Using the probabilistic theory of first passage times, we design a numerical scheme based on a rigorous Finite State Projection and coupling techniques to compute the mean extinction time and the cell number at extinction time. We find that the feedback term clearly lowers the number of proliferative cells at the extinction time. We calibrate the model parameters using an exact likelihood approach. We carry out a comprehensive comparison between the initial model and a series of submodels, which helps to select the critical cell events taking place during activation, and suggests that awakening is prominent over proliferation.
|
1508.00623
|
Nicholas Noll
|
Nicholas Noll, Madhav Mani, Idse Heemskerk, Sebastian Streichan, Boris
I. Shraiman
|
Active Tension Network model reveals an exotic mechanical state realized
in epithelial tissues
|
The central argument as well as the initial reported results remain
unchanged. This revision represents a restructuring of the initial arguments
to make it more readable and easier to understand to a wider audience.
Furthermore, additional movies were analyzed to bolster our claim made that
VF formation is primarily isogonal deformations
| null | null | null |
q-bio.TO q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
It is now widely recognized that mechanical interactions between cells play a
crucial role in epithelial morphogenesis, yet understanding the mechanisms
through which stress and deformation affect cell behavior remains an open
problem due to the complexity inherent in the mechanical behavior of cells and
the difficulty of direct measurement of forces within tissues. Theoretical
models can help by focusing experimental studies and by providing the framework
for interpreting measurements. To that end, "vertex models" have introduced an
approximation of epithelial cell mechanics based on a polygonal tiling
representation of planar tissue. Here we formulate and analyze an Active
Tension Network (ATN) model, which is based on the same polygonal
representation of epithelial tissue geometry, but in addition i) assumes that
mechanical balance is dominated by cortical tension and ii) introduces tension
dependent local remodeling of the cortex, representing the active nature of
cytoskeletal mechanics. The tension-dominance assumption has immediate
implications for the geometry of cells, which we demonstrate to hold in certain
types of Drosophila epithelial tissues. We demonstrate that stationary
configurations of an ATN form a manifold with one degree of freedom per cell,
corresponding to "isogonal" - i.e. angle preserving - deformations of cells,
which dominate the dynamic response to perturbations. We show that isogonal
modes account for approximately 90% of experimentally observed deformation of
cells during the process of ventral furrow formation in Drosophila. Other
interesting properties of our model include the exponential screening of
mechanical stress and a negative Poisson ratio response to external uniaxial
stress. We also provide a new approach to the problem of inferring local
cortical tensions from the observed geometry of epithelial cells in a tissue
|
[
{
"created": "Mon, 3 Aug 2015 23:53:26 GMT",
"version": "v1"
},
{
"created": "Wed, 18 Jan 2017 23:31:46 GMT",
"version": "v2"
}
] |
2017-01-20
|
[
[
"Noll",
"Nicholas",
""
],
[
"Mani",
"Madhav",
""
],
[
"Heemskerk",
"Idse",
""
],
[
"Streichan",
"Sebastian",
""
],
[
"Shraiman",
"Boris I.",
""
]
] |
It is now widely recognized that mechanical interactions between cells play a crucial role in epithelial morphogenesis, yet understanding the mechanisms through which stress and deformation affect cell behavior remains an open problem due to the complexity inherent in the mechanical behavior of cells and the difficulty of direct measurement of forces within tissues. Theoretical models can help by focusing experimental studies and by providing the framework for interpreting measurements. To that end, "vertex models" have introduced an approximation of epithelial cell mechanics based on a polygonal tiling representation of planar tissue. Here we formulate and analyze an Active Tension Network (ATN) model, which is based on the same polygonal representation of epithelial tissue geometry, but in addition i) assumes that mechanical balance is dominated by cortical tension and ii) introduces tension dependent local remodeling of the cortex, representing the active nature of cytoskeletal mechanics. The tension-dominance assumption has immediate implications for the geometry of cells, which we demonstrate to hold in certain types of Drosophila epithelial tissues. We demonstrate that stationary configurations of an ATN form a manifold with one degree of freedom per cell, corresponding to "isogonal" - i.e. angle preserving - deformations of cells, which dominate the dynamic response to perturbations. We show that isogonal modes account for approximately 90% of experimentally observed deformation of cells during the process of ventral furrow formation in Drosophila. Other interesting properties of our model include the exponential screening of mechanical stress and a negative Poisson ratio response to external uniaxial stress. We also provide a new approach to the problem of inferring local cortical tensions from the observed geometry of epithelial cells in a tissue
|
1812.08031
|
Gestionnaire Hal-Su
|
St\'ephane Epelbaum (ICM, IM2A, UPMC), Vincent Bouteloup (ISPED, BPH),
Jean Mangin (CATI, NEUROSPIN), Valentina La Corte (UPD5 Psychologie, CPN -
U894), Raffaela Migliaccio (ICM, IM2A, UPMC), Hugo Bertin (LIB, CATI, UPMC),
Marie O. Habert (LIB, CATI, UPMC), Clara Fischer (CATI, NEUROSPIN), Chabha
Azouani (CATI), Ludovic Fillon (CATI), Marie Chupin (CATI), Bruno Vellas,
Florence Pasquier, Jean Dartigues (BPH, ISPED), Fr\'ed\'eric Blanc, Audrey
Gabelle (CHRU Montpellier), Mathieu Ceccaldi (INS, TIMONE), Pierre
Krolak-Salmon (HCL), Jacques Hugon (UPD7), Olivier Hanon (UPD5), Olivier
Rouaud (CHU Dijon), Renaud David (CMRR Nice), Genevi\`eve Ch\^ene (BPH,
ISPED), Bruno Dubois (IM2A, ICM, UPMC), Carole Dufouil (BPH, ISPED)
|
Neural correlates of episodic memory in the Memento cohort
| null |
Alzheimer's & Dementia: Translational Research & Clinical
Interventions, 2018, 4, pp.224-233
|
10.1016/j.trci.2018.03.010
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
IntroductionThe free and cued selective reminding test is used to identify
memory deficits in mild cognitive impairment and demented patients. It allows
assessing three processes: encoding, storage, and recollection of verbal
episodic memory.MethodsWe investigated the neural correlates of these three
memory processes in a large cohort study. The Memento cohort enrolled 2323
outpatients presenting either with subjective cognitive decline or mild
cognitive impairment who underwent cognitive, structural MRI and, for a subset,
fluorodeoxyglucose--positron emission tomography evaluations.ResultsEncoding
was associated with a network including parietal and temporal cortices; storage
was mainly associated with entorhinal and parahippocampal regions, bilaterally;
retrieval was associated with a widespread network encompassing frontal
regions.DiscussionThe neural correlates of episodic memory processes can be
assessed in large and standardized cohorts of patients at risk for Alzheimer's
disease. Their relation to pathophysiological markers of Alzheimer's disease
remains to be studied.
|
[
{
"created": "Wed, 19 Dec 2018 15:44:51 GMT",
"version": "v1"
}
] |
2018-12-20
|
[
[
"Epelbaum",
"Stéphane",
"",
"ICM, IM2A, UPMC"
],
[
"Bouteloup",
"Vincent",
"",
"ISPED, BPH"
],
[
"Mangin",
"Jean",
"",
"CATI, NEUROSPIN"
],
[
"La Corte",
"Valentina",
"",
"UPD5 Psychologie, CPN -\n U894"
],
[
"Migliaccio",
"Raffaela",
"",
"ICM, IM2A, UPMC"
],
[
"Bertin",
"Hugo",
"",
"LIB, CATI, UPMC"
],
[
"Habert",
"Marie O.",
"",
"LIB, CATI, UPMC"
],
[
"Fischer",
"Clara",
"",
"CATI, NEUROSPIN"
],
[
"Azouani",
"Chabha",
"",
"CATI"
],
[
"Fillon",
"Ludovic",
"",
"CATI"
],
[
"Chupin",
"Marie",
"",
"CATI"
],
[
"Vellas",
"Bruno",
"",
"BPH, ISPED"
],
[
"Pasquier",
"Florence",
"",
"BPH, ISPED"
],
[
"Dartigues",
"Jean",
"",
"BPH, ISPED"
],
[
"Blanc",
"Frédéric",
"",
"CHRU Montpellier"
],
[
"Gabelle",
"Audrey",
"",
"CHRU Montpellier"
],
[
"Ceccaldi",
"Mathieu",
"",
"INS, TIMONE"
],
[
"Krolak-Salmon",
"Pierre",
"",
"HCL"
],
[
"Hugon",
"Jacques",
"",
"UPD7"
],
[
"Hanon",
"Olivier",
"",
"UPD5"
],
[
"Rouaud",
"Olivier",
"",
"CHU Dijon"
],
[
"David",
"Renaud",
"",
"CMRR Nice"
],
[
"Chêne",
"Geneviève",
"",
"BPH,\n ISPED"
],
[
"Dubois",
"Bruno",
"",
"IM2A, ICM, UPMC"
],
[
"Dufouil",
"Carole",
"",
"BPH, ISPED"
]
] |
IntroductionThe free and cued selective reminding test is used to identify memory deficits in mild cognitive impairment and demented patients. It allows assessing three processes: encoding, storage, and recollection of verbal episodic memory.MethodsWe investigated the neural correlates of these three memory processes in a large cohort study. The Memento cohort enrolled 2323 outpatients presenting either with subjective cognitive decline or mild cognitive impairment who underwent cognitive, structural MRI and, for a subset, fluorodeoxyglucose--positron emission tomography evaluations.ResultsEncoding was associated with a network including parietal and temporal cortices; storage was mainly associated with entorhinal and parahippocampal regions, bilaterally; retrieval was associated with a widespread network encompassing frontal regions.DiscussionThe neural correlates of episodic memory processes can be assessed in large and standardized cohorts of patients at risk for Alzheimer's disease. Their relation to pathophysiological markers of Alzheimer's disease remains to be studied.
|
1511.01810
|
Sebastien Benzekry
|
S\'ebastien Benzekry (IMB, MONC), J. M. L. Ebos
|
On the growth and dissemination laws in a mathematical model of
metastatic growth
| null | null | null | null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Metastasis represents one of the main clinical challenge in cancer treatment
since it is associated with the majority of deaths. Recent technological
advances allow quantification of the dynamics of the process by means of
noninvasive techniques such as longitudinal tracking of bioluminescent cells.
The metastatic process was simplified here into two essential components --
dissemination and colonization -- which were mathematically formalized in terms
of simple quantitative laws. The resulting mathematical model was confronted to
in vivo experimental data of spontaneous metastasis after primary tumor
resection. We discuss how much information can be inferred from confrontation
of theories to the data with emphasis on identifiability issues. It is shown
that two mutually exclusive assumptions for the secondary growth law (namely
same or different from the primary tumor growth law) could fit equally well the
data. Similarly, the fractal dimension coefficient in the dissemination law
could not be uniquely determined from data on total metastatic burden only.
Together, these results delimitate the range of information that can be
recovered from fitting data of metastatic growth to already simplified
mathematical models.
|
[
{
"created": "Wed, 4 Nov 2015 12:59:36 GMT",
"version": "v1"
}
] |
2015-11-06
|
[
[
"Benzekry",
"Sébastien",
"",
"IMB, MONC"
],
[
"Ebos",
"J. M. L.",
""
]
] |
Metastasis represents one of the main clinical challenge in cancer treatment since it is associated with the majority of deaths. Recent technological advances allow quantification of the dynamics of the process by means of noninvasive techniques such as longitudinal tracking of bioluminescent cells. The metastatic process was simplified here into two essential components -- dissemination and colonization -- which were mathematically formalized in terms of simple quantitative laws. The resulting mathematical model was confronted to in vivo experimental data of spontaneous metastasis after primary tumor resection. We discuss how much information can be inferred from confrontation of theories to the data with emphasis on identifiability issues. It is shown that two mutually exclusive assumptions for the secondary growth law (namely same or different from the primary tumor growth law) could fit equally well the data. Similarly, the fractal dimension coefficient in the dissemination law could not be uniquely determined from data on total metastatic burden only. Together, these results delimitate the range of information that can be recovered from fitting data of metastatic growth to already simplified mathematical models.
|
2308.14715
|
Ethan Levien
|
Ethan Levien
|
Coalescent processes emerging from large deviations
|
15 pages, 3 figures. Major revision incorporating comments from
anonymous referees
| null | null | null |
q-bio.PE cond-mat.stat-mech
|
http://creativecommons.org/licenses/by/4.0/
|
The classical model for the genealogies of a neutrally evolving population in
a fixed environment is due to Kingman. Kingman's coalescent process, which
produces a binary tree, universally emerges from many microscopic models in
which the variance in the number of offspring is finite. It is understood that
power-law offspring distributions with infinite variance can result in a very
different type of coalescent structure with merging of more than two lineages.
Here we investigate the regime where the variance of the offspring distribution
is finite but comparable to the population size. This is achieved by studying a
model in which the log offspring sizes have a stretched exponential form. Such
offspring distributions are motivated by biology, where they emerge from a toy
model of growth in a heterogenous environment, but also mathematics and
statistical physics, where limit theorems and phase transitions for sums over
random exponentials have received considerable attention due to their
appearance in the partition function of Derrida's Random Energy Model (REM). We
find that the limit coalescent is a $\beta$-coalescent -- a previously studied
model emerging from evolutionary dynamics models with heavy-tailed offspring
distributions. We also discuss the connection to previous results on the REM.
|
[
{
"created": "Mon, 28 Aug 2023 17:15:54 GMT",
"version": "v1"
},
{
"created": "Tue, 5 Sep 2023 01:22:17 GMT",
"version": "v2"
},
{
"created": "Mon, 4 Dec 2023 16:13:45 GMT",
"version": "v3"
}
] |
2023-12-05
|
[
[
"Levien",
"Ethan",
""
]
] |
The classical model for the genealogies of a neutrally evolving population in a fixed environment is due to Kingman. Kingman's coalescent process, which produces a binary tree, universally emerges from many microscopic models in which the variance in the number of offspring is finite. It is understood that power-law offspring distributions with infinite variance can result in a very different type of coalescent structure with merging of more than two lineages. Here we investigate the regime where the variance of the offspring distribution is finite but comparable to the population size. This is achieved by studying a model in which the log offspring sizes have a stretched exponential form. Such offspring distributions are motivated by biology, where they emerge from a toy model of growth in a heterogenous environment, but also mathematics and statistical physics, where limit theorems and phase transitions for sums over random exponentials have received considerable attention due to their appearance in the partition function of Derrida's Random Energy Model (REM). We find that the limit coalescent is a $\beta$-coalescent -- a previously studied model emerging from evolutionary dynamics models with heavy-tailed offspring distributions. We also discuss the connection to previous results on the REM.
|
2307.16231
|
R\'edoane Daoudi
|
R\'edoane Daoudi
|
Strategies for targeting chondrosarcomas in vivo and molecular
dissection of oncogenic events in chondrosarcomas: is epigenetics the
culprit?
|
21 pages, 1 figure, 1 table
| null | null | null |
q-bio.MN q-bio.SC
|
http://creativecommons.org/licenses/by/4.0/
|
It is obvious that both epigenetic and non-epigenetic actors contribute to
tumorigenesis in chondrosarcomas and more generally in other cancers. Thus, the
main altered pathways in chondrosarcomas are now well established and include
both epigenetic and non-epigenetic pathways such as the PI3K-AKT signaling,
EGFR overexpression, SPARC overexpression, c-myc overexpression, IHH/GLI1 axis,
loss of Rb function, HIF1-alpha stabilization, IDH1 mutations, hypermethylation
and SIRT1. This review aims to provide a detailed analysis of these pathways
and highlights recurrent interactions between non-epigenetic and epigenetic
actors in chondrosarcomas, raising the intriguing possibility of developing
therapeutics targeting both epigenetic and non-epigenetic actors and supporting
data from previous studies. Finally, we propose some strategies for targeting
chondrosarcomas in vivo based on properties of this tumor.
|
[
{
"created": "Sun, 30 Jul 2023 13:43:33 GMT",
"version": "v1"
}
] |
2023-08-01
|
[
[
"Daoudi",
"Rédoane",
""
]
] |
It is obvious that both epigenetic and non-epigenetic actors contribute to tumorigenesis in chondrosarcomas and more generally in other cancers. Thus, the main altered pathways in chondrosarcomas are now well established and include both epigenetic and non-epigenetic pathways such as the PI3K-AKT signaling, EGFR overexpression, SPARC overexpression, c-myc overexpression, IHH/GLI1 axis, loss of Rb function, HIF1-alpha stabilization, IDH1 mutations, hypermethylation and SIRT1. This review aims to provide a detailed analysis of these pathways and highlights recurrent interactions between non-epigenetic and epigenetic actors in chondrosarcomas, raising the intriguing possibility of developing therapeutics targeting both epigenetic and non-epigenetic actors and supporting data from previous studies. Finally, we propose some strategies for targeting chondrosarcomas in vivo based on properties of this tumor.
|
1511.04001
|
Burkhard Morgenstern
|
Lars Hahn, Chris-Andr\'e Leimeister, Rachid Ounit, Stefano Lonardi,
Burkhard Morgenstern
|
RasBhari: optimizing spaced seeds for database searching, read mapping
and alignment-free sequence comparison
| null | null |
10.1371/journal.pcbi.1005107
| null |
q-bio.GN cs.DS q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Many algorithms for sequence analysis rely on word matching or word
statistics. Often, these approaches can be improved if binary patterns
representing match and don't-care positions are used as a filter, such that
only those positions of words are considered that correspond to the match
positions of the patterns. The performance of these approaches, however,
depends on the underlying patterns. Herein, we show that the overlap complexity
of a pattern set that was introduced by Ilie and Ilie is closely related to the
variance of the number of matches between two evolutionarily related sequences
with respect to this pattern set. We propose a modified hill-climbing algorithm
to optimize pattern sets for database searching, read mapping and
alignment-free sequence comparison of nucleic-acid sequences; our
implementation of this algorithm is called rasbhari. Depending on the
application at hand, rasbhari can either minimize the overlap complexity of
pattern sets, maximize their sensitivity in database searching or minimize the
variance of the number of pattern-based matches in alignment-free sequence
comparison. We show that, for database searching, rasbhari generates pattern
sets with slightly higher sensitivity than existing approaches. In our Spaced
Words approach to alignment-free sequence comparison, pattern sets calculated
with rasbhari led to more accurate estimates of phylogenetic distances than the
randomly generated pattern sets that we previously used. Finally, we used
rasbhari to generate patterns for short read classification with CLARK-S. Here
too, the sensitivity of the results could be improved, compared to the default
patterns of the program. We integrated rasbhari into Spaced Words; the source
code of rasbhari is freely available at http://rasbhari.gobics.de/
|
[
{
"created": "Thu, 12 Nov 2015 18:48:08 GMT",
"version": "v1"
},
{
"created": "Wed, 20 Jul 2016 13:06:46 GMT",
"version": "v2"
}
] |
2017-02-08
|
[
[
"Hahn",
"Lars",
""
],
[
"Leimeister",
"Chris-André",
""
],
[
"Ounit",
"Rachid",
""
],
[
"Lonardi",
"Stefano",
""
],
[
"Morgenstern",
"Burkhard",
""
]
] |
Many algorithms for sequence analysis rely on word matching or word statistics. Often, these approaches can be improved if binary patterns representing match and don't-care positions are used as a filter, such that only those positions of words are considered that correspond to the match positions of the patterns. The performance of these approaches, however, depends on the underlying patterns. Herein, we show that the overlap complexity of a pattern set that was introduced by Ilie and Ilie is closely related to the variance of the number of matches between two evolutionarily related sequences with respect to this pattern set. We propose a modified hill-climbing algorithm to optimize pattern sets for database searching, read mapping and alignment-free sequence comparison of nucleic-acid sequences; our implementation of this algorithm is called rasbhari. Depending on the application at hand, rasbhari can either minimize the overlap complexity of pattern sets, maximize their sensitivity in database searching or minimize the variance of the number of pattern-based matches in alignment-free sequence comparison. We show that, for database searching, rasbhari generates pattern sets with slightly higher sensitivity than existing approaches. In our Spaced Words approach to alignment-free sequence comparison, pattern sets calculated with rasbhari led to more accurate estimates of phylogenetic distances than the randomly generated pattern sets that we previously used. Finally, we used rasbhari to generate patterns for short read classification with CLARK-S. Here too, the sensitivity of the results could be improved, compared to the default patterns of the program. We integrated rasbhari into Spaced Words; the source code of rasbhari is freely available at http://rasbhari.gobics.de/
|
1801.04825
|
Radha Srinivasan
|
Kiran Vishwasrao, Yasmin Khan and S. Radha
|
The cellular uptake mechanism of SPIONs: an in-vitro study
|
8 pages, 3 figures, Part of work presented at International
Conference of Magnetism 2012 (Busan, S.Korea)
| null | null | null |
q-bio.CB cond-mat.soft physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The Superparamagnetic Iron Oxide Nanoparticles (SPIONs) of sizes ranging from
10-50 nm are being used in a large number of biological studies because of
their peculiar characteristics of inducing local hyperthermia, MR imaging,
specific targeting and drug delivery. An in-vitro study of the cytotoxicity and
an understanding of the specific pathway of cellular uptake will enable
manipulation of conditions for optimal cellular uptake of SPIONs for targeted
therapy. The objective of the present study was to identify the endocytotic
pathway through which the SPIONs are taken up by C6 glioma cells. The cells
were pre-incubated with different concentrations of pharmacological inhibitors
and then exposed to SPIONs for a few hours. The endocytosed particles were
localized and quantitatively estimated using Perl's or Prussian Blue reaction.
There was significant reduction in the uptake of SPIONs when incubated with the
inhibitor indicating the uptake of nanoparticles is being inhibited. This
reduction in SPION uptake was found to be dependent on the concentration of the
inhibitors and also the nature of the inhibitors. By a systematic study of
choosing various inhibitors, the data can be narrowed down to the final pathway
that may be involved in the SPION uptake. The present preliminary investigation
is expected to provide insight of testing the possible mechanisms with
complementary techniques.
|
[
{
"created": "Mon, 15 Jan 2018 14:40:35 GMT",
"version": "v1"
}
] |
2018-01-16
|
[
[
"Vishwasrao",
"Kiran",
""
],
[
"Khan",
"Yasmin",
""
],
[
"Radha",
"S.",
""
]
] |
The Superparamagnetic Iron Oxide Nanoparticles (SPIONs) of sizes ranging from 10-50 nm are being used in a large number of biological studies because of their peculiar characteristics of inducing local hyperthermia, MR imaging, specific targeting and drug delivery. An in-vitro study of the cytotoxicity and an understanding of the specific pathway of cellular uptake will enable manipulation of conditions for optimal cellular uptake of SPIONs for targeted therapy. The objective of the present study was to identify the endocytotic pathway through which the SPIONs are taken up by C6 glioma cells. The cells were pre-incubated with different concentrations of pharmacological inhibitors and then exposed to SPIONs for a few hours. The endocytosed particles were localized and quantitatively estimated using Perl's or Prussian Blue reaction. There was significant reduction in the uptake of SPIONs when incubated with the inhibitor indicating the uptake of nanoparticles is being inhibited. This reduction in SPION uptake was found to be dependent on the concentration of the inhibitors and also the nature of the inhibitors. By a systematic study of choosing various inhibitors, the data can be narrowed down to the final pathway that may be involved in the SPION uptake. The present preliminary investigation is expected to provide insight of testing the possible mechanisms with complementary techniques.
|
2204.01847
|
Qi Zhang
|
Qi Zhang, Chang Liu, Stephen Wu and Ryo Yoshida
|
Bayesian Sequential Stacking Algorithm for Concurrently Designing
Molecules and Synthetic Reaction Networks
| null | null | null | null |
q-bio.BM cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In the last few years, de novo molecular design using machine learning has
made great technical progress but its practical deployment has not been as
successful. This is mostly owing to the cost and technical difficulty of
synthesizing such computationally designed molecules. To overcome such
barriers, various methods for synthetic route design using deep neural networks
have been studied intensively in recent years. However, little progress has
been made in designing molecules and their synthetic routes simultaneously.
Here, we formulate the problem of simultaneously designing molecules with the
desired set of properties and their synthetic routes within the framework of
Bayesian inference. The design variables consist of a set of reactants in a
reaction network and its network topology. The design space is extremely large
because it consists of all combinations of purchasable reactants, often in the
order of millions or more. In addition, the designed reaction networks can
adopt any topology beyond simple multistep linear reaction routes. To solve
this hard combinatorial problem, we present a powerful sequential Monte Carlo
algorithm that recursively designs a synthetic reaction network by sequentially
building up single-step reactions. In a case study of designing drug-like
molecules based on commercially available compounds, compared with heuristic
combinatorial search methods, the proposed method shows overwhelming
performance in terms of computational efficiency and coverage and novelty with
respect to existing compounds.
|
[
{
"created": "Tue, 1 Mar 2022 14:55:32 GMT",
"version": "v1"
}
] |
2022-04-06
|
[
[
"Zhang",
"Qi",
""
],
[
"Liu",
"Chang",
""
],
[
"Wu",
"Stephen",
""
],
[
"Yoshida",
"Ryo",
""
]
] |
In the last few years, de novo molecular design using machine learning has made great technical progress but its practical deployment has not been as successful. This is mostly owing to the cost and technical difficulty of synthesizing such computationally designed molecules. To overcome such barriers, various methods for synthetic route design using deep neural networks have been studied intensively in recent years. However, little progress has been made in designing molecules and their synthetic routes simultaneously. Here, we formulate the problem of simultaneously designing molecules with the desired set of properties and their synthetic routes within the framework of Bayesian inference. The design variables consist of a set of reactants in a reaction network and its network topology. The design space is extremely large because it consists of all combinations of purchasable reactants, often in the order of millions or more. In addition, the designed reaction networks can adopt any topology beyond simple multistep linear reaction routes. To solve this hard combinatorial problem, we present a powerful sequential Monte Carlo algorithm that recursively designs a synthetic reaction network by sequentially building up single-step reactions. In a case study of designing drug-like molecules based on commercially available compounds, compared with heuristic combinatorial search methods, the proposed method shows overwhelming performance in terms of computational efficiency and coverage and novelty with respect to existing compounds.
|
2306.08015
|
Reindorf Borkor
|
Reindorf Nartey Borkor and Adu Sakyi and Peter Amoako-Yirenkyi
|
Investigation of Fractional Compartmental Models with Application to
Amiodarone Drug Diffusion in Pharmacokinetics
| null | null | null | null |
q-bio.QM cs.NA math.NA
|
http://creativecommons.org/licenses/by/4.0/
|
This paper presents three fractional models formulated from a classical
Pharmacokinetics compartmental system: commensurable, non-commensurable, and
implicit non-commensurable models. Their distinguishing characteristics are
further examined comprehensively. Because analytic solutions for such models
are typically challenging to obtain, we study the application of the Fractional
Finite Difference Method (FFDM) to simulate approximate solutions. The
characteristic of the non-commensurable model is shown to be incompatible with
the concept of mass balance. However, it appeared to outlast fractional
calculus theory when simulating anomalous kinetics. We proved this by fitting
the proposed fractional and classical models to an experimental data set
(amiodarone) and estimated the parameters using the least-square approach. The
classical model diverged, but the non-commensurable model predicted a fit
comparable to the other two fractional models. The fractional models described
anomalous diffusion better than classical theories. The numerical results
showed that the proposed numerical method is equally efficient in solving any
complex compartmental models, as they performed well in simulations for the
classic example of the model.
|
[
{
"created": "Tue, 13 Jun 2023 12:23:26 GMT",
"version": "v1"
}
] |
2023-06-16
|
[
[
"Borkor",
"Reindorf Nartey",
""
],
[
"Sakyi",
"Adu",
""
],
[
"Amoako-Yirenkyi",
"Peter",
""
]
] |
This paper presents three fractional models formulated from a classical Pharmacokinetics compartmental system: commensurable, non-commensurable, and implicit non-commensurable models. Their distinguishing characteristics are further examined comprehensively. Because analytic solutions for such models are typically challenging to obtain, we study the application of the Fractional Finite Difference Method (FFDM) to simulate approximate solutions. The characteristic of the non-commensurable model is shown to be incompatible with the concept of mass balance. However, it appeared to outlast fractional calculus theory when simulating anomalous kinetics. We proved this by fitting the proposed fractional and classical models to an experimental data set (amiodarone) and estimated the parameters using the least-square approach. The classical model diverged, but the non-commensurable model predicted a fit comparable to the other two fractional models. The fractional models described anomalous diffusion better than classical theories. The numerical results showed that the proposed numerical method is equally efficient in solving any complex compartmental models, as they performed well in simulations for the classic example of the model.
|
1611.02272
|
Alexander Tait
|
Alexander N. Tait, Thomas Ferreira de Lima, Ellen Zhou, Allie X. Wu,
Mitchell A. Nahmias, Bhavin J. Shastri, and Paul R. Prucnal
|
Neuromorphic Silicon Photonic Networks
|
12 pages, 4 figures, accepted in Scientific Reports
|
Sci.Rep. 7 (2017) 7430
|
10.1038/s41598-017-07754-z
| null |
q-bio.NC cs.NE physics.optics
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Photonic systems for high-performance information processing have attracted
renewed interest. Neuromorphic silicon photonics has the potential to integrate
processing functions that vastly exceed the capabilities of electronics. We
report first observations of a recurrent silicon photonic neural network, in
which connections are configured by microring weight banks. A mathematical
isomorphism between the silicon photonic circuit and a continuous neural
network model is demonstrated through dynamical bifurcation analysis.
Exploiting this isomorphism, a simulated 24-node silicon photonic neural
network is programmed using "neural compiler" to solve a differential system
emulation task. A 294-fold acceleration against a conventional benchmark is
predicted. We also propose and derive power consumption analysis for
modulator-class neurons that, as opposed to laser-class neurons, are compatible
with silicon photonic platforms. At increased scale, Neuromorphic silicon
photonics could access new regimes of ultrafast information processing for
radio, control, and scientific computing.
|
[
{
"created": "Sat, 5 Nov 2016 00:15:59 GMT",
"version": "v1"
},
{
"created": "Wed, 22 Mar 2017 17:35:37 GMT",
"version": "v2"
},
{
"created": "Mon, 12 Jun 2017 15:56:45 GMT",
"version": "v3"
}
] |
2017-11-17
|
[
[
"Tait",
"Alexander N.",
""
],
[
"de Lima",
"Thomas Ferreira",
""
],
[
"Zhou",
"Ellen",
""
],
[
"Wu",
"Allie X.",
""
],
[
"Nahmias",
"Mitchell A.",
""
],
[
"Shastri",
"Bhavin J.",
""
],
[
"Prucnal",
"Paul R.",
""
]
] |
Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.
|
1603.09415
|
Benjamin Drinkwater
|
Benjamin Drinkwater, Angela Qiao, and Michael A. Charleston
|
WiSPA: A new approach for dealing with widespread parasitism
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Traditionally, studies of coevolving systems have considered cases where a
parasite may inhabit only a single host. The case where a parasite may infect
many hosts, widespread parasitism, has until recently gained little traction.
This is due in part to the computational complexity involved in reconstructing
the coevolutionary histories where parasites may infect only a single host,
which is NP-Hard. Allowing parasites to inhabit more than one host has been
seen to only further compound this computationally intractable problem.
Recently however, well-established algorithms for estimating the problem
instance where a parasite may infect only a single host have been extended to
handle widespread parasites. Although this has offered significant progress, it
has been noted that these algorithms poorly handle parasites that inhabit
phylogenetically distant hosts.
In this work we extend these previous algorithms to handle cases where
parasites inhabit phylogenetically distant hosts using an additional
evolutionary event which we call spread. Our new framework is shown to infer
significantly more congruent coevolutionary histories compared to existing
methods over both synthetic and biological data sets. We then apply the newly
proposed algorithm, which we call WiSPA (WideSpread Parasitism Analyser), to
the well studied coevolutionary system of Primates and Enterobius (pinworms),
where existing methods have been unable to reconcile the widespread parasitism
present without permitting additional divergence events. Using WiSPA and the
new biological event, spread, we provide the first statistically significant
coevolutionary hypothesis for this system.
|
[
{
"created": "Wed, 30 Mar 2016 23:32:50 GMT",
"version": "v1"
}
] |
2016-04-01
|
[
[
"Drinkwater",
"Benjamin",
""
],
[
"Qiao",
"Angela",
""
],
[
"Charleston",
"Michael A.",
""
]
] |
Traditionally, studies of coevolving systems have considered cases where a parasite may inhabit only a single host. The case where a parasite may infect many hosts, widespread parasitism, has until recently gained little traction. This is due in part to the computational complexity involved in reconstructing the coevolutionary histories where parasites may infect only a single host, which is NP-Hard. Allowing parasites to inhabit more than one host has been seen to only further compound this computationally intractable problem. Recently however, well-established algorithms for estimating the problem instance where a parasite may infect only a single host have been extended to handle widespread parasites. Although this has offered significant progress, it has been noted that these algorithms poorly handle parasites that inhabit phylogenetically distant hosts. In this work we extend these previous algorithms to handle cases where parasites inhabit phylogenetically distant hosts using an additional evolutionary event which we call spread. Our new framework is shown to infer significantly more congruent coevolutionary histories compared to existing methods over both synthetic and biological data sets. We then apply the newly proposed algorithm, which we call WiSPA (WideSpread Parasitism Analyser), to the well studied coevolutionary system of Primates and Enterobius (pinworms), where existing methods have been unable to reconcile the widespread parasitism present without permitting additional divergence events. Using WiSPA and the new biological event, spread, we provide the first statistically significant coevolutionary hypothesis for this system.
|
1402.5327
|
Jian-Jun Shu
|
Jian-Jun Shu, Kian Yan Yong and Weng Kong Chan
|
An improved scoring matrix for multiple sequence alignment
| null |
Mathematical Problems in Engineering, Vol. 2012, No. 490649, pp.
1-9, 2012
|
10.1155/2012/490649
| null |
q-bio.QM q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The way for performing multiple sequence alignment is based on the criterion
of the maximum scored information content computed from a weight matrix, but it
is possible to have two or more alignments to have the same highest score
leading to ambiguities in selecting the best alignment. This paper addresses
this issue by introducing the concept of joint weight matrix to eliminate the
randomness in selecting the best multiple sequence alignment. Alignments with
equal scores are iteratively rescored with the joint weight matrix of
increasing level (nucleotide pairs, triplets and so on) until one single best
alignment is eventually found. This method for resolving ambiguity in multiple
sequence alignment can be easily implemented by use of the improved scoring
matrix.
|
[
{
"created": "Fri, 21 Feb 2014 15:44:25 GMT",
"version": "v1"
},
{
"created": "Fri, 28 Feb 2014 14:20:00 GMT",
"version": "v2"
}
] |
2014-03-03
|
[
[
"Shu",
"Jian-Jun",
""
],
[
"Yong",
"Kian Yan",
""
],
[
"Chan",
"Weng Kong",
""
]
] |
The way for performing multiple sequence alignment is based on the criterion of the maximum scored information content computed from a weight matrix, but it is possible to have two or more alignments to have the same highest score leading to ambiguities in selecting the best alignment. This paper addresses this issue by introducing the concept of joint weight matrix to eliminate the randomness in selecting the best multiple sequence alignment. Alignments with equal scores are iteratively rescored with the joint weight matrix of increasing level (nucleotide pairs, triplets and so on) until one single best alignment is eventually found. This method for resolving ambiguity in multiple sequence alignment can be easily implemented by use of the improved scoring matrix.
|
1309.3312
|
Armita Nourmohammad
|
Armita Nourmohammad, Torsten Held, Michael L\"assig
|
Universality and predictability in molecular quantitative genetics
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Molecular traits, such as gene expression levels or protein binding
affinities, are increasingly accessible to quantitative measurement by modern
high-throughput techniques. Such traits measure molecular functions and, from
an evolutionary point of view, are important as targets of natural selection.
We review recent developments in evolutionary theory and experiments that are
expected to become building blocks of a quantitative genetics of molecular
traits. We focus on universal evolutionary characteristics: these are largely
independent of a trait's genetic basis, which is often at least partially
unknown. We show that universal measurements can be used to infer selection on
a quantitative trait, which determines its evolutionary mode of conservation or
adaptation. Furthermore, universality is closely linked to predictability of
trait evolution across lineages. We argue that universal trait statistics
extends over a range of cellular scales and opens new avenues of quantitative
evolutionary systems biology.
|
[
{
"created": "Thu, 12 Sep 2013 21:30:16 GMT",
"version": "v1"
},
{
"created": "Thu, 14 Nov 2013 15:23:28 GMT",
"version": "v2"
}
] |
2013-11-15
|
[
[
"Nourmohammad",
"Armita",
""
],
[
"Held",
"Torsten",
""
],
[
"Lässig",
"Michael",
""
]
] |
Molecular traits, such as gene expression levels or protein binding affinities, are increasingly accessible to quantitative measurement by modern high-throughput techniques. Such traits measure molecular functions and, from an evolutionary point of view, are important as targets of natural selection. We review recent developments in evolutionary theory and experiments that are expected to become building blocks of a quantitative genetics of molecular traits. We focus on universal evolutionary characteristics: these are largely independent of a trait's genetic basis, which is often at least partially unknown. We show that universal measurements can be used to infer selection on a quantitative trait, which determines its evolutionary mode of conservation or adaptation. Furthermore, universality is closely linked to predictability of trait evolution across lineages. We argue that universal trait statistics extends over a range of cellular scales and opens new avenues of quantitative evolutionary systems biology.
|
2406.12625
|
Polina Turishcheva
|
Polina Turishcheva, Max Burg, Fabian H. Sinz, Alexander Ecker
|
Reproducibility of predictive networks for mouse visual cortex
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Deep predictive models of neuronal activity have recently enabled several new
discoveries about the selectivity and invariance of neurons in the visual
cortex. These models learn a shared set of nonlinear basis functions, which are
linearly combined via a learned weight vector to represent a neuron's function.
Such weight vectors, which can be thought as embeddings of neuronal function,
have been proposed to define functional cell types via unsupervised clustering.
However, as deep models are usually highly overparameterized, the learning
problem is unlikely to have a unique solution, which raises the question if
such embeddings can be used in a meaningful way for downstream analysis. In
this paper, we investigate how stable neuronal embeddings are with respect to
changes in model architecture and initialization. We find that $L_1$
regularization to be an important ingredient for structured embeddings and
develop an adaptive regularization that adjusts the strength of regularization
per neuron. This regularization improves both predictive performance and how
consistently neuronal embeddings cluster across model fits compared to uniform
regularization. To overcome overparametrization, we propose an iterative
feature pruning strategy which reduces the dimensionality of
performance-optimized models by half without loss of performance and improves
the consistency of neuronal embeddings with respect to clustering neurons. This
result suggests that to achieve an objective taxonomy of cell types or a
compact representation of the functional landscape, we need novel architectures
or learning techniques that improve identifiability. We will make our code
available at publication time.
|
[
{
"created": "Tue, 18 Jun 2024 13:50:08 GMT",
"version": "v1"
}
] |
2024-06-19
|
[
[
"Turishcheva",
"Polina",
""
],
[
"Burg",
"Max",
""
],
[
"Sinz",
"Fabian H.",
""
],
[
"Ecker",
"Alexander",
""
]
] |
Deep predictive models of neuronal activity have recently enabled several new discoveries about the selectivity and invariance of neurons in the visual cortex. These models learn a shared set of nonlinear basis functions, which are linearly combined via a learned weight vector to represent a neuron's function. Such weight vectors, which can be thought as embeddings of neuronal function, have been proposed to define functional cell types via unsupervised clustering. However, as deep models are usually highly overparameterized, the learning problem is unlikely to have a unique solution, which raises the question if such embeddings can be used in a meaningful way for downstream analysis. In this paper, we investigate how stable neuronal embeddings are with respect to changes in model architecture and initialization. We find that $L_1$ regularization to be an important ingredient for structured embeddings and develop an adaptive regularization that adjusts the strength of regularization per neuron. This regularization improves both predictive performance and how consistently neuronal embeddings cluster across model fits compared to uniform regularization. To overcome overparametrization, we propose an iterative feature pruning strategy which reduces the dimensionality of performance-optimized models by half without loss of performance and improves the consistency of neuronal embeddings with respect to clustering neurons. This result suggests that to achieve an objective taxonomy of cell types or a compact representation of the functional landscape, we need novel architectures or learning techniques that improve identifiability. We will make our code available at publication time.
|
2005.13692
|
Sergei Chekmarev F.
|
Sergei F. Chekmarev
|
First-Passage Time Distributions in Two-State Protein Folding Kinetics:
Exploring the Native-Like States vs Overcoming the Free Energy Barrier
|
27 pages, 21 figures
| null |
10.1039/D0CP06560A
| null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Using a beta-hairpin protein as a representative example of two-state
folders, we studied how the exploration of native-like states affects the
folding kinetics. It has been found that the first-passage time (FPT)
distributions are essentially single-exponential not only for the times to
overcome the free energy barrier that separates unfolded and native-like states
but also for the times to find the native state among the native-like ones. If
the protein explores native-like states for a time much longer than the time to
overcome the free energy barrier, which was found to be characteristic of high
temperatures, the resulting FPT distribution to reach the native state remains
close to exponential but the mean FPT (MFPT) is determined not by the height of
the free energy barrier but by the time to explore native-like states. The mean
time to overcome the free energy barrier is found to be in reasonable agreement
with the Kramers rate formula and generally far shorter than the MFPT to reach
the native state. The time to find the native state among native-like ones
increases with temperature, which explains the known U-shape dependence of the
MFPTs on temperature.
|
[
{
"created": "Wed, 27 May 2020 22:41:53 GMT",
"version": "v1"
},
{
"created": "Thu, 6 Aug 2020 19:13:16 GMT",
"version": "v2"
}
] |
2021-11-16
|
[
[
"Chekmarev",
"Sergei F.",
""
]
] |
Using a beta-hairpin protein as a representative example of two-state folders, we studied how the exploration of native-like states affects the folding kinetics. It has been found that the first-passage time (FPT) distributions are essentially single-exponential not only for the times to overcome the free energy barrier that separates unfolded and native-like states but also for the times to find the native state among the native-like ones. If the protein explores native-like states for a time much longer than the time to overcome the free energy barrier, which was found to be characteristic of high temperatures, the resulting FPT distribution to reach the native state remains close to exponential but the mean FPT (MFPT) is determined not by the height of the free energy barrier but by the time to explore native-like states. The mean time to overcome the free energy barrier is found to be in reasonable agreement with the Kramers rate formula and generally far shorter than the MFPT to reach the native state. The time to find the native state among native-like ones increases with temperature, which explains the known U-shape dependence of the MFPTs on temperature.
|
2201.03306
|
Diederik Aerts
|
Diederik Aerts and Lester Beltran
|
A Planck Radiation and Quantization Scheme for Human Cognition and
Language
|
7 figures
|
Frontiers in Psychology 13, 850725 (2022)
|
10.3389/fpsyg.2022.850725
| null |
q-bio.NC cs.CL quant-ph
|
http://creativecommons.org/licenses/by/4.0/
|
As a result of the identification of 'identity' and 'indistinguishability'
and strong experimental evidence for the presence of the associated
Bose-Einstein statistics in human cognition and language, we argued in previous
work for an extension of the research domain of quantum cognition. In addition
to quantum complex vector spaces and quantum probability models, we showed that
quantization itself, with words as quanta, is relevant and potentially
important to human cognition. In the present work, we build on this result, and
introduce a powerful radiation quantization scheme for human cognition. We show
that the lack of independence of the Bose-Einstein statistics compared to the
Maxwell-Boltzmann statistics can be explained by the presence of a 'meaning
dynamics', which causes words to be attracted to the same words. And so words
clump together in the same states, a phenomenon well known for photons in the
early years of quantum mechanics, leading to fierce disagreements between
Planck and Einstein. Using a simple example, we introduce all the elements to
get a better and detailed view of this 'meaning dynamics', such as micro and
macro states, and Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac numbers and
weights, and compare this example and its graphs, with the radiation
quantization scheme of a Winnie the Pooh story, also with its graphs. By
connecting a concept directly to human experience, we show that entanglement is
a necessity for preserving the 'meaning dynamics' we identified, and it becomes
clear in what way Fermi-Dirac addresses human memory. Within the human mind, as
a crucial aspect of memory, in spaces with internal parameters, identical words
can nevertheless be assigned different states and hence realize locally and
contextually the necessary distinctiveness, structured by a Pauli exclusion
principle, for human thought to thrive.
|
[
{
"created": "Mon, 10 Jan 2022 12:13:23 GMT",
"version": "v1"
},
{
"created": "Fri, 4 Mar 2022 10:31:22 GMT",
"version": "v2"
}
] |
2023-02-27
|
[
[
"Aerts",
"Diederik",
""
],
[
"Beltran",
"Lester",
""
]
] |
As a result of the identification of 'identity' and 'indistinguishability' and strong experimental evidence for the presence of the associated Bose-Einstein statistics in human cognition and language, we argued in previous work for an extension of the research domain of quantum cognition. In addition to quantum complex vector spaces and quantum probability models, we showed that quantization itself, with words as quanta, is relevant and potentially important to human cognition. In the present work, we build on this result, and introduce a powerful radiation quantization scheme for human cognition. We show that the lack of independence of the Bose-Einstein statistics compared to the Maxwell-Boltzmann statistics can be explained by the presence of a 'meaning dynamics', which causes words to be attracted to the same words. And so words clump together in the same states, a phenomenon well known for photons in the early years of quantum mechanics, leading to fierce disagreements between Planck and Einstein. Using a simple example, we introduce all the elements to get a better and detailed view of this 'meaning dynamics', such as micro and macro states, and Maxwell-Boltzmann, Bose-Einstein and Fermi-Dirac numbers and weights, and compare this example and its graphs, with the radiation quantization scheme of a Winnie the Pooh story, also with its graphs. By connecting a concept directly to human experience, we show that entanglement is a necessity for preserving the 'meaning dynamics' we identified, and it becomes clear in what way Fermi-Dirac addresses human memory. Within the human mind, as a crucial aspect of memory, in spaces with internal parameters, identical words can nevertheless be assigned different states and hence realize locally and contextually the necessary distinctiveness, structured by a Pauli exclusion principle, for human thought to thrive.
|
1804.01217
|
Md Nafiz Hamid
|
Md-Nafiz Hamid
|
Gene Co-expression Network analysis of Lung Squamous Cell Carcinoma data
| null | null | null | null |
q-bio.GN q-bio.MN
|
http://creativecommons.org/licenses/by/4.0/
|
We performed a gene co-expression analysis on Lung Squamous Cell Carcinoma
data to find modules (groups) of genes that may highly impact the growth of
these type of tumors. Additionally, we used cancer survival data to relate
modules to prognostic significance in terms of survival time. Analysis on
RNA-seq data revealed modules which are significant in gene enrichment
analysis. Specifically, two genes - RFC4 and ECT2 - have been found to be
significant in terms of survival time. We also performed a second gene
co-expression analysis on a second dataset of microarray data, and many
significant genes found in this analysis could also be found in the RNA-seq
data implying that these genes might indeed play a crucial role in Lung
Squamous Cancer. All the R code for the analysis can be found at:
\url{https://github.com/nafizh/Gene_coexpression_analysis_lung_cancer}
|
[
{
"created": "Wed, 4 Apr 2018 02:38:26 GMT",
"version": "v1"
}
] |
2018-04-05
|
[
[
"Hamid",
"Md-Nafiz",
""
]
] |
We performed a gene co-expression analysis on Lung Squamous Cell Carcinoma data to find modules (groups) of genes that may highly impact the growth of these type of tumors. Additionally, we used cancer survival data to relate modules to prognostic significance in terms of survival time. Analysis on RNA-seq data revealed modules which are significant in gene enrichment analysis. Specifically, two genes - RFC4 and ECT2 - have been found to be significant in terms of survival time. We also performed a second gene co-expression analysis on a second dataset of microarray data, and many significant genes found in this analysis could also be found in the RNA-seq data implying that these genes might indeed play a crucial role in Lung Squamous Cancer. All the R code for the analysis can be found at: \url{https://github.com/nafizh/Gene_coexpression_analysis_lung_cancer}
|
1410.4711
|
Sarah Hallerberg
|
Heike Vester, Kurt Hammerschmidt, Marc Timme, Sarah Hallerberg
|
Bag-of-calls analysis reveals group-specific vocal repertoire in
long-finned pilot whales
|
under review
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Besides humans, several marine mammal species exhibit prerequisites to evolve
language: high cognitive abilities, flexibility in vocal production and
advanced social interactions. Here, we describe and analyse the vocal
repertoire of long-finned pilot whales (Globicephalus melas) recorded in
northern Norway. Observer based analysis reveals a complex vocal repertoire
with 140 different call types, call sequences, call repetitions and
group-specific differences in the usage of call types. Developing and applying
a new automated analysis method, the bag-of-calls approach, we find that groups
of pilot whales can be distinguished purely by statistical properties of their
vocalisations. Comparing inter-and intra-group differences of ensembles of
calls allows to identify and quantify group-specificity. Consequently, the
bag-of-calls approach is a valid method to specify difference and concordance
in acoustic communication in the absence of exact knowledge about signalers,
which is common observing marine mammals under natural conditions.
|
[
{
"created": "Fri, 17 Oct 2014 13:06:09 GMT",
"version": "v1"
},
{
"created": "Fri, 12 Jun 2015 12:05:44 GMT",
"version": "v2"
}
] |
2015-06-15
|
[
[
"Vester",
"Heike",
""
],
[
"Hammerschmidt",
"Kurt",
""
],
[
"Timme",
"Marc",
""
],
[
"Hallerberg",
"Sarah",
""
]
] |
Besides humans, several marine mammal species exhibit prerequisites to evolve language: high cognitive abilities, flexibility in vocal production and advanced social interactions. Here, we describe and analyse the vocal repertoire of long-finned pilot whales (Globicephalus melas) recorded in northern Norway. Observer based analysis reveals a complex vocal repertoire with 140 different call types, call sequences, call repetitions and group-specific differences in the usage of call types. Developing and applying a new automated analysis method, the bag-of-calls approach, we find that groups of pilot whales can be distinguished purely by statistical properties of their vocalisations. Comparing inter-and intra-group differences of ensembles of calls allows to identify and quantify group-specificity. Consequently, the bag-of-calls approach is a valid method to specify difference and concordance in acoustic communication in the absence of exact knowledge about signalers, which is common observing marine mammals under natural conditions.
|
1207.3811
|
Arda Halu
|
Arda Halu and Ginestra Bianconi
|
Monochromaticity in Neutral Evolutionary Network Models
|
8 pages, 14 figures
|
Phys. Rev. E 86, 066101 (2012)
|
10.1103/PhysRevE.86.066101
| null |
q-bio.MN cond-mat.dis-nn cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recent studies on epistatic networks of model organisms have unveiled a
certain type of modular property called monochromaticity in which the networks
are clusterable into functional modules that interact with each other through
the same type of epistasis. Here we propose and study three epistatic network
models that are inspired by the Duplication-Divergence mechanism to gain
insight into the evolutionary basis of monochromaticity and to test if it can
be explained as the outcome of a neutral evolutionary hypothesis. We show that
the epistatic networks formed by these stochastic evolutionary models have
monochromaticity conflict distributions that are centered close to zero and are
statistically significantly different from their randomized counterparts. In
particular, the last model we propose yields a strictly monochromatic solution.
Our results agree with the monochromaticity findings in real organisms and
point toward the possible role of a neutral mechanism in the evolution of this
phenomenon.
|
[
{
"created": "Mon, 16 Jul 2012 20:05:55 GMT",
"version": "v1"
},
{
"created": "Sat, 17 Nov 2012 05:12:47 GMT",
"version": "v2"
}
] |
2013-05-30
|
[
[
"Halu",
"Arda",
""
],
[
"Bianconi",
"Ginestra",
""
]
] |
Recent studies on epistatic networks of model organisms have unveiled a certain type of modular property called monochromaticity in which the networks are clusterable into functional modules that interact with each other through the same type of epistasis. Here we propose and study three epistatic network models that are inspired by the Duplication-Divergence mechanism to gain insight into the evolutionary basis of monochromaticity and to test if it can be explained as the outcome of a neutral evolutionary hypothesis. We show that the epistatic networks formed by these stochastic evolutionary models have monochromaticity conflict distributions that are centered close to zero and are statistically significantly different from their randomized counterparts. In particular, the last model we propose yields a strictly monochromatic solution. Our results agree with the monochromaticity findings in real organisms and point toward the possible role of a neutral mechanism in the evolution of this phenomenon.
|
2007.13368
|
Henning Stumpf
|
Henning Stumpf (1), Andreja Ambriovi\'c-Ristov (2), Aleksandra
Radenovic (3), Ana-Sun\v{c}ana Smith (1 and 4) ((1) PULS Group, Institute for
Theoretical Physics, Interdisciplinary Center for Nanostructured Films,
Friedrich-Alexander-Universit\"at Erlangen-N\"urnberg, Erlangen, Germany, (2)
Laboratory for Cell Biology and Signalling, Division of Molecular Biology,
Ru{\dj}er Bo\v{s}kovi\'c Institute, Zagreb, Croatia, (3) Laboratory of
Nanoscale Biology, \'Ecole Polytechnique F\'ed\'erale de Lausanne, Lausanne,
Switzerland, (4) Group for Computational Life Sciences, Department of
Physical Chemistry, Ru{\dj}er Bo\v{s}kovi\'c Institute, Zagreb, Croatia)
|
Recent Advances and Prospects in the Research of Nascent Adhesions
|
38 pages, 2 figures, review article
| null |
10.3389/fphys.2020.574371
| null |
q-bio.SC physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Nascent adhesions are submicron transient structures promoting the early
adhesion of cells to the extracellular matrix. Nascent adhesions typically
consist of several tens of integrins, and serve as platforms for the
recruitment and activation of proteins to build mature focal adhesions. They
are also associated with early stage signalling and the mechanoresponse.
Despite their crucial role in sampling the local extracellular matrix, very
little is known about the mechanism of their formation. Consequently, there is
a strong scientific activity focused on elucidating the physical and
biochemical foundation of their development and function. Precisely the results
of this effort will be summarized in this article.
|
[
{
"created": "Mon, 27 Jul 2020 08:35:15 GMT",
"version": "v1"
}
] |
2021-01-19
|
[
[
"Stumpf",
"Henning",
"",
"1 and 4"
],
[
"Ambriović-Ristov",
"Andreja",
"",
"1 and 4"
],
[
"Radenovic",
"Aleksandra",
"",
"1 and 4"
],
[
"Smith",
"Ana-Sunčana",
"",
"1 and 4"
]
] |
Nascent adhesions are submicron transient structures promoting the early adhesion of cells to the extracellular matrix. Nascent adhesions typically consist of several tens of integrins, and serve as platforms for the recruitment and activation of proteins to build mature focal adhesions. They are also associated with early stage signalling and the mechanoresponse. Despite their crucial role in sampling the local extracellular matrix, very little is known about the mechanism of their formation. Consequently, there is a strong scientific activity focused on elucidating the physical and biochemical foundation of their development and function. Precisely the results of this effort will be summarized in this article.
|
1906.07463
|
Tom Chou
|
Renaud Dessalles, Yunbei Pan, Mingtao Xia, Davide Maestrini, Maria R.
D'Orsogna, Tom Chou
|
How heterogeneous thymic output and homeostatic proliferation shape
naive T cell receptor clone abundance distributions
|
significant revision, including improved data fitting, 23 pages, 11
figures
| null | null | null |
q-bio.PE q-bio.TO
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
The set of T cells that express the same T cell receptor (TCR) sequence
represents a T cell clone. The number of different naive T cell clones in an
organism reflects the number of different T cell receptors (TCRs) arising from
recombination of the V(D)J gene segments during T cell development in the
thymus. TCR diversity and more specifically, the clone abundance distribution
is an important factor in immune function. Specific recombination patterns
occur more frequently than others while subsequent interactions between TCRs
and self-antigens are known to trigger proliferation and sustain naive T cell
survival. These processes are TCR-dependent, leading to clone-dependent thymic
export and naive T cell proliferation rates. Using a mean-field approximation
to the solution of a regulated birth-death-immigration model and a modification
arising from sampling, we systematically quantify how TCR-dependent
heterogeneities in immigration and proliferation rates affect the shape of
clone abundance distributions (the number of different clones that are
represented by a specific number of cells, or "clone counts"). By comparing
predicted clone counts derived from our heterogeneous birth-death-immigration
model with experimentally sampled clone abundances, we show that although
heterogeneity in immigration rates causes very little change to predicted
clone-counts, significant heterogeneity in proliferation rates is necessary to
generate the observed abundances with reasonable physiological parameter
values. Our analysis provides constraints among physiological parameters that
are necessary to yield predictions that qualitatively match the data.
Assumptions of the model and potentially other important mechanistic factors
are discussed.
|
[
{
"created": "Tue, 18 Jun 2019 09:33:31 GMT",
"version": "v1"
},
{
"created": "Thu, 5 Mar 2020 04:15:31 GMT",
"version": "v2"
}
] |
2020-03-06
|
[
[
"Dessalles",
"Renaud",
""
],
[
"Pan",
"Yunbei",
""
],
[
"Xia",
"Mingtao",
""
],
[
"Maestrini",
"Davide",
""
],
[
"D'Orsogna",
"Maria R.",
""
],
[
"Chou",
"Tom",
""
]
] |
The set of T cells that express the same T cell receptor (TCR) sequence represents a T cell clone. The number of different naive T cell clones in an organism reflects the number of different T cell receptors (TCRs) arising from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution is an important factor in immune function. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. Using a mean-field approximation to the solution of a regulated birth-death-immigration model and a modification arising from sampling, we systematically quantify how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells, or "clone counts"). By comparing predicted clone counts derived from our heterogeneous birth-death-immigration model with experimentally sampled clone abundances, we show that although heterogeneity in immigration rates causes very little change to predicted clone-counts, significant heterogeneity in proliferation rates is necessary to generate the observed abundances with reasonable physiological parameter values. Our analysis provides constraints among physiological parameters that are necessary to yield predictions that qualitatively match the data. Assumptions of the model and potentially other important mechanistic factors are discussed.
|
2106.14192
|
Jianye Pang
|
Kai Yi, Jianye Pang, Yungeng Zhang, Xiangrui Zeng, Min Xu
|
Disentangling semantic features of macromolecules in Cryo-Electron
Tomography
| null | null | null | null |
q-bio.BM cs.CV
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Cryo-electron tomography (Cryo-ET) is a 3D imaging technique that enables the
systemic study of shape, abundance, and distribution of macromolecular
structures in single cells in near-atomic resolution. However, the systematic
and efficient $\textit{de novo}$ recognition and recovery of macromolecular
structures captured by Cryo-ET are very challenging due to the structural
complexity and imaging limits. Even macromolecules with identical structures
have various appearances due to different orientations and imaging limits, such
as noise and the missing wedge effect. Explicitly disentangling the semantic
features of macromolecules is crucial for performing several downstream
analyses on the macromolecules. This paper has addressed the problem by
proposing a 3D Spatial Variational Autoencoder that explicitly disentangle the
structure, orientation, and shift of macromolecules. Extensive experiments on
both synthesized and real cryo-ET datasets and cross-domain evaluations
demonstrate the efficacy of our method.
|
[
{
"created": "Sun, 27 Jun 2021 10:41:26 GMT",
"version": "v1"
}
] |
2021-06-29
|
[
[
"Yi",
"Kai",
""
],
[
"Pang",
"Jianye",
""
],
[
"Zhang",
"Yungeng",
""
],
[
"Zeng",
"Xiangrui",
""
],
[
"Xu",
"Min",
""
]
] |
Cryo-electron tomography (Cryo-ET) is a 3D imaging technique that enables the systemic study of shape, abundance, and distribution of macromolecular structures in single cells in near-atomic resolution. However, the systematic and efficient $\textit{de novo}$ recognition and recovery of macromolecular structures captured by Cryo-ET are very challenging due to the structural complexity and imaging limits. Even macromolecules with identical structures have various appearances due to different orientations and imaging limits, such as noise and the missing wedge effect. Explicitly disentangling the semantic features of macromolecules is crucial for performing several downstream analyses on the macromolecules. This paper has addressed the problem by proposing a 3D Spatial Variational Autoencoder that explicitly disentangle the structure, orientation, and shift of macromolecules. Extensive experiments on both synthesized and real cryo-ET datasets and cross-domain evaluations demonstrate the efficacy of our method.
|
1905.01933
|
Maria Masoliver
|
Maria Masoliver and Cristina Masoller
|
Neuronal coupling benefits the encoding of weak periodic signals in
symbolic spike patterns
| null | null |
10.1016/j.cnsns.2019.105023
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A good understanding of how neurons use electrical pulses (i.e, spikes) to
encode the signal information remains elusive. Analyzing spike sequences
generated by individual neurons and by two coupled neurons (using the
stochastic FitzHugh-Nagumo model), recent theoretical studies have found that
the relative timing of the spikes can encode the signal information. Using a
symbolic method to analyze the spike sequence, preferred and infrequent spike
patterns were detected, whose probabilities vary with both, the amplitude and
the frequency of the signal. To investigate if this encoding mechanism is
plausible also for neuronal ensembles, here we analyze the activity of a group
of neurons, when they all perceive a weak periodic signal. We find that, as in
the case of one or two coupled neurons, the probabilities of the spike
patterns, now computed from the spike sequences of all the neurons, depend on
the signal's amplitude and period, and thus, the patterns' probabilities encode
the information of the signal. We also find that the resonances with the period
of the signal or with the noise level are more pronounced when a group of
neurons perceive the signal, in comparison with when only one or two coupled
neurons perceive it. Neuronal coupling is beneficial for signal encoding as a
group of neurons is able to encode a small-amplitude signal, which could not be
encoded when it is perceived by just one or two coupled neurons. Interestingly,
we find that for a group of neurons, just a few connections with one another
can significantly improve the encoding of small-amplitude signals. Our findings
indicate that information encoding in preferred and infrequent spike patterns
is a plausible mechanism that can be employed by neuronal populations to encode
weak periodic inputs, exploiting the presence of neural noise.
|
[
{
"created": "Mon, 6 May 2019 11:25:24 GMT",
"version": "v1"
}
] |
2019-10-23
|
[
[
"Masoliver",
"Maria",
""
],
[
"Masoller",
"Cristina",
""
]
] |
A good understanding of how neurons use electrical pulses (i.e, spikes) to encode the signal information remains elusive. Analyzing spike sequences generated by individual neurons and by two coupled neurons (using the stochastic FitzHugh-Nagumo model), recent theoretical studies have found that the relative timing of the spikes can encode the signal information. Using a symbolic method to analyze the spike sequence, preferred and infrequent spike patterns were detected, whose probabilities vary with both, the amplitude and the frequency of the signal. To investigate if this encoding mechanism is plausible also for neuronal ensembles, here we analyze the activity of a group of neurons, when they all perceive a weak periodic signal. We find that, as in the case of one or two coupled neurons, the probabilities of the spike patterns, now computed from the spike sequences of all the neurons, depend on the signal's amplitude and period, and thus, the patterns' probabilities encode the information of the signal. We also find that the resonances with the period of the signal or with the noise level are more pronounced when a group of neurons perceive the signal, in comparison with when only one or two coupled neurons perceive it. Neuronal coupling is beneficial for signal encoding as a group of neurons is able to encode a small-amplitude signal, which could not be encoded when it is perceived by just one or two coupled neurons. Interestingly, we find that for a group of neurons, just a few connections with one another can significantly improve the encoding of small-amplitude signals. Our findings indicate that information encoding in preferred and infrequent spike patterns is a plausible mechanism that can be employed by neuronal populations to encode weak periodic inputs, exploiting the presence of neural noise.
|
1806.05753
|
Thierry Mora
|
Andreas Mayer, Vijay Balasubramanian, Aleksandra M. Walczak, Thierry
Mora
|
How a well-adapting immune system remembers
| null |
Proc Natl Acad Sci 116(18) 8815-8823 (2019)
|
10.1073/pnas.1812810116
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
An adaptive agent predicting the future state of an environment must weigh
trust in new observations against prior experiences. In this light, we propose
a view of the adaptive immune system as a dynamic Bayesian machinery that
updates its memory repertoire by balancing evidence from new pathogen
encounters against past experience of infection to predict and prepare for
future threats. This framework links the observed initial rapid increase of the
memory pool early in life followed by a mid-life plateau to the ease of
learning salient features of sparse environments. We also derive a modulated
memory pool update rule in agreement with current vaccine response experiments.
Our results suggest that pathogenic environments are sparse and that memory
repertoires significantly decrease infection costs even with moderate sampling.
The predicted optimal update scheme maps onto commonly considered competitive
dynamics for antigen receptors.
|
[
{
"created": "Thu, 14 Jun 2018 22:03:55 GMT",
"version": "v1"
},
{
"created": "Tue, 13 Nov 2018 10:58:08 GMT",
"version": "v2"
}
] |
2019-05-14
|
[
[
"Mayer",
"Andreas",
""
],
[
"Balasubramanian",
"Vijay",
""
],
[
"Walczak",
"Aleksandra M.",
""
],
[
"Mora",
"Thierry",
""
]
] |
An adaptive agent predicting the future state of an environment must weigh trust in new observations against prior experiences. In this light, we propose a view of the adaptive immune system as a dynamic Bayesian machinery that updates its memory repertoire by balancing evidence from new pathogen encounters against past experience of infection to predict and prepare for future threats. This framework links the observed initial rapid increase of the memory pool early in life followed by a mid-life plateau to the ease of learning salient features of sparse environments. We also derive a modulated memory pool update rule in agreement with current vaccine response experiments. Our results suggest that pathogenic environments are sparse and that memory repertoires significantly decrease infection costs even with moderate sampling. The predicted optimal update scheme maps onto commonly considered competitive dynamics for antigen receptors.
|
2009.05285
|
Amit Tewari
|
Amit Tewari
|
Temporal Analysis of COVID-19 Peak Outbreak
|
5 pages, 10 figures, 2 tables
| null | null | null |
q-bio.PE physics.soc-ph
|
http://creativecommons.org/licenses/by-sa/4.0/
|
Intent of this research is to explore how mathematical models, specifically
Susceptible-Infected-Removed (SIR) model, can be utilized to forecast peak
outbreak timeline of COVID-19 epidemic amongst a population of interest
starting from the date of first reported case. Till the time of this research,
there was no effective and universally accepted vaccine to control transmission
and spread of this infection. COVID-19 primarily spreads in population through
respiratory droplets from an infected person cough and sneeze which infects
people who are in proximity. COVID-19 is spreading contagiously across the
world. If health policy makers and medical experts could get early and timely
insights into when peak infection rate would occur after first reported case,
they could plan and optimize medical personnel, ventilators supply, and other
medical resources without over-taxing the infrastructure. The predictions may
also help policymakers devise strategies to control the epidemic, potentially
saving many lives. Thus, it can aid in critical decision-making process by
providing actionable insights into COVID-19 outbreak by leveraging available
data.
|
[
{
"created": "Fri, 11 Sep 2020 08:34:28 GMT",
"version": "v1"
}
] |
2020-09-14
|
[
[
"Tewari",
"Amit",
""
]
] |
Intent of this research is to explore how mathematical models, specifically Susceptible-Infected-Removed (SIR) model, can be utilized to forecast peak outbreak timeline of COVID-19 epidemic amongst a population of interest starting from the date of first reported case. Till the time of this research, there was no effective and universally accepted vaccine to control transmission and spread of this infection. COVID-19 primarily spreads in population through respiratory droplets from an infected person cough and sneeze which infects people who are in proximity. COVID-19 is spreading contagiously across the world. If health policy makers and medical experts could get early and timely insights into when peak infection rate would occur after first reported case, they could plan and optimize medical personnel, ventilators supply, and other medical resources without over-taxing the infrastructure. The predictions may also help policymakers devise strategies to control the epidemic, potentially saving many lives. Thus, it can aid in critical decision-making process by providing actionable insights into COVID-19 outbreak by leveraging available data.
|
1104.5458
|
George Kesidis
|
Yaman Aksu, David J. Miller, George Kesidis, Don C. Bigler, Qing X.
Yang
|
An MRI-Derived Definition of MCI-to-AD Conversion for Long-Term,
Automati c Prognosis of MCI Patients
| null | null |
10.1371/journal.pone.0025074
| null |
q-bio.NC physics.med-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Alzheimer's disease (AD) and mild cognitive impairment (MCI), continue to be
widely studied. While there is no consensus on whether MCIs actually "convert"
to AD, the more important question is not whether MCIs convert, but what is the
best such definition. We focus on automatic prognostication, nominally using
only a baseline image brain scan, of whether an MCI individual will convert to
AD within a multi-year period following the initial clinical visit. This is in
fact not a traditional supervised learning problem since, in ADNI, there are no
definitive labeled examples of MCI conversion. Prior works have defined MCI
subclasses based on whether or not clinical/cognitive scores such as CDR
significantly change from baseline. There are concerns with these definitions,
however, since e.g. most MCIs (and ADs) do not change from a baseline CDR=0.5,
even while physiological changes may be occurring. These works ignore rich
phenotypical information in an MCI patient's brain scan and labeled AD and
Control examples, in defining conversion. We propose an innovative conversion
definition, wherein an MCI patient is declared to be a converter if any of the
patient's brain scans (at follow-up visits) are classified "AD" by an
(accurately-designed) Control-AD classifier. This novel definition bootstraps
the design of a second classifier, specifically trained to predict whether or
not MCIs will convert. This second classifier thus predicts whether an
AD-Control classifier will predict that a patient has AD. Our results
demonstrate this new definition leads not only to much higher prognostic
accuracy than by-CDR conversion, but also to subpopulations much more
consistent with known AD brain region biomarkers. We also identify key
prognostic region biomarkers, essential for accurately discriminating the
converter and nonconverter groups.
|
[
{
"created": "Thu, 28 Apr 2011 17:56:32 GMT",
"version": "v1"
}
] |
2015-05-28
|
[
[
"Aksu",
"Yaman",
""
],
[
"Miller",
"David J.",
""
],
[
"Kesidis",
"George",
""
],
[
"Bigler",
"Don C.",
""
],
[
"Yang",
"Qing X.",
""
]
] |
Alzheimer's disease (AD) and mild cognitive impairment (MCI), continue to be widely studied. While there is no consensus on whether MCIs actually "convert" to AD, the more important question is not whether MCIs convert, but what is the best such definition. We focus on automatic prognostication, nominally using only a baseline image brain scan, of whether an MCI individual will convert to AD within a multi-year period following the initial clinical visit. This is in fact not a traditional supervised learning problem since, in ADNI, there are no definitive labeled examples of MCI conversion. Prior works have defined MCI subclasses based on whether or not clinical/cognitive scores such as CDR significantly change from baseline. There are concerns with these definitions, however, since e.g. most MCIs (and ADs) do not change from a baseline CDR=0.5, even while physiological changes may be occurring. These works ignore rich phenotypical information in an MCI patient's brain scan and labeled AD and Control examples, in defining conversion. We propose an innovative conversion definition, wherein an MCI patient is declared to be a converter if any of the patient's brain scans (at follow-up visits) are classified "AD" by an (accurately-designed) Control-AD classifier. This novel definition bootstraps the design of a second classifier, specifically trained to predict whether or not MCIs will convert. This second classifier thus predicts whether an AD-Control classifier will predict that a patient has AD. Our results demonstrate this new definition leads not only to much higher prognostic accuracy than by-CDR conversion, but also to subpopulations much more consistent with known AD brain region biomarkers. We also identify key prognostic region biomarkers, essential for accurately discriminating the converter and nonconverter groups.
|
1303.3332
|
Brent Pedersen
|
Brent S Pedersen, Ivana V Yang, Subhajyoti De
|
CruzDB: software for annotation of genomic intervals with UCSC
genome-browser data
|
4 pages, 1 figure
| null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The biological significance of genomic features is often context-dependent.
We present CruzDB, a fast and intuitive programmatic interface to the UCSC
genome browser that facilitates integrative analyses of diverse local and
remotely hosted datasets. We showcase the syntax of CruzDB using miRNA-binding
sites as examples, and further demonstrate its utility with 3 novel biological
discoveries. First, we find that while exons replicate early, introns tend to
replicate late, suggesting a complex replication pattern in gene regions.
Second, variants associated with cognitive functions map to lincRNA transcripts
of relevant function. Third, lamina-associated domains are highly enriched in
olfaction-related genes. CruzDB is available at
https://github.com/brentp/cruzdb
|
[
{
"created": "Thu, 14 Mar 2013 01:41:09 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Jul 2013 22:02:30 GMT",
"version": "v2"
}
] |
2013-07-11
|
[
[
"Pedersen",
"Brent S",
""
],
[
"Yang",
"Ivana V",
""
],
[
"De",
"Subhajyoti",
""
]
] |
The biological significance of genomic features is often context-dependent. We present CruzDB, a fast and intuitive programmatic interface to the UCSC genome browser that facilitates integrative analyses of diverse local and remotely hosted datasets. We showcase the syntax of CruzDB using miRNA-binding sites as examples, and further demonstrate its utility with 3 novel biological discoveries. First, we find that while exons replicate early, introns tend to replicate late, suggesting a complex replication pattern in gene regions. Second, variants associated with cognitive functions map to lincRNA transcripts of relevant function. Third, lamina-associated domains are highly enriched in olfaction-related genes. CruzDB is available at https://github.com/brentp/cruzdb
|
1912.05433
|
Tiberiu Tesileanu
|
Tiberiu Tesileanu, Mary M. Conte, John J. Briguglio, Ann M.
Hermundstad, Jonathan D. Victor, Vijay Balasubramanian
|
Efficient coding of natural scene statistics predicts discrimination
thresholds for grayscale textures
|
33 pages, 12 figures
| null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
Previously, in (Hermundstad et al., 2014), we showed that when sampling is
limiting, the efficient coding principle leads to a "variance is salience"
hypothesis, and that this hypothesis accounts for visual sensitivity to binary
image statistics. Here, using extensive new psychophysical data and image
analysis, we show that this hypothesis accounts for visual sensitivity to a
large set of grayscale image statistics at a striking level of detail, and also
identify the limits of the prediction. We define a 66-dimensional space of
local grayscale light-intensity correlations, and measure the relevance of each
direction to natural scenes. The "variance is salience" hypothesis predicts
that two-point correlations are most salient, and predicts their relative
salience. We tested these predictions in a texture-segregation task using
un-natural, synthetic textures. As predicted, correlations beyond second order
are not salient, and predicted thresholds for over 300 second-order
correlations match psychophysical thresholds closely (median fractional error
<0.13).
|
[
{
"created": "Wed, 11 Dec 2019 16:41:27 GMT",
"version": "v1"
},
{
"created": "Fri, 10 Jul 2020 19:39:24 GMT",
"version": "v2"
}
] |
2020-07-14
|
[
[
"Tesileanu",
"Tiberiu",
""
],
[
"Conte",
"Mary M.",
""
],
[
"Briguglio",
"John J.",
""
],
[
"Hermundstad",
"Ann M.",
""
],
[
"Victor",
"Jonathan D.",
""
],
[
"Balasubramanian",
"Vijay",
""
]
] |
Previously, in (Hermundstad et al., 2014), we showed that when sampling is limiting, the efficient coding principle leads to a "variance is salience" hypothesis, and that this hypothesis accounts for visual sensitivity to binary image statistics. Here, using extensive new psychophysical data and image analysis, we show that this hypothesis accounts for visual sensitivity to a large set of grayscale image statistics at a striking level of detail, and also identify the limits of the prediction. We define a 66-dimensional space of local grayscale light-intensity correlations, and measure the relevance of each direction to natural scenes. The "variance is salience" hypothesis predicts that two-point correlations are most salient, and predicts their relative salience. We tested these predictions in a texture-segregation task using un-natural, synthetic textures. As predicted, correlations beyond second order are not salient, and predicted thresholds for over 300 second-order correlations match psychophysical thresholds closely (median fractional error <0.13).
|
2306.11768
|
Zaixi Zhang
|
Zaixi Zhang, Jiaxian Yan, Qi Liu, Enhong Chen, and Marinka Zitnik
|
A Systematic Survey in Geometric Deep Learning for Structure-based Drug
Design
|
20 pages, under review
| null | null | null |
q-bio.QM cs.CE cs.LG
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Structure-based drug design (SBDD) utilizes the three-dimensional geometry of
proteins to identify potential drug candidates. Traditional methods, grounded
in physicochemical modeling and informed by domain expertise, are
resource-intensive. Recent developments in geometric deep learning, focusing on
the integration and processing of 3D geometric data, coupled with the
availability of accurate protein 3D structure predictions from tools like
AlphaFold, have greatly advanced the field of structure-based drug design. This
paper systematically reviews the current state of geometric deep learning in
SBDD. We first outline foundational tasks in SBDD, detail prevalent 3D protein
representations, and highlight representative predictive and generative models.
We then offer in-depth reviews of each key task, including binding site
prediction, binding pose generation, \emph{de novo} molecule generation, linker
design, and binding affinity prediction. We provide formal problem definitions
and outline each task's representative methods, datasets, evaluation metrics,
and performance benchmarks. Finally, we summarize the current challenges and
future opportunities: current challenges in SBDD include oversimplified problem
formulations, inadequate out-of-distribution generalization, a lack of reliable
evaluation metrics and large-scale benchmarks, and the need for experimental
verification and enhanced model understanding; opportunities include leveraging
multimodal datasets, integrating domain knowledge, building comprehensive
benchmarks, designing criteria based on clinical endpoints, and developing
foundation models that broaden the range of design tasks. We also curate
\url{https://github.com/zaixizhang/Awesome-SBDD}, reflecting ongoing
contributions and new datasets in SBDD.
|
[
{
"created": "Tue, 20 Jun 2023 14:21:58 GMT",
"version": "v1"
},
{
"created": "Thu, 22 Jun 2023 03:05:21 GMT",
"version": "v2"
},
{
"created": "Mon, 3 Jul 2023 14:38:17 GMT",
"version": "v3"
},
{
"created": "Sat, 14 Oct 2023 20:54:09 GMT",
"version": "v4"
},
{
"created": "Tue, 24 Oct 2023 14:22:59 GMT",
"version": "v5"
}
] |
2023-10-25
|
[
[
"Zhang",
"Zaixi",
""
],
[
"Yan",
"Jiaxian",
""
],
[
"Liu",
"Qi",
""
],
[
"Chen",
"Enhong",
""
],
[
"Zitnik",
"Marinka",
""
]
] |
Structure-based drug design (SBDD) utilizes the three-dimensional geometry of proteins to identify potential drug candidates. Traditional methods, grounded in physicochemical modeling and informed by domain expertise, are resource-intensive. Recent developments in geometric deep learning, focusing on the integration and processing of 3D geometric data, coupled with the availability of accurate protein 3D structure predictions from tools like AlphaFold, have greatly advanced the field of structure-based drug design. This paper systematically reviews the current state of geometric deep learning in SBDD. We first outline foundational tasks in SBDD, detail prevalent 3D protein representations, and highlight representative predictive and generative models. We then offer in-depth reviews of each key task, including binding site prediction, binding pose generation, \emph{de novo} molecule generation, linker design, and binding affinity prediction. We provide formal problem definitions and outline each task's representative methods, datasets, evaluation metrics, and performance benchmarks. Finally, we summarize the current challenges and future opportunities: current challenges in SBDD include oversimplified problem formulations, inadequate out-of-distribution generalization, a lack of reliable evaluation metrics and large-scale benchmarks, and the need for experimental verification and enhanced model understanding; opportunities include leveraging multimodal datasets, integrating domain knowledge, building comprehensive benchmarks, designing criteria based on clinical endpoints, and developing foundation models that broaden the range of design tasks. We also curate \url{https://github.com/zaixizhang/Awesome-SBDD}, reflecting ongoing contributions and new datasets in SBDD.
|
2407.18329
|
Shuqiang Wang
|
Yongcheng Zong, Shuqiang Wang
|
A New Brain Network Construction Paradigm for Brain Disorder via
Diffusion-based Graph Contrastive Learning
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Brain network analysis plays an increasingly important role in studying brain
function and the exploring of disease mechanisms. However, existing brain
network construction tools have some limitations, including dependency on
empirical users, weak consistency in repeated experiments and time-consuming
processes. In this work, a diffusion-based brain network pipeline, DGCL is
designed for end-to-end construction of brain networks. Initially, the brain
region-aware module (BRAM) precisely determines the spatial locations of brain
regions by the diffusion process, avoiding subjective parameter selection.
Subsequently, DGCL employs graph contrastive learning to optimize brain
connections by eliminating individual differences in redundant connections
unrelated to diseases, thereby enhancing the consistency of brain networks
within the same group. Finally, the node-graph contrastive loss and
classification loss jointly constrain the learning process of the model to
obtain the reconstructed brain network, which is then used to analyze important
brain connections. Validation on two datasets, ADNI and ABIDE, demonstrates
that DGCL surpasses traditional methods and other deep learning models in
predicting disease development stages. Significantly, the proposed model
improves the efficiency and generalization of brain network construction. In
summary, the proposed DGCL can be served as a universal brain network
construction scheme, which can effectively identify important brain connections
through generative paradigms and has the potential to provide disease
interpretability support for neuroscience research.
|
[
{
"created": "Sat, 6 Jul 2024 02:47:48 GMT",
"version": "v1"
}
] |
2024-07-29
|
[
[
"Zong",
"Yongcheng",
""
],
[
"Wang",
"Shuqiang",
""
]
] |
Brain network analysis plays an increasingly important role in studying brain function and the exploring of disease mechanisms. However, existing brain network construction tools have some limitations, including dependency on empirical users, weak consistency in repeated experiments and time-consuming processes. In this work, a diffusion-based brain network pipeline, DGCL is designed for end-to-end construction of brain networks. Initially, the brain region-aware module (BRAM) precisely determines the spatial locations of brain regions by the diffusion process, avoiding subjective parameter selection. Subsequently, DGCL employs graph contrastive learning to optimize brain connections by eliminating individual differences in redundant connections unrelated to diseases, thereby enhancing the consistency of brain networks within the same group. Finally, the node-graph contrastive loss and classification loss jointly constrain the learning process of the model to obtain the reconstructed brain network, which is then used to analyze important brain connections. Validation on two datasets, ADNI and ABIDE, demonstrates that DGCL surpasses traditional methods and other deep learning models in predicting disease development stages. Significantly, the proposed model improves the efficiency and generalization of brain network construction. In summary, the proposed DGCL can be served as a universal brain network construction scheme, which can effectively identify important brain connections through generative paradigms and has the potential to provide disease interpretability support for neuroscience research.
|
q-bio/0310031
|
Paul Higgs
|
P.G.Higgs, D.Jameson, H.Jow, M.Rattray
|
The Evolution of tRNA-Leu Genes in Animal Mitochondrial Genomes
|
20 pages, 6 figures. J. Mol. Evol. (in press)
| null | null | null |
q-bio.PE
| null |
Animal mitochondrial genomes usually have two transfer RNAs for Leucine: one,
with anticodon UAG, translates the four-codon family CUN, whilst the other,
with anticodon UAA, translates the two-codon family UUR. These two genes must
differ at the third anticodon position, but in some species the genes differ at
many additional sites, indicating that these genes have been independent for a
long time. Duplication and deletion of genes in mitochondrial genomes occurs
frequently during the evolution of the Metazoa. If a tRNA-Leu gene were
duplicated and a substitution occurred in the anticodon, this would effectively
turn one type of tRNA into the other. The original copy of the second tRNA type
might then be lost by a deletion elsewhere in the genome. There are several
groups of species in which the two tRNA-Leu genes occur next to one another (or
very close) on the genome, which suggests that tandem duplication has occurred.
Here we use RNA-specific phylogenetic methods to determine evolutionary trees
for both genes. We present evidence that the process of duplication, anticodon
mutation and deletion of tRNA-Leu genes has occurred at least five times during
the evolution of the Metazoa - once in the common ancestor of all Protostomes,
once in the common ancestor of Echinoderms and Hemichordates, once in the
hermit crab, and twice independently in Molluscs.
|
[
{
"created": "Thu, 23 Oct 2003 22:11:13 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Higgs",
"P. G.",
""
],
[
"Jameson",
"D.",
""
],
[
"Jow",
"H.",
""
],
[
"Rattray",
"M.",
""
]
] |
Animal mitochondrial genomes usually have two transfer RNAs for Leucine: one, with anticodon UAG, translates the four-codon family CUN, whilst the other, with anticodon UAA, translates the two-codon family UUR. These two genes must differ at the third anticodon position, but in some species the genes differ at many additional sites, indicating that these genes have been independent for a long time. Duplication and deletion of genes in mitochondrial genomes occurs frequently during the evolution of the Metazoa. If a tRNA-Leu gene were duplicated and a substitution occurred in the anticodon, this would effectively turn one type of tRNA into the other. The original copy of the second tRNA type might then be lost by a deletion elsewhere in the genome. There are several groups of species in which the two tRNA-Leu genes occur next to one another (or very close) on the genome, which suggests that tandem duplication has occurred. Here we use RNA-specific phylogenetic methods to determine evolutionary trees for both genes. We present evidence that the process of duplication, anticodon mutation and deletion of tRNA-Leu genes has occurred at least five times during the evolution of the Metazoa - once in the common ancestor of all Protostomes, once in the common ancestor of Echinoderms and Hemichordates, once in the hermit crab, and twice independently in Molluscs.
|
1702.01568
|
Volker Pernice
|
Volker Pernice, Rava Azeredo da Silveira
|
Interpretation of Correlated Neural Variability from Models of
Feed-Forward and Recurrent Circuits
|
41 pages, 10 figures
| null |
10.1371/journal.pcbi.1005979
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The correlated variability in the responses of a neural population to the
repeated presentation of a sensory stimulus is a universally observed
phenomenon. Such correlations have been studied in much detail, both with
respect to their mechanistic origin and to their influence on stimulus
discrimination and on the performance of population codes. In particular,
recurrent neural network models have been used to understand the origin (or
lack) of correlations in neural activity. Here, we apply a model of recurrently
connected stochastic neurons to interpret correlations found in a population of
neurons recorded from mouse auditory cortex. We study the consequences of
recurrent connections on the stimulus dependence of correlations, and we
compare them to those from alternative sources of correlated variability, like
correlated gain fluctuations and common input in feed-forward architectures. We
find that a recurrent network model with random effective connections
reproduces observed statistics, like the relation between noise and signal
correlations in the data, in a natural way. In the model, we can analyze
directly the relation between network parameters, correlations, and how well
pairs of stimuli can be discriminated based on population activity. In this
way, we can relate circuit parameters to information processing.
|
[
{
"created": "Mon, 6 Feb 2017 11:13:15 GMT",
"version": "v1"
}
] |
2018-07-04
|
[
[
"Pernice",
"Volker",
""
],
[
"da Silveira",
"Rava Azeredo",
""
]
] |
The correlated variability in the responses of a neural population to the repeated presentation of a sensory stimulus is a universally observed phenomenon. Such correlations have been studied in much detail, both with respect to their mechanistic origin and to their influence on stimulus discrimination and on the performance of population codes. In particular, recurrent neural network models have been used to understand the origin (or lack) of correlations in neural activity. Here, we apply a model of recurrently connected stochastic neurons to interpret correlations found in a population of neurons recorded from mouse auditory cortex. We study the consequences of recurrent connections on the stimulus dependence of correlations, and we compare them to those from alternative sources of correlated variability, like correlated gain fluctuations and common input in feed-forward architectures. We find that a recurrent network model with random effective connections reproduces observed statistics, like the relation between noise and signal correlations in the data, in a natural way. In the model, we can analyze directly the relation between network parameters, correlations, and how well pairs of stimuli can be discriminated based on population activity. In this way, we can relate circuit parameters to information processing.
|
2308.08898
|
Sitabhra Sinha
|
Anand Pathak, Shakti N. Menon and Sitabhra Sinha
|
A hierarchy index for networks in the brain reveals a complex entangled
organizational structure
|
16 pages, 5 figures + 10 pages Supplementary Information
|
PNAS 121, e2314291121 (2024)
|
10.1073/pnas.2314291121
| null |
q-bio.NC physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Networks involved in information processing often have their nodes arranged
hierarchically, with the majority of connections occurring in adjacent levels.
However, despite being an intuitively appealing concept, the hierarchical
organization of large networks, such as those in the brain, are difficult to
identify, especially in absence of additional information beyond that provided
by the connectome. In this paper, we propose a framework to uncover the
hierarchical structure of a given network, that identifies the nodes occupying
each level as well as the sequential order of the levels. It involves
optimizing a metric that we use to quantify the extent of hierarchy present in
a network. Applying this measure to various brain networks, ranging from the
nervous system of the nematode Caenorhabditis elegans to the human connectome,
we unexpectedly find that they exhibit a common network architectural motif
intertwining hierarchy and modularity. This suggests that brain networks may
have evolved to simultaneously exploit the functional advantages of these two
types of organizations, viz., relatively independent modules performing
distributed processing in parallel and a hierarchical structure that allows
sequential pooling of these multiple processing streams. An intriguing
possibility is that this property we report may be common to information
processing networks in general.
|
[
{
"created": "Thu, 17 Aug 2023 10:15:36 GMT",
"version": "v1"
}
] |
2024-07-02
|
[
[
"Pathak",
"Anand",
""
],
[
"Menon",
"Shakti N.",
""
],
[
"Sinha",
"Sitabhra",
""
]
] |
Networks involved in information processing often have their nodes arranged hierarchically, with the majority of connections occurring in adjacent levels. However, despite being an intuitively appealing concept, the hierarchical organization of large networks, such as those in the brain, are difficult to identify, especially in absence of additional information beyond that provided by the connectome. In this paper, we propose a framework to uncover the hierarchical structure of a given network, that identifies the nodes occupying each level as well as the sequential order of the levels. It involves optimizing a metric that we use to quantify the extent of hierarchy present in a network. Applying this measure to various brain networks, ranging from the nervous system of the nematode Caenorhabditis elegans to the human connectome, we unexpectedly find that they exhibit a common network architectural motif intertwining hierarchy and modularity. This suggests that brain networks may have evolved to simultaneously exploit the functional advantages of these two types of organizations, viz., relatively independent modules performing distributed processing in parallel and a hierarchical structure that allows sequential pooling of these multiple processing streams. An intriguing possibility is that this property we report may be common to information processing networks in general.
|
1102.4039
|
Andrew Gray Mr
|
Andrew R. Gray
|
Notes on Hybridization in Leaf frogs of the Genus Agalychnis (Anura,
Hylidae, Phyllomedusinae)
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Two species of Endangered Leaf frogs, Agalychnis moreletii and Agalychnis
annae, belonging to the tree frog Subfamily Phyllomedusinae, Genus Agalychnis,
were hybridized for the first time whilst being maintained in captivity.
Previous to this, these allopatric Central American species were considered as
being distinctly separate. Crossbreeding following genetic analysis reveals
that the two species are extremely closely related, and the hybrid of A.
moreletii and A. annae is presented for the first time. The importance of
identifying degrees of genetic variation between species and different
populations of the same species, for conservation purposes, is highlighted and
discussed.
|
[
{
"created": "Sun, 20 Feb 2011 02:37:59 GMT",
"version": "v1"
}
] |
2011-02-22
|
[
[
"Gray",
"Andrew R.",
""
]
] |
Two species of Endangered Leaf frogs, Agalychnis moreletii and Agalychnis annae, belonging to the tree frog Subfamily Phyllomedusinae, Genus Agalychnis, were hybridized for the first time whilst being maintained in captivity. Previous to this, these allopatric Central American species were considered as being distinctly separate. Crossbreeding following genetic analysis reveals that the two species are extremely closely related, and the hybrid of A. moreletii and A. annae is presented for the first time. The importance of identifying degrees of genetic variation between species and different populations of the same species, for conservation purposes, is highlighted and discussed.
|
q-bio/0609005
|
Horacio Ceva
|
E. Burgos, H. Ceva, R. Perazzo, M. Devoto, D. Medan, M. Zimmermann, A.
M. Delbue
|
Why Nestedness in Mutualistic Networks?
|
Journal of Theoretical Biology (Accepted, 2007)
| null |
10.1016/j.jtbi.2007.07.030
| null |
q-bio.PE
| null |
We investigate the relationship between the nested organization of
mutualistic systems and their robustness against the extinction of species. We
establish that a nested pattern of contacts is the best possible one as far as
robustness is concerned, but only when the least linked species have the
greater probability of becoming extinct. We introduce a coefficient that
provides a quantitative measure of the robustness of a mutualistic system.
|
[
{
"created": "Tue, 5 Sep 2006 14:00:56 GMT",
"version": "v1"
},
{
"created": "Thu, 20 Sep 2007 16:53:20 GMT",
"version": "v2"
}
] |
2007-09-20
|
[
[
"Burgos",
"E.",
""
],
[
"Ceva",
"H.",
""
],
[
"Perazzo",
"R.",
""
],
[
"Devoto",
"M.",
""
],
[
"Medan",
"D.",
""
],
[
"Zimmermann",
"M.",
""
],
[
"Delbue",
"A. M.",
""
]
] |
We investigate the relationship between the nested organization of mutualistic systems and their robustness against the extinction of species. We establish that a nested pattern of contacts is the best possible one as far as robustness is concerned, but only when the least linked species have the greater probability of becoming extinct. We introduce a coefficient that provides a quantitative measure of the robustness of a mutualistic system.
|
1511.03965
|
Paul Fran\c{c}ois
|
Paul Fran\c{c}ois, Mathieu Hemery, Kyle A. Johnson, Laura N. Saunders
|
Phenotypic spandrel: absolute discrimination and ligand antagonism
| null | null |
10.1088/1478-3975/13/6/066011
| null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We consider the general problem of sensitive and specific discrimination
between biochemical species. An important instance is immune discrimination
between self and not-self, where it is also observed experimentally that
ligands just below discrimination threshold negatively impact response, a
phenomenon called antagonism. We characterize mathematically the generic
properties of such discrimination, first relating it to biochemical adaptation.
Then, based on basic biochemical rules, we establish that, surprisingly,
antagonism is a generic consequence of any strictly specific discrimination
made independently from ligand concentration. Thus antagonism constitutes a
"phenotypic spandrel": a phenotype existing as a necessary by-product of
another phenotype. We exhibit a simple analytic model of discrimination
displaying antagonism, where antagonism strength is linear in distance from
detection threshold. This contrasts with traditional proofreading based models
where antagonism vanishes far from threshold and thus displays an inverted
hierarchy of antagonism compared to simpler models. The phenotypic spandrel
studied here is expected to structure many decision pathways such as immune
detection mediated by TCRs and FC$\epsilon$RIs, as well as endocrine
signalling/disruption.
|
[
{
"created": "Thu, 12 Nov 2015 16:59:31 GMT",
"version": "v1"
},
{
"created": "Fri, 8 Jan 2016 15:49:29 GMT",
"version": "v2"
},
{
"created": "Fri, 7 Oct 2016 15:52:09 GMT",
"version": "v3"
}
] |
2016-12-21
|
[
[
"François",
"Paul",
""
],
[
"Hemery",
"Mathieu",
""
],
[
"Johnson",
"Kyle A.",
""
],
[
"Saunders",
"Laura N.",
""
]
] |
We consider the general problem of sensitive and specific discrimination between biochemical species. An important instance is immune discrimination between self and not-self, where it is also observed experimentally that ligands just below discrimination threshold negatively impact response, a phenomenon called antagonism. We characterize mathematically the generic properties of such discrimination, first relating it to biochemical adaptation. Then, based on basic biochemical rules, we establish that, surprisingly, antagonism is a generic consequence of any strictly specific discrimination made independently from ligand concentration. Thus antagonism constitutes a "phenotypic spandrel": a phenotype existing as a necessary by-product of another phenotype. We exhibit a simple analytic model of discrimination displaying antagonism, where antagonism strength is linear in distance from detection threshold. This contrasts with traditional proofreading based models where antagonism vanishes far from threshold and thus displays an inverted hierarchy of antagonism compared to simpler models. The phenotypic spandrel studied here is expected to structure many decision pathways such as immune detection mediated by TCRs and FC$\epsilon$RIs, as well as endocrine signalling/disruption.
|
1410.8087
|
Gabriele Micali
|
Diana Clausznitzer, Gabriele Micali, Silke Neumann, Victor Sourjik and
Robert G. Endres
|
Predicting chemical environments of bacteria from receptor signaling
|
DG and GM contributed equally to this work
|
PLoS Comput Biol 10(10): e1003870 (2014)
|
10.1371/journal.pcbi.1003870
| null |
q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Sensory systems have evolved to respond to input stimuli of certain
statistical properties, and to reliably transmit this information through
biochemical pathways. Hence, for an experimentally well-characterized sensory
system, one ought to be able to extract valuable information about the
statistics of the stimuli. Based on dose-response curves from in vivo
fluorescence resonance energy transfer (FRET) experiments of the bacterial
chemotaxis sensory system, we predict the chemical gradients chemotactic
Escherichia coli cells typically encounter in their natural environment. To
predict average gradients cells experience, we revaluate the phenomenological
Weber's law and its generalizations to the Weber-Fechner law and fold-change
detection. To obtain full distributions of gradients we use information theory
and simulations, considering limitations of information transmission from both
cell-external and internal noise. We identify broad distributions of
exponential gradients, which lead to log-normal stimuli and maximal drift
velocity. Our results thus provide a first step towards deciphering the
chemical nature of complex, experimentally inaccessible cellular
microenvironments, such as the human intestine.
|
[
{
"created": "Mon, 27 Oct 2014 11:38:09 GMT",
"version": "v1"
}
] |
2014-10-30
|
[
[
"Clausznitzer",
"Diana",
""
],
[
"Micali",
"Gabriele",
""
],
[
"Neumann",
"Silke",
""
],
[
"Sourjik",
"Victor",
""
],
[
"Endres",
"Robert G.",
""
]
] |
Sensory systems have evolved to respond to input stimuli of certain statistical properties, and to reliably transmit this information through biochemical pathways. Hence, for an experimentally well-characterized sensory system, one ought to be able to extract valuable information about the statistics of the stimuli. Based on dose-response curves from in vivo fluorescence resonance energy transfer (FRET) experiments of the bacterial chemotaxis sensory system, we predict the chemical gradients chemotactic Escherichia coli cells typically encounter in their natural environment. To predict average gradients cells experience, we revaluate the phenomenological Weber's law and its generalizations to the Weber-Fechner law and fold-change detection. To obtain full distributions of gradients we use information theory and simulations, considering limitations of information transmission from both cell-external and internal noise. We identify broad distributions of exponential gradients, which lead to log-normal stimuli and maximal drift velocity. Our results thus provide a first step towards deciphering the chemical nature of complex, experimentally inaccessible cellular microenvironments, such as the human intestine.
|
1304.6661
|
Carsten Conradi
|
Katharina Holstein and Dietrich Flockerzi and Carsten Conradi
|
Multistationarity in sequential distributed multisite phosphorylation
networks
| null | null | null | null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Multisite phosphorylation networks are encountered in many intracellular
processes like signal transduction, cell-cycle control or nuclear signal
integration. In this contribution networks describing the phosphorylation and
dephosphorylation of a protein at $n$ sites in a sequential distributive
mechanism are considered. Multistationarity (i.e.\ the existence of at least
two positive steady state solutions of the associated polynomial dynamical
system) has been analyzed and established in several contributions. It is, for
example, known that there exist values for he rate constants where
multistationarity occurs. However, nothing else is known about these rate
constants.
Here we present a sign condition that is necessary and sufficient for
multistationarity in $n$-site sequential, distributive phosphorylation. We
express this sign condition in terms of linear systems and show that solutions
of these systems define rate constants where multistationarity is possible. We
then present, for $n\geq 2$, a collection of {\em feasible} linear systems and
hence give a new and independent proof that multistationarity is possible for
$n\geq 2$. Moreover, our results allow to explicitly obtain values for the rate
constants where multistationarity is possible. Hence we believe that, for the
first time, a systematic exploration of the region in parameter space where
multistationarity occurs has become possible.One consequence of our work is
that, for any pair of steady states, the ratio of the steady state
concentrations of kinase-substrate complexes equals that of
phosphatase-substrate complexes.
|
[
{
"created": "Wed, 24 Apr 2013 16:39:38 GMT",
"version": "v1"
},
{
"created": "Tue, 7 May 2013 13:34:12 GMT",
"version": "v2"
},
{
"created": "Tue, 2 Jul 2013 16:02:06 GMT",
"version": "v3"
}
] |
2013-07-03
|
[
[
"Holstein",
"Katharina",
""
],
[
"Flockerzi",
"Dietrich",
""
],
[
"Conradi",
"Carsten",
""
]
] |
Multisite phosphorylation networks are encountered in many intracellular processes like signal transduction, cell-cycle control or nuclear signal integration. In this contribution networks describing the phosphorylation and dephosphorylation of a protein at $n$ sites in a sequential distributive mechanism are considered. Multistationarity (i.e.\ the existence of at least two positive steady state solutions of the associated polynomial dynamical system) has been analyzed and established in several contributions. It is, for example, known that there exist values for he rate constants where multistationarity occurs. However, nothing else is known about these rate constants. Here we present a sign condition that is necessary and sufficient for multistationarity in $n$-site sequential, distributive phosphorylation. We express this sign condition in terms of linear systems and show that solutions of these systems define rate constants where multistationarity is possible. We then present, for $n\geq 2$, a collection of {\em feasible} linear systems and hence give a new and independent proof that multistationarity is possible for $n\geq 2$. Moreover, our results allow to explicitly obtain values for the rate constants where multistationarity is possible. Hence we believe that, for the first time, a systematic exploration of the region in parameter space where multistationarity occurs has become possible.One consequence of our work is that, for any pair of steady states, the ratio of the steady state concentrations of kinase-substrate complexes equals that of phosphatase-substrate complexes.
|
q-bio/0612027
|
Michael Deem
|
Jeong-Man Park and Michael W. Deem
|
Phase Diagrams of Quasispecies Theory with Recombination and Horizontal
Gene Transfer
|
5 pages, 1 figure, to appear in Physics Review Letters
| null |
10.1103/PhysRevLett.98.058101
| null |
q-bio.PE
| null |
We consider how transfer of genetic information between individuals
influences the phase diagram and mean fitness of both the Eigen and the
parallel, or Crow-Kimura, models of evolution. In the absence of genetic
transfer, these physical models of evolution consider the replication and point
mutation of the genomes of independent individuals in a large population. A
phase transition occurs, such that below a critical mutation rate an
identifiable quasispecies forms. We generalize these models of quasispecies
evolution to include horizontal gene transfer. We show how transfer of genetic
information changes the phase diagram and mean fitness and introduces
metastability in quasispecies theory, via an analytic field theoretic mapping.
|
[
{
"created": "Thu, 14 Dec 2006 21:33:05 GMT",
"version": "v1"
}
] |
2009-11-13
|
[
[
"Park",
"Jeong-Man",
""
],
[
"Deem",
"Michael W.",
""
]
] |
We consider how transfer of genetic information between individuals influences the phase diagram and mean fitness of both the Eigen and the parallel, or Crow-Kimura, models of evolution. In the absence of genetic transfer, these physical models of evolution consider the replication and point mutation of the genomes of independent individuals in a large population. A phase transition occurs, such that below a critical mutation rate an identifiable quasispecies forms. We generalize these models of quasispecies evolution to include horizontal gene transfer. We show how transfer of genetic information changes the phase diagram and mean fitness and introduces metastability in quasispecies theory, via an analytic field theoretic mapping.
|
1203.2883
|
Serena Bradde
|
Vanni Bucci, Serena Bradde, Giulio Biroli and Joao B. Xavier
|
Social interaction, noise and antibiotic-mediated switches in the
intestinal microbiota
|
20 pages, 5 figures accepted for publication in Plos Comp Bio.
Supplementary video and information available
| null |
10.1371/journal.pcbi.1002497
| null |
q-bio.QM cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The intestinal microbiota plays important roles in digestion and resistance
against entero-pathogens. As with other ecosystems, its species composition is
resilient against small disturbances but strong perturbations such as
antibiotics can affect the consortium dramatically. Antibiotic cessation does
not necessarily restore pre-treatment conditions and disturbed microbiota are
often susceptible to pathogen invasion. Here we propose a mathematical model to
explain how antibiotic-mediated switches in the microbiota composition can
result from simple social interactions between antibiotic-tolerant and
antibiotic-sensitive bacterial groups. We build a two-species (e.g. two
functional-groups) model and identify regions of domination by
antibiotic-sensitive or antibiotic-tolerant bacteria, as well as a region of
multistability where domination by either group is possible. Using a new
framework that we derived from statistical physics, we calculate the duration
of each microbiota composition state. This is shown to depend on the balance
between random fluctuations in the bacterial densities and the strength of
microbial interactions. The singular value decomposition of recent metagenomic
data confirms our assumption of grouping microbes as antibiotic-tolerant or
antibiotic-sensitive in response to a single antibiotic. Our methodology can be
extended to multiple bacterial groups and thus it provides an ecological
formalism to help interpret the present surge in microbiome data.
|
[
{
"created": "Tue, 13 Mar 2012 18:05:39 GMT",
"version": "v1"
}
] |
2015-06-04
|
[
[
"Bucci",
"Vanni",
""
],
[
"Bradde",
"Serena",
""
],
[
"Biroli",
"Giulio",
""
],
[
"Xavier",
"Joao B.",
""
]
] |
The intestinal microbiota plays important roles in digestion and resistance against entero-pathogens. As with other ecosystems, its species composition is resilient against small disturbances but strong perturbations such as antibiotics can affect the consortium dramatically. Antibiotic cessation does not necessarily restore pre-treatment conditions and disturbed microbiota are often susceptible to pathogen invasion. Here we propose a mathematical model to explain how antibiotic-mediated switches in the microbiota composition can result from simple social interactions between antibiotic-tolerant and antibiotic-sensitive bacterial groups. We build a two-species (e.g. two functional-groups) model and identify regions of domination by antibiotic-sensitive or antibiotic-tolerant bacteria, as well as a region of multistability where domination by either group is possible. Using a new framework that we derived from statistical physics, we calculate the duration of each microbiota composition state. This is shown to depend on the balance between random fluctuations in the bacterial densities and the strength of microbial interactions. The singular value decomposition of recent metagenomic data confirms our assumption of grouping microbes as antibiotic-tolerant or antibiotic-sensitive in response to a single antibiotic. Our methodology can be extended to multiple bacterial groups and thus it provides an ecological formalism to help interpret the present surge in microbiome data.
|
1606.02801
|
Edmund Crampin
|
Patrick E. McSharry and Edmund J. Crampin
|
Identifying statistically significant patterns in gene expression data
| null | null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Motivation: Clustering techniques are routinely applied to identify patterns
of co-expression in gene expression data. Co-regulation, and involvement of
genes in similar cellular function, is subsequently inferred from the clusters
which are obtained. Increasingly sophisticated algorithms have been applied to
microarray data, however, less attention has been given to the statistical
significance of the results of clustering studies. We present a technique for
the analysis of commonly used hierarchical linkage-based clustering called
Significance Analysis of Linkage Trees (SALT).
Results: The statistical significance of pairwise similarity levels between
gene expression profiles, a measure of co-expression, is established using a
surrogate data analysis method. We find that a modified version of the standard
linkage technique, complete-linkage, must be used to generate hierarchical
linkage trees with the appropriate properties. The approach is illustrated
using synthetic data generated from a novel model of gene expression profiles
and is then applied to previously analysed microarray data on the
transcriptional response of human fibroblasts to serum stimulation.
|
[
{
"created": "Thu, 9 Jun 2016 02:20:57 GMT",
"version": "v1"
}
] |
2016-06-10
|
[
[
"McSharry",
"Patrick E.",
""
],
[
"Crampin",
"Edmund J.",
""
]
] |
Motivation: Clustering techniques are routinely applied to identify patterns of co-expression in gene expression data. Co-regulation, and involvement of genes in similar cellular function, is subsequently inferred from the clusters which are obtained. Increasingly sophisticated algorithms have been applied to microarray data, however, less attention has been given to the statistical significance of the results of clustering studies. We present a technique for the analysis of commonly used hierarchical linkage-based clustering called Significance Analysis of Linkage Trees (SALT). Results: The statistical significance of pairwise similarity levels between gene expression profiles, a measure of co-expression, is established using a surrogate data analysis method. We find that a modified version of the standard linkage technique, complete-linkage, must be used to generate hierarchical linkage trees with the appropriate properties. The approach is illustrated using synthetic data generated from a novel model of gene expression profiles and is then applied to previously analysed microarray data on the transcriptional response of human fibroblasts to serum stimulation.
|
1206.4434
|
S\'ilvio Duarte Queir\'os M.
|
Andrea Cavagna, Silvio M. Duarte Queiros, Irene Giardina, Fabio
Stefanini, Massimiliano Viale
|
Diffusion of individual birds in starling flocks
|
22 pages, 10 figures
|
Proc. R. Soc. B 280, 20122484 (2013)
|
10.1098/rspb.2012.2484
| null |
q-bio.PE physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Flocking is a paradigmatic example of collective animal behaviour, where
decentralized interaction rules give rise to a globally ordered state. In the
emergence of order out of self-organization we find similarities between
biological systems, as bird flocks, and some physical systems, as ferromagnets.
In both cases, the tendency of individuals to align to their neighbours gives
rise to a polarized state. There is, however, one crucial difference: the
interaction network within an animal group is not necessarily fixed in time, as
each individual moves and may change its neighbours. Therefore, the dynamical
interaction mechanism in biological and physical system can be quite different,
not only due to the gross disparity in the complexity of the individual
entities, but also because of the potential role of inter-individual motion. To
assess the relevance of this mechanism it is necessary to gain quantitative
experimental information about how much individuals move with respect to each
other within the group. Here, by using data from field observations on
starlings, we study the diffusion properties of individual birds within a flock
and investigate the effect of diffusion on the dynamics of the interaction
network. We find that birds diffuse faster than Brownian particles
(superdiffusion) and in a strongly anisotropic way. We also find that
neighbours change in time exclusively as a consequence of diffusion, so that no
specific mechanism to keep one's neighbours seems to be enforced. Finally, we
study the diffusion properties of birds at the border of the flock. We find
that these individuals remain on the border significantly longer than what
would be expected on the basis of a purely diffusional model, suggesting that
there is a sort barrier a bird must cross to make the transition from border to
interior of the flock.
|
[
{
"created": "Wed, 20 Jun 2012 09:52:31 GMT",
"version": "v1"
},
{
"created": "Wed, 13 Feb 2013 20:34:18 GMT",
"version": "v2"
}
] |
2013-02-14
|
[
[
"Cavagna",
"Andrea",
""
],
[
"Queiros",
"Silvio M. Duarte",
""
],
[
"Giardina",
"Irene",
""
],
[
"Stefanini",
"Fabio",
""
],
[
"Viale",
"Massimiliano",
""
]
] |
Flocking is a paradigmatic example of collective animal behaviour, where decentralized interaction rules give rise to a globally ordered state. In the emergence of order out of self-organization we find similarities between biological systems, as bird flocks, and some physical systems, as ferromagnets. In both cases, the tendency of individuals to align to their neighbours gives rise to a polarized state. There is, however, one crucial difference: the interaction network within an animal group is not necessarily fixed in time, as each individual moves and may change its neighbours. Therefore, the dynamical interaction mechanism in biological and physical system can be quite different, not only due to the gross disparity in the complexity of the individual entities, but also because of the potential role of inter-individual motion. To assess the relevance of this mechanism it is necessary to gain quantitative experimental information about how much individuals move with respect to each other within the group. Here, by using data from field observations on starlings, we study the diffusion properties of individual birds within a flock and investigate the effect of diffusion on the dynamics of the interaction network. We find that birds diffuse faster than Brownian particles (superdiffusion) and in a strongly anisotropic way. We also find that neighbours change in time exclusively as a consequence of diffusion, so that no specific mechanism to keep one's neighbours seems to be enforced. Finally, we study the diffusion properties of birds at the border of the flock. We find that these individuals remain on the border significantly longer than what would be expected on the basis of a purely diffusional model, suggesting that there is a sort barrier a bird must cross to make the transition from border to interior of the flock.
|
1806.07469
|
Xiaochang Leng
|
Xiaochang Leng, Yingchao Yang, Xiaomin Deng, Susan M. Lessner, Michael
A. Sutton, Tarek Shazly
|
Micromechanical Experimental and Numerical Studies of Collagen Fibers
Failure in Arterial Tissue
|
33 pages, 11 figures
| null | null | null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Arterial tissue failures lead to a number of clinical conditions that develop
rapidly and unpredictably in vivo. Structural components and their interfacial
mechanical strength of arterial tissue play a critical role in the process of
arterail delamination. Therefore, there is a pressing need to understand the
micromechanical mechanisms of arterial delamination. The objective of this
study was to investigate various failure mechanisms (e.g. failure of collagen
fibers) responsible for arterial interfacial delamination. In-situ tensile
tests of fibers were performed on a micro-tester in the scanning electron
microscope. A 3D unit cell model containing an individual fiber bridging two
arterial tissue layers was constructed. An exponential cohesive zone model
(CZM) was used to assess the stiffening and softening mechanical behaviors of
collagen fiber bundles between the two arterial layers. An anisotropic
constitutive model was implemented for characterizing the mechanical properties
of the amorphous matrix which includes the fibrous cap and the underlying
plaque tissue and a nonlinear elastic model was adopted for characterizing the
mechanical properties of the fibers. The CZM and elastic parameter values of
fibers were identified through an inverse boundary value approach that matches
the load-displacement curves from simulation predictions of tensile test of
collagen fibers with experimental measurements. The identified parameter values
were then used as input in the 3D unit cell model, through which
micromechanical factors affecting the resultant traction-separation relation
for the unit cell were investigated via a parametric analysis. Results of the
parametric analysis showed the applicability of the 3D unit cell model approach
for evaluating the micromechanical mechanisms of arterial tissue failure
processes.
|
[
{
"created": "Tue, 19 Jun 2018 21:11:39 GMT",
"version": "v1"
}
] |
2018-06-21
|
[
[
"Leng",
"Xiaochang",
""
],
[
"Yang",
"Yingchao",
""
],
[
"Deng",
"Xiaomin",
""
],
[
"Lessner",
"Susan M.",
""
],
[
"Sutton",
"Michael A.",
""
],
[
"Shazly",
"Tarek",
""
]
] |
Arterial tissue failures lead to a number of clinical conditions that develop rapidly and unpredictably in vivo. Structural components and their interfacial mechanical strength of arterial tissue play a critical role in the process of arterail delamination. Therefore, there is a pressing need to understand the micromechanical mechanisms of arterial delamination. The objective of this study was to investigate various failure mechanisms (e.g. failure of collagen fibers) responsible for arterial interfacial delamination. In-situ tensile tests of fibers were performed on a micro-tester in the scanning electron microscope. A 3D unit cell model containing an individual fiber bridging two arterial tissue layers was constructed. An exponential cohesive zone model (CZM) was used to assess the stiffening and softening mechanical behaviors of collagen fiber bundles between the two arterial layers. An anisotropic constitutive model was implemented for characterizing the mechanical properties of the amorphous matrix which includes the fibrous cap and the underlying plaque tissue and a nonlinear elastic model was adopted for characterizing the mechanical properties of the fibers. The CZM and elastic parameter values of fibers were identified through an inverse boundary value approach that matches the load-displacement curves from simulation predictions of tensile test of collagen fibers with experimental measurements. The identified parameter values were then used as input in the 3D unit cell model, through which micromechanical factors affecting the resultant traction-separation relation for the unit cell were investigated via a parametric analysis. Results of the parametric analysis showed the applicability of the 3D unit cell model approach for evaluating the micromechanical mechanisms of arterial tissue failure processes.
|
2105.13288
|
Soumyajyoti Biswas
|
Anvesh Reddy, Hanesh Koganti, Sai Krishna, Suhas Reddy, Soumyajyoti
Biswas
|
Machine learning predictions of COVID-19 second wave end-times in Indian
states
|
8 pages, 6 figures, 1 table
|
Indian Journal of Physics (2021)
|
10.1007/s12648-021-02195-x
| null |
q-bio.PE physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The estimate of the remaining time of an ongoing wave of epidemic spreading
is a critical issue. Due to the variations of a wide range of parameters in an
epidemic, for simple models such as Susceptible-Infected-Removed (SIR) model,
it is difficult to estimate such a time scale. On the other hand,
multidimensional data with a large set attributes are precisely what one can
use in statistical learning algorithms to make predictions. Here we show, how
the predictability of the SIR model changes with various parameters using a
supervised learning algorithm. We then estimate the condition in which the
model gives the least error in predicting the duration of the first wave of the
COVID-19 pandemic in different states in India. Finally, we use the SIR model
with the above mentioned optimal conditions to generate a training data set and
use it in the supervised learning algorithm to estimate the end-time of the
ongoing second wave of the pandemic in different states in India.
|
[
{
"created": "Wed, 26 May 2021 14:19:22 GMT",
"version": "v1"
}
] |
2021-10-12
|
[
[
"Reddy",
"Anvesh",
""
],
[
"Koganti",
"Hanesh",
""
],
[
"Krishna",
"Sai",
""
],
[
"Reddy",
"Suhas",
""
],
[
"Biswas",
"Soumyajyoti",
""
]
] |
The estimate of the remaining time of an ongoing wave of epidemic spreading is a critical issue. Due to the variations of a wide range of parameters in an epidemic, for simple models such as Susceptible-Infected-Removed (SIR) model, it is difficult to estimate such a time scale. On the other hand, multidimensional data with a large set attributes are precisely what one can use in statistical learning algorithms to make predictions. Here we show, how the predictability of the SIR model changes with various parameters using a supervised learning algorithm. We then estimate the condition in which the model gives the least error in predicting the duration of the first wave of the COVID-19 pandemic in different states in India. Finally, we use the SIR model with the above mentioned optimal conditions to generate a training data set and use it in the supervised learning algorithm to estimate the end-time of the ongoing second wave of the pandemic in different states in India.
|
2308.05115
|
Ziyang Xu
|
Ziyang Xu, Haitian Zhong, Bingrui He, Xueying Wang and Tianchi Lu
|
PTransIPs: Identification of phosphorylation sites enhanced by protein
PLM embeddings
| null | null |
10.1109/JBHI.2024.3377362
| null |
q-bio.QM cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Phosphorylation is pivotal in numerous fundamental cellular processes and
plays a significant role in the onset and progression of various diseases. The
accurate identification of these phosphorylation sites is crucial for
unraveling the molecular mechanisms within cells and during viral infections,
potentially leading to the discovery of novel therapeutic targets. In this
study, we develop PTransIPs, a new deep learning framework for the
identification of phosphorylation sites. Independent testing results
demonstrate that PTransIPs outperforms existing state-of-the-art (SOTA)
methods, achieving AUCs of 0.9232 and 0.9660 for the identification of
phosphorylated S/T and Y sites, respectively. PTransIPs contributes from three
aspects. 1) PTransIPs is the first to apply protein pre-trained language model
(PLM) embeddings to this task. It utilizes ProtTrans and EMBER2 to extract
sequence and structure embeddings, respectively, as additional inputs into the
model, effectively addressing issues of dataset size and overfitting, thus
enhancing model performance; 2) PTransIPs is based on Transformer architecture,
optimized through the integration of convolutional neural networks and TIM loss
function, providing practical insights for model design and training; 3) The
encoding of amino acids in PTransIPs enables it to serve as a universal
framework for other peptide bioactivity tasks, with its excellent performance
shown in extended experiments of this paper. Our code, data and models are
publicly available at https://github.com/StatXzy7/PTransIPs.
|
[
{
"created": "Tue, 8 Aug 2023 07:50:38 GMT",
"version": "v1"
},
{
"created": "Fri, 18 Aug 2023 06:35:50 GMT",
"version": "v2"
},
{
"created": "Wed, 13 Mar 2024 05:02:32 GMT",
"version": "v3"
}
] |
2024-03-27
|
[
[
"Xu",
"Ziyang",
""
],
[
"Zhong",
"Haitian",
""
],
[
"He",
"Bingrui",
""
],
[
"Wang",
"Xueying",
""
],
[
"Lu",
"Tianchi",
""
]
] |
Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. The accurate identification of these phosphorylation sites is crucial for unraveling the molecular mechanisms within cells and during viral infections, potentially leading to the discovery of novel therapeutic targets. In this study, we develop PTransIPs, a new deep learning framework for the identification of phosphorylation sites. Independent testing results demonstrate that PTransIPs outperforms existing state-of-the-art (SOTA) methods, achieving AUCs of 0.9232 and 0.9660 for the identification of phosphorylated S/T and Y sites, respectively. PTransIPs contributes from three aspects. 1) PTransIPs is the first to apply protein pre-trained language model (PLM) embeddings to this task. It utilizes ProtTrans and EMBER2 to extract sequence and structure embeddings, respectively, as additional inputs into the model, effectively addressing issues of dataset size and overfitting, thus enhancing model performance; 2) PTransIPs is based on Transformer architecture, optimized through the integration of convolutional neural networks and TIM loss function, providing practical insights for model design and training; 3) The encoding of amino acids in PTransIPs enables it to serve as a universal framework for other peptide bioactivity tasks, with its excellent performance shown in extended experiments of this paper. Our code, data and models are publicly available at https://github.com/StatXzy7/PTransIPs.
|
2302.06842
|
Gerry Gralton
|
S. Gerry Gralton, Farah Alkhatib, Ben Zwick, George Bourantas, Adam
Wittek, Karol Miller
|
Random boundaries: quantifying segmentation uncertainty in solutions to
boundary-value problems
| null | null | null | null |
q-bio.TO
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Engineering simulations using boundary-value partial differential equations
often implicitly assume that the uncertainty in the location of the boundary
has a negligible impact on the output of the simulation. In this work, we
develop a novel method for describing the geometric uncertainty in
image-derived models and use a naive method for subsequently quantifying a
simulation's sensitivity to that uncertainty. A Gaussian random field is
constructed to represent the space of possible geometries, based on
image-derived quantities such as pixel size, which can then be used to probe
the simulation's output space. The algorithm is demonstrated with examples from
biomechanics where patient-specific geometries are often segmented from
low-resolution, three-dimensional images. These examples show the method's wide
applicability with examples using linear elasticity and fluid dynamics. We show
that important biomechanical outputs of these example simulations, namely
maximum principal stress and wall shear stress, can be highly sensitive to
realistic uncertainties in geometry.
|
[
{
"created": "Tue, 14 Feb 2023 05:33:06 GMT",
"version": "v1"
},
{
"created": "Sun, 28 Jan 2024 12:53:23 GMT",
"version": "v2"
},
{
"created": "Mon, 10 Jun 2024 02:56:39 GMT",
"version": "v3"
}
] |
2024-06-11
|
[
[
"Gralton",
"S. Gerry",
""
],
[
"Alkhatib",
"Farah",
""
],
[
"Zwick",
"Ben",
""
],
[
"Bourantas",
"George",
""
],
[
"Wittek",
"Adam",
""
],
[
"Miller",
"Karol",
""
]
] |
Engineering simulations using boundary-value partial differential equations often implicitly assume that the uncertainty in the location of the boundary has a negligible impact on the output of the simulation. In this work, we develop a novel method for describing the geometric uncertainty in image-derived models and use a naive method for subsequently quantifying a simulation's sensitivity to that uncertainty. A Gaussian random field is constructed to represent the space of possible geometries, based on image-derived quantities such as pixel size, which can then be used to probe the simulation's output space. The algorithm is demonstrated with examples from biomechanics where patient-specific geometries are often segmented from low-resolution, three-dimensional images. These examples show the method's wide applicability with examples using linear elasticity and fluid dynamics. We show that important biomechanical outputs of these example simulations, namely maximum principal stress and wall shear stress, can be highly sensitive to realistic uncertainties in geometry.
|
1907.09151
|
Luca Ciandrini
|
Pascal S. Rogalla, Timothy J. Rudge and Luca Ciandrini
|
An equilibrium model for ribosome competition
| null | null |
10.1088/1478-3975/ab4fbc
| null |
q-bio.SC cond-mat.stat-mech physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The number of ribosomes in a cell is considered as limiting, and gene
expression is thus largely determined by their cellular concentration. In this
work we develop a toy model to study the trade-off between the ribosomal supply
and the demand of the translation machinery, dictated by the composition of the
transcript pool. Our equilibrium framework is useful to highlight qualitative
behaviours and new means of gene expression regulation determined by the fine
balance of this trade-off. We also speculate on the possible impact of these
mechanisms on cellular physiology.
|
[
{
"created": "Mon, 22 Jul 2019 06:35:29 GMT",
"version": "v1"
},
{
"created": "Mon, 14 Oct 2019 20:42:24 GMT",
"version": "v2"
}
] |
2020-02-19
|
[
[
"Rogalla",
"Pascal S.",
""
],
[
"Rudge",
"Timothy J.",
""
],
[
"Ciandrini",
"Luca",
""
]
] |
The number of ribosomes in a cell is considered as limiting, and gene expression is thus largely determined by their cellular concentration. In this work we develop a toy model to study the trade-off between the ribosomal supply and the demand of the translation machinery, dictated by the composition of the transcript pool. Our equilibrium framework is useful to highlight qualitative behaviours and new means of gene expression regulation determined by the fine balance of this trade-off. We also speculate on the possible impact of these mechanisms on cellular physiology.
|
1806.01467
|
Susan Cheng
|
Jeramie D. Watrous, Teemu Niiranen, Kim A. Lagerborg, Mir Henglin,
Yong-Jian Xu, Sonia Sharma, Ramachandran S. Vasan, Martin G. Larson, Aaron
Armando, Oswald Quehenberger, Edward A. Dennis, Susan Cheng, Mohit Jain
|
Directed Non-Targeted Mass Spectrometry and Chemical Networking for
Discovery of Eicosanoids
| null | null | null | null |
q-bio.BM
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Eicosanoids and related species are critical, small bioactive mediators of
human physiology and inflammation. While ~1100 distinct eicosanoids have been
predicted to exist, to date, less than 150 of these molecules have been
measured in humans, limiting our understanding of eicosanoids and their role in
human biology. Using a directed non-targeted mass spectrometry approach in
conjunction with computational chemical networking of spectral fragmentation
patterns, we find over 500 discrete chemical signals highly consistent with
known and putative eicosanoids in human plasma, including 46 putative novel
molecules not previously described, thereby greatly expanding the breath of
prior analytical strategies. In plasma samples from 1500 individuals, we find
members of this expanded eicosanoid library hold close association with markers
of inflammation, as well as clinical characteristics linked with inflammation,
including advancing age and obesity. These experimental and computational
approaches enable discovery of new chemical entities and will shed important
insight into the role of bioactive molecules in human disease.
|
[
{
"created": "Tue, 5 Jun 2018 02:24:59 GMT",
"version": "v1"
}
] |
2018-06-06
|
[
[
"Watrous",
"Jeramie D.",
""
],
[
"Niiranen",
"Teemu",
""
],
[
"Lagerborg",
"Kim A.",
""
],
[
"Henglin",
"Mir",
""
],
[
"Xu",
"Yong-Jian",
""
],
[
"Sharma",
"Sonia",
""
],
[
"Vasan",
"Ramachandran S.",
""
],
[
"Larson",
"Martin G.",
""
],
[
"Armando",
"Aaron",
""
],
[
"Quehenberger",
"Oswald",
""
],
[
"Dennis",
"Edward A.",
""
],
[
"Cheng",
"Susan",
""
],
[
"Jain",
"Mohit",
""
]
] |
Eicosanoids and related species are critical, small bioactive mediators of human physiology and inflammation. While ~1100 distinct eicosanoids have been predicted to exist, to date, less than 150 of these molecules have been measured in humans, limiting our understanding of eicosanoids and their role in human biology. Using a directed non-targeted mass spectrometry approach in conjunction with computational chemical networking of spectral fragmentation patterns, we find over 500 discrete chemical signals highly consistent with known and putative eicosanoids in human plasma, including 46 putative novel molecules not previously described, thereby greatly expanding the breath of prior analytical strategies. In plasma samples from 1500 individuals, we find members of this expanded eicosanoid library hold close association with markers of inflammation, as well as clinical characteristics linked with inflammation, including advancing age and obesity. These experimental and computational approaches enable discovery of new chemical entities and will shed important insight into the role of bioactive molecules in human disease.
|
1208.1560
|
Jiang Zhang
|
Jiang Zhang and Yuanjing Feng
|
Common Patterns of Energy Flow and Biomass Distribution on Weighted Food
Webs
|
26 pages, 7 figures
| null | null | null |
q-bio.PE physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Weights of edges and nodes on food webs which are available from the
empirical data hide much information about energy flows and biomass
distributions in ecosystem. We define a set of variables related to weights for
each species $i$, including the throughflow $T_i$, the total biomass $X_i$, and
the dissipated flow $D_i$ (output to the environment) to uncover the following
common patterns in 19 empirical weighted food webs: (1) DGBD distributions
(Discrete version of a Generalized Beta Distribution), a kind of deformed
Zipf's law, of energy flow and storage biomass; (2) The allometric scaling law
$T_i\propto X_i^{\alpha}$, which can be viewed as the counterpart of the
Kleiber's 3/4 law at the population level; (3) The dissipation law $D_i\propto
T_i^{\beta}$; and (4) The gravity law, including univariate version
$f_{ij}\propto (T_iT_j)^{\gamma}$ and bivariate approvement $f_{ij}\propto
T_i^{\gamma_1}T_j^{\gamma_2}$. These patterns are very common and significant
in all collected webs, as a result, some remarkable regularities are hidden in
weights.
|
[
{
"created": "Wed, 8 Aug 2012 01:25:39 GMT",
"version": "v1"
}
] |
2012-08-09
|
[
[
"Zhang",
"Jiang",
""
],
[
"Feng",
"Yuanjing",
""
]
] |
Weights of edges and nodes on food webs which are available from the empirical data hide much information about energy flows and biomass distributions in ecosystem. We define a set of variables related to weights for each species $i$, including the throughflow $T_i$, the total biomass $X_i$, and the dissipated flow $D_i$ (output to the environment) to uncover the following common patterns in 19 empirical weighted food webs: (1) DGBD distributions (Discrete version of a Generalized Beta Distribution), a kind of deformed Zipf's law, of energy flow and storage biomass; (2) The allometric scaling law $T_i\propto X_i^{\alpha}$, which can be viewed as the counterpart of the Kleiber's 3/4 law at the population level; (3) The dissipation law $D_i\propto T_i^{\beta}$; and (4) The gravity law, including univariate version $f_{ij}\propto (T_iT_j)^{\gamma}$ and bivariate approvement $f_{ij}\propto T_i^{\gamma_1}T_j^{\gamma_2}$. These patterns are very common and significant in all collected webs, as a result, some remarkable regularities are hidden in weights.
|
2102.04720
|
Brian Mathias
|
Brian Mathias, Christian Andrae, Anika Schwager, Manuela Macedonia,
Katharina von Kriegstein
|
Twelve- and fourteen-year-old school children differentially benefit
from sensorimotor- and multisensory-enriched vocabulary training
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Both children and adults have been shown to benefit from the integration of
multisensory and sensorimotor enrichment into pedagogy. For example,
integrating pictures or gestures into foreign language (L2) vocabulary learning
can improve learning outcomes relative to unisensory learning. However, whereas
adults seem to benefit to a greater extent from sensorimotor enrichment such as
the performance of gestures in contrast to multisensory enrichment with
pictures, this is not the case in elementary school children. Here, we compared
multisensory- and sensorimotor-enriched learning in an intermediate age group
that falls between the age groups tested in previous studies (elementary school
children and young adults), in an attempt to determine the developmental time
point at which children's responses to enrichment mature from a child-like
pattern into an adult-like pattern. Twelve-year-old and fourteen-year-old
German children were trained over 5 consecutive days on auditorily-presented,
concrete and abstract, Spanish vocabulary. The vocabulary was learned under
picture-enriched, gesture-enriched, and non-enriched (auditory-only)
conditions. The children performed vocabulary recall and translation tests at 3
days, 2 months, and 6 months post-learning. Both picture and gesture enrichment
interventions were found to benefit children's L2 learning relative to
non-enriched learning up to 6 months post-training. Interestingly,
gesture-enriched learning was even more beneficial than picture-enriched
learning for the fourteen-year-olds, while the twelve-year-olds benefitted
equivalently from learning enriched with pictures and gestures. These findings
provide evidence for opting to integrate gestures rather than pictures into L2
pedagogy starting at fourteen years of age.
|
[
{
"created": "Tue, 9 Feb 2021 09:32:12 GMT",
"version": "v1"
}
] |
2021-02-10
|
[
[
"Mathias",
"Brian",
""
],
[
"Andrae",
"Christian",
""
],
[
"Schwager",
"Anika",
""
],
[
"Macedonia",
"Manuela",
""
],
[
"von Kriegstein",
"Katharina",
""
]
] |
Both children and adults have been shown to benefit from the integration of multisensory and sensorimotor enrichment into pedagogy. For example, integrating pictures or gestures into foreign language (L2) vocabulary learning can improve learning outcomes relative to unisensory learning. However, whereas adults seem to benefit to a greater extent from sensorimotor enrichment such as the performance of gestures in contrast to multisensory enrichment with pictures, this is not the case in elementary school children. Here, we compared multisensory- and sensorimotor-enriched learning in an intermediate age group that falls between the age groups tested in previous studies (elementary school children and young adults), in an attempt to determine the developmental time point at which children's responses to enrichment mature from a child-like pattern into an adult-like pattern. Twelve-year-old and fourteen-year-old German children were trained over 5 consecutive days on auditorily-presented, concrete and abstract, Spanish vocabulary. The vocabulary was learned under picture-enriched, gesture-enriched, and non-enriched (auditory-only) conditions. The children performed vocabulary recall and translation tests at 3 days, 2 months, and 6 months post-learning. Both picture and gesture enrichment interventions were found to benefit children's L2 learning relative to non-enriched learning up to 6 months post-training. Interestingly, gesture-enriched learning was even more beneficial than picture-enriched learning for the fourteen-year-olds, while the twelve-year-olds benefitted equivalently from learning enriched with pictures and gestures. These findings provide evidence for opting to integrate gestures rather than pictures into L2 pedagogy starting at fourteen years of age.
|
q-bio/0407023
|
Steven Samuel Plotkin
|
C. Clementi and S. S. Plotkin
|
The effects of non-native interactions on protein folding rates: Theory
and simulation
|
35 pages, 12 figures, 1 table
|
Protein Science 2004 13: 1750-1766
| null | null |
q-bio.BM
| null |
Proteins are minimally frustrated polymers. However, for realistic protein
models non-native interactions must be taken into account. In this paper we
analyze the effect of non-native interactions on the folding rate and on the
folding free energy barrier. We present an analytic theory to account for the
modification on the free energy landscape upon introduction of non-native
contacts, added as a perturbation to the strong native interactions driving
folding. Our theory predicts a rate-enhancement regime at fixed temperature,
under the introduction of weak, non-native interactions. We have thoroughly
tested this theoretical prediction with simulations of a coarse-grained protein
model, by employing an off-lattice $C_\alpha$ model of the src-SH3 domain. The
strong agreement between results from simulations and theory confirm the non
trivial result that a relatively small amount of non-native interaction energy
can actually assist the folding to the native structure.
|
[
{
"created": "Thu, 15 Jul 2004 01:44:42 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Clementi",
"C.",
""
],
[
"Plotkin",
"S. S.",
""
]
] |
Proteins are minimally frustrated polymers. However, for realistic protein models non-native interactions must be taken into account. In this paper we analyze the effect of non-native interactions on the folding rate and on the folding free energy barrier. We present an analytic theory to account for the modification on the free energy landscape upon introduction of non-native contacts, added as a perturbation to the strong native interactions driving folding. Our theory predicts a rate-enhancement regime at fixed temperature, under the introduction of weak, non-native interactions. We have thoroughly tested this theoretical prediction with simulations of a coarse-grained protein model, by employing an off-lattice $C_\alpha$ model of the src-SH3 domain. The strong agreement between results from simulations and theory confirm the non trivial result that a relatively small amount of non-native interaction energy can actually assist the folding to the native structure.
|
1907.06909
|
Kevin Woods
|
Kevin J P Woods, Adam Hewett, Andrea Spencer, Benjamin Morillon,
Psyche Loui
|
Modulation in background music influences sustained attention
|
20 pages, 5 figures. Behavioral portion of larger planned manuscript
to include neuroimaging. Comments welcome (kevin@brain.fm)
| null | null | null |
q-bio.NC q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Background music is known to affect performance on cognitive tasks, possibly
due to temporal modulations in the acoustic signal, but little is known about
how music should be designed to aid performance. Since acoustic modulation has
been shown to shape neural activity in known networks, we chose to test the
effects of acoustic modulation on sustained attention, which requires activity
in these networks and is a common ingredient for success across many tasks. To
understand how specific aspects of background music influence sustained
attention, we manipulated the rate and depth of amplitude modulations imposed
on otherwise identical music. This produced stimuli that were musically and
acoustically identical except for a peak in the modulation spectrum that could
change intensity or shift location under manipulations of depth or rate
respectively. These controlled musical backgrounds were presented to
participants (total N = 677) during the sustained attention to response (SART)
task. In two experiments, we show performance benefits due to added modulation,
with best performance at 16 Hz (beta band) rate and higher modulation depths;
neighboring parameter settings did not produce this benefit. Further
examination of individual differences within our overall sample showed that
those with a high level of self-reported ADHD symptomaticity tended to perform
better with more intense beta modulation. These results suggest optimal
parameters for adding modulation to background music, which are consistent with
theories of oscillatory dynamics that relate auditory stimulation to behavior,
yet demonstrate the need for a personalized approach in creating functional
music for everyday use.
|
[
{
"created": "Tue, 16 Jul 2019 09:33:39 GMT",
"version": "v1"
}
] |
2019-07-17
|
[
[
"Woods",
"Kevin J P",
""
],
[
"Hewett",
"Adam",
""
],
[
"Spencer",
"Andrea",
""
],
[
"Morillon",
"Benjamin",
""
],
[
"Loui",
"Psyche",
""
]
] |
Background music is known to affect performance on cognitive tasks, possibly due to temporal modulations in the acoustic signal, but little is known about how music should be designed to aid performance. Since acoustic modulation has been shown to shape neural activity in known networks, we chose to test the effects of acoustic modulation on sustained attention, which requires activity in these networks and is a common ingredient for success across many tasks. To understand how specific aspects of background music influence sustained attention, we manipulated the rate and depth of amplitude modulations imposed on otherwise identical music. This produced stimuli that were musically and acoustically identical except for a peak in the modulation spectrum that could change intensity or shift location under manipulations of depth or rate respectively. These controlled musical backgrounds were presented to participants (total N = 677) during the sustained attention to response (SART) task. In two experiments, we show performance benefits due to added modulation, with best performance at 16 Hz (beta band) rate and higher modulation depths; neighboring parameter settings did not produce this benefit. Further examination of individual differences within our overall sample showed that those with a high level of self-reported ADHD symptomaticity tended to perform better with more intense beta modulation. These results suggest optimal parameters for adding modulation to background music, which are consistent with theories of oscillatory dynamics that relate auditory stimulation to behavior, yet demonstrate the need for a personalized approach in creating functional music for everyday use.
|
1810.08362
|
Gerardo F. Goya
|
V. Raffa, F. Falcone, M.P. Calatayud, G.F. Goya and A. Cuschieri
|
Pico-Newton mechanical forces promote neurite growth
|
16 pages, 3 figures
| null |
10.1016/j.bpj.2018.10.009
| null |
q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Investigations over half a century have indicated that mechanical forces
induce neurite growth - with neurites elongating at a rate of
0.1-0.3{\mu}mh^{-1} per pico-Newton (pN) of applied force - when mechanical
tension exceeds a threshold, with this being identified as 400-1000 pN for
neurites of PC12 cells. Here we demonstrate that there is no threshold for
neurite elongation of PC12 cells in response to applied mechanical forces.
Instead, this proceeds at the same previously identified rate, on the
application of tensions with intensity below 1pN. This supports the idea of
mechanical tension as an endogenous signal used by neurons for promoting
neurite elongation.
|
[
{
"created": "Fri, 19 Oct 2018 06:20:53 GMT",
"version": "v1"
}
] |
2018-10-22
|
[
[
"Raffa",
"V.",
""
],
[
"Falcone",
"F.",
""
],
[
"Calatayud",
"M. P.",
""
],
[
"Goya",
"G. F.",
""
],
[
"Cuschieri",
"A.",
""
]
] |
Investigations over half a century have indicated that mechanical forces induce neurite growth - with neurites elongating at a rate of 0.1-0.3{\mu}mh^{-1} per pico-Newton (pN) of applied force - when mechanical tension exceeds a threshold, with this being identified as 400-1000 pN for neurites of PC12 cells. Here we demonstrate that there is no threshold for neurite elongation of PC12 cells in response to applied mechanical forces. Instead, this proceeds at the same previously identified rate, on the application of tensions with intensity below 1pN. This supports the idea of mechanical tension as an endogenous signal used by neurons for promoting neurite elongation.
|
0912.5450
|
Piotr Su{\l}kowski
|
Joanna I. Su{\l}kowska, Piotr Su{\l}kowski, Jos\'e N. Onuchic
|
Dodging the crisis of folding proteins with knots
|
29 pages, 11 figures, 1 table
|
PNAS 106 (2009) 3119-3124
|
10.1073/pnas.0811147106
| null |
q-bio.BM cond-mat.soft
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Proteins with nontrivial topology, containing knots and slipknots, have the
ability to fold to their native states without any additional external forces
invoked. A mechanism is suggested for folding of these proteins, such as YibK
and YbeA, which involves an intermediate configuration with a slipknot. It
elucidates the role of topological barriers and backtracking during the folding
event. It also illustrates that native contacts are sufficient to guarantee
folding in around 1-2% of the simulations, and how slipknot intermediates are
needed to reduce the topological bottlenecks. As expected, simulations of
proteins with similar structure but with knot removed fold much more
efficiently, clearly demonstrating the origin of these topological barriers.
Although these studies are based on a simple coarse-grained model, they are
already able to extract some of the underlying principles governing folding in
such complex topologies.
|
[
{
"created": "Wed, 30 Dec 2009 20:55:10 GMT",
"version": "v1"
}
] |
2010-01-06
|
[
[
"Sułkowska",
"Joanna I.",
""
],
[
"Sułkowski",
"Piotr",
""
],
[
"Onuchic",
"José N.",
""
]
] |
Proteins with nontrivial topology, containing knots and slipknots, have the ability to fold to their native states without any additional external forces invoked. A mechanism is suggested for folding of these proteins, such as YibK and YbeA, which involves an intermediate configuration with a slipknot. It elucidates the role of topological barriers and backtracking during the folding event. It also illustrates that native contacts are sufficient to guarantee folding in around 1-2% of the simulations, and how slipknot intermediates are needed to reduce the topological bottlenecks. As expected, simulations of proteins with similar structure but with knot removed fold much more efficiently, clearly demonstrating the origin of these topological barriers. Although these studies are based on a simple coarse-grained model, they are already able to extract some of the underlying principles governing folding in such complex topologies.
|
1702.06665
|
Michael Beyeler
|
Michael Beyeler and Nikil Dutt and Jeffrey L. Krichmar
|
Visual response properties of MSTd emerge from a sparse population code
| null | null |
10.1523/JNEUROSCI.0396-16.2016
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Neurons in the dorsal subregion of the medial superior temporal (MSTd) area
respond to large, complex patterns of retinal flow, implying a role in the
analysis of self-motion. Some neurons are selective for the expanding radial
motion that occurs as an observer moves through the environment ("heading"),
and computational models can account for this finding. However, ample evidence
suggests that MSTd neurons may exhibit a continuum of visual response
selectivity to large-field motion stimuli, but the underlying computational
principles by which these response properties are derived remain poorly
understood. Here we describe a computational model of MSTd based on the
hypothesis that neurons in MSTd efficiently encode the continuum of large-field
retinal flow patterns on the basis of inputs received from neurons in MT, with
receptive fields that resemble basis vectors recovered with nonnegative matrix
factorization (NMF). These assumptions are sufficient to quantitatively
simulate neurophysiological response properties of MSTd cells such as radial,
circular, and spiral motion tuning, suggesting that these properties might
simply be a by-product of MSTd neurons performing dimensionality reduction on
their inputs. At the population level, model MSTd accurately predicts heading
using a sparse distributed code, consistent with the idea that biological MSTd
might operate in a sparseness regime well-suited to efficiently encode a number
of self-motion variables. The present work provides an alternative to the
template-model view of MSTd, and offers a biologically plausible account of the
receptive field structure across a wide range of visual response properties in
MSTd.
|
[
{
"created": "Wed, 22 Feb 2017 03:41:02 GMT",
"version": "v1"
}
] |
2017-02-24
|
[
[
"Beyeler",
"Michael",
""
],
[
"Dutt",
"Nikil",
""
],
[
"Krichmar",
"Jeffrey L.",
""
]
] |
Neurons in the dorsal subregion of the medial superior temporal (MSTd) area respond to large, complex patterns of retinal flow, implying a role in the analysis of self-motion. Some neurons are selective for the expanding radial motion that occurs as an observer moves through the environment ("heading"), and computational models can account for this finding. However, ample evidence suggests that MSTd neurons may exhibit a continuum of visual response selectivity to large-field motion stimuli, but the underlying computational principles by which these response properties are derived remain poorly understood. Here we describe a computational model of MSTd based on the hypothesis that neurons in MSTd efficiently encode the continuum of large-field retinal flow patterns on the basis of inputs received from neurons in MT, with receptive fields that resemble basis vectors recovered with nonnegative matrix factorization (NMF). These assumptions are sufficient to quantitatively simulate neurophysiological response properties of MSTd cells such as radial, circular, and spiral motion tuning, suggesting that these properties might simply be a by-product of MSTd neurons performing dimensionality reduction on their inputs. At the population level, model MSTd accurately predicts heading using a sparse distributed code, consistent with the idea that biological MSTd might operate in a sparseness regime well-suited to efficiently encode a number of self-motion variables. The present work provides an alternative to the template-model view of MSTd, and offers a biologically plausible account of the receptive field structure across a wide range of visual response properties in MSTd.
|
1510.06748
|
Luca Ferretti
|
Luca Ferretti, Alice Ledda, Guillaume Achaz, Thomas Wiehe and
Sebastian E. Ramos-Onsins
|
Decomposing the site frequency spectrum: the impact of tree topology on
neutrality tests
|
23 pages, 8 figures
| null | null | null |
q-bio.PE q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We investigate the dependence of the site frequency spectrum (SFS) on the
topological structure of genealogical trees. We show that basic population
genetic statistics - for instance estimators of $\theta$ or neutrality tests
such as Tajima's $D$ - can be decomposed into components of waiting times
between coalescent events and of tree topology. Our results clarify the
relative impact of the two components on these statistics. We provide a
rigorous interpretation of positive or negative values of an important class of
neutrality tests in terms of the underlying tree shape. In particular, we show
that values of Tajima's $D$ and Fay and Wu's $H$ depend in a direct way on a
peculiar measure of tree balance which is mostly determined by the root balance
of the tree. We present a new test for selection in the same class as Fay and
Wu's $H$ and discuss its interpretation and power. Finally, we determine the
trees corresponding to extreme expected values of these neutrality tests and
present formulae for these extreme values as a function of sample size and
number of segregating sites.
|
[
{
"created": "Thu, 22 Oct 2015 20:10:48 GMT",
"version": "v1"
},
{
"created": "Thu, 12 Jan 2017 23:50:59 GMT",
"version": "v2"
}
] |
2017-01-16
|
[
[
"Ferretti",
"Luca",
""
],
[
"Ledda",
"Alice",
""
],
[
"Achaz",
"Guillaume",
""
],
[
"Wiehe",
"Thomas",
""
],
[
"Ramos-Onsins",
"Sebastian E.",
""
]
] |
We investigate the dependence of the site frequency spectrum (SFS) on the topological structure of genealogical trees. We show that basic population genetic statistics - for instance estimators of $\theta$ or neutrality tests such as Tajima's $D$ - can be decomposed into components of waiting times between coalescent events and of tree topology. Our results clarify the relative impact of the two components on these statistics. We provide a rigorous interpretation of positive or negative values of an important class of neutrality tests in terms of the underlying tree shape. In particular, we show that values of Tajima's $D$ and Fay and Wu's $H$ depend in a direct way on a peculiar measure of tree balance which is mostly determined by the root balance of the tree. We present a new test for selection in the same class as Fay and Wu's $H$ and discuss its interpretation and power. Finally, we determine the trees corresponding to extreme expected values of these neutrality tests and present formulae for these extreme values as a function of sample size and number of segregating sites.
|
0711.1010
|
Akira Kinjo
|
Akira R. Kinjo and Haruki Nakamura
|
Nature of protein family signatures: Insights from singular value
analysis of position-specific scoring matrices
|
22 pages, 7 figures, 4 tables
|
PLoS ONE, 3:e1963 (2008)
|
10.1371/journal.pone.0001963
| null |
q-bio.BM
| null |
Position-specific scoring matrices (PSSMs) are useful for detecting weak
homology in protein sequence analysis, and they are thought to contain some
essential signatures of the protein families. In order to elucidate what kind
of ingredients constitute such family-specific signatures, we apply singular
value decomposition to a set of PSSMs and examine the properties of dominant
right and left singular vectors. The first right singular vectors were
correlated with various amino acid indices including relative mutability, amino
acid composition in protein interior, hydropathy, or turn propensity, depending
on proteins. A significant correlation between the first left singular vector
and a measure of site conservation was observed. It is shown that the
contribution of the first singular component to the PSSMs act to disfavor
potentially but falsely functionally important residues at conserved sites. The
second right singular vectors were highly correlated with hydrophobicity
scales, and the corresponding left singular vectors with contact numbers of
protein structures. It is suggested that sequence alignment with a PSSM is
essentially equivalent to threading supplemented with functional information.
The presented method may be used to separate functionally important sites from
structurally important ones, and thus it may be a useful tool for predicting
protein functions.
|
[
{
"created": "Wed, 7 Nov 2007 05:20:40 GMT",
"version": "v1"
}
] |
2008-04-14
|
[
[
"Kinjo",
"Akira R.",
""
],
[
"Nakamura",
"Haruki",
""
]
] |
Position-specific scoring matrices (PSSMs) are useful for detecting weak homology in protein sequence analysis, and they are thought to contain some essential signatures of the protein families. In order to elucidate what kind of ingredients constitute such family-specific signatures, we apply singular value decomposition to a set of PSSMs and examine the properties of dominant right and left singular vectors. The first right singular vectors were correlated with various amino acid indices including relative mutability, amino acid composition in protein interior, hydropathy, or turn propensity, depending on proteins. A significant correlation between the first left singular vector and a measure of site conservation was observed. It is shown that the contribution of the first singular component to the PSSMs act to disfavor potentially but falsely functionally important residues at conserved sites. The second right singular vectors were highly correlated with hydrophobicity scales, and the corresponding left singular vectors with contact numbers of protein structures. It is suggested that sequence alignment with a PSSM is essentially equivalent to threading supplemented with functional information. The presented method may be used to separate functionally important sites from structurally important ones, and thus it may be a useful tool for predicting protein functions.
|
2305.02223
|
Maryam Al Yahyai
|
Maryam Al-Yahyai (1), Fatma Al-Musalhi (1), Nasser Al-Salti (2) and
Ibrahim Elmojtaba (1) ((1) Department of Mathematics, College of Science,
Sultan Qaboos University, Muscat, Oman, (2) Department of Applied Mathematics
and Science, National University of Science and Technology, Muscat, Oman)
|
The Role of Quarantine and Isolation in Controlling COVID-19
Hospitalization in Oman
|
34 pages
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we build a mathematical model for the dynamics of COVID-19 to
assess the impact of placing healthy individuals in quarantine and isolating
infected ones on the number of hospitalization and intensive care unit cases.
The proposed model is fully analyzed in order to prove the positivity of
solutions, to study the local and global stability of the disease-free
equilibria and to drive the basic and control reproduction numbers of the
model. Oman COVID-19 data is used to calibrate the model and estimate the
parameters. In particular, the published data for the year 2020 is used, when
two waves of the disease hit the country. Moreover, this period of time is
chosen when no vaccine had been introduced, but only the non-pharmaceutical
intervention (NPI) strategies were the only effective methods to control the
spread and, consequently, control the hospitalization cases to avoid pressuring
the health system. Based on the estimated parameters, the reproduction number
and contribution of different transmission routes are approximated numerically.
Sensitivity analysis is performed to identify the significant parameters in
spreading the disease. Numerical simulation is carried out to demonstrate the
effects of quarantine and isolation on the number of hospitalized cases.
|
[
{
"created": "Wed, 3 May 2023 16:03:27 GMT",
"version": "v1"
}
] |
2023-05-04
|
[
[
"Al-Yahyai",
"Maryam",
""
],
[
"Al-Musalhi",
"Fatma",
""
],
[
"Al-Salti",
"Nasser",
""
],
[
"Elmojtaba",
"Ibrahim",
""
]
] |
In this paper, we build a mathematical model for the dynamics of COVID-19 to assess the impact of placing healthy individuals in quarantine and isolating infected ones on the number of hospitalization and intensive care unit cases. The proposed model is fully analyzed in order to prove the positivity of solutions, to study the local and global stability of the disease-free equilibria and to drive the basic and control reproduction numbers of the model. Oman COVID-19 data is used to calibrate the model and estimate the parameters. In particular, the published data for the year 2020 is used, when two waves of the disease hit the country. Moreover, this period of time is chosen when no vaccine had been introduced, but only the non-pharmaceutical intervention (NPI) strategies were the only effective methods to control the spread and, consequently, control the hospitalization cases to avoid pressuring the health system. Based on the estimated parameters, the reproduction number and contribution of different transmission routes are approximated numerically. Sensitivity analysis is performed to identify the significant parameters in spreading the disease. Numerical simulation is carried out to demonstrate the effects of quarantine and isolation on the number of hospitalized cases.
|
2102.03676
|
Xavier Michalet
|
Xavier Michalet
|
An overview of continuous and discrete phasor analysis of binned or
time-gated periodic decays
|
12 pages, 4 figures, submitted as a Proceedings of SPIE (BiOS
Conference 11648, March 6-11, 2021)
|
Proc. SPIE 11648 (2021) 116480E
|
10.1063/5.0027834
| null |
q-bio.QM
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Time-resolved analysis of periodically excited luminescence decays by the
phasor method in the presence of time-gating or binning is revisited.
Analytical expressions for discrete configurations of square gates are derived
and the locus of the phasors of such modified periodic single-exponential
decays is compared to the canonical universal semicircle. The effects of IRF
offset, decay truncation and gate shape are also discussed. Finally, modified
expressions for the phase and modulus lifetimes are provided for some simple
cases. A discussion of a modified phasor calibration approach is presented.
|
[
{
"created": "Sat, 6 Feb 2021 22:00:55 GMT",
"version": "v1"
},
{
"created": "Thu, 11 Feb 2021 21:49:10 GMT",
"version": "v2"
}
] |
2024-06-12
|
[
[
"Michalet",
"Xavier",
""
]
] |
Time-resolved analysis of periodically excited luminescence decays by the phasor method in the presence of time-gating or binning is revisited. Analytical expressions for discrete configurations of square gates are derived and the locus of the phasors of such modified periodic single-exponential decays is compared to the canonical universal semicircle. The effects of IRF offset, decay truncation and gate shape are also discussed. Finally, modified expressions for the phase and modulus lifetimes are provided for some simple cases. A discussion of a modified phasor calibration approach is presented.
|
2004.02398
|
Siyu Liu
|
Jiwei Jia, Siyu Liu, Jing Ding, Guidong Liao, Lihua Zhang, Ran Zhang
|
The impact of multilateral imported cases of COVID-19 on the epidemic
control in China
| null | null | null | null |
q-bio.PE math.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Nowadays, the epidemic of COVID-19 in China is under control. However, the
epidemic are developing rapidly around the world. Due to the normal migration
of population, China is facing high risk from imported cases. The potential
specific medicine and vaccine is still in the process of clinical trials.
Currently, controlling the impact of imported cases is the key to prevent new
outbreak of COVID-19 in China. In this paper, we propose two impulsive systems
to describe the impact of multilateral imported cases of COVID-19. Based on the
published data, we simulate and discussed the epidemic trends under different
control strategies. We compare four different scenarios and show the
corresponding medical burden. The results help to design appropriate control
strategy for imported cases in practice.
|
[
{
"created": "Mon, 6 Apr 2020 04:31:52 GMT",
"version": "v1"
}
] |
2020-04-07
|
[
[
"Jia",
"Jiwei",
""
],
[
"Liu",
"Siyu",
""
],
[
"Ding",
"Jing",
""
],
[
"Liao",
"Guidong",
""
],
[
"Zhang",
"Lihua",
""
],
[
"Zhang",
"Ran",
""
]
] |
Nowadays, the epidemic of COVID-19 in China is under control. However, the epidemic are developing rapidly around the world. Due to the normal migration of population, China is facing high risk from imported cases. The potential specific medicine and vaccine is still in the process of clinical trials. Currently, controlling the impact of imported cases is the key to prevent new outbreak of COVID-19 in China. In this paper, we propose two impulsive systems to describe the impact of multilateral imported cases of COVID-19. Based on the published data, we simulate and discussed the epidemic trends under different control strategies. We compare four different scenarios and show the corresponding medical burden. The results help to design appropriate control strategy for imported cases in practice.
|
1202.4691
|
Teresa Ruiz Herrero
|
Teresa Ruiz-Herrero, Enrique Velasco, Michael F. Hagan
|
Mechanisms of budding of nanoscale particles through lipid bilayers
| null | null | null | null |
q-bio.SC cond-mat.soft
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We examine the budding of a nanoscale particle through a lipid bilayer using
molecular dynamics simulations, free energy calculations, and an elastic
theory, with the aim of determining the extent to which equilibrium elasticity
theory can describe the factors that control the mechanism and efficiency of
budding. The particle is a smooth sphere which experiences attractive
interactions to the lipid head groups. Depending on the parameters, we observe
four classes of dynamical trajectories: particle adhesion to the membrane,
stalled partially wrapped states, budding followed by scission, and membrane
rupture. In most regions of parameter space we find that the elastic theory
agrees nearly quantitatively with the simulated phase behavior as a function of
adhesion strength, membrane bending rigidity, and particle radius. However, at
parameter values near the transition between particle adhesion and budding, we
observe long-lived partially wrapped states which are not captured by existing
elastic theories. These states could constrain the accessible system parameters
for those enveloped viruses or drug delivery vehicles which rely on exo- or
endocytosis for membrane transport.
|
[
{
"created": "Tue, 21 Feb 2012 16:19:48 GMT",
"version": "v1"
}
] |
2012-02-22
|
[
[
"Ruiz-Herrero",
"Teresa",
""
],
[
"Velasco",
"Enrique",
""
],
[
"Hagan",
"Michael F.",
""
]
] |
We examine the budding of a nanoscale particle through a lipid bilayer using molecular dynamics simulations, free energy calculations, and an elastic theory, with the aim of determining the extent to which equilibrium elasticity theory can describe the factors that control the mechanism and efficiency of budding. The particle is a smooth sphere which experiences attractive interactions to the lipid head groups. Depending on the parameters, we observe four classes of dynamical trajectories: particle adhesion to the membrane, stalled partially wrapped states, budding followed by scission, and membrane rupture. In most regions of parameter space we find that the elastic theory agrees nearly quantitatively with the simulated phase behavior as a function of adhesion strength, membrane bending rigidity, and particle radius. However, at parameter values near the transition between particle adhesion and budding, we observe long-lived partially wrapped states which are not captured by existing elastic theories. These states could constrain the accessible system parameters for those enveloped viruses or drug delivery vehicles which rely on exo- or endocytosis for membrane transport.
|
1806.05017
|
Jordi Sol\'e-Casals
|
Jordi Sole-Casals, Cesar F. Caiafa, Qibin Zhao and Adrzej Cichocki
|
Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion
Approach
|
21 pages, 3 tables, 4 figures
|
Sole-Casals, J., Caiafa, C.F., Zhao, Q. et al. Cogn Comput (2018).
https://doi.org/10.1007/s12559-018-9574-9
|
10.1007/s12559-018-9574-9
| null |
q-bio.QM eess.SP stat.ML
|
http://creativecommons.org/licenses/by/4.0/
|
One of the current issues in Brain-Computer Interface is how to deal with
noisy Electroencephalography measurements organized as multidimensional
datasets. On the other hand, recently, significant advances have been made in
multidimensional signal completion algorithms that exploit tensor decomposition
models to capture the intricate relationship among entries in a
multidimensional signal. We propose to use tensor completion applied to EEG
data for improving the classification performance in a motor imagery BCI system
with corrupted measurements. Noisy measurements are considered as unknowns that
are inferred from a tensor decomposition model. We evaluate the performance of
four recently proposed tensor completion algorithms plus a simple interpolation
strategy, first with random missing entries and then with missing samples
constrained to have a specific structure (random missing channels), which is a
more realistic assumption in BCI Applications. We measured the ability of these
algorithms to reconstruct the tensor from observed data. Then, we tested the
classification accuracy of imagined movement in a BCI experiment with missing
samples. We show that for random missing entries, all tensor completion
algorithms can recover missing samples increasing the classification
performance compared to a simple interpolation approach. For the random missing
channels case, we show that tensor completion algorithms help to reconstruct
missing channels, significantly improving the accuracy in the classification of
motor imagery, however, not at the same level as clean data. Tensor completion
algorithms are useful in real BCI applications. The proposed strategy could
allow using motor imagery BCI systems even when EEG data is highly affected by
missing channels and/or samples, avoiding the need of new acquisitions in the
calibration stage.
|
[
{
"created": "Wed, 13 Jun 2018 13:16:28 GMT",
"version": "v1"
},
{
"created": "Thu, 26 Jul 2018 15:53:29 GMT",
"version": "v2"
}
] |
2018-07-27
|
[
[
"Sole-Casals",
"Jordi",
""
],
[
"Caiafa",
"Cesar F.",
""
],
[
"Zhao",
"Qibin",
""
],
[
"Cichocki",
"Adrzej",
""
]
] |
One of the current issues in Brain-Computer Interface is how to deal with noisy Electroencephalography measurements organized as multidimensional datasets. On the other hand, recently, significant advances have been made in multidimensional signal completion algorithms that exploit tensor decomposition models to capture the intricate relationship among entries in a multidimensional signal. We propose to use tensor completion applied to EEG data for improving the classification performance in a motor imagery BCI system with corrupted measurements. Noisy measurements are considered as unknowns that are inferred from a tensor decomposition model. We evaluate the performance of four recently proposed tensor completion algorithms plus a simple interpolation strategy, first with random missing entries and then with missing samples constrained to have a specific structure (random missing channels), which is a more realistic assumption in BCI Applications. We measured the ability of these algorithms to reconstruct the tensor from observed data. Then, we tested the classification accuracy of imagined movement in a BCI experiment with missing samples. We show that for random missing entries, all tensor completion algorithms can recover missing samples increasing the classification performance compared to a simple interpolation approach. For the random missing channels case, we show that tensor completion algorithms help to reconstruct missing channels, significantly improving the accuracy in the classification of motor imagery, however, not at the same level as clean data. Tensor completion algorithms are useful in real BCI applications. The proposed strategy could allow using motor imagery BCI systems even when EEG data is highly affected by missing channels and/or samples, avoiding the need of new acquisitions in the calibration stage.
|
1909.10139
|
Alex McAvoy
|
Alex McAvoy, Benjamin Allen, Martin A. Nowak
|
Social goods dilemmas in heterogeneous societies
|
72 pages; final version
|
Nature Human Behaviour (2020)
|
10.1038/s41562-020-0881-2
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Prosocial behaviors are encountered in the donation game, the prisoner's
dilemma, relaxed social dilemmas, and public goods games. Many studies assume
that the population structure is homogeneous, meaning all individuals have the
same number of interaction partners, or that the social good is of one
particular type. Here, we explore general evolutionary dynamics for arbitrary
spatial structures and social goods. We find that heterogeneous networks,
wherein some individuals have many more interaction partners than others, can
enhance the evolution of prosocial behaviors. However, they often accumulate
most of the benefits in the hands of a few highly-connected individuals, while
many others receive low or negative payoff. Surprisingly, selection can favor
producers of social goods even if the total costs exceed the total benefits. In
summary, heterogeneous structures have the ability to strongly promote the
emergence of prosocial behaviors, but they also create the possibility of
generating large inequality.
|
[
{
"created": "Mon, 23 Sep 2019 03:30:07 GMT",
"version": "v1"
},
{
"created": "Fri, 1 May 2020 03:53:18 GMT",
"version": "v2"
}
] |
2020-05-28
|
[
[
"McAvoy",
"Alex",
""
],
[
"Allen",
"Benjamin",
""
],
[
"Nowak",
"Martin A.",
""
]
] |
Prosocial behaviors are encountered in the donation game, the prisoner's dilemma, relaxed social dilemmas, and public goods games. Many studies assume that the population structure is homogeneous, meaning all individuals have the same number of interaction partners, or that the social good is of one particular type. Here, we explore general evolutionary dynamics for arbitrary spatial structures and social goods. We find that heterogeneous networks, wherein some individuals have many more interaction partners than others, can enhance the evolution of prosocial behaviors. However, they often accumulate most of the benefits in the hands of a few highly-connected individuals, while many others receive low or negative payoff. Surprisingly, selection can favor producers of social goods even if the total costs exceed the total benefits. In summary, heterogeneous structures have the ability to strongly promote the emergence of prosocial behaviors, but they also create the possibility of generating large inequality.
|
1605.01905
|
Carina Curto
|
Carina Curto
|
What can topology tell us about the neural code?
|
16 pages, 9 figures
|
Bulletin of the AMS, vol. 54, no. 1, pp. 63-78, January 2017
| null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Neuroscience is undergoing a period of rapid experimental progress and
expansion. New mathematical tools, previously unknown in the neuroscience
community, are now being used to tackle fundamental questions and analyze
emerging data sets. Consistent with this trend, the last decade has seen an
uptick in the use of topological ideas and methods in neuroscience. In this
talk I will survey recent applications of topology in neuroscience, and explain
why topology is an especially natural tool for understanding neural codes.
Note: This is a write-up of my talk for the Current Events Bulletin, held at
the 2016 Joint Math Meetings in Seattle, WA.
|
[
{
"created": "Fri, 6 May 2016 12:06:15 GMT",
"version": "v1"
}
] |
2016-12-28
|
[
[
"Curto",
"Carina",
""
]
] |
Neuroscience is undergoing a period of rapid experimental progress and expansion. New mathematical tools, previously unknown in the neuroscience community, are now being used to tackle fundamental questions and analyze emerging data sets. Consistent with this trend, the last decade has seen an uptick in the use of topological ideas and methods in neuroscience. In this talk I will survey recent applications of topology in neuroscience, and explain why topology is an especially natural tool for understanding neural codes. Note: This is a write-up of my talk for the Current Events Bulletin, held at the 2016 Joint Math Meetings in Seattle, WA.
|
2009.10049
|
Ananth V S
|
Bishal Chhetri, Vijay M. Bhagat, D. K. K. Vamsi, Ananth V S, Bhanu
Prakash, Swapna Muthuswamy, Pradeep Deshmukh, Carani B Sanjeevi
|
Optimal Drug Regimen and Combined Drug Therapy and its Efficacy in the
Treatment of COVID-19 : An Within-Host Modeling Study
|
16 pages, 13 figures
| null |
10.1007/s10441-022-09440-8
| null |
q-bio.PE math.DS math.OC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The COVID-19 pandemic has resulted in more than 30.35 million infections and
9, 50, 625 deaths in 212 countries over the last few months. Different drug
intervention acting at multiple stages of pathogenesis of COVID-19 can
substantially reduce the infection induced mortality. The current within-host
mathematical modeling studies deals with the optimal drug regimen and the
efficacy of combined therapy in treatment of COVID-19. The drugs/interventions
considered include Arbidol, Remdesivir, Inteferon (INF) and
Lopinavir/Ritonavir. It is concluded that these drug interventions when
administered individually or in combination reduce the infected cells and viral
load. Four scenarios involving administration of single drug intervention, two
drug interventions, three drug interventions and all the four have been
discussed. In all these scenarios the optimal drug regimen is proposed based on
two methods. In the first method these medical interventions are modeled as
control interventions and a corresponding objective function and optimal
control problem is formulated. In this setting the optimal drug regimen is
proposed. Later using the the comparative effectiveness method the optimal drug
regimen is proposed based on basic reproduction number and viral load. The
average infected cell count and viral load decreased the most when all the four
interventions were applied together. On the other hand the average susceptible
cell count decreased the best when Arbidol alone was administered. The basic
reproduction number and viral count decreased the best when all the four
interventions were applied together reinstating the fact obtained earlier in
the optimal control setting. These findings may help physicians with decision
making in treatment of life-threatening COVID-19 pneumonia.
|
[
{
"created": "Mon, 21 Sep 2020 17:43:20 GMT",
"version": "v1"
}
] |
2023-09-01
|
[
[
"Chhetri",
"Bishal",
""
],
[
"Bhagat",
"Vijay M.",
""
],
[
"Vamsi",
"D. K. K.",
""
],
[
"S",
"Ananth V",
""
],
[
"Prakash",
"Bhanu",
""
],
[
"Muthuswamy",
"Swapna",
""
],
[
"Deshmukh",
"Pradeep",
""
],
[
"Sanjeevi",
"Carani B",
""
]
] |
The COVID-19 pandemic has resulted in more than 30.35 million infections and 9, 50, 625 deaths in 212 countries over the last few months. Different drug intervention acting at multiple stages of pathogenesis of COVID-19 can substantially reduce the infection induced mortality. The current within-host mathematical modeling studies deals with the optimal drug regimen and the efficacy of combined therapy in treatment of COVID-19. The drugs/interventions considered include Arbidol, Remdesivir, Inteferon (INF) and Lopinavir/Ritonavir. It is concluded that these drug interventions when administered individually or in combination reduce the infected cells and viral load. Four scenarios involving administration of single drug intervention, two drug interventions, three drug interventions and all the four have been discussed. In all these scenarios the optimal drug regimen is proposed based on two methods. In the first method these medical interventions are modeled as control interventions and a corresponding objective function and optimal control problem is formulated. In this setting the optimal drug regimen is proposed. Later using the the comparative effectiveness method the optimal drug regimen is proposed based on basic reproduction number and viral load. The average infected cell count and viral load decreased the most when all the four interventions were applied together. On the other hand the average susceptible cell count decreased the best when Arbidol alone was administered. The basic reproduction number and viral count decreased the best when all the four interventions were applied together reinstating the fact obtained earlier in the optimal control setting. These findings may help physicians with decision making in treatment of life-threatening COVID-19 pneumonia.
|
1401.0002
|
Evgenii Levites
|
Svetlana Sergeevna Kirikovich and Evgenii Vladimirovich Levites
|
Phenotypic class ratios as marker signs of different types of
agamospermy
|
8 pages, 2 tables, 23 references
| null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This article focuses on the development of the method for the genetic
classification of agamospermous reproduction types in plants using sugar beet
as an example. The classification feasibility is ensured by the use of isozymes
as genetic markers allowing the identification of all three phenotypic classes
in the progeny of individual heterozygous diploid plant and is based on
different phenotypic class ratios in the progenies obtained by meiotic and
mitotic agamospermy. The data indicate that for sugar beet meiotic agamospermy
is the more typical since 13 of 15 explored progenies were classified as those
produced by meiotic agamospermy and only 2 as produced by mitotic agamospermy.
|
[
{
"created": "Sat, 28 Dec 2013 11:39:53 GMT",
"version": "v1"
}
] |
2014-01-03
|
[
[
"Kirikovich",
"Svetlana Sergeevna",
""
],
[
"Levites",
"Evgenii Vladimirovich",
""
]
] |
This article focuses on the development of the method for the genetic classification of agamospermous reproduction types in plants using sugar beet as an example. The classification feasibility is ensured by the use of isozymes as genetic markers allowing the identification of all three phenotypic classes in the progeny of individual heterozygous diploid plant and is based on different phenotypic class ratios in the progenies obtained by meiotic and mitotic agamospermy. The data indicate that for sugar beet meiotic agamospermy is the more typical since 13 of 15 explored progenies were classified as those produced by meiotic agamospermy and only 2 as produced by mitotic agamospermy.
|
1107.2834
|
John Burke
|
John Burke, Mathieu Desroches, Anna M. Barry, Tasso J. Kaper, and Mark
A. Kramer
|
A showcase of torus canards in neuronal bursters
| null | null | null | null |
q-bio.NC math.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Rapid action potential generation --- spiking --- and alternating intervals
of spiking and quiescence --- bursting --- are two dynamic patterns observed in
neuronal activity. In computational models of neuronal systems, the transition
from spiking to bursting often exhibits complex bifurcation structure. One type
of transition involves the torus canard, which was originally observed in a
simple biophysical model of a Purkinje cell. In this article, we expand on that
original result by showing that torus canards arise in a broad array of
well-known computational neuronal models with three different classes of
bursting dynamics: sub-Hopf/fold cycle bursting, circle/fold cycle bursting,
and fold/fold cycle bursting. The essential features that these models share
are multiple time scales leading naturally to decomposition into slow and fast
systems, a saddle-node of periodic orbits in the fast system, and a torus
bifurcation in the full system. We show that the transition from spiking to
bursting in each model system is given by an explosion of torus canards. Based
on these examples, as well as on emerging theory, we propose that torus canards
are a common dynamic phenomenon separating the regimes of spiking and bursting
activity.
|
[
{
"created": "Thu, 14 Jul 2011 14:14:29 GMT",
"version": "v1"
}
] |
2011-07-15
|
[
[
"Burke",
"John",
""
],
[
"Desroches",
"Mathieu",
""
],
[
"Barry",
"Anna M.",
""
],
[
"Kaper",
"Tasso J.",
""
],
[
"Kramer",
"Mark A.",
""
]
] |
Rapid action potential generation --- spiking --- and alternating intervals of spiking and quiescence --- bursting --- are two dynamic patterns observed in neuronal activity. In computational models of neuronal systems, the transition from spiking to bursting often exhibits complex bifurcation structure. One type of transition involves the torus canard, which was originally observed in a simple biophysical model of a Purkinje cell. In this article, we expand on that original result by showing that torus canards arise in a broad array of well-known computational neuronal models with three different classes of bursting dynamics: sub-Hopf/fold cycle bursting, circle/fold cycle bursting, and fold/fold cycle bursting. The essential features that these models share are multiple time scales leading naturally to decomposition into slow and fast systems, a saddle-node of periodic orbits in the fast system, and a torus bifurcation in the full system. We show that the transition from spiking to bursting in each model system is given by an explosion of torus canards. Based on these examples, as well as on emerging theory, we propose that torus canards are a common dynamic phenomenon separating the regimes of spiking and bursting activity.
|
1909.13327
|
Christoph Feinauer
|
Matteo Negri, Davide Bergamini, Carlo Baldassi, Riccardo Zecchina,
Christoph Feinauer
|
Natural representation of composite data with replicated autoencoders
|
11 pages, 4 figures
| null | null | null |
q-bio.QM cs.LG stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Generative processes in biology and other fields often produce data that can
be regarded as resulting from a composition of basic features. Here we present
an unsupervised method based on autoencoders for inferring these basic features
of data. The main novelty in our approach is that the training is based on the
optimization of the `local entropy' rather than the standard loss, resulting in
a more robust inference, and enhancing the performance on this type of data
considerably. Algorithmically, this is realized by training an interacting
system of replicated autoencoders. We apply this method to synthetic and
protein sequence data, and show that it is able to infer a hidden
representation that correlates well with the underlying generative process,
without requiring any prior knowledge.
|
[
{
"created": "Sun, 29 Sep 2019 17:41:44 GMT",
"version": "v1"
}
] |
2019-10-04
|
[
[
"Negri",
"Matteo",
""
],
[
"Bergamini",
"Davide",
""
],
[
"Baldassi",
"Carlo",
""
],
[
"Zecchina",
"Riccardo",
""
],
[
"Feinauer",
"Christoph",
""
]
] |
Generative processes in biology and other fields often produce data that can be regarded as resulting from a composition of basic features. Here we present an unsupervised method based on autoencoders for inferring these basic features of data. The main novelty in our approach is that the training is based on the optimization of the `local entropy' rather than the standard loss, resulting in a more robust inference, and enhancing the performance on this type of data considerably. Algorithmically, this is realized by training an interacting system of replicated autoencoders. We apply this method to synthetic and protein sequence data, and show that it is able to infer a hidden representation that correlates well with the underlying generative process, without requiring any prior knowledge.
|
1408.2253
|
Tatjana Tchumatchenko
|
T. Tchumatchenko, T. Reichenbach
|
Cochlear-bone wave can yield a hearing sensation as well as otoacoustic
emission
|
37 pages, 4 figures, Nature Communications 2014
| null |
10.1038/ncomms5160
| null |
q-bio.QM q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A hearing sensation arises when the elastic basilar membrane inside the
cochlea vibrates. The basilar membrane is typically set into motion through
airborne sound that displaces the middle ear and induces a pressure difference
across the membrane. A second, alternative pathway exists, however: stimulation
of the cochlear bone vibrates the basilar membrane as well. This pathway,
referred to as bone conduction, is increasingly used in the construction of
headphones that bypass the ear canal and the middle ear. Furthermore,
otoacoustic emissions, sounds generated inside the ear and measured in the ear
canal, may not involve the usual wave on the basilar membrane, suggesting that
additional cochlear structures are involved in their propagation. Here we
describe a novel propagation mode that emerges through deformation of the
cochlear bone. Through a mathematical and computational approach we demonstrate
that this wave can explain bone conduction as well as numerous properties of
otoacoustic emissions.
|
[
{
"created": "Sun, 10 Aug 2014 16:55:32 GMT",
"version": "v1"
}
] |
2015-06-22
|
[
[
"Tchumatchenko",
"T.",
""
],
[
"Reichenbach",
"T.",
""
]
] |
A hearing sensation arises when the elastic basilar membrane inside the cochlea vibrates. The basilar membrane is typically set into motion through airborne sound that displaces the middle ear and induces a pressure difference across the membrane. A second, alternative pathway exists, however: stimulation of the cochlear bone vibrates the basilar membrane as well. This pathway, referred to as bone conduction, is increasingly used in the construction of headphones that bypass the ear canal and the middle ear. Furthermore, otoacoustic emissions, sounds generated inside the ear and measured in the ear canal, may not involve the usual wave on the basilar membrane, suggesting that additional cochlear structures are involved in their propagation. Here we describe a novel propagation mode that emerges through deformation of the cochlear bone. Through a mathematical and computational approach we demonstrate that this wave can explain bone conduction as well as numerous properties of otoacoustic emissions.
|
1005.4393
|
Adrian Melott
|
Adrian L. Melott (University of Kansas) and Richard K. Bambach
(National Museum of Natural History)
|
A ubiquitous ~62-Myr periodic fluctuation superimposed on general trends
in fossil biodiversity. I. Documentation
|
56 pages. In press at Paleobiology. Submitted to conform with
copyedited version
|
Paleobiology 37:92,2011
| null | null |
q-bio.PE astro-ph.EP astro-ph.GA physics.bio-ph physics.geo-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We use Fourier analysis and related techniques to investigate the question of
periodicities in fossil biodiversity. These techniques are able to identify
cycles superimposed on the long-term trends of the Phanerozoic. We review prior
results and analyze data previously reduced and published. Joint time-series
analysis of various reductions of the Sepkoski Data, Paleobiology Database, and
Fossil Record 2 indicate the same periodicity in biodiversity of marine animals
at 62 Myr. We have not found this periodicity in the terrestrial fossil record.
We have found that the signal strength decreases with time because of the
accumulation of apparently "resistant" long-lived genera. The existence of a
62-Myr periodicity despite very different treatment of systematic error,
particularly sampling-strength biases, in all three major databases strongly
argues for its reality in the fossil record.
|
[
{
"created": "Mon, 24 May 2010 18:25:31 GMT",
"version": "v1"
},
{
"created": "Wed, 25 Aug 2010 17:05:17 GMT",
"version": "v2"
}
] |
2010-11-26
|
[
[
"Melott",
"Adrian L.",
"",
"University of Kansas"
],
[
"Bambach",
"Richard K.",
"",
"National Museum of Natural History"
]
] |
We use Fourier analysis and related techniques to investigate the question of periodicities in fossil biodiversity. These techniques are able to identify cycles superimposed on the long-term trends of the Phanerozoic. We review prior results and analyze data previously reduced and published. Joint time-series analysis of various reductions of the Sepkoski Data, Paleobiology Database, and Fossil Record 2 indicate the same periodicity in biodiversity of marine animals at 62 Myr. We have not found this periodicity in the terrestrial fossil record. We have found that the signal strength decreases with time because of the accumulation of apparently "resistant" long-lived genera. The existence of a 62-Myr periodicity despite very different treatment of systematic error, particularly sampling-strength biases, in all three major databases strongly argues for its reality in the fossil record.
|
1212.1135
|
Henry Tuckwell
|
Henry C. Tuckwell
|
Biophysical properties and computational modeling of calcium spikes in
serotonergic neurons of the dorsal raphe nucleus
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Serotonergic neurons of the dorsal raphe nuclei, with their extensive
innervation of nearly the whole brain have important modulatory effects on many
cognitive and physiological processes. They play important roles in clinical
depression and other psychiatric disorders. In order to quantify the effects of
serotonergic transmission on target cells it is desirable to construct
computational models and to this end these it is necessary to have details of
the biophysical and spike properties of the serotonergic neurons. Here several
basic properties are reviewed with data from several studies since the 1960s to
the present. The quantities included are input resistance, resting membrane
potential, membrane time constant, firing rate, spike duration, spike and
afterhyperpolarization (AHP) amplitude, spike threshold, cell capacitance, soma
and somadendritic areas. The action potentials of these cells are normally
triggered by a combination of sodium and calcium currents which may result in
autonomous pacemaker activity. We here analyse the mechanisms of high-threshold
calcium spikes which have been demonstrated in these cells the presence of TTX.
The parameters for calcium dynamics required to give calcium spikes are quite
different from those for regular spiking which suggests the involvement of
restricted parts of the soma-dendritic surface as has been found, for example,
in hippocampal neurons.
|
[
{
"created": "Wed, 5 Dec 2012 19:33:29 GMT",
"version": "v1"
}
] |
2012-12-06
|
[
[
"Tuckwell",
"Henry C.",
""
]
] |
Serotonergic neurons of the dorsal raphe nuclei, with their extensive innervation of nearly the whole brain have important modulatory effects on many cognitive and physiological processes. They play important roles in clinical depression and other psychiatric disorders. In order to quantify the effects of serotonergic transmission on target cells it is desirable to construct computational models and to this end these it is necessary to have details of the biophysical and spike properties of the serotonergic neurons. Here several basic properties are reviewed with data from several studies since the 1960s to the present. The quantities included are input resistance, resting membrane potential, membrane time constant, firing rate, spike duration, spike and afterhyperpolarization (AHP) amplitude, spike threshold, cell capacitance, soma and somadendritic areas. The action potentials of these cells are normally triggered by a combination of sodium and calcium currents which may result in autonomous pacemaker activity. We here analyse the mechanisms of high-threshold calcium spikes which have been demonstrated in these cells the presence of TTX. The parameters for calcium dynamics required to give calcium spikes are quite different from those for regular spiking which suggests the involvement of restricted parts of the soma-dendritic surface as has been found, for example, in hippocampal neurons.
|
q-bio/0612041
|
Etay Ziv
|
Etay Ziv, Ilya Nemenman, and Chris H. Wiggins
|
Optimal signal processing in small stochastic biochemical networks
|
41 pages 7 figures, 5 tables
| null |
10.1371/journal.pone.0001077
|
LA-UR-06-8411
|
q-bio.MN q-bio.QM
| null |
We quantify the influence of the topology of a transcriptional regulatory
network on its ability to process environmental signals. By posing the problem
in terms of information theory, we may do this without specifying the function
performed by the network. Specifically, we study the maximum mutual information
between the input (chemical) signal and the output (genetic) response
attainable by the network in the context of an analytic model of particle
number fluctuations. We perform this analysis for all biochemical circuits,
including various feedback loops, that can be built out of 3 chemical species,
each under the control of one regulator. We find that a generic network,
constrained to low molecule numbers and reasonable response times, can
transduce more information than a simple binary switch and, in fact, manages to
achieve close to the optimal information transmission fidelity. These
high-information solutions are robust to tenfold changes in most of the
networks' biochemical parameters; moreover they are easier to achieve in
networks containing cycles with an odd number of negative regulators (overall
negative feedback) due to their decreased molecular noise (a result which we
derive analytically). Finally, we demonstrate that a single circuit can support
multiple high-information solutions. These findings suggest a potential
resolution of the "cross-talk" dilemma as well as the previously unexplained
observation that transcription factors which undergo proteolysis are more
likely to be auto-repressive.
|
[
{
"created": "Thu, 21 Dec 2006 20:39:46 GMT",
"version": "v1"
}
] |
2015-06-26
|
[
[
"Ziv",
"Etay",
""
],
[
"Nemenman",
"Ilya",
""
],
[
"Wiggins",
"Chris H.",
""
]
] |
We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we may do this without specifying the function performed by the network. Specifically, we study the maximum mutual information between the input (chemical) signal and the output (genetic) response attainable by the network in the context of an analytic model of particle number fluctuations. We perform this analysis for all biochemical circuits, including various feedback loops, that can be built out of 3 chemical species, each under the control of one regulator. We find that a generic network, constrained to low molecule numbers and reasonable response times, can transduce more information than a simple binary switch and, in fact, manages to achieve close to the optimal information transmission fidelity. These high-information solutions are robust to tenfold changes in most of the networks' biochemical parameters; moreover they are easier to achieve in networks containing cycles with an odd number of negative regulators (overall negative feedback) due to their decreased molecular noise (a result which we derive analytically). Finally, we demonstrate that a single circuit can support multiple high-information solutions. These findings suggest a potential resolution of the "cross-talk" dilemma as well as the previously unexplained observation that transcription factors which undergo proteolysis are more likely to be auto-repressive.
|
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