id stringlengths 9 13 | submitter stringlengths 4 48 | authors stringlengths 4 9.62k | title stringlengths 4 343 | comments stringlengths 2 480 ⌀ | journal-ref stringlengths 9 309 ⌀ | doi stringlengths 12 138 ⌀ | report-no stringclasses 277 values | categories stringlengths 8 87 | license stringclasses 9 values | orig_abstract stringlengths 27 3.76k | versions listlengths 1 15 | update_date stringlengths 10 10 | authors_parsed listlengths 1 147 | abstract stringlengths 24 3.75k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
q-bio/0604015 | Radhakrishnan Nagarajan | Radhakrishnan Nagarajan, Meenakshi Upreti | Qualitative Assessment of Gene Expression in Affymetrix Genechip Arrays | 22 Pages, 7 Figures, 1 Table | null | 10.1016/j.physa.2006.06.004 | null | q-bio.GN | null | Affymetrix Genechip microarrays are used widely to determine the simultaneous
expression of genes in a given biological paradigm. Probes on the Genechip
array are atomic entities which by definition are randomly distributed across
the array and in turn govern the gene expression. In the present study, we make
several interesting observations. We show that there is considerable
correlation between the probe intensities across the array which defy the
independence assumption. While the mechanism behind such correlations is
unclear, we show that scaling behavior and the profiles of perfect match (PM)
as well as mismatch (MM) probes are similar and immune to background
subtraction. We believe that the observed correlations are possibly an outcome
of inherent non-stationarities or patchiness in the array devoid of biological
significance. This is demonstrated by inspecting their scaling behavior and
profiles of the PM and MM probe intensities obtained from publicly available
Genechip arrays from three eukaryotic genomes, namely: Drosophila Melanogaster,
Homo Sapiens and Mus musculus across distinct biological paradigms and across
laboratories, with and without background subtraction. The fluctuation
functions were estimated using detrended fluctuation analysis (DFA) with fourth
order polynomial detrending. The results presented in this study provide new
insights into correlation signatures of PM and MM probe intensities and
suggests the choice of DFA as a tool for qualitative assessment of Affymetrix
Genechip microarrays prior to their analysis. A more detailed investigation is
necessary in order to understand the source of these correlations.
| [
{
"created": "Wed, 12 Apr 2006 20:20:03 GMT",
"version": "v1"
},
{
"created": "Fri, 19 May 2006 15:27:25 GMT",
"version": "v2"
}
] | 2009-11-13 | [
[
"Nagarajan",
"Radhakrishnan",
""
],
[
"Upreti",
"Meenakshi",
""
]
] | Affymetrix Genechip microarrays are used widely to determine the simultaneous expression of genes in a given biological paradigm. Probes on the Genechip array are atomic entities which by definition are randomly distributed across the array and in turn govern the gene expression. In the present study, we make several interesting observations. We show that there is considerable correlation between the probe intensities across the array which defy the independence assumption. While the mechanism behind such correlations is unclear, we show that scaling behavior and the profiles of perfect match (PM) as well as mismatch (MM) probes are similar and immune to background subtraction. We believe that the observed correlations are possibly an outcome of inherent non-stationarities or patchiness in the array devoid of biological significance. This is demonstrated by inspecting their scaling behavior and profiles of the PM and MM probe intensities obtained from publicly available Genechip arrays from three eukaryotic genomes, namely: Drosophila Melanogaster, Homo Sapiens and Mus musculus across distinct biological paradigms and across laboratories, with and without background subtraction. The fluctuation functions were estimated using detrended fluctuation analysis (DFA) with fourth order polynomial detrending. The results presented in this study provide new insights into correlation signatures of PM and MM probe intensities and suggests the choice of DFA as a tool for qualitative assessment of Affymetrix Genechip microarrays prior to their analysis. A more detailed investigation is necessary in order to understand the source of these correlations. |
2407.09509 | Heng Huang | Heng Huang, Lin Zhao, Zihao Wu, Xiaowei Yu, Jing Zhang, Xintao Hu,
Dajiang Zhu, Tianming Liu | Brain Dialogue Interface (BDI): A User-Friendly fMRI Model for
Interactive Brain Decoding | null | null | null | null | q-bio.NC cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Brain decoding techniques are essential for understanding the neurocognitive
system. Although numerous methods have been introduced in this field,
accurately aligning complex external stimuli with brain activities remains a
formidable challenge. To alleviate alignment difficulties, many studies have
simplified their models by employing single-task paradigms and establishing
direct links between brain/world through classification strategies. Despite
improvements in decoding accuracy, this strategy frequently encounters issues
with generality when adapting these models to various task paradigms. To
address this issue, this study introduces a user-friendly decoding model that
enables dynamic communication with the brain, as opposed to the static decoding
approaches utilized by traditional studies. The model functions as a brain
simulator, allowing for interactive engagement with the brain and enabling the
decoding of a subject's experiences through dialogue-like queries. Uniquely,
our model is trained in a completely unsupervised and task-free manner. Our
experiments demonstrate the feasibility and versatility of our proposed method.
Notably, our model demonstrates exceptional capabilities in signal compression,
successfully representing the entire brain signal of approximately 185,751
voxels with just 32 signals. Furthermore, we show how our model can integrate
seamlessly with multimodal models, thus enhancing the potential for controlling
brain decoding through textual or image inputs.
| [
{
"created": "Mon, 17 Jun 2024 04:38:19 GMT",
"version": "v1"
}
] | 2024-07-16 | [
[
"Huang",
"Heng",
""
],
[
"Zhao",
"Lin",
""
],
[
"Wu",
"Zihao",
""
],
[
"Yu",
"Xiaowei",
""
],
[
"Zhang",
"Jing",
""
],
[
"Hu",
"Xintao",
""
],
[
"Zhu",
"Dajiang",
""
],
[
"Liu",
"Tianming",
""
]
] | Brain decoding techniques are essential for understanding the neurocognitive system. Although numerous methods have been introduced in this field, accurately aligning complex external stimuli with brain activities remains a formidable challenge. To alleviate alignment difficulties, many studies have simplified their models by employing single-task paradigms and establishing direct links between brain/world through classification strategies. Despite improvements in decoding accuracy, this strategy frequently encounters issues with generality when adapting these models to various task paradigms. To address this issue, this study introduces a user-friendly decoding model that enables dynamic communication with the brain, as opposed to the static decoding approaches utilized by traditional studies. The model functions as a brain simulator, allowing for interactive engagement with the brain and enabling the decoding of a subject's experiences through dialogue-like queries. Uniquely, our model is trained in a completely unsupervised and task-free manner. Our experiments demonstrate the feasibility and versatility of our proposed method. Notably, our model demonstrates exceptional capabilities in signal compression, successfully representing the entire brain signal of approximately 185,751 voxels with just 32 signals. Furthermore, we show how our model can integrate seamlessly with multimodal models, thus enhancing the potential for controlling brain decoding through textual or image inputs. |
1608.05855 | Christophe Guyeux | Jacques M. Bahi and Nathalie C\^ot\'e and Christophe Guyeux and Michel
Salomon | Protein Folding in the 2D Hydrophobic-Hydrophilic (HP) Square Lattice
Model is Chaotic | Cognitive Computation (2012). arXiv admin note: text overlap with
arXiv:1511.00139 | null | null | null | q-bio.BM math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Among the unsolved problems in computational biology, protein folding is one
of the most interesting challenges. To study this folding, tools like neural
networks and genetic algorithms have received a lot of attention, mainly due to
the NP-completeness of the folding process. The background idea that has given
rise to the use of these algorithms is obviously that the folding process is
predictable. However, this important assumption is disputable as chaotic
properties of such a process have been recently highlighted. In this paper,
which is an extension of a former work accepted to the 2011 International Joint
Conference on Neural Networks (IJCNN11), the topological behavior of a
well-known dynamical system used for protein folding prediction is evaluated.
It is mathematically established that the folding dynamics in the 2D
hydrophobic-hydrophilic (HP) square lattice model, simply called "the 2D model"
in this document, is indeed a chaotic dynamical system as defined by Devaney.
Furthermore, the chaotic behavior of this model is qualitatively and
quantitatively deepened, by studying other mathematical properties of disorder,
namely: the indecomposability, instability, strong transitivity, and constants
of expansivity and sensitivity. Some consequences for both biological paradigms
and structure prediction using this model are then discussed. In particular, it
is shown that some neural networks seems to be unable to predict the evolution
of this model with accuracy, due to its complex behavior.
| [
{
"created": "Sat, 20 Aug 2016 17:57:02 GMT",
"version": "v1"
}
] | 2016-08-23 | [
[
"Bahi",
"Jacques M.",
""
],
[
"Côté",
"Nathalie",
""
],
[
"Guyeux",
"Christophe",
""
],
[
"Salomon",
"Michel",
""
]
] | Among the unsolved problems in computational biology, protein folding is one of the most interesting challenges. To study this folding, tools like neural networks and genetic algorithms have received a lot of attention, mainly due to the NP-completeness of the folding process. The background idea that has given rise to the use of these algorithms is obviously that the folding process is predictable. However, this important assumption is disputable as chaotic properties of such a process have been recently highlighted. In this paper, which is an extension of a former work accepted to the 2011 International Joint Conference on Neural Networks (IJCNN11), the topological behavior of a well-known dynamical system used for protein folding prediction is evaluated. It is mathematically established that the folding dynamics in the 2D hydrophobic-hydrophilic (HP) square lattice model, simply called "the 2D model" in this document, is indeed a chaotic dynamical system as defined by Devaney. Furthermore, the chaotic behavior of this model is qualitatively and quantitatively deepened, by studying other mathematical properties of disorder, namely: the indecomposability, instability, strong transitivity, and constants of expansivity and sensitivity. Some consequences for both biological paradigms and structure prediction using this model are then discussed. In particular, it is shown that some neural networks seems to be unable to predict the evolution of this model with accuracy, due to its complex behavior. |
1912.12980 | Benjamin Cramer | Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber, Benjamin
Cramer, Andreas Baumbach, Dominik Dold, Julian G\"oltz, Akos F. Kungl, Timo
C. Wunderlich, Andreas Hartel, Eric M\"uller, Oliver Breitwieser, Christian
Mauch, Mitja Kleider, Andreas Gr\"ubl, David St\"ockel, Christian Pehle,
Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter
Senn, Mihai A. Petrovici, Johannes Schemmel, Karlheinz Meier | Versatile emulation of spiking neural networks on an accelerated
neuromorphic substrate | null | null | 10.1109/ISCAS45731.2020.9180741 | null | q-bio.NC cs.NE | http://creativecommons.org/licenses/by/4.0/ | We present first experimental results on the novel BrainScaleS-2 neuromorphic
architecture based on an analog neuro-synaptic core and augmented by embedded
microprocessors for complex plasticity and experiment control. The high
acceleration factor of 1000 compared to biological dynamics enables the
execution of computationally expensive tasks, by allowing the fast emulation of
long-duration experiments or rapid iteration over many consecutive trials. The
flexibility of our architecture is demonstrated in a suite of five distinct
experiments, which emphasize different aspects of the BrainScaleS-2 system.
| [
{
"created": "Mon, 30 Dec 2019 16:12:14 GMT",
"version": "v1"
},
{
"created": "Mon, 9 May 2022 10:27:37 GMT",
"version": "v2"
}
] | 2022-05-10 | [
[
"Billaudelle",
"Sebastian",
""
],
[
"Stradmann",
"Yannik",
""
],
[
"Schreiber",
"Korbinian",
""
],
[
"Cramer",
"Benjamin",
""
],
[
"Baumbach",
"Andreas",
""
],
[
"Dold",
"Dominik",
""
],
[
"Göltz",
"Julian",
""
],
[
"Kungl",
"Akos F.",
""
],
[
"Wunderlich",
"Timo C.",
""
],
[
"Hartel",
"Andreas",
""
],
[
"Müller",
"Eric",
""
],
[
"Breitwieser",
"Oliver",
""
],
[
"Mauch",
"Christian",
""
],
[
"Kleider",
"Mitja",
""
],
[
"Grübl",
"Andreas",
""
],
[
"Stöckel",
"David",
""
],
[
"Pehle",
"Christian",
""
],
[
"Heimbrecht",
"Arthur",
""
],
[
"Spilger",
"Philipp",
""
],
[
"Kiene",
"Gerd",
""
],
[
"Karasenko",
"Vitali",
""
],
[
"Senn",
"Walter",
""
],
[
"Petrovici",
"Mihai A.",
""
],
[
"Schemmel",
"Johannes",
""
],
[
"Meier",
"Karlheinz",
""
]
] | We present first experimental results on the novel BrainScaleS-2 neuromorphic architecture based on an analog neuro-synaptic core and augmented by embedded microprocessors for complex plasticity and experiment control. The high acceleration factor of 1000 compared to biological dynamics enables the execution of computationally expensive tasks, by allowing the fast emulation of long-duration experiments or rapid iteration over many consecutive trials. The flexibility of our architecture is demonstrated in a suite of five distinct experiments, which emphasize different aspects of the BrainScaleS-2 system. |
1004.3162 | Frank Le Foll | Jennifer Pasquier, Pierre Magal, C\'eline Boulang\'e-Lecomte, Glenn
Webb and Frank Le Foll | Consequences of cell-to-cell P-glycoprotein transfer on acquired
multidrug resistance in breast cancer: a cell population dynamics model | 13 pages, 8 figures, 1 table | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cancer is a proliferation disease affecting a genetically unstable cell
population, in which molecular alterations can be somatically inherited by
genetic, epigenetic or extragenetic transmission processes, leading to a
cooperation of neoplastic cells within tumoral tissue. The efflux protein
P-glycoprotein (P gp) is overexpressed in many cancer cells and has known
capacity to confer multidrug resistance to cytotoxic therapies. Recently,
cell-to-cell P-gp transfers have been shown. Herein, we combine experimental
evidence and a mathematical model to examine the consequences of an
intercellular P-gp trafficking in the extragenetic transfer of multidrug
resistance from resistant to sensitive cell subpopulations. We report
cell-to-cell transfers of functional P-gp in co-cultures of a P-gp
overexpressing human breast cancer MCF-7 cell variant, selected for its
resistance towards doxorubicin, with the parental sensitive cell line. We found
that P-gp as well as efflux activity distribution are progressively reorganized
over time in co-cultures analyzed by flow cytometry. A mathematical model based
on a Boltzmann type integro-partial differential equation structured by a
continuum variable corresponding to P-gp activity describes the cell
populations in co-culture. The mathematical model elucidates the population
elements in the experimental data, specifically, the initial proportions, the
proliferative growth rates, and the transfer rates of P-gp in the sensitive and
resistant subpopulations. We confirmed cell-to-cell transfer of functional
P-gp. The transfer process depends on the gradient of P-gp expression in the
donor-recipient cell interactions, as they evolve over time. Extragenetically
acquired drug resistance is an additional aptitude of neoplastic cells which
has implications in the diagnostic value of P-gp expression and in the design
of chemotherapy regimens
| [
{
"created": "Mon, 19 Apr 2010 11:32:31 GMT",
"version": "v1"
}
] | 2010-04-20 | [
[
"Pasquier",
"Jennifer",
""
],
[
"Magal",
"Pierre",
""
],
[
"Boulangé-Lecomte",
"Céline",
""
],
[
"Webb",
"Glenn",
""
],
[
"Foll",
"Frank Le",
""
]
] | Cancer is a proliferation disease affecting a genetically unstable cell population, in which molecular alterations can be somatically inherited by genetic, epigenetic or extragenetic transmission processes, leading to a cooperation of neoplastic cells within tumoral tissue. The efflux protein P-glycoprotein (P gp) is overexpressed in many cancer cells and has known capacity to confer multidrug resistance to cytotoxic therapies. Recently, cell-to-cell P-gp transfers have been shown. Herein, we combine experimental evidence and a mathematical model to examine the consequences of an intercellular P-gp trafficking in the extragenetic transfer of multidrug resistance from resistant to sensitive cell subpopulations. We report cell-to-cell transfers of functional P-gp in co-cultures of a P-gp overexpressing human breast cancer MCF-7 cell variant, selected for its resistance towards doxorubicin, with the parental sensitive cell line. We found that P-gp as well as efflux activity distribution are progressively reorganized over time in co-cultures analyzed by flow cytometry. A mathematical model based on a Boltzmann type integro-partial differential equation structured by a continuum variable corresponding to P-gp activity describes the cell populations in co-culture. The mathematical model elucidates the population elements in the experimental data, specifically, the initial proportions, the proliferative growth rates, and the transfer rates of P-gp in the sensitive and resistant subpopulations. We confirmed cell-to-cell transfer of functional P-gp. The transfer process depends on the gradient of P-gp expression in the donor-recipient cell interactions, as they evolve over time. Extragenetically acquired drug resistance is an additional aptitude of neoplastic cells which has implications in the diagnostic value of P-gp expression and in the design of chemotherapy regimens |
2004.09133 | Laura Wadkin MMath | Laura E Wadkin, Sirio Orozco-Fuentes, Irina Neganova, Majlinda Lako, R
A Barrio, A W Baggaley, Nicholas G Parker, Anvar Shukurov | OCT4 expression in human embryonic stem cells: spatio-temporal dynamics
and fate transitions | null | null | null | null | q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The improved in-vitro regulation of human embryonic stem cell (hESC)
pluripotency and differentiation trajectories is required for their promising
clinical applications. The temporal and spatial quantification of the molecular
interactions controlling pluripotency is also necessary for the development of
successful mathematical and computational models. Here we use time-lapse
experimental data of OCT4-mCherry fluorescence intensity to quantify the
temporal and spatial dynamics of the pluripotency transcription factor OCT4 in
a growing hESC colony in the presence and absence of BMP4. We characterise the
internal self-regulation of OCT4 using the Hurst exponent and autocorrelation
analysis, quantify the intra-cellular fluctuations and consider the diffusive
nature of OCT4 evolution for individual cells and pairs of their descendants.
We find that OCT4 abundance in the daughter cells fluctuates sub-diffusively,
showing anti-persistent self-regulation. We obtain the stationary probability
distributions governing hESC transitions amongst the different cell states and
establish the times at which pro-fate cells (which later give rise to
pluripotent or differentiated cells) cluster in the colony. By quantifying the
similarities between the OCT4 expression amongst neighbouring cells, we show
that hESCs express similar OCT4 to cells within their local neighbourhood
within the first two days of the experiment and before BMP4 treatment. Our
framework allows us to quantify the relevant properties of proliferating hESC
colonies and the procedure is widely applicable to other transcription factors
and cell populations.
| [
{
"created": "Mon, 20 Apr 2020 08:55:27 GMT",
"version": "v1"
},
{
"created": "Mon, 4 May 2020 13:48:42 GMT",
"version": "v2"
},
{
"created": "Thu, 21 May 2020 16:39:49 GMT",
"version": "v3"
},
{
"created": "Tue, 27 Oct 2020 13:50:45 GMT",
"version": "v4"
}
] | 2020-10-28 | [
[
"Wadkin",
"Laura E",
""
],
[
"Orozco-Fuentes",
"Sirio",
""
],
[
"Neganova",
"Irina",
""
],
[
"Lako",
"Majlinda",
""
],
[
"Barrio",
"R A",
""
],
[
"Baggaley",
"A W",
""
],
[
"Parker",
"Nicholas G",
""
],
[
"Shukurov",
"Anvar",
""
]
] | The improved in-vitro regulation of human embryonic stem cell (hESC) pluripotency and differentiation trajectories is required for their promising clinical applications. The temporal and spatial quantification of the molecular interactions controlling pluripotency is also necessary for the development of successful mathematical and computational models. Here we use time-lapse experimental data of OCT4-mCherry fluorescence intensity to quantify the temporal and spatial dynamics of the pluripotency transcription factor OCT4 in a growing hESC colony in the presence and absence of BMP4. We characterise the internal self-regulation of OCT4 using the Hurst exponent and autocorrelation analysis, quantify the intra-cellular fluctuations and consider the diffusive nature of OCT4 evolution for individual cells and pairs of their descendants. We find that OCT4 abundance in the daughter cells fluctuates sub-diffusively, showing anti-persistent self-regulation. We obtain the stationary probability distributions governing hESC transitions amongst the different cell states and establish the times at which pro-fate cells (which later give rise to pluripotent or differentiated cells) cluster in the colony. By quantifying the similarities between the OCT4 expression amongst neighbouring cells, we show that hESCs express similar OCT4 to cells within their local neighbourhood within the first two days of the experiment and before BMP4 treatment. Our framework allows us to quantify the relevant properties of proliferating hESC colonies and the procedure is widely applicable to other transcription factors and cell populations. |
1207.6090 | Steven Kelk | Teresa Piovesan and Steven Kelk | A simple fixed parameter tractable algorithm for computing the
hybridization number of two (not necessarily binary) trees | null | null | null | null | q-bio.QM math.CO q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Here we present a new fixed parameter tractable algorithm to compute the
hybridization number r of two rooted, not necessarily binary phylogenetic trees
on taxon set X in time (6^r.r!).poly(n)$, where n=|X|. The novelty of this
approach is its use of terminals, which are maximal elements of a natural
partial order on X, and several insights from the softwired clusters
literature. This yields a surprisingly simple and practical bounded-search
algorithm and offers an alternative perspective on the underlying combinatorial
structure of the hybridization number problem.
| [
{
"created": "Wed, 25 Jul 2012 19:11:42 GMT",
"version": "v1"
}
] | 2012-07-26 | [
[
"Piovesan",
"Teresa",
""
],
[
"Kelk",
"Steven",
""
]
] | Here we present a new fixed parameter tractable algorithm to compute the hybridization number r of two rooted, not necessarily binary phylogenetic trees on taxon set X in time (6^r.r!).poly(n)$, where n=|X|. The novelty of this approach is its use of terminals, which are maximal elements of a natural partial order on X, and several insights from the softwired clusters literature. This yields a surprisingly simple and practical bounded-search algorithm and offers an alternative perspective on the underlying combinatorial structure of the hybridization number problem. |
1808.08033 | Lucas Patty | C.H. Lucas Patty, Freek Ariese, Wybren Jan Buma, Inge Loes ten Kate,
Rob J.M. van Spanning, Frans Snik | Circular spectropolarimetric sensing of higher plant and algal
chloroplast structural variations | 25 pages, 9 figures | null | 10.1007/s11120-018-0572-2 | null | q-bio.BM physics.bio-ph | http://creativecommons.org/licenses/by/4.0/ | Photosynthetic eukaryotes show a remarkable variability in photosynthesis,
including large differences in light harvesting proteins and pigment
composition. In vivo circular spectropolarimetry enables us to probe the
molecular architecture of photosynthesis in a non-invasive and non-destructive
way and, as such, can offer a wealth of physiological and structural
information. In the present study we have measured the circular polarizance of
several multicellular green, red and brown algae and higher plants, which show
large variations in circular spectropolarimetric signals with differences in
both spectral shape and magnitude. Many of the algae display spectral
characteristics not previously reported, indicating a larger variation in
molecular organization than previously assumed. As the strengths of these
signals vary by three orders of magnitude, these results also have important
implications in terms of detectability for the use of circular polarization as
a signature of life.
| [
{
"created": "Fri, 24 Aug 2018 07:36:36 GMT",
"version": "v1"
}
] | 2018-08-27 | [
[
"Patty",
"C. H. Lucas",
""
],
[
"Ariese",
"Freek",
""
],
[
"Buma",
"Wybren Jan",
""
],
[
"Kate",
"Inge Loes ten",
""
],
[
"van Spanning",
"Rob J. M.",
""
],
[
"Snik",
"Frans",
""
]
] | Photosynthetic eukaryotes show a remarkable variability in photosynthesis, including large differences in light harvesting proteins and pigment composition. In vivo circular spectropolarimetry enables us to probe the molecular architecture of photosynthesis in a non-invasive and non-destructive way and, as such, can offer a wealth of physiological and structural information. In the present study we have measured the circular polarizance of several multicellular green, red and brown algae and higher plants, which show large variations in circular spectropolarimetric signals with differences in both spectral shape and magnitude. Many of the algae display spectral characteristics not previously reported, indicating a larger variation in molecular organization than previously assumed. As the strengths of these signals vary by three orders of magnitude, these results also have important implications in terms of detectability for the use of circular polarization as a signature of life. |
2211.07294 | Xianhang Luo | Enqiang Zhu, Xianhang Luo, Chanjuan Liu, Xiaolong Shi, Jin Xu | A universal DNA computing model for solving NP-hard subset problems | null | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | DNA computing, a nontraditional computing mechanism, provides a feasible and
effective method for solving NP-hard problems because of the vast parallelism
and high-density storage of DNA molecules. Although DNA computing has been
exploited to solve various intractable computational problems, such as the
Hamiltonian path problem, SAT problem, and graph coloring problem, there has
been little discussion of designing universal DNA computing-based models, which
can solve a class of problems. In this paper, by leveraging the dynamic and
enzyme-free properties of DNA strand displacement, we propose a universal model
named DCMSubset for solving subset problems in graph theory. The model aims to
find a minimum (or maximum) set satisfying given constraints. For each element
x involved in a given problem, DCMSubset uses an exclusive single-stranded DNA
molecule to model x as well as a specific DNA complex to model the relationship
between x and other elements. Based on the proposed model, we conducted
simulation and biochemical experiments on three kinds of subset problems, a
minimum dominating set, maximum independent set, and minimum vertex cover. We
observed that DCMSubset can also be used to solve the graph coloring problem.
Moreover, we extended DCMSubset to a model for solving the SAT problem. The
results of experiments showed the feasibility and university of the proposed
method. Our results highlighted the potential for DNA strand displacement to
act as a computation tool to solve NP-hard problems.
| [
{
"created": "Mon, 14 Nov 2022 11:59:18 GMT",
"version": "v1"
},
{
"created": "Wed, 16 Nov 2022 04:18:11 GMT",
"version": "v2"
}
] | 2022-11-17 | [
[
"Zhu",
"Enqiang",
""
],
[
"Luo",
"Xianhang",
""
],
[
"Liu",
"Chanjuan",
""
],
[
"Shi",
"Xiaolong",
""
],
[
"Xu",
"Jin",
""
]
] | DNA computing, a nontraditional computing mechanism, provides a feasible and effective method for solving NP-hard problems because of the vast parallelism and high-density storage of DNA molecules. Although DNA computing has been exploited to solve various intractable computational problems, such as the Hamiltonian path problem, SAT problem, and graph coloring problem, there has been little discussion of designing universal DNA computing-based models, which can solve a class of problems. In this paper, by leveraging the dynamic and enzyme-free properties of DNA strand displacement, we propose a universal model named DCMSubset for solving subset problems in graph theory. The model aims to find a minimum (or maximum) set satisfying given constraints. For each element x involved in a given problem, DCMSubset uses an exclusive single-stranded DNA molecule to model x as well as a specific DNA complex to model the relationship between x and other elements. Based on the proposed model, we conducted simulation and biochemical experiments on three kinds of subset problems, a minimum dominating set, maximum independent set, and minimum vertex cover. We observed that DCMSubset can also be used to solve the graph coloring problem. Moreover, we extended DCMSubset to a model for solving the SAT problem. The results of experiments showed the feasibility and university of the proposed method. Our results highlighted the potential for DNA strand displacement to act as a computation tool to solve NP-hard problems. |
0808.0220 | Ping Ao | P. Ao, L.W. Lee, Me Lidstrom, L. Yin, X. M. Zhu | Towards Kinetic Modeling of Global Metabolic Networks with Incomplete
Experimental Input on Kinetic Parameters | 15 pages, pdf format | Towards Kinetic Modeling of Global Metabolic Networks:
Methylobacterium extorquens AM1 Growth as Validation, Chinese J. Biotech 24
(2008) 980-994 | null | null | q-bio.MN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This is the first report, to our knowledge, on a systematic method for
constructing a large scale kinetic metabolic model with incomplete information
on kinetic parametersr, and its initial application to the modeling of central
metabolism of Methylobacterium extorquens AM1, a methylotrophic and
environmental important bacterium, with all necessary constraints. Through a
systematic and consistent procedure of finding a set of parameters in the
physiological range we overcome an outstanding difficulty in large scale
kinetic modeling: the requirement for a massive number of enzymatic reaction
parameters. We are able to construct the kinetic model based on general
biological considerations and incomplete experimental kinetic parameters. The
success of our approach with incompletely input information is guaranteed by
two known principles in biology, the robustness of the system and the
cooperation among its various parts. (Will be pleased to be informed on other
methodologies dealing with same type of problems: aoping@u.washington.edu)
| [
{
"created": "Sat, 2 Aug 2008 00:57:05 GMT",
"version": "v1"
}
] | 2008-08-05 | [
[
"Ao",
"P.",
""
],
[
"Lee",
"L. W.",
""
],
[
"Lidstrom",
"Me",
""
],
[
"Yin",
"L.",
""
],
[
"Zhu",
"X. M.",
""
]
] | This is the first report, to our knowledge, on a systematic method for constructing a large scale kinetic metabolic model with incomplete information on kinetic parametersr, and its initial application to the modeling of central metabolism of Methylobacterium extorquens AM1, a methylotrophic and environmental important bacterium, with all necessary constraints. Through a systematic and consistent procedure of finding a set of parameters in the physiological range we overcome an outstanding difficulty in large scale kinetic modeling: the requirement for a massive number of enzymatic reaction parameters. We are able to construct the kinetic model based on general biological considerations and incomplete experimental kinetic parameters. The success of our approach with incompletely input information is guaranteed by two known principles in biology, the robustness of the system and the cooperation among its various parts. (Will be pleased to be informed on other methodologies dealing with same type of problems: aoping@u.washington.edu) |
2210.01772 | Anne-Marie Rickmann | Anne-Marie Rickmann, Fabian Bongratz, Sebastian P\"olsterl, Ignacio
Sarasua, Christian Wachinger | Joint Reconstruction and Parcellation of Cortical Surfaces | accepted at MLCN workshop 2022 | null | null | null | q-bio.NC cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The reconstruction of cerebral cortex surfaces from brain MRI scans is
instrumental for the analysis of brain morphology and the detection of cortical
thinning in neurodegenerative diseases like Alzheimer's disease (AD). Moreover,
for a fine-grained analysis of atrophy patterns, the parcellation of the
cortical surfaces into individual brain regions is required. For the former
task, powerful deep learning approaches, which provide highly accurate brain
surfaces of tissue boundaries from input MRI scans in seconds, have recently
been proposed. However, these methods do not come with the ability to provide a
parcellation of the reconstructed surfaces. Instead, separate
brain-parcellation methods have been developed, which typically consider the
cortical surfaces as given, often computed beforehand with FreeSurfer. In this
work, we propose two options, one based on a graph classification branch and
another based on a novel generic 3D reconstruction loss, to augment
template-deformation algorithms such that the surface meshes directly come with
an atlas-based brain parcellation. By combining both options with two of the
latest cortical surface reconstruction algorithms, we attain highly accurate
parcellations with a Dice score of 90.2 (graph classification branch) and 90.4
(novel reconstruction loss) together with state-of-the-art surfaces.
| [
{
"created": "Mon, 19 Sep 2022 11:45:39 GMT",
"version": "v1"
}
] | 2022-10-05 | [
[
"Rickmann",
"Anne-Marie",
""
],
[
"Bongratz",
"Fabian",
""
],
[
"Pölsterl",
"Sebastian",
""
],
[
"Sarasua",
"Ignacio",
""
],
[
"Wachinger",
"Christian",
""
]
] | The reconstruction of cerebral cortex surfaces from brain MRI scans is instrumental for the analysis of brain morphology and the detection of cortical thinning in neurodegenerative diseases like Alzheimer's disease (AD). Moreover, for a fine-grained analysis of atrophy patterns, the parcellation of the cortical surfaces into individual brain regions is required. For the former task, powerful deep learning approaches, which provide highly accurate brain surfaces of tissue boundaries from input MRI scans in seconds, have recently been proposed. However, these methods do not come with the ability to provide a parcellation of the reconstructed surfaces. Instead, separate brain-parcellation methods have been developed, which typically consider the cortical surfaces as given, often computed beforehand with FreeSurfer. In this work, we propose two options, one based on a graph classification branch and another based on a novel generic 3D reconstruction loss, to augment template-deformation algorithms such that the surface meshes directly come with an atlas-based brain parcellation. By combining both options with two of the latest cortical surface reconstruction algorithms, we attain highly accurate parcellations with a Dice score of 90.2 (graph classification branch) and 90.4 (novel reconstruction loss) together with state-of-the-art surfaces. |
2212.12114 | Nan Xi | Angelos Vasilopoulos and Nan Miles Xi | Predicting Survival of Tongue Cancer Patients by Machine Learning Models | null | null | null | null | q-bio.QM cs.LG | http://creativecommons.org/licenses/by/4.0/ | Tongue cancer is a common oral cavity malignancy that originates in the mouth
and throat. Much effort has been invested in improving its diagnosis,
treatment, and management. Surgical removal, chemotherapy, and radiation
therapy remain the major treatment for tongue cancer. The survival of patients
determines the treatment effect. Previous studies have identified certain
survival and risk factors based on descriptive statistics, ignoring the
complex, nonlinear relationship among clinical and demographic variables. In
this study, we utilize five cutting-edge machine learning models and clinical
data to predict the survival of tongue cancer patients after treatment.
Five-fold cross-validation, bootstrap analysis, and permutation feature
importance are applied to estimate and interpret model performance. The
prognostic factors identified by our method are consistent with previous
clinical studies. Our method is accurate, interpretable, and thus useable as
additional evidence in tongue cancer treatment and management.
| [
{
"created": "Fri, 23 Dec 2022 03:00:20 GMT",
"version": "v1"
}
] | 2022-12-26 | [
[
"Vasilopoulos",
"Angelos",
""
],
[
"Xi",
"Nan Miles",
""
]
] | Tongue cancer is a common oral cavity malignancy that originates in the mouth and throat. Much effort has been invested in improving its diagnosis, treatment, and management. Surgical removal, chemotherapy, and radiation therapy remain the major treatment for tongue cancer. The survival of patients determines the treatment effect. Previous studies have identified certain survival and risk factors based on descriptive statistics, ignoring the complex, nonlinear relationship among clinical and demographic variables. In this study, we utilize five cutting-edge machine learning models and clinical data to predict the survival of tongue cancer patients after treatment. Five-fold cross-validation, bootstrap analysis, and permutation feature importance are applied to estimate and interpret model performance. The prognostic factors identified by our method are consistent with previous clinical studies. Our method is accurate, interpretable, and thus useable as additional evidence in tongue cancer treatment and management. |
1702.00489 | Ryan Evans | Ryan M. Evans and David A. Edwards | Transport Effects on Multiple-Component Reactions in Optical Biosensors | null | Bulletin of Mathematical Biology, 79 (2017): 2214--2241 | 10.1007/s11538-017-0327-9 | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Optical biosensors are often used to measure kinetic rate constants
associated with chemical reactions. Such instruments operate in the
\textit{surface-volume} configuration, in which ligand molecules are convected
through a fluid-filled volume over a surface to which receptors are confined.
Currently, scientists are using optical biosenors to measure the kinetic rate
constants associated with DNA translesion synthesis--a process critical to DNA
damage repair. Biosensor experiments to study this process involve multiple
interacting components on the sensor surface. This multiple-component biosensor
experiment is modeled with a set of nonlinear integrodifferential equations
(IDEs). It is shown that in physically relevant asymptotic limits these
equations reduce to a much simpler set of Ordinary Differential Equations
(ODEs). To verify the validity of our ODE approximation, a numerical method for
the IDE system is developed and studied. Results from the ODE model agree with
simulations of the IDE model, rendering our ODE model useful for parameter
estimation.
| [
{
"created": "Thu, 26 Jan 2017 20:11:40 GMT",
"version": "v1"
},
{
"created": "Thu, 12 Oct 2017 16:09:54 GMT",
"version": "v2"
}
] | 2017-10-13 | [
[
"Evans",
"Ryan M.",
""
],
[
"Edwards",
"David A.",
""
]
] | Optical biosensors are often used to measure kinetic rate constants associated with chemical reactions. Such instruments operate in the \textit{surface-volume} configuration, in which ligand molecules are convected through a fluid-filled volume over a surface to which receptors are confined. Currently, scientists are using optical biosenors to measure the kinetic rate constants associated with DNA translesion synthesis--a process critical to DNA damage repair. Biosensor experiments to study this process involve multiple interacting components on the sensor surface. This multiple-component biosensor experiment is modeled with a set of nonlinear integrodifferential equations (IDEs). It is shown that in physically relevant asymptotic limits these equations reduce to a much simpler set of Ordinary Differential Equations (ODEs). To verify the validity of our ODE approximation, a numerical method for the IDE system is developed and studied. Results from the ODE model agree with simulations of the IDE model, rendering our ODE model useful for parameter estimation. |
q-bio/0605035 | Mathieu Emily | Mathieu Emily and Olivier Francois | A continuous model for cell sorting | 21 pages; 6 Figures; 1 Table | null | null | null | q-bio.TO | null | The differential Adhesion Hypothesis (DAH) is a theory of the organization of
cells within a tissue. In this study we introduce a stochastic model supporting
the DAH, that can be seen as a continuous version of a discrete model of Graner
and Glazier. Our approach is based on the mathematical framework of Gibbsian
marked point processes. We provide a Markov chain Monte Carlo algorithm that
can reproduce classical biological patterns, and we propose an estimation
procedure for a parameter that quantifies the strength of adhesion between
cells. This procedure is tested through simulations.
| [
{
"created": "Sat, 20 May 2006 12:59:31 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Emily",
"Mathieu",
""
],
[
"Francois",
"Olivier",
""
]
] | The differential Adhesion Hypothesis (DAH) is a theory of the organization of cells within a tissue. In this study we introduce a stochastic model supporting the DAH, that can be seen as a continuous version of a discrete model of Graner and Glazier. Our approach is based on the mathematical framework of Gibbsian marked point processes. We provide a Markov chain Monte Carlo algorithm that can reproduce classical biological patterns, and we propose an estimation procedure for a parameter that quantifies the strength of adhesion between cells. This procedure is tested through simulations. |
2310.16439 | Gennadi Glinsky | Gennadi Glinsky | Genomic regulatory architecture of human embryo retroviral LTR elements
affecting evolution, development, and pathophysiology of Modern Humans | 66 pages, 16 figures | null | null | null | q-bio.GN q-bio.MN q-bio.NC q-bio.PE q-bio.TO | http://creativecommons.org/licenses/by/4.0/ | Two distinct families of pan-primate endogenous retroviruses, namely HERVL
and HERVH, infected primates germline, colonized host genomes, and evolved into
the global retroviral genomic regulatory dominion (GRD) operating during human
embryogenesis (HE). HE retroviral GRD constitutes 8839 highly conserved fixed
LTR elements linked to 5444 down-stream target genes forged by evolution into a
functionally-consonant constellation of 26 genome-wide multimodular genomic
regulatory networks (GRNs), each of which is defined by significant enrichment
of numerous single gene ontology (GO)-specific traits. Locations of GRNs appear
scattered across chromosomes to occupy from 5.5%-15.09% of human genome. Each
GRN harbors from 529-1486 retroviral LTRs derived from LTR7, MLT2A1, and MLT2A2
sequences that are quantitatively balanced according to their genome-wide
abundance. GRNs integrate activities from 199-805 down-stream target genes,
including transcription factors, chromatin-state remodelers, signal-sensing and
signal-transduction mediators, enzymatic and receptor binding effectors,
intracellular complexes and extracellular matrix elements, and cell-cell
adhesion molecules. GRNs compositions consist of several hundred to thousands
smaller GO enrichment-defined genomic regulatory modules (GRMs) combining from
a dozen to hundreds LTRs and down-stream target genes, which appear to operate
on individuals life-span timescale along specific phenotypic avenues to exert
profound effects on patterns of transcription, protein-protein interactions,
developmental phenotypes, physiological traits, and pathological conditions of
Modern Humans. Overall, this study identifies 69,573 statistically significant
retroviral LTR-linked GRMs (Binominal FDR q-value threshold of 0.001),
including 27,601 GRMs validated by the single GO-specific directed acyclic
graph (DAG) analyses across six GO annotations.
| [
{
"created": "Wed, 25 Oct 2023 08:04:58 GMT",
"version": "v1"
}
] | 2023-10-26 | [
[
"Glinsky",
"Gennadi",
""
]
] | Two distinct families of pan-primate endogenous retroviruses, namely HERVL and HERVH, infected primates germline, colonized host genomes, and evolved into the global retroviral genomic regulatory dominion (GRD) operating during human embryogenesis (HE). HE retroviral GRD constitutes 8839 highly conserved fixed LTR elements linked to 5444 down-stream target genes forged by evolution into a functionally-consonant constellation of 26 genome-wide multimodular genomic regulatory networks (GRNs), each of which is defined by significant enrichment of numerous single gene ontology (GO)-specific traits. Locations of GRNs appear scattered across chromosomes to occupy from 5.5%-15.09% of human genome. Each GRN harbors from 529-1486 retroviral LTRs derived from LTR7, MLT2A1, and MLT2A2 sequences that are quantitatively balanced according to their genome-wide abundance. GRNs integrate activities from 199-805 down-stream target genes, including transcription factors, chromatin-state remodelers, signal-sensing and signal-transduction mediators, enzymatic and receptor binding effectors, intracellular complexes and extracellular matrix elements, and cell-cell adhesion molecules. GRNs compositions consist of several hundred to thousands smaller GO enrichment-defined genomic regulatory modules (GRMs) combining from a dozen to hundreds LTRs and down-stream target genes, which appear to operate on individuals life-span timescale along specific phenotypic avenues to exert profound effects on patterns of transcription, protein-protein interactions, developmental phenotypes, physiological traits, and pathological conditions of Modern Humans. Overall, this study identifies 69,573 statistically significant retroviral LTR-linked GRMs (Binominal FDR q-value threshold of 0.001), including 27,601 GRMs validated by the single GO-specific directed acyclic graph (DAG) analyses across six GO annotations. |
1902.10117 | Giovanni Stilo | Lorenzo Madeddu, Giovanni Stilo, Paola Velardi | Network-based methods for disease-gene prediction | null | null | null | null | q-bio.MN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We predict disease-genes relations on the Human Interactome network using a
methodology that jointly learns functional and connectivity patterns
surrounding proteins. Contrary to other data structures, the Interactome is
characterized by high incompleteness and absence of explicit negative
knowledge, which makes predictive tasks particularly challenging. To exploit at
best latent information in the network, we propose an extended version of
random walks, named Random Watcher-Walker ($RW^2$), which is able to learn rich
representations of disease genes (or gene products) features. Our method
successfully compares with the best known system for disease gene prediction,
and other state-of-the-art graph-based methods. We perform sensitivity analysis
and apply perturbations to ensure robustness. In contrast with previous
studies, our results demonstrate that connectivity alone is not sufficient to
classify disease-related genes.
| [
{
"created": "Tue, 26 Feb 2019 18:48:27 GMT",
"version": "v1"
}
] | 2019-02-27 | [
[
"Madeddu",
"Lorenzo",
""
],
[
"Stilo",
"Giovanni",
""
],
[
"Velardi",
"Paola",
""
]
] | We predict disease-genes relations on the Human Interactome network using a methodology that jointly learns functional and connectivity patterns surrounding proteins. Contrary to other data structures, the Interactome is characterized by high incompleteness and absence of explicit negative knowledge, which makes predictive tasks particularly challenging. To exploit at best latent information in the network, we propose an extended version of random walks, named Random Watcher-Walker ($RW^2$), which is able to learn rich representations of disease genes (or gene products) features. Our method successfully compares with the best known system for disease gene prediction, and other state-of-the-art graph-based methods. We perform sensitivity analysis and apply perturbations to ensure robustness. In contrast with previous studies, our results demonstrate that connectivity alone is not sufficient to classify disease-related genes. |
1303.4835 | Justin Fay | Gareth A. Cromie, Katie E. Hyma, Catherine L. Ludlow, Cecilia
Garmendia-Torres, Teresa L. Gilbert, Patrick May, Angela A. Huang, Aim\'ee M.
Dudley, Justin C. Fay | Genomic Sequence Diversity and Population Structure of Saccharomyces
cerevisiae Assessed by RAD-seq | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/3.0/ | The budding yeast Saccharomyces cerevisiae is important for human food
production and as a model organism for biological research. The genetic
diversity contained in the global population of yeast strains represents a
valuable resource for a number of fields, including genetics, bioengineering,
and studies of evolution and population structure. Here, we apply a
multiplexed, reduced genome sequencing strategy (known as RAD-seq) to genotype
a large collection of S. cerevisiae strains, isolated from a wide range of
geographical locations and environmental niches. The method permits the
sequencing of the same 1% of all genomes, producing a multiple sequence
alignment of 116,880 bases across 262 strains. We find diversity among these
strains is principally organized by geography, with European, North American,
Asian and African/S. E. Asian populations defining the major axes of genetic
variation. At a finer scale, small groups of strains from cacao, olives and
sake are defined by unique variants not present in other strains. One
population, containing strains from a variety of fermentations, exhibits high
levels of heterozygosity and mixtures of alleles from European and Asian
populations, indicating an admixed origin for this group. In the context of
this global diversity, we demonstrate that a collection of seven strains
commonly used in the laboratory encompasses only one quarter of the genetic
diversity present in the full collection of strains, underscoring the
relatively limited genetic diversity captured by the current set of lab
strains. We propose a model of geographic differentiation followed by
human-associated admixture, primarily between European and Asian populations
and more recently between European and North American populations. The large
collection of genotyped yeast strains characterized here will provide a useful
resource for the broad community of yeast researchers.
| [
{
"created": "Wed, 20 Mar 2013 04:08:54 GMT",
"version": "v1"
}
] | 2015-03-13 | [
[
"Cromie",
"Gareth A.",
""
],
[
"Hyma",
"Katie E.",
""
],
[
"Ludlow",
"Catherine L.",
""
],
[
"Garmendia-Torres",
"Cecilia",
""
],
[
"Gilbert",
"Teresa L.",
""
],
[
"May",
"Patrick",
""
],
[
"Huang",
"Angela A.",
""
],
[
"Dudley",
"Aimée M.",
""
],
[
"Fay",
"Justin C.",
""
]
] | The budding yeast Saccharomyces cerevisiae is important for human food production and as a model organism for biological research. The genetic diversity contained in the global population of yeast strains represents a valuable resource for a number of fields, including genetics, bioengineering, and studies of evolution and population structure. Here, we apply a multiplexed, reduced genome sequencing strategy (known as RAD-seq) to genotype a large collection of S. cerevisiae strains, isolated from a wide range of geographical locations and environmental niches. The method permits the sequencing of the same 1% of all genomes, producing a multiple sequence alignment of 116,880 bases across 262 strains. We find diversity among these strains is principally organized by geography, with European, North American, Asian and African/S. E. Asian populations defining the major axes of genetic variation. At a finer scale, small groups of strains from cacao, olives and sake are defined by unique variants not present in other strains. One population, containing strains from a variety of fermentations, exhibits high levels of heterozygosity and mixtures of alleles from European and Asian populations, indicating an admixed origin for this group. In the context of this global diversity, we demonstrate that a collection of seven strains commonly used in the laboratory encompasses only one quarter of the genetic diversity present in the full collection of strains, underscoring the relatively limited genetic diversity captured by the current set of lab strains. We propose a model of geographic differentiation followed by human-associated admixture, primarily between European and Asian populations and more recently between European and North American populations. The large collection of genotyped yeast strains characterized here will provide a useful resource for the broad community of yeast researchers. |
1212.1067 | Christian Hilbe | Christian Hilbe and Martin A. Nowak and Karl Sigmund | The Evolution of Extortion in Iterated Prisoner's Dilemma Games | contains 4 figures | null | 10.1073/pnas.1214834110 | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Iterated games are a fundamental component of economic and evolutionary game
theory. They describe situations where two players interact repeatedly and have
the possibility to use conditional strategies that depend on the outcome of
previous interactions. In the context of evolution of cooperation, repeated
games represent the mechanism of reciprocation. Recently a new class of
strategies has been proposed, so called 'zero determinant strategies'. These
strategies enforce a fixed linear relationship between one's own payoff and
that of the other player. A subset of those strategies are 'extortioners' which
ensure that any increase in the own payoff exceeds that of the other player by
a fixed percentage. Here we analyze the evolutionary performance of this new
class of strategies. We show that in reasonably large populations they can act
as catalysts for the evolution of cooperation, similar to tit-for-tat, but they
are not the stable outcome of natural selection. In very small populations,
however, relative payoff differences between two players in a contest matter,
and extortioners hold their ground. Extortion strategies do particularly well
in co-evolutionary arms races between two distinct populations: significantly,
they benefit the population which evolves at the slower rate - an instance of
the so-called Red King effect. This may affect the evolution of interactions
between host species and their endosymbionts.
| [
{
"created": "Wed, 5 Dec 2012 15:56:04 GMT",
"version": "v1"
}
] | 2015-06-12 | [
[
"Hilbe",
"Christian",
""
],
[
"Nowak",
"Martin A.",
""
],
[
"Sigmund",
"Karl",
""
]
] | Iterated games are a fundamental component of economic and evolutionary game theory. They describe situations where two players interact repeatedly and have the possibility to use conditional strategies that depend on the outcome of previous interactions. In the context of evolution of cooperation, repeated games represent the mechanism of reciprocation. Recently a new class of strategies has been proposed, so called 'zero determinant strategies'. These strategies enforce a fixed linear relationship between one's own payoff and that of the other player. A subset of those strategies are 'extortioners' which ensure that any increase in the own payoff exceeds that of the other player by a fixed percentage. Here we analyze the evolutionary performance of this new class of strategies. We show that in reasonably large populations they can act as catalysts for the evolution of cooperation, similar to tit-for-tat, but they are not the stable outcome of natural selection. In very small populations, however, relative payoff differences between two players in a contest matter, and extortioners hold their ground. Extortion strategies do particularly well in co-evolutionary arms races between two distinct populations: significantly, they benefit the population which evolves at the slower rate - an instance of the so-called Red King effect. This may affect the evolution of interactions between host species and their endosymbionts. |
1909.05910 | Jahan Schad | Jahan N. Schad | Brain Neurological Constructs: The Neuronal Computational Schemes for
Resolution of Life's Complexities | 5 Pages | J Neurol Neurophysiol 2016, 7:1 | 10.4172/2155-9562.1000356 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | For complex life to evolve, a sophisticated nervous system for handling its
complexities was fundamental. The demand resulted in the emergence of brain's
computational facility, the neuronal network. This facet of the brain is
attested solidly by its inspired scientific computational neural nets which
(mathematically) resolve and solve many complex problems. The presumptive
general semblance of the computational operation between the two systems allows
for the inference that the process in brain's neural domain also renders
complexities for solution, as sets of parametric equations, like the basic
implicit algorithmic formalisms underlying the operations of the scientific
neural nets. This parallel is based on the fact that such devices resolve
complex problems for which no declarative logical formulation is deployed. The
mathematically resolved neural net problem formalism also resembled that of any
theoretically known and formulated complexities which are algorithmized, in
their discretized solution domains, within the context of initial and boundary
value problems for direct or iterative solution by computers. The brain
neuronal net algorithmization of complexities delineate the governing equations
of life and living, solutions of which are achieved by trial and error
learning, deploying rest of the nervous system and other faculties of living
beings. The computational operations of the brain delineate two mental states:
consciousness and the unconscious; the aware and unaware states which describes
the interactive living processes involved in charting life's path.
| [
{
"created": "Tue, 10 Sep 2019 18:58:24 GMT",
"version": "v1"
}
] | 2019-09-16 | [
[
"Schad",
"Jahan N.",
""
]
] | For complex life to evolve, a sophisticated nervous system for handling its complexities was fundamental. The demand resulted in the emergence of brain's computational facility, the neuronal network. This facet of the brain is attested solidly by its inspired scientific computational neural nets which (mathematically) resolve and solve many complex problems. The presumptive general semblance of the computational operation between the two systems allows for the inference that the process in brain's neural domain also renders complexities for solution, as sets of parametric equations, like the basic implicit algorithmic formalisms underlying the operations of the scientific neural nets. This parallel is based on the fact that such devices resolve complex problems for which no declarative logical formulation is deployed. The mathematically resolved neural net problem formalism also resembled that of any theoretically known and formulated complexities which are algorithmized, in their discretized solution domains, within the context of initial and boundary value problems for direct or iterative solution by computers. The brain neuronal net algorithmization of complexities delineate the governing equations of life and living, solutions of which are achieved by trial and error learning, deploying rest of the nervous system and other faculties of living beings. The computational operations of the brain delineate two mental states: consciousness and the unconscious; the aware and unaware states which describes the interactive living processes involved in charting life's path. |
2110.06352 | Nazmi Burak Budanur | Nazmi Burak Budanur and Bj\"orn Hof | An autonomous compartmental model for accelerating epidemics | null | PLoS ONE 17(7): e0269975 (2022) | 10.1371/journal.pone.0269975 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In Fall 2020, several European countries reported rapid increases in COVID-19
cases along with growing estimates of the effective reproduction rates. Such an
acceleration in epidemic spread is usually attributed to time-dependent
effects, e.g. human travel, seasonal behavioral changes, mutations of the
pathogen etc. In this case however the acceleration occurred when counter
measures such as testing and contact tracing exceeded their capacity limit.
Considering Austria as an example, here we show that this dynamics can be
captured by a time-independent, i.e. autonomous, compartmental model that
incorporates these capacity limits. In this model, the epidemic acceleration
coincides with the exhaustion of mitigation efforts, resulting in an increasing
fraction of undetected cases that drive the effective reproduction rate
progressively higher. We demonstrate that standard models which does not
include this effect necessarily result in a systematic underestimation of the
effective reproduction rate.
| [
{
"created": "Tue, 12 Oct 2021 20:53:53 GMT",
"version": "v1"
},
{
"created": "Wed, 6 Jul 2022 09:47:01 GMT",
"version": "v2"
}
] | 2022-11-30 | [
[
"Budanur",
"Nazmi Burak",
""
],
[
"Hof",
"Björn",
""
]
] | In Fall 2020, several European countries reported rapid increases in COVID-19 cases along with growing estimates of the effective reproduction rates. Such an acceleration in epidemic spread is usually attributed to time-dependent effects, e.g. human travel, seasonal behavioral changes, mutations of the pathogen etc. In this case however the acceleration occurred when counter measures such as testing and contact tracing exceeded their capacity limit. Considering Austria as an example, here we show that this dynamics can be captured by a time-independent, i.e. autonomous, compartmental model that incorporates these capacity limits. In this model, the epidemic acceleration coincides with the exhaustion of mitigation efforts, resulting in an increasing fraction of undetected cases that drive the effective reproduction rate progressively higher. We demonstrate that standard models which does not include this effect necessarily result in a systematic underestimation of the effective reproduction rate. |
1812.03321 | Mitchell Eithun | Mitchell Eithun, Daniel H. Chitwood, James Larson, Gregory Lang,
Elizabeth Munch | Isolating phyllotactic patterns embedded in the secondary growth of
sweet cherry (Prunus avium L.) using magnetic resonance imaging | Code: https://github.com/eithun/cherry-phyllotaxy | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Epicormic branches arise from dormant buds patterned during the growth of
previous years. Dormant epicormic buds remain on the surface of trees, pushed
outward from the pith during secondary growth, but maintaining vascular
connections. Epicormic buds can be reactivated, either through natural
processes or intentionally, to rejuvenate orchards and control tree
architecture. Because epicormic structures are embedded within secondary
growth, tomographic approaches are a useful method to study them and understand
their development.
We apply techniques from image processing to determine the locations of
epicormic vascular traces embedded within secondary growth of sweet cherry
(Prunus avium L.), revealing the juvenile phyllotactic pattern in the trunk of
an adult tree. Techniques include breadth-first search to find the pith of the
tree, edge detection to approximate the radius, and a conversion to polar
coordinates to threshold and segment phyllotactic features. Intensity values
from Magnetic Resonance Imaging (MRI) of the trunk are projected onto the
surface of a perfect cylinder to find the locations of traces in the "boundary
image". Mathematical phyllotaxy provides a means to capture the patterns in the
boundary image by modeling phyllotactic parameters. Our cherry tree specimen
has the conspicuous parastichy pair $(2,3)$, phyllotactic fraction 2/5, and
divergence angle of approximately 143 degrees.
The methods described not only provide a framework to study phyllotaxy, but
for image processing of volumetric image data in plants. Our results have
practical implications for orchard rejuvenation and directed approaches to
influence tree architecture. The study of epicormic structures, which are
hidden within secondary growth, using tomographic methods also opens the
possibility of studying the genetic and environmental basis of such structures.
| [
{
"created": "Sat, 8 Dec 2018 14:00:48 GMT",
"version": "v1"
}
] | 2018-12-11 | [
[
"Eithun",
"Mitchell",
""
],
[
"Chitwood",
"Daniel H.",
""
],
[
"Larson",
"James",
""
],
[
"Lang",
"Gregory",
""
],
[
"Munch",
"Elizabeth",
""
]
] | Epicormic branches arise from dormant buds patterned during the growth of previous years. Dormant epicormic buds remain on the surface of trees, pushed outward from the pith during secondary growth, but maintaining vascular connections. Epicormic buds can be reactivated, either through natural processes or intentionally, to rejuvenate orchards and control tree architecture. Because epicormic structures are embedded within secondary growth, tomographic approaches are a useful method to study them and understand their development. We apply techniques from image processing to determine the locations of epicormic vascular traces embedded within secondary growth of sweet cherry (Prunus avium L.), revealing the juvenile phyllotactic pattern in the trunk of an adult tree. Techniques include breadth-first search to find the pith of the tree, edge detection to approximate the radius, and a conversion to polar coordinates to threshold and segment phyllotactic features. Intensity values from Magnetic Resonance Imaging (MRI) of the trunk are projected onto the surface of a perfect cylinder to find the locations of traces in the "boundary image". Mathematical phyllotaxy provides a means to capture the patterns in the boundary image by modeling phyllotactic parameters. Our cherry tree specimen has the conspicuous parastichy pair $(2,3)$, phyllotactic fraction 2/5, and divergence angle of approximately 143 degrees. The methods described not only provide a framework to study phyllotaxy, but for image processing of volumetric image data in plants. Our results have practical implications for orchard rejuvenation and directed approaches to influence tree architecture. The study of epicormic structures, which are hidden within secondary growth, using tomographic methods also opens the possibility of studying the genetic and environmental basis of such structures. |
1508.06936 | Alex Barnett | Alex H. Barnett, Jeremy F. Magland, and Leslie F. Greengard | Validation of neural spike sorting algorithms without ground-truth
information | 22 pages, 7 figures; submitted to J. Neurosci. Meth | null | null | null | q-bio.NC cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We describe a suite of validation metrics that assess the credibility of a
given automatic spike sorting algorithm applied to a given electrophysiological
recording, when ground-truth is unavailable. By rerunning the spike sorter two
or more times, the metrics measure stability under various perturbations
consistent with variations in the data itself, making no assumptions about the
noise model, nor about the internal workings of the sorting algorithm. Such
stability is a prerequisite for reproducibility of results. We illustrate the
metrics on standard sorting algorithms for both in vivo and ex vivo recordings.
We believe that such metrics could reduce the significant human labor currently
spent on validation, and should form an essential part of large-scale automated
spike sorting and systematic benchmarking of algorithms.
| [
{
"created": "Thu, 27 Aug 2015 16:53:20 GMT",
"version": "v1"
}
] | 2015-08-28 | [
[
"Barnett",
"Alex H.",
""
],
[
"Magland",
"Jeremy F.",
""
],
[
"Greengard",
"Leslie F.",
""
]
] | We describe a suite of validation metrics that assess the credibility of a given automatic spike sorting algorithm applied to a given electrophysiological recording, when ground-truth is unavailable. By rerunning the spike sorter two or more times, the metrics measure stability under various perturbations consistent with variations in the data itself, making no assumptions about the noise model, nor about the internal workings of the sorting algorithm. Such stability is a prerequisite for reproducibility of results. We illustrate the metrics on standard sorting algorithms for both in vivo and ex vivo recordings. We believe that such metrics could reduce the significant human labor currently spent on validation, and should form an essential part of large-scale automated spike sorting and systematic benchmarking of algorithms. |
1212.0159 | C. Titus Brown | Adina Chuang Howe, Jason Pell, Rosangela Canino-Koning, Rachel
Mackelprang, Susannah Tringe, Janet Jansson, James M. Tiedje, C. Titus Brown | Illumina Sequencing Artifacts Revealed by Connectivity Analysis of
Metagenomic Datasets | null | null | null | null | q-bio.GN | http://creativecommons.org/licenses/publicdomain/ | Sequencing errors and biases in metagenomic datasets affect coverage-based
assemblies and are often ignored during analysis. Here, we analyze read
connectivity in metagenomes and identify the presence of problematic and likely
a-biological connectivity within metagenome assembly graphs. Specifically, we
identify highly connected sequences which join a large proportion of reads
within each real metagenome. These sequences show position-specific bias in
shotgun reads, suggestive of sequencing artifacts, and are only minimally
incorporated into contigs by assembly. The removal of these sequences prior to
assembly results in similar assembly content for most metagenomes and enables
the use of graph partitioning to decrease assembly memory and time
requirements.
| [
{
"created": "Sat, 1 Dec 2012 20:57:59 GMT",
"version": "v1"
}
] | 2012-12-04 | [
[
"Howe",
"Adina Chuang",
""
],
[
"Pell",
"Jason",
""
],
[
"Canino-Koning",
"Rosangela",
""
],
[
"Mackelprang",
"Rachel",
""
],
[
"Tringe",
"Susannah",
""
],
[
"Jansson",
"Janet",
""
],
[
"Tiedje",
"James M.",
""
],
[
"Brown",
"C. Titus",
""
]
] | Sequencing errors and biases in metagenomic datasets affect coverage-based assemblies and are often ignored during analysis. Here, we analyze read connectivity in metagenomes and identify the presence of problematic and likely a-biological connectivity within metagenome assembly graphs. Specifically, we identify highly connected sequences which join a large proportion of reads within each real metagenome. These sequences show position-specific bias in shotgun reads, suggestive of sequencing artifacts, and are only minimally incorporated into contigs by assembly. The removal of these sequences prior to assembly results in similar assembly content for most metagenomes and enables the use of graph partitioning to decrease assembly memory and time requirements. |
1505.04828 | Jaegil Kim | Jaegil Kim, Atanas Kamburov, Michal Lawrence, Yosef Maruvka, Gad Getz | An exact method to compute a $p$-value for the beyond-pairwise
correlations among cancer gene mutations | null | null | null | null | q-bio.QM q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The increasing observation of mutual exclusivity correlations among cancer
gene mutations is a key component for identifying driver events or pathways in
cancer genome analysis. Here we report a rigorous statistical method to compute
an exact $p$-value for the beyond-pairwise mutual exclusivity or co-occurrence
relationships among cancer gene mutations by enumerating a null distribution of
overlapping mutations across more than two genes. The validity and the
advantage of our method is explicitly demonstrated in both cancer gene
mutations and simulation data through the comparison to the permutation test.
| [
{
"created": "Mon, 18 May 2015 21:56:48 GMT",
"version": "v1"
}
] | 2015-05-20 | [
[
"Kim",
"Jaegil",
""
],
[
"Kamburov",
"Atanas",
""
],
[
"Lawrence",
"Michal",
""
],
[
"Maruvka",
"Yosef",
""
],
[
"Getz",
"Gad",
""
]
] | The increasing observation of mutual exclusivity correlations among cancer gene mutations is a key component for identifying driver events or pathways in cancer genome analysis. Here we report a rigorous statistical method to compute an exact $p$-value for the beyond-pairwise mutual exclusivity or co-occurrence relationships among cancer gene mutations by enumerating a null distribution of overlapping mutations across more than two genes. The validity and the advantage of our method is explicitly demonstrated in both cancer gene mutations and simulation data through the comparison to the permutation test. |
2302.14064 | Adrian Bach | Adrian Bach | Exploring locust hopper bands emergent patterns using parallel computing | Masters project supervised by Jerome Buhl (The University of
Adelaide) | null | null | null | q-bio.NC nlin.AO physics.soc-ph | http://creativecommons.org/licenses/by-nc-nd/4.0/ | To date, the mechanisms underlying the diversity of the emergent patterns of
collective motion in locust hopper bands remain to be unveiled. This study
investigates the role of speed heterogeneity in the emergence of the most
common patterns (frontal and columnar), following the Self-Organization
framework. To address whether marching activity intermittency and
density-dependant hopping individual behaviours could underlie the formation of
such patterns, a three-zone Self-Propelled Particles model variant was
formulated. In this model, individuals alternated between marching and resting
periods, and were more likely to hop when crowded. The model successfully
predicted the emergence of both patterns of interest, with the presence of a
density-dependent hopping probability being a necessary condition. Short to
absent pause periods mostly resulted in columnar shapes, similar to the ones
observed in the brown locust (Locustana pardalina) and long pause periods
rather resulted in frontal shapes, such as exhibited by the Australian plague
locust (Chortoicetes terminifera). Furthermore, the density profiles of
simulated frontal formations displayed the same shape as empirical profiles of
Australian plague locust hopper bands. Both simulated and experimental paint
marking experiments showed that locusts initially located at different
positions in the band were find together at its front after a few hours
marching; an expected global behavior in hopper bands undergoing activity
intermittency. These results represent an important first step towards a
cross-species comparison of locust mass migration patterns.
| [
{
"created": "Tue, 28 Feb 2023 16:32:07 GMT",
"version": "v1"
}
] | 2023-03-01 | [
[
"Bach",
"Adrian",
""
]
] | To date, the mechanisms underlying the diversity of the emergent patterns of collective motion in locust hopper bands remain to be unveiled. This study investigates the role of speed heterogeneity in the emergence of the most common patterns (frontal and columnar), following the Self-Organization framework. To address whether marching activity intermittency and density-dependant hopping individual behaviours could underlie the formation of such patterns, a three-zone Self-Propelled Particles model variant was formulated. In this model, individuals alternated between marching and resting periods, and were more likely to hop when crowded. The model successfully predicted the emergence of both patterns of interest, with the presence of a density-dependent hopping probability being a necessary condition. Short to absent pause periods mostly resulted in columnar shapes, similar to the ones observed in the brown locust (Locustana pardalina) and long pause periods rather resulted in frontal shapes, such as exhibited by the Australian plague locust (Chortoicetes terminifera). Furthermore, the density profiles of simulated frontal formations displayed the same shape as empirical profiles of Australian plague locust hopper bands. Both simulated and experimental paint marking experiments showed that locusts initially located at different positions in the band were find together at its front after a few hours marching; an expected global behavior in hopper bands undergoing activity intermittency. These results represent an important first step towards a cross-species comparison of locust mass migration patterns. |
1503.02846 | Steven Lade | Steven J. Lade, Susa Niiranen | Generalized modeling of empirical social-ecological systems | This is the authors' accepted manuscript. The final version of the
paper including copy-editing can be accessed at
http://onlinelibrary.wiley.com/doi/10.1111/nrm.12129/full | null | 10.1111/nrm.12129 | null | q-bio.QM q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Modeling social-ecological systems is difficult due to the complexity of
ecosystems and of individual and collective human behavior. Key components of
the social-ecological system are often over-simplified or omitted. Generalized
modeling is a dynamical systems approach that can overcome some of these
challenges. It can rigorously analyze qualitative system dynamics such as
regime shifts despite incomplete knowledge of the model's constituent
processes. Here, we review generalized modeling and use a recent study on the
Baltic Sea cod fishery's boom and collapse to demonstrate its application to
modeling the dynamics of empirical social-ecological systems. These empirical
applications demand new methods of analysis suited to larger, more complicated
generalized models. Generalized modeling is a promising tool for rapidly
developing mathematically rigorous, process-based understanding of a
social-ecological system's dynamics despite limited knowledge of the system.
| [
{
"created": "Tue, 10 Mar 2015 10:15:23 GMT",
"version": "v1"
},
{
"created": "Wed, 24 May 2017 16:17:15 GMT",
"version": "v2"
}
] | 2017-05-25 | [
[
"Lade",
"Steven J.",
""
],
[
"Niiranen",
"Susa",
""
]
] | Modeling social-ecological systems is difficult due to the complexity of ecosystems and of individual and collective human behavior. Key components of the social-ecological system are often over-simplified or omitted. Generalized modeling is a dynamical systems approach that can overcome some of these challenges. It can rigorously analyze qualitative system dynamics such as regime shifts despite incomplete knowledge of the model's constituent processes. Here, we review generalized modeling and use a recent study on the Baltic Sea cod fishery's boom and collapse to demonstrate its application to modeling the dynamics of empirical social-ecological systems. These empirical applications demand new methods of analysis suited to larger, more complicated generalized models. Generalized modeling is a promising tool for rapidly developing mathematically rigorous, process-based understanding of a social-ecological system's dynamics despite limited knowledge of the system. |
2012.02831 | Aurelien Tellier | Wolfgang Stephan and Aur\'elien Tellier | Stochastic processes and host-parasite coevolution: linking
coevolutionary dynamics and DNA polymorphism data | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Between-species coevolution, and in particular antagonistic host-parasite
coevolution, is a major process shaping within-species diversity. In this paper
we investigate the role of various stochastic processes affecting the outcome
of the deterministic coevolutionary models. Specifically, we assess 1) the
impact of genetic drift and mutation on the maintenance of polymorphism at the
interacting loci, and 2) the change in neutral allele frequencies across the
genome of both coevolving species due to co-demographic population size
changes. We find that genetic drift decreases the likelihood to observe classic
balancing selection signatures, and that for most realistic values of the
coevolutionary parameters, balancing selection signatures cannot be seen at the
host loci. Further, we reveal that contrary to classic expectations, fast
changes in parasite population size due to eco-evo feedbacks can be tracked by
the allelic site-frequency spectrum measured at several time points. Changes in
host population size are, however, less pronounced and thus not observable.
Finally, we also review several understudied stochastic processes occurring in
host-parasite coevolution which are of importance to predict maintenance of
polymorphism at the underlying loci and the genome-wide nucleotide diversity of
host and parasite populations.
| [
{
"created": "Fri, 4 Dec 2020 20:10:50 GMT",
"version": "v1"
}
] | 2020-12-08 | [
[
"Stephan",
"Wolfgang",
""
],
[
"Tellier",
"Aurélien",
""
]
] | Between-species coevolution, and in particular antagonistic host-parasite coevolution, is a major process shaping within-species diversity. In this paper we investigate the role of various stochastic processes affecting the outcome of the deterministic coevolutionary models. Specifically, we assess 1) the impact of genetic drift and mutation on the maintenance of polymorphism at the interacting loci, and 2) the change in neutral allele frequencies across the genome of both coevolving species due to co-demographic population size changes. We find that genetic drift decreases the likelihood to observe classic balancing selection signatures, and that for most realistic values of the coevolutionary parameters, balancing selection signatures cannot be seen at the host loci. Further, we reveal that contrary to classic expectations, fast changes in parasite population size due to eco-evo feedbacks can be tracked by the allelic site-frequency spectrum measured at several time points. Changes in host population size are, however, less pronounced and thus not observable. Finally, we also review several understudied stochastic processes occurring in host-parasite coevolution which are of importance to predict maintenance of polymorphism at the underlying loci and the genome-wide nucleotide diversity of host and parasite populations. |
1905.08912 | Max Allen | Maximilian L. Allen, Nathan M. Roberts, Andrew S. Norton, Timothy R.
Van Deelen | Estimation of black bear abundance by management zone in Wisconsin | 1 table, 2 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Estimates of population abundance are fundamental to wildlife management and
conservation, but are difficult to obtain across large geographic scales and
for cryptic species. We used a state-space model with age-at-harvest data in a
Bayesian framework to model American black bear (Ursus americanus) abundance
and demographic parameters in four management zones in Wisconsin from
2011-2017. We had limited demographic data available from the population, and
relied upon a) the model, b) age-at-harvest data, and c) informative prior
distributions from a literature review. The estimated posterior means and
distributions for abundance and demographic parameters from our models were
reasonable for each management zone, and indicated a decreasing trend in zones
A and B, and a generally stable trend in zones C and D. The age-at-harvest data
updated the posterior distribution and means for initial population size,
harvest season survival, and non-harvest season survival, with a notable
increase in precision for the survival values. A strength of the model for
managers is the formalized process for providing biologically supported
information as prior distributions to transparently accommodate expert opinion
with measures of confidence when estimating wildlife populations, which can
then be updated by the age-at-harvest data and model structure. The integration
of prior information and age-at-harvest state-space models in a Bayesian
framework efficiently leverage all available information for making
zone-specific abundance estimates for the management of harvested species. This
may create more informative data for decision-makers when setting harvest
quotas, and could lead to more effective monitoring, conservation, and
management of cryptic carnivore species.
| [
{
"created": "Wed, 22 May 2019 01:06:20 GMT",
"version": "v1"
}
] | 2019-05-23 | [
[
"Allen",
"Maximilian L.",
""
],
[
"Roberts",
"Nathan M.",
""
],
[
"Norton",
"Andrew S.",
""
],
[
"Van Deelen",
"Timothy R.",
""
]
] | Estimates of population abundance are fundamental to wildlife management and conservation, but are difficult to obtain across large geographic scales and for cryptic species. We used a state-space model with age-at-harvest data in a Bayesian framework to model American black bear (Ursus americanus) abundance and demographic parameters in four management zones in Wisconsin from 2011-2017. We had limited demographic data available from the population, and relied upon a) the model, b) age-at-harvest data, and c) informative prior distributions from a literature review. The estimated posterior means and distributions for abundance and demographic parameters from our models were reasonable for each management zone, and indicated a decreasing trend in zones A and B, and a generally stable trend in zones C and D. The age-at-harvest data updated the posterior distribution and means for initial population size, harvest season survival, and non-harvest season survival, with a notable increase in precision for the survival values. A strength of the model for managers is the formalized process for providing biologically supported information as prior distributions to transparently accommodate expert opinion with measures of confidence when estimating wildlife populations, which can then be updated by the age-at-harvest data and model structure. The integration of prior information and age-at-harvest state-space models in a Bayesian framework efficiently leverage all available information for making zone-specific abundance estimates for the management of harvested species. This may create more informative data for decision-makers when setting harvest quotas, and could lead to more effective monitoring, conservation, and management of cryptic carnivore species. |
2107.08575 | Claire Miller | Claire Miller, Edmund Crampin, James Osborne | Multiscale modelling of desquamation in the interfollicular epidermis | null | PLOS Computational Biology 18(8): e1010368 (2022) | 10.1371/journal.pcbi.1010368 | null | q-bio.TO q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Maintenance of epidermal thickness is critical to the barrier function of the
skin. Decreased tissue thickness, specifically in the stratum corneum (the
outermost layer of the tissue), causes discomfort and inflammation, and is
related to several severe diseases of the tissue. In order to maintain both
stratum corneum thickness and overall tissue thickness it is necessary for the
system to balance cell proliferation and cell loss. Cell proliferation in the
epidermis occurs in the basal layer and causes constant upwards movement in the
tissue. Cell loss occurs when dead cells at the top of the tissue are lost to
the environment through a process called desquamation. Desquamation is thought
to occur through a gradual reduction in adhesion between cells, due to the
cleaving of adhesion proteins by enzymes, in the stratum corneum.
In this paper we will investigate combining a (mass action) subcellular model
of desquamation with a three dimensional (cell centre based) multicellular
model of the interfollicular epidermis to better understand maintenance of
epidermal thickness. These investigations show that hypothesised biological
models for the degradation of cell-cell adhesion from the literature are able
to provide a consistent rate of cell loss in the multicellular model. This loss
balances proliferation, and hence maintains a homeostatic tissue thickness.
Moreover, we find that multiple proliferative cell populations in the basal
layer can be represented by a single proliferative cell population, simplifying
investigations with this model.
The model is used to investigate a disorder (Netherton Syndrome) which
disrupts desquamation. The model shows how biochemical changes can cause
disruptions to the tissue, resulting in a reduced tissue thickness and
consequently diminishing the protective role of the tissue. A hypothetical
treatment result is also investigated. [ABR]
| [
{
"created": "Mon, 19 Jul 2021 01:43:52 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Aug 2021 04:17:54 GMT",
"version": "v2"
},
{
"created": "Mon, 12 Sep 2022 00:48:53 GMT",
"version": "v3"
}
] | 2022-09-13 | [
[
"Miller",
"Claire",
""
],
[
"Crampin",
"Edmund",
""
],
[
"Osborne",
"James",
""
]
] | Maintenance of epidermal thickness is critical to the barrier function of the skin. Decreased tissue thickness, specifically in the stratum corneum (the outermost layer of the tissue), causes discomfort and inflammation, and is related to several severe diseases of the tissue. In order to maintain both stratum corneum thickness and overall tissue thickness it is necessary for the system to balance cell proliferation and cell loss. Cell proliferation in the epidermis occurs in the basal layer and causes constant upwards movement in the tissue. Cell loss occurs when dead cells at the top of the tissue are lost to the environment through a process called desquamation. Desquamation is thought to occur through a gradual reduction in adhesion between cells, due to the cleaving of adhesion proteins by enzymes, in the stratum corneum. In this paper we will investigate combining a (mass action) subcellular model of desquamation with a three dimensional (cell centre based) multicellular model of the interfollicular epidermis to better understand maintenance of epidermal thickness. These investigations show that hypothesised biological models for the degradation of cell-cell adhesion from the literature are able to provide a consistent rate of cell loss in the multicellular model. This loss balances proliferation, and hence maintains a homeostatic tissue thickness. Moreover, we find that multiple proliferative cell populations in the basal layer can be represented by a single proliferative cell population, simplifying investigations with this model. The model is used to investigate a disorder (Netherton Syndrome) which disrupts desquamation. The model shows how biochemical changes can cause disruptions to the tissue, resulting in a reduced tissue thickness and consequently diminishing the protective role of the tissue. A hypothetical treatment result is also investigated. [ABR] |
2110.15400 | Beth Martin | Beth K. Martin, Chengxiang Qiu, Eva Nichols, Melissa Phung, Rula
Green-Gladden, Sanjay Srivatsan, Ronnie Blecher-Gonen, Brian J. Beliveau,
Cole Trapnell, Junyue Cao, Jay Shendure | An optimized protocol for single cell transcriptional profiling by
combinatorial indexing | fixed a couple errors | null | null | null | q-bio.GN | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful
method for recovering gene expression data from an exponentially scalable
number of individual cells or nuclei. However, sci-RNA-seq is a complex
protocol that has historically exhibited variable performance on different
tissues, as well as lower sensitivity than alternative methods. Here we report
a simplified, optimized version of the three-level sci-RNA-seq protocol that is
faster, higher yield, more robust, and more sensitive, than the original
sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or
less. We showcase the optimized protocol via whole organism analysis of an
E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally,
we introduce a "tiny sci-*" protocol for experiments where input is extremely
limited.
| [
{
"created": "Thu, 28 Oct 2021 19:01:59 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Nov 2021 19:55:28 GMT",
"version": "v2"
},
{
"created": "Mon, 6 Dec 2021 17:57:58 GMT",
"version": "v3"
},
{
"created": "Thu, 6 Jan 2022 17:22:51 GMT",
"version": "v4"
}
] | 2022-01-07 | [
[
"Martin",
"Beth K.",
""
],
[
"Qiu",
"Chengxiang",
""
],
[
"Nichols",
"Eva",
""
],
[
"Phung",
"Melissa",
""
],
[
"Green-Gladden",
"Rula",
""
],
[
"Srivatsan",
"Sanjay",
""
],
[
"Blecher-Gonen",
"Ronnie",
""
],
[
"Beliveau",
"Brian J.",
""
],
[
"Trapnell",
"Cole",
""
],
[
"Cao",
"Junyue",
""
],
[
"Shendure",
"Jay",
""
]
] | Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here we report a simplified, optimized version of the three-level sci-RNA-seq protocol that is faster, higher yield, more robust, and more sensitive, than the original sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or less. We showcase the optimized protocol via whole organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a "tiny sci-*" protocol for experiments where input is extremely limited. |
1606.00054 | Ronan M.T. Fleming Dr | Ding Ma, Laurence Yang, Ronan M. T. Fleming, Ines Thiele, Bernhard O.
Palsson and Michael A. Saunders | Reliable and efficient solution of genome-scale models of Metabolism and
macromolecular Expression | 14 pages, 1 figures | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Constraint-Based Reconstruction and Analysis (COBRA) is currently the only
methodology that permits integrated modeling of Metabolism and macromolecular
Expression (ME) at genome-scale. Linear optimization computes steady-state flux
solutions to ME models, but flux values are spread over many orders of
magnitude. Standard double-precision solvers may return inaccurate solutions or
report that no solution exists. Exact simplex solvers are extremely slow and
hence not practical for ME models that currently have 70,000 constraints and
variables and will grow larger. We have developed a quadruple-precision version
of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ)
involving Double and Quad MINOS that achieves efficiency and reliability for ME
models. DQQ enables extensive use of large, multiscale, linear and nonlinear
models in systems biology and many other applications.
| [
{
"created": "Tue, 31 May 2016 21:38:04 GMT",
"version": "v1"
},
{
"created": "Mon, 26 Sep 2016 21:02:08 GMT",
"version": "v2"
}
] | 2016-09-28 | [
[
"Ma",
"Ding",
""
],
[
"Yang",
"Laurence",
""
],
[
"Fleming",
"Ronan M. T.",
""
],
[
"Thiele",
"Ines",
""
],
[
"Palsson",
"Bernhard O.",
""
],
[
"Saunders",
"Michael A.",
""
]
] | Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers are extremely slow and hence not practical for ME models that currently have 70,000 constraints and variables and will grow larger. We have developed a quadruple-precision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves efficiency and reliability for ME models. DQQ enables extensive use of large, multiscale, linear and nonlinear models in systems biology and many other applications. |
1506.05647 | Luiz Henrique Bertolucci | L. H. B. Bertolucci, E. F. Costa, V. A. Oliveira, D. Karam | A unified model for wild resistance dynamics and weed control using
herbicide | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A major issue in the modelling of weed resistance to herbicide lies in
effectively handling the wild dynamics, that is, the allele frequency prior to
the herbicide application, and in particular when starting to use the
herbicide. The wild allele frequency is a key variable as the resistance
evolution is highly sensitive to it, moreover it is extremely difficult to
measure in the agricultural field. In this paper we propose a model for weed
control that handles the allele frequency in a direct manner, grounded on the
very dynamics of the weed life cycle, with no need of a priori distributions
nor the use of the Hardy-Weinberg equilibrium. The proposed model is individual
based, stochastic, and considers some phenomena like the relative fitnesses and
mutation that are prominent in the resistance dynamics without herbicide. A
case study is presented for the herbicide nicosulfuron in a field with the weed
Bidens pilosa. Another two models having a standard deterministic dynamics are
compared with ours in terms of the initial allele frequency, its time
evolution, and the resistance visualization in the field, indicating that the
proposed model is effective to provide more realistic simulations for the weed
resistance.
| [
{
"created": "Thu, 18 Jun 2015 12:21:50 GMT",
"version": "v1"
}
] | 2015-06-19 | [
[
"Bertolucci",
"L. H. B.",
""
],
[
"Costa",
"E. F.",
""
],
[
"Oliveira",
"V. A.",
""
],
[
"Karam",
"D.",
""
]
] | A major issue in the modelling of weed resistance to herbicide lies in effectively handling the wild dynamics, that is, the allele frequency prior to the herbicide application, and in particular when starting to use the herbicide. The wild allele frequency is a key variable as the resistance evolution is highly sensitive to it, moreover it is extremely difficult to measure in the agricultural field. In this paper we propose a model for weed control that handles the allele frequency in a direct manner, grounded on the very dynamics of the weed life cycle, with no need of a priori distributions nor the use of the Hardy-Weinberg equilibrium. The proposed model is individual based, stochastic, and considers some phenomena like the relative fitnesses and mutation that are prominent in the resistance dynamics without herbicide. A case study is presented for the herbicide nicosulfuron in a field with the weed Bidens pilosa. Another two models having a standard deterministic dynamics are compared with ours in terms of the initial allele frequency, its time evolution, and the resistance visualization in the field, indicating that the proposed model is effective to provide more realistic simulations for the weed resistance. |
1404.6453 | Gabriel Kreiman | Thomas Miconi, Laura Groomes, Gabriel Kreiman | A normalization model of visual search predicts single trial human
fixations in an object search task | 8 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | When searching for an object in a scene, how does the brain decide where to
look next? Theories of visual search suggest the existence of a global
attentional map, computed by integrating bottom-up visual information with
top-down, target-specific signals. Where, when and how this integration is
performed remains unclear. Here we describe a simple mechanistic model of
visual search that is consistent with neurophysiological and neuroanatomical
constraints, can localize target objects in complex scenes, and predicts
single-trial human behavior in a search task among complex objects. This model
posits that target-specific modulation is applied at every point of a
retinotopic area selective for complex visual features and implements local
normalization through divisive inhibition. The combination of multiplicative
modulation and divisive normalization creates an attentional map in which
aggregate activity at any location tracks the correlation between input and
target features, with relative and controllable independence from bottom-up
saliency. We first show that this model can localize objects in both composite
images and natural scenes and demonstrate the importance of normalization for
successful search. We next show that this model can predict human fixations on
single trials, including error and target-absent trials. We argue that this
simple model captures non-trivial properties of the attentional system that
guides visual search in humans.
| [
{
"created": "Fri, 25 Apr 2014 15:16:42 GMT",
"version": "v1"
}
] | 2014-04-28 | [
[
"Miconi",
"Thomas",
""
],
[
"Groomes",
"Laura",
""
],
[
"Kreiman",
"Gabriel",
""
]
] | When searching for an object in a scene, how does the brain decide where to look next? Theories of visual search suggest the existence of a global attentional map, computed by integrating bottom-up visual information with top-down, target-specific signals. Where, when and how this integration is performed remains unclear. Here we describe a simple mechanistic model of visual search that is consistent with neurophysiological and neuroanatomical constraints, can localize target objects in complex scenes, and predicts single-trial human behavior in a search task among complex objects. This model posits that target-specific modulation is applied at every point of a retinotopic area selective for complex visual features and implements local normalization through divisive inhibition. The combination of multiplicative modulation and divisive normalization creates an attentional map in which aggregate activity at any location tracks the correlation between input and target features, with relative and controllable independence from bottom-up saliency. We first show that this model can localize objects in both composite images and natural scenes and demonstrate the importance of normalization for successful search. We next show that this model can predict human fixations on single trials, including error and target-absent trials. We argue that this simple model captures non-trivial properties of the attentional system that guides visual search in humans. |
0711.2497 | Pankaj Mehta | Pankaj Mehta, Ranjan Mukhopadhyay, Ned S. Wingreen | Exponential sensitivity of noise-driven switching in genetic networks | 5 pages, 3 figures | Physical Biology 5, 026005 (2008) | 10.1088/1478-3975/5/2/026005 | null | q-bio.MN cond-mat.stat-mech q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cells are known to utilize biochemical noise to probabilistically switch
between distinct gene expression states. We demonstrate that such noise-driven
switching is dominated by tails of probability distributions and is therefore
exponentially sensitive to changes in physiological parameters such as
transcription and translation rates. However, provided mRNA lifetimes are
short, switching can still be accurately simulated using protein-only models of
gene expression. Exponential sensitivity limits the robustness of noise-driven
switching, suggesting cells may use other mechanisms in order to switch
reliably.
| [
{
"created": "Thu, 15 Nov 2007 20:04:50 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Sep 2008 21:27:06 GMT",
"version": "v2"
}
] | 2009-11-13 | [
[
"Mehta",
"Pankaj",
""
],
[
"Mukhopadhyay",
"Ranjan",
""
],
[
"Wingreen",
"Ned S.",
""
]
] | Cells are known to utilize biochemical noise to probabilistically switch between distinct gene expression states. We demonstrate that such noise-driven switching is dominated by tails of probability distributions and is therefore exponentially sensitive to changes in physiological parameters such as transcription and translation rates. However, provided mRNA lifetimes are short, switching can still be accurately simulated using protein-only models of gene expression. Exponential sensitivity limits the robustness of noise-driven switching, suggesting cells may use other mechanisms in order to switch reliably. |
1809.03393 | Nikolai Zolotykh | Alena I. Kalyakulina, Igor I. Yusipov, Victor A. Moskalenko, Alexander
V. Nikolskiy, Konstantin A. Kosonogov, Grigory V. Osipov, Nikolai Yu.
Zolotykh, Mikhail V. Ivanchenko | LUDB: a new open-access validation tool for electrocardiogram
delineation algorithms | 11 pages, 10 figures, 6 tables | null | null | null | q-bio.QM eess.SP physics.med-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We report Lobachevsky University Database (LUDB) of ECG signals, an open tool
for validating ECG delineation algorithms, that is superior to the existing
publicly available data bases in several aspects. LUDB contains 200 recordings
of 10-second 12-lead electrocardiograms (ECG) from different subjects,
representative of a variety of signal morphologies. The boundaries and peaks of
QRS complexes and P and T waves are manually annotated by cardiologists for all
recordings and independently for each lead, and all records received an expert
classification by abnormalities. We present a case study for the recently
proposed wavelet-based algorithm and the broadly used ecg-kit tool, and
demonstrate the advantage of multi-lead ECG data analysis. LUDB contributes to
the diversity of public databases employed in developing and validating novel
ECG analysis algorithms, including the most advanced based on deep learning
neural networks.
| [
{
"created": "Thu, 30 Aug 2018 16:05:16 GMT",
"version": "v1"
},
{
"created": "Tue, 18 Sep 2018 20:27:57 GMT",
"version": "v2"
},
{
"created": "Fri, 28 Aug 2020 16:39:07 GMT",
"version": "v3"
},
{
"created": "Wed, 16 Sep 2020 09:08:54 GMT",
"version": "v4"
}
] | 2020-09-17 | [
[
"Kalyakulina",
"Alena I.",
""
],
[
"Yusipov",
"Igor I.",
""
],
[
"Moskalenko",
"Victor A.",
""
],
[
"Nikolskiy",
"Alexander V.",
""
],
[
"Kosonogov",
"Konstantin A.",
""
],
[
"Osipov",
"Grigory V.",
""
],
[
"Zolotykh",
"Nikolai Yu.",
""
],
[
"Ivanchenko",
"Mikhail V.",
""
]
] | We report Lobachevsky University Database (LUDB) of ECG signals, an open tool for validating ECG delineation algorithms, that is superior to the existing publicly available data bases in several aspects. LUDB contains 200 recordings of 10-second 12-lead electrocardiograms (ECG) from different subjects, representative of a variety of signal morphologies. The boundaries and peaks of QRS complexes and P and T waves are manually annotated by cardiologists for all recordings and independently for each lead, and all records received an expert classification by abnormalities. We present a case study for the recently proposed wavelet-based algorithm and the broadly used ecg-kit tool, and demonstrate the advantage of multi-lead ECG data analysis. LUDB contributes to the diversity of public databases employed in developing and validating novel ECG analysis algorithms, including the most advanced based on deep learning neural networks. |
1604.08314 | Jonathan Harrison | Jonathan U. Harrison, Christian A. Yates | A hybrid algorithm for coupling PDE and compartment-based dynamics | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Stochastic simulation methods can be applied successfully to model exact
spatio-temporally resolved reaction-diffusion systems. However, in many cases,
these methods can quickly become extremely computationally intensive with
increasing particle numbers. An alternative description of many of these
systems can be derived in the diffusive limit as a deterministic, continuum
system of partial differential equations. Although the numerical solution of
such partial differential equations is, in general, much more efficient than
the full stochastic simulation, the deterministic continuum description is
generally not valid when copy numbers are low and stochastic effects dominate.
Therefore, to take advantage of the benefits of both of these types of models,
each of which may be appropriate in different parts of a spatial domain, we
have developed an algorithm that can be used to couple these two types of model
together. This hybrid coupling algorithm uses an overlap region between the two
modelling regimes. By coupling fluxes at one end of the interface and using a
concentration-matching condition at the other end, we ensure that mass is
appropriately transferred between PDE- and compartment-based regimes. Our
methodology gives notable reductions in simulation time in comparison with
using a fully stochastic model, whilst maintaining the important stochastic
features of the system and providing detail in appropriate areas of the domain.
We test our hybrid methodology robustly by applying it to several biologically
motivated problems including diffusion and morphogen gradient formation. Our
analysis shows that the resulting error is small, unbiased and does not grow
over time.
| [
{
"created": "Thu, 28 Apr 2016 05:55:22 GMT",
"version": "v1"
}
] | 2016-04-29 | [
[
"Harrison",
"Jonathan U.",
""
],
[
"Yates",
"Christian A.",
""
]
] | Stochastic simulation methods can be applied successfully to model exact spatio-temporally resolved reaction-diffusion systems. However, in many cases, these methods can quickly become extremely computationally intensive with increasing particle numbers. An alternative description of many of these systems can be derived in the diffusive limit as a deterministic, continuum system of partial differential equations. Although the numerical solution of such partial differential equations is, in general, much more efficient than the full stochastic simulation, the deterministic continuum description is generally not valid when copy numbers are low and stochastic effects dominate. Therefore, to take advantage of the benefits of both of these types of models, each of which may be appropriate in different parts of a spatial domain, we have developed an algorithm that can be used to couple these two types of model together. This hybrid coupling algorithm uses an overlap region between the two modelling regimes. By coupling fluxes at one end of the interface and using a concentration-matching condition at the other end, we ensure that mass is appropriately transferred between PDE- and compartment-based regimes. Our methodology gives notable reductions in simulation time in comparison with using a fully stochastic model, whilst maintaining the important stochastic features of the system and providing detail in appropriate areas of the domain. We test our hybrid methodology robustly by applying it to several biologically motivated problems including diffusion and morphogen gradient formation. Our analysis shows that the resulting error is small, unbiased and does not grow over time. |
1206.3108 | Alfonso P\'erez-Escudero | Sara Arganda, Alfonso P\'erez-Escudero, Gonzalo G. de Polavieja | A common rule for decision-making in animal collectives across species | null | Proc Natl Acad Sci USA vol. 109 no. 50 20508-20513 (2012) | 10.1073/pnas.1210664109 | null | q-bio.PE q-bio.NC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A diversity of decision-making systems has been observed in animal
collectives. In some species, choices depend on the differences of the numbers
of animals that have chosen each of the available options, while in other
species on the relative differences (a behavior known as Weber's law) or follow
more complex rules. We here show that this diversity of decision systems
corresponds to a single rule of decision-making in collectives. We first
obtained a decision rule based on Bayesian estimation that uses the information
provided by the behaviors of the other individuals to improve the estimation of
the structure of the world. We then tested this rule in decision experiments
using zebrafish (Danio rerio), and in existing rich datasets of argentine ants
(Linepithema humile) and sticklebacks (Gasterosteus aculeatus), showing that a
unified model across species can quantitatively explain the diversity of
decision systems. Further, these results show that the different counting
systems used by animals, including humans, can emerge from the common principle
of using social information to make good decisions.
| [
{
"created": "Thu, 14 Jun 2012 13:57:28 GMT",
"version": "v1"
},
{
"created": "Mon, 8 Oct 2012 17:56:38 GMT",
"version": "v2"
},
{
"created": "Wed, 12 Dec 2012 07:00:59 GMT",
"version": "v3"
}
] | 2012-12-13 | [
[
"Arganda",
"Sara",
""
],
[
"Pérez-Escudero",
"Alfonso",
""
],
[
"de Polavieja",
"Gonzalo G.",
""
]
] | A diversity of decision-making systems has been observed in animal collectives. In some species, choices depend on the differences of the numbers of animals that have chosen each of the available options, while in other species on the relative differences (a behavior known as Weber's law) or follow more complex rules. We here show that this diversity of decision systems corresponds to a single rule of decision-making in collectives. We first obtained a decision rule based on Bayesian estimation that uses the information provided by the behaviors of the other individuals to improve the estimation of the structure of the world. We then tested this rule in decision experiments using zebrafish (Danio rerio), and in existing rich datasets of argentine ants (Linepithema humile) and sticklebacks (Gasterosteus aculeatus), showing that a unified model across species can quantitatively explain the diversity of decision systems. Further, these results show that the different counting systems used by animals, including humans, can emerge from the common principle of using social information to make good decisions. |
2209.01060 | Chao Wang | Chao Wang | The path integral formula for the stochastic evolutionary game dynamics
in the Moran process | 14 pages, 2 figures | null | null | null | q-bio.PE math-ph math.MP physics.app-ph | http://creativecommons.org/licenses/by/4.0/ | The Moran process is one of an basic mathematical structure in the
evolutionary game theory. In this work, we introduce the formulation of the
path integral approach for evolutionary game theory based on the Moran process.
We derive the transition probability by the path integral from the initial
state to the final state with updating rule of the Moran process. In this
framework, the transition probability is the sum of all the evolutionary paths.
The path integral formula of the transition probability maybe expected to be a
new mathematical tool to explore the stochastic game evolutionary dynamics.
| [
{
"created": "Fri, 2 Sep 2022 13:52:20 GMT",
"version": "v1"
}
] | 2022-09-05 | [
[
"Wang",
"Chao",
""
]
] | The Moran process is one of an basic mathematical structure in the evolutionary game theory. In this work, we introduce the formulation of the path integral approach for evolutionary game theory based on the Moran process. We derive the transition probability by the path integral from the initial state to the final state with updating rule of the Moran process. In this framework, the transition probability is the sum of all the evolutionary paths. The path integral formula of the transition probability maybe expected to be a new mathematical tool to explore the stochastic game evolutionary dynamics. |
q-bio/0506030 | Pierre Sens | Pierre Sens and Matthew S. Turner | Budded membrane microdomains as regulators for cellular tension | http://hogarth.pct.espci.fr/~pierre/ | null | null | null | q-bio.SC cond-mat.soft | null | We propose a mechanism for mechanical regulation at the membrane of living
cells, based on the exchange of membrane area between the cell membrane and a
membrane reservoir. The reservoir is composed of invaginated membrane
microdomains which are liable to flatten upon increase of membrane strain,
effectively controlling membrane tension. We show that the domain shape
transition is first order, allowing for coexistence between flat and
invaginated domains. During coexistence, the membrane tension is controlled by
the domains elasticity and by the kinetics of the shape transition. We show
that the tension of the plasma membrane of living cells is inherently transient
and dynamical, and that valuable insights into the organization of the cell
membrane can be obtained by studying the variation of the cell membrane tension
upon mechanical perturbation.
| [
{
"created": "Tue, 21 Jun 2005 06:58:41 GMT",
"version": "v1"
},
{
"created": "Mon, 19 Sep 2005 23:56:37 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Sens",
"Pierre",
""
],
[
"Turner",
"Matthew S.",
""
]
] | We propose a mechanism for mechanical regulation at the membrane of living cells, based on the exchange of membrane area between the cell membrane and a membrane reservoir. The reservoir is composed of invaginated membrane microdomains which are liable to flatten upon increase of membrane strain, effectively controlling membrane tension. We show that the domain shape transition is first order, allowing for coexistence between flat and invaginated domains. During coexistence, the membrane tension is controlled by the domains elasticity and by the kinetics of the shape transition. We show that the tension of the plasma membrane of living cells is inherently transient and dynamical, and that valuable insights into the organization of the cell membrane can be obtained by studying the variation of the cell membrane tension upon mechanical perturbation. |
2402.07012 | Gabriel Calvo | Gabriel F. Calvo, Bel\'en Cort\'es-Llanos, Juan Belmonte-Beitia, Gorka
Salas and \'Angel Ayuso-Sacido | Modelling the role of flux density and coating on nanoparticle
internalization by tumor cells under centrifugation | 39 pages, 9 figures. Manuscript published in Applied Mathematical
Modelling 78, 98-116 (2020) | Applied Mathematical Modelling 78, 98-116 (2020) | 10.1016/j.apm.2019.10.005 | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Nanoparticle (NP)-based applications are becoming increasingly important in
the biomedical field. However, understanding the interactions of NPs with
biofluids and cells is a major issue in order to develop novel approaches aimed
at boosting their internalization and, therefore, their translation into the
clinic. To this end, we put forward a transport mathematical model to describe
the spatio-temporal dynamics of iron oxide NPs and their interaction with cells
under moderate centrifugation. Our numerical simulations allowed us to quantify
the relevance of the flux density as one of the unavoidable key features
driving NPs interaction with the media as well as for cell internalization
processes. These findings will help to increase the efficiency of cell
labelling for biomedical applications.
| [
{
"created": "Sat, 10 Feb 2024 18:19:51 GMT",
"version": "v1"
}
] | 2024-02-13 | [
[
"Calvo",
"Gabriel F.",
""
],
[
"Cortés-Llanos",
"Belén",
""
],
[
"Belmonte-Beitia",
"Juan",
""
],
[
"Salas",
"Gorka",
""
],
[
"Ayuso-Sacido",
"Ángel",
""
]
] | Nanoparticle (NP)-based applications are becoming increasingly important in the biomedical field. However, understanding the interactions of NPs with biofluids and cells is a major issue in order to develop novel approaches aimed at boosting their internalization and, therefore, their translation into the clinic. To this end, we put forward a transport mathematical model to describe the spatio-temporal dynamics of iron oxide NPs and their interaction with cells under moderate centrifugation. Our numerical simulations allowed us to quantify the relevance of the flux density as one of the unavoidable key features driving NPs interaction with the media as well as for cell internalization processes. These findings will help to increase the efficiency of cell labelling for biomedical applications. |
1810.07367 | Ryan Renslow | Jamie R. Nu\~nez, Sean M. Colby, Dennis G. Thomas, Malak M. Tfaily,
Nikola Tolic, Elin M. Ulrich, Jon R. Sobus, Thomas O. Metz, Justin G.
Teeguarden, and Ryan S. Renslow | Advancing Standards-Free Methods for the Identification of Small
Molecules in Complex Samples | null | null | null | null | q-bio.BM q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The current gold standard for unambiguous identification in metabolomics
analysis is based on comparing two or more orthogonal properties from the
analysis of authentic, pure reference materials (standards) to experimental
data acquired in the same laboratory with the same analytical methods. This
represents a significant limitation for comprehensive chemical identification
of small molecules in complex samples since this process is time-consuming and
costly, and the majority of molecules are not yet represented by standards,
leading to a need for standards-free identification. To address this need, we
are advancing chemical property calculations and developing multi-attribute
scoring and matching algorithms to utilize data from multiple analytical
platforms through the utilization and creation of the in silico Chemical
Library Engine (ISiCLE) and the Multi-Attribute Matching Engine (MAME). Here,
we describe our results in a blinded analysis of synthetic chemical mixtures as
part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis
Collaborative Trial (ENTACT). The blinded false negative rate (FNR), false
discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For
high confidence identifications, the FDR was 35%. After unblinding of the
sample compositions, we improved our approach by optimizing the scoring
parameters used to increase confidence. The final FNR, FDR, and accuracy were
67%, 53%, and 96%, respectively. For high confidence identifications, the FDR
was 10%. This study demonstrates that standards-free small molecule
identification and multi-attribute matching methods can significantly reduce
reliance on standards.
| [
{
"created": "Wed, 17 Oct 2018 03:08:41 GMT",
"version": "v1"
}
] | 2018-10-18 | [
[
"Nuñez",
"Jamie R.",
""
],
[
"Colby",
"Sean M.",
""
],
[
"Thomas",
"Dennis G.",
""
],
[
"Tfaily",
"Malak M.",
""
],
[
"Tolic",
"Nikola",
""
],
[
"Ulrich",
"Elin M.",
""
],
[
"Sobus",
"Jon R.",
""
],
[
"Metz",
"Thomas O.",
""
],
[
"Teeguarden",
"Justin G.",
""
],
[
"Renslow",
"Ryan S.",
""
]
] | The current gold standard for unambiguous identification in metabolomics analysis is based on comparing two or more orthogonal properties from the analysis of authentic, pure reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples since this process is time-consuming and costly, and the majority of molecules are not yet represented by standards, leading to a need for standards-free identification. To address this need, we are advancing chemical property calculations and developing multi-attribute scoring and matching algorithms to utilize data from multiple analytical platforms through the utilization and creation of the in silico Chemical Library Engine (ISiCLE) and the Multi-Attribute Matching Engine (MAME). Here, we describe our results in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT). The blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high confidence identifications, the FDR was 35%. After unblinding of the sample compositions, we improved our approach by optimizing the scoring parameters used to increase confidence. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high confidence identifications, the FDR was 10%. This study demonstrates that standards-free small molecule identification and multi-attribute matching methods can significantly reduce reliance on standards. |
2304.01356 | Robert Corless | Chris Brimacombe and Robert M. Corless and Mair Zamir | Elliptic cross sections in blood flow regulation | 31 pages, 17 figures | null | null | null | q-bio.TO cs.NA math.NA | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Arterial deformations arise in blood flow when surrounding tissue invades the
space available for a blood vessel to maintain its circular cross section, the
most immediate effects being a reduction in blood flow and redistribution of
shear stress. Here we consider deformations from circular to elliptic cross
sections. Solution of this problem in steady flow is fairly straightforward.
The focus in the present paper is on pulsatile flow where the change from
circular to elliptic cross sections is associated with a transition in the
character of the equations governing the flow from Bessel to Mathieu equations.
The study of this problem has been hampered in the past because of difficulties
involved in the solution of the governing equations. In the present study we
describe methods we have used to overcome some of these difficulties and
present a comprehensive set of results based on these methods. In particular,
vessel deformation is examined under two different conditions relevant to blood
flow regulation: (i) keeping cross sectional area constant and (ii) keeping
cross sectional circumference constant. The results provide an important
context for the mechanism of neurovascular control of blood flow under the
pathological conditions of vessel deformation.
| [
{
"created": "Thu, 19 Jan 2023 21:57:51 GMT",
"version": "v1"
}
] | 2023-04-05 | [
[
"Brimacombe",
"Chris",
""
],
[
"Corless",
"Robert M.",
""
],
[
"Zamir",
"Mair",
""
]
] | Arterial deformations arise in blood flow when surrounding tissue invades the space available for a blood vessel to maintain its circular cross section, the most immediate effects being a reduction in blood flow and redistribution of shear stress. Here we consider deformations from circular to elliptic cross sections. Solution of this problem in steady flow is fairly straightforward. The focus in the present paper is on pulsatile flow where the change from circular to elliptic cross sections is associated with a transition in the character of the equations governing the flow from Bessel to Mathieu equations. The study of this problem has been hampered in the past because of difficulties involved in the solution of the governing equations. In the present study we describe methods we have used to overcome some of these difficulties and present a comprehensive set of results based on these methods. In particular, vessel deformation is examined under two different conditions relevant to blood flow regulation: (i) keeping cross sectional area constant and (ii) keeping cross sectional circumference constant. The results provide an important context for the mechanism of neurovascular control of blood flow under the pathological conditions of vessel deformation. |
q-bio/0512036 | Jose Vilar | Leonor Saiz, J. Miguel Rubi, and Jose M. G. Vilar | Inferring the in vivo looping properties of DNA | 20 pages, 4 figures | Proc. Natl. Acad. Sci. USA 102, 17642-17645 (2005) | 10.1073/pnas.0505693102 | null | q-bio.BM cond-mat.soft physics.bio-ph q-bio.QM q-bio.SC | null | The free energy of looping DNA by proteins and protein complexes determines
to what extent distal DNA sites can affect each other. We inferred its in vivo
value through a combined computational-experimental approach for different
lengths of the loop and found that, in addition to the intrinsic periodicity of
the DNA double helix, the free energy has an oscillatory component with about
half the helical period. Moreover, the oscillations have such an amplitude that
the effects of regulatory molecules become strongly dependent on their precise
DNA positioning and yet easily tunable by their cooperative interactions. These
unexpected results can confer to the physical properties of DNA a more
prominent role at shaping the properties of gene regulation than previously
thought.
| [
{
"created": "Tue, 20 Dec 2005 00:52:51 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Saiz",
"Leonor",
""
],
[
"Rubi",
"J. Miguel",
""
],
[
"Vilar",
"Jose M. G.",
""
]
] | The free energy of looping DNA by proteins and protein complexes determines to what extent distal DNA sites can affect each other. We inferred its in vivo value through a combined computational-experimental approach for different lengths of the loop and found that, in addition to the intrinsic periodicity of the DNA double helix, the free energy has an oscillatory component with about half the helical period. Moreover, the oscillations have such an amplitude that the effects of regulatory molecules become strongly dependent on their precise DNA positioning and yet easily tunable by their cooperative interactions. These unexpected results can confer to the physical properties of DNA a more prominent role at shaping the properties of gene regulation than previously thought. |
1809.00759 | Angus McLure | Angus McLure, Archie C. A. Clements, Martyn Kirk, Kathryn Glass | Modelling diverse sources of Clostridium difficile in the community:
importance of animals, infants and asymptomatic carriers | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Clostridium difficile infections (CDIs) affect patients in hospitals and in
the community, but the relative importance of transmission in each setting is
unknown. We developed a mathematical model of C. difficile transmission in a
hospital and surrounding community that included infants, adults, and
transmission from animal reservoirs. We assessed the role of these transmission
routes in maintaining disease and evaluated the recommended classification
system for hospital and community-acquired CDIs. The reproduction number in the
hospital was <1 (range: 0.16-0.46) for all scenarios. Outside the hospital, the
reproduction number was >1 for nearly all scenarios without transmission from
animal reservoirs (range: 1.0-1.34). However, the reproduction number for the
human population was <1 if a minority (>3.5-26.0%) of human exposures
originated from animal reservoirs. Symptomatic adults accounted for <10%
transmission in the community. Under conservative assumptions, infants
accounted for 17% of community transmission. An estimated 33-40% of
community-acquired cases were reported but 28-39% of these reported cases were
misclassified as hospital-acquired by recommended definitions. Transmission
could be plausibly sustained by asymptomatically colonized adults and infants
in the community or exposure to animal reservoirs, but not hospital
transmission alone. Underreporting of community-onset cases and systematic
misclassification underplays the role of community transmission.
| [
{
"created": "Tue, 4 Sep 2018 00:54:37 GMT",
"version": "v1"
}
] | 2018-09-05 | [
[
"McLure",
"Angus",
""
],
[
"Clements",
"Archie C. A.",
""
],
[
"Kirk",
"Martyn",
""
],
[
"Glass",
"Kathryn",
""
]
] | Clostridium difficile infections (CDIs) affect patients in hospitals and in the community, but the relative importance of transmission in each setting is unknown. We developed a mathematical model of C. difficile transmission in a hospital and surrounding community that included infants, adults, and transmission from animal reservoirs. We assessed the role of these transmission routes in maintaining disease and evaluated the recommended classification system for hospital and community-acquired CDIs. The reproduction number in the hospital was <1 (range: 0.16-0.46) for all scenarios. Outside the hospital, the reproduction number was >1 for nearly all scenarios without transmission from animal reservoirs (range: 1.0-1.34). However, the reproduction number for the human population was <1 if a minority (>3.5-26.0%) of human exposures originated from animal reservoirs. Symptomatic adults accounted for <10% transmission in the community. Under conservative assumptions, infants accounted for 17% of community transmission. An estimated 33-40% of community-acquired cases were reported but 28-39% of these reported cases were misclassified as hospital-acquired by recommended definitions. Transmission could be plausibly sustained by asymptomatically colonized adults and infants in the community or exposure to animal reservoirs, but not hospital transmission alone. Underreporting of community-onset cases and systematic misclassification underplays the role of community transmission. |
2003.12457 | Daniele Lanteri | D.Lanteri, D.Carco' and P.Castorina | How macroscopic laws describe complex dynamics: asymptomatic population
and CoviD-19 spreading | null | International Journal of Modern Physics CVol. 31, No. 08, 2050112
(2020) | 10.1142/S0129183120501120 | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Macroscopic growth laws, solutions of mean field equations, describe in an
effective way an underlying complex dynamics. They are applied to study the
spreading of infections, as in the case of CoviD-19, where the counting of the
cumulated number $N(t)$ of detected infected individuals is a generally
accepted, coarse-grain, variable to understand the epidemic phase. However
$N(t)$ does not take into account the unknown number of asymptomatic, not
detected, cases $A(t)$. Therefore, the question arises if the observed time
series of data of $N(t)$ is a reliable tool for monitoring the evolution of the
infectious disease. We study a system of coupled differential equations which
includes the dynamics of the spreading among symptomatic and asymptomatic
individuals and the strong containment effects due to the social isolation. The
solution is therefore compared with a macroscopic law for the population $N(t)$
coming from a single, non-linear, differential equation with no explicit
reference to $A(t)$, showing the equivalence of the two methods. Indeed, $N(t)$
takes into account a more complex and detailed population dynamics which
permits the evaluation of the number of asymptomatic individuals also. The
model is then applied to Covid-19 spreading in Italy where a transition from an
exponential behavior to a Gompertz growth for $N(t)$ has been observed in more
recent data. Then the information contained in the data analysis of $N(t)$ is
reliable to understand the epidemic phase, although it does not describe the
total infected population. The asymptomatic population is larger than the
symptomatic one in the fast growth phase of the spreading.
| [
{
"created": "Fri, 27 Mar 2020 15:03:38 GMT",
"version": "v1"
},
{
"created": "Sun, 19 Apr 2020 09:53:05 GMT",
"version": "v2"
}
] | 2020-12-01 | [
[
"Lanteri",
"D.",
""
],
[
"Carco'",
"D.",
""
],
[
"Castorina",
"P.",
""
]
] | Macroscopic growth laws, solutions of mean field equations, describe in an effective way an underlying complex dynamics. They are applied to study the spreading of infections, as in the case of CoviD-19, where the counting of the cumulated number $N(t)$ of detected infected individuals is a generally accepted, coarse-grain, variable to understand the epidemic phase. However $N(t)$ does not take into account the unknown number of asymptomatic, not detected, cases $A(t)$. Therefore, the question arises if the observed time series of data of $N(t)$ is a reliable tool for monitoring the evolution of the infectious disease. We study a system of coupled differential equations which includes the dynamics of the spreading among symptomatic and asymptomatic individuals and the strong containment effects due to the social isolation. The solution is therefore compared with a macroscopic law for the population $N(t)$ coming from a single, non-linear, differential equation with no explicit reference to $A(t)$, showing the equivalence of the two methods. Indeed, $N(t)$ takes into account a more complex and detailed population dynamics which permits the evaluation of the number of asymptomatic individuals also. The model is then applied to Covid-19 spreading in Italy where a transition from an exponential behavior to a Gompertz growth for $N(t)$ has been observed in more recent data. Then the information contained in the data analysis of $N(t)$ is reliable to understand the epidemic phase, although it does not describe the total infected population. The asymptomatic population is larger than the symptomatic one in the fast growth phase of the spreading. |
2103.16496 | Timothee Brochier | Timoth\'ee Brochier (IRD, SU, ESP Dakar, UMMISCO), Alassane Bah (ESP
Dakar, UMMISCO) | FisherMob : a bioeconomic model of fishers' migrations | in French | null | null | null | q-bio.PE cs.MA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sea fishing is a highly mobile activity, favoured by the vastness of the
oceans, the absence of physical boundaries and the abstraction of legislative
boundaries. Understanding and anticipating this mobility is a major challenge
for fisheries management issues, both at the national and international levels.
''FisherMob'' is a free Gama tool designed to study the effect of economic and
biological factors on the dynamics of connected fisheries. It incorporate the
most important processes involved in fisheries dynamics: fish abundance
variability, price of the fishing effort and ex-vessel fish market price that
which depends on the ratio between offer and demand. The tool uses as input a
scheme of a coastal area with delimited fishing sites, fish biological
parameters and fisheries parameters. It runs with a userfriendly graphic
interface and generates output files that can be post-processed easily using
graphic and statistical software.
| [
{
"created": "Mon, 29 Mar 2021 14:34:16 GMT",
"version": "v1"
}
] | 2021-03-31 | [
[
"Brochier",
"Timothée",
"",
"IRD, SU, ESP Dakar, UMMISCO"
],
[
"Bah",
"Alassane",
"",
"ESP\n Dakar, UMMISCO"
]
] | Sea fishing is a highly mobile activity, favoured by the vastness of the oceans, the absence of physical boundaries and the abstraction of legislative boundaries. Understanding and anticipating this mobility is a major challenge for fisheries management issues, both at the national and international levels. ''FisherMob'' is a free Gama tool designed to study the effect of economic and biological factors on the dynamics of connected fisheries. It incorporate the most important processes involved in fisheries dynamics: fish abundance variability, price of the fishing effort and ex-vessel fish market price that which depends on the ratio between offer and demand. The tool uses as input a scheme of a coastal area with delimited fishing sites, fish biological parameters and fisheries parameters. It runs with a userfriendly graphic interface and generates output files that can be post-processed easily using graphic and statistical software. |
q-bio/0611070 | Herv\'e Isambert | Kirill Evlampiev and Herve Isambert | Asymptotic Evolution of Protein-Protein Interaction Networks for General
Duplication-Divergence Models | 6 pages, 5 figures (+ supporting information: 17 pages 3 figures) | null | null | null | q-bio.MN q-bio.PE | null | Genomic duplication-divergence events, which are the primary source of new
protein functions, occur stochastically at a wide range of genomic scales, from
single gene to whole genome duplications. Clearly, this fundamental
evolutionary process must have largely conditioned the emerging structure of
protein-protein interaction (PPI) networks, that control many cellular
activities. We propose and asymptotically solve a general
duplication-divergence model of PPI network evolution based on the statistical
selection of duplication-derived interactions. We also introduce a conservation
index, that formally defines the statistical evolutionary conservation of PPI
networks. Distinct conditions on microscopic parameters are then shown to
control global conservation and topology of emerging PPI networks. In
particular, conserved, non-dense networks, which are the only ones of potential
biological relevance, are also shown to be necessary scale-free.
| [
{
"created": "Wed, 22 Nov 2006 13:40:15 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Evlampiev",
"Kirill",
""
],
[
"Isambert",
"Herve",
""
]
] | Genomic duplication-divergence events, which are the primary source of new protein functions, occur stochastically at a wide range of genomic scales, from single gene to whole genome duplications. Clearly, this fundamental evolutionary process must have largely conditioned the emerging structure of protein-protein interaction (PPI) networks, that control many cellular activities. We propose and asymptotically solve a general duplication-divergence model of PPI network evolution based on the statistical selection of duplication-derived interactions. We also introduce a conservation index, that formally defines the statistical evolutionary conservation of PPI networks. Distinct conditions on microscopic parameters are then shown to control global conservation and topology of emerging PPI networks. In particular, conserved, non-dense networks, which are the only ones of potential biological relevance, are also shown to be necessary scale-free. |
2312.16097 | Si Wen | Si Wen and Brandon D. Gallas | Expanding to Arbitrary Study Designs: ANOVA to Estimate Limits of
Agreement for MRMC Studies | null | null | null | null | q-bio.QM | http://creativecommons.org/publicdomain/zero/1.0/ | A multi-reader multi-case (MRMC) analysis is applied to account for both
reader and case variability when evaluating the clinical performance of a
medical imaging device or reader performance under different reading
modalities. For a clinical task that measures a quantitative biomarker an
agreement analysis, such as limits of agreement (LOA), can be used. In this
work, we decompose the total variation in the data using a three-way mixed
effect ANOVA model to estimate the MRMC variance of individual differences and
the LOA between different reading modalities. There are rules for writing down
the expectation of the mean squares in terms of the variance components for
fully-crossed data, i.e. data where all the readers read all the cases in all
modalities being studied. Sometimes the annotation task is labor-intensive and
time-consuming or distributed across sites, so that a fully-crossed study is
not practical. In this work, we focus on estimating the MRMC variance in the
within- and between-readers and within- and between-modalities LOA for an
arbitrary study design. Simulation studies were conducted to validate the LOA
variance estimates. The method was also applied to a dataset to compare
pathologist performance for assessing the density of stromal tumor infiltrating
lymphocytes on different platforms.
| [
{
"created": "Tue, 26 Dec 2023 15:49:42 GMT",
"version": "v1"
}
] | 2023-12-27 | [
[
"Wen",
"Si",
""
],
[
"Gallas",
"Brandon D.",
""
]
] | A multi-reader multi-case (MRMC) analysis is applied to account for both reader and case variability when evaluating the clinical performance of a medical imaging device or reader performance under different reading modalities. For a clinical task that measures a quantitative biomarker an agreement analysis, such as limits of agreement (LOA), can be used. In this work, we decompose the total variation in the data using a three-way mixed effect ANOVA model to estimate the MRMC variance of individual differences and the LOA between different reading modalities. There are rules for writing down the expectation of the mean squares in terms of the variance components for fully-crossed data, i.e. data where all the readers read all the cases in all modalities being studied. Sometimes the annotation task is labor-intensive and time-consuming or distributed across sites, so that a fully-crossed study is not practical. In this work, we focus on estimating the MRMC variance in the within- and between-readers and within- and between-modalities LOA for an arbitrary study design. Simulation studies were conducted to validate the LOA variance estimates. The method was also applied to a dataset to compare pathologist performance for assessing the density of stromal tumor infiltrating lymphocytes on different platforms. |
2102.05459 | Olivier Rivoire | Anton S Zadorin, Olivier Rivoire | Sex as information processing: optimality and evolution | null | Phys. Rev. E 103, 062413 (2021) | 10.1103/PhysRevE.103.062413 | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The long-term growth rate of populations in varying environments quantifies
the evolutionary value of processing the information that biological
individuals inherit from their ancestors and acquire from their environment.
Previous models were limited to asexual reproduction with inherited information
coming from a single parent with no recombination. We present a general
extension to sexual reproduction and an analytical solution for a particular
but important case, the infinitesimal model of quantitative genetics which
assumes traits to be normally distributed. We study with this model the
conditions under which sexual reproduction is advantageous and can evolve in
the context of autocorrelated or directionally varying environments, mutational
biases, spatial heterogeneities and phenotypic plasticity. Our results
generalize and unify previous analyses. We also examine the proposal made by
Geodakyan that the presence of two phenotypically distinct sexes permits an
optimal adaptation to varying environments. We verify that conditions exists
where sexual dimorphism is adaptive but find that its evolutionary value does
not generally compensate for the two-fold cost of males.
| [
{
"created": "Wed, 10 Feb 2021 14:26:35 GMT",
"version": "v1"
},
{
"created": "Tue, 15 Jun 2021 09:33:12 GMT",
"version": "v2"
}
] | 2021-06-30 | [
[
"Zadorin",
"Anton S",
""
],
[
"Rivoire",
"Olivier",
""
]
] | The long-term growth rate of populations in varying environments quantifies the evolutionary value of processing the information that biological individuals inherit from their ancestors and acquire from their environment. Previous models were limited to asexual reproduction with inherited information coming from a single parent with no recombination. We present a general extension to sexual reproduction and an analytical solution for a particular but important case, the infinitesimal model of quantitative genetics which assumes traits to be normally distributed. We study with this model the conditions under which sexual reproduction is advantageous and can evolve in the context of autocorrelated or directionally varying environments, mutational biases, spatial heterogeneities and phenotypic plasticity. Our results generalize and unify previous analyses. We also examine the proposal made by Geodakyan that the presence of two phenotypically distinct sexes permits an optimal adaptation to varying environments. We verify that conditions exists where sexual dimorphism is adaptive but find that its evolutionary value does not generally compensate for the two-fold cost of males. |
2109.04261 | Nicolas Deperrois | Nicolas Deperrois, Mihai A. Petrovici, Walter Senn, and Jakob Jordan | Learning cortical representations through perturbed and adversarial
dreaming | 35 pages, 15 figures; ; Jakob Jordan and Walter Senn share senior
authorship | null | null | null | q-bio.NC cs.LG | http://creativecommons.org/licenses/by/4.0/ | Humans and other animals learn to extract general concepts from sensory
experience without extensive teaching. This ability is thought to be
facilitated by offline states like sleep where previous experiences are
systemically replayed. However, the characteristic creative nature of dreams
suggests that learning semantic representations may go beyond merely replaying
previous experiences. We support this hypothesis by implementing a cortical
architecture inspired by generative adversarial networks (GANs). Learning in
our model is organized across three different global brain states mimicking
wakefulness, NREM and REM sleep, optimizing different, but complementary
objective functions. We train the model on standard datasets of natural images
and evaluate the quality of the learned representations. Our results suggest
that generating new, virtual sensory inputs via adversarial dreaming during REM
sleep is essential for extracting semantic concepts, while replaying episodic
memories via perturbed dreaming during NREM sleep improves the robustness of
latent representations. The model provides a new computational perspective on
sleep states, memory replay and dreams and suggests a cortical implementation
of GANs.
| [
{
"created": "Thu, 9 Sep 2021 13:31:13 GMT",
"version": "v1"
},
{
"created": "Mon, 3 Jan 2022 15:49:18 GMT",
"version": "v2"
},
{
"created": "Fri, 18 Feb 2022 18:01:48 GMT",
"version": "v3"
}
] | 2022-02-21 | [
[
"Deperrois",
"Nicolas",
""
],
[
"Petrovici",
"Mihai A.",
""
],
[
"Senn",
"Walter",
""
],
[
"Jordan",
"Jakob",
""
]
] | Humans and other animals learn to extract general concepts from sensory experience without extensive teaching. This ability is thought to be facilitated by offline states like sleep where previous experiences are systemically replayed. However, the characteristic creative nature of dreams suggests that learning semantic representations may go beyond merely replaying previous experiences. We support this hypothesis by implementing a cortical architecture inspired by generative adversarial networks (GANs). Learning in our model is organized across three different global brain states mimicking wakefulness, NREM and REM sleep, optimizing different, but complementary objective functions. We train the model on standard datasets of natural images and evaluate the quality of the learned representations. Our results suggest that generating new, virtual sensory inputs via adversarial dreaming during REM sleep is essential for extracting semantic concepts, while replaying episodic memories via perturbed dreaming during NREM sleep improves the robustness of latent representations. The model provides a new computational perspective on sleep states, memory replay and dreams and suggests a cortical implementation of GANs. |
1203.3884 | Philippe Desjardins-Proulx | Philippe Desjardins-Proulx and Dominique Gravel | A complex speciation-richness relationship in a simple neutral model | 9 pages, 5 figures, 1 table, 50 references | Ecology and Evolution 2(8): 1781-1790, 2012 | 10.1002/ece3.292 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Speciation is the "elephant in the room" of community ecology. As the
ultimate source of biodiversity, its integration in ecology's theoretical
corpus is necessary to understand community assembly. Yet, speciation is often
completely ignored or stripped of its spatial dimension. Recent approaches
based on network theory have allowed ecologists to effectively model complex
landscapes. In this study, we use this framework to model allopatric and
parapatric speciation in networks of communities and focus on the relationship
between speciation, richness, and the spatial structure of communities. We find
a strong opposition between speciation and local richness, with speciation
being more common in isolated communities and local richness being higher in
more connected communities. Unlike previous models, we also find a transition
to a positive relationship between speciation and local richness when dispersal
is low and the number of communities is small. Also, we use several measures of
centrality to characterize the effect of network structure on diversity. The
degree, the simplest measure of centrality, is found to be the best predictor
of local richness and speciation, although it loses some of its predictive
power as connectivity grows. Our framework shows how a simple neutral model can
be combined with network theory to reveal complex relationships between
speciation, richness, and the spatial organization of populations.
| [
{
"created": "Sat, 17 Mar 2012 18:25:57 GMT",
"version": "v1"
},
{
"created": "Fri, 11 May 2012 00:30:32 GMT",
"version": "v2"
}
] | 2012-08-07 | [
[
"Desjardins-Proulx",
"Philippe",
""
],
[
"Gravel",
"Dominique",
""
]
] | Speciation is the "elephant in the room" of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities and focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. Also, we use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is found to be the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations. |
1903.10310 | Danilo Bzdok | Danilo Bzdok (PARIETAL), John Ioannidis | Exploration, inference and prediction in neuroscience and biomedicine | null | Trends in Neurosciences, Elsevier, 2019 | null | null | q-bio.NC stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The last decades saw dramatic progress in brain research. These advances were
often buttressed by probing single variables to make circumscribed discoveries,
typically through null hypothesis significance testing. New ways for generating
massive data fueled tension between the traditional methodology, used to infer
statistically relevant effects in carefully-chosen variables, and
pattern-learning algorithms, used to identify predictive signatures by
searching through abundant information. In this article, we detail the
antagonistic philosophies behind two quantitative approaches: certifying robust
effects in understandable variables, and evaluating how accurately a built
model can forecast future outcomes. We discourage choosing analysis tools via
categories like 'statistics' or 'machine learning'. Rather, to establish
reproducible knowledge about the brain, we advocate prioritizing tools in view
of the core motivation of each quantitative analysis: aiming towards
mechanistic insight, or optimizing predictive accuracy.
| [
{
"created": "Thu, 21 Feb 2019 13:08:29 GMT",
"version": "v1"
}
] | 2019-03-26 | [
[
"Bzdok",
"Danilo",
"",
"PARIETAL"
],
[
"Ioannidis",
"John",
""
]
] | The last decades saw dramatic progress in brain research. These advances were often buttressed by probing single variables to make circumscribed discoveries, typically through null hypothesis significance testing. New ways for generating massive data fueled tension between the traditional methodology, used to infer statistically relevant effects in carefully-chosen variables, and pattern-learning algorithms, used to identify predictive signatures by searching through abundant information. In this article, we detail the antagonistic philosophies behind two quantitative approaches: certifying robust effects in understandable variables, and evaluating how accurately a built model can forecast future outcomes. We discourage choosing analysis tools via categories like 'statistics' or 'machine learning'. Rather, to establish reproducible knowledge about the brain, we advocate prioritizing tools in view of the core motivation of each quantitative analysis: aiming towards mechanistic insight, or optimizing predictive accuracy. |
q-bio/0309007 | Voislav Golo | Voislav Golo | The Inter-Strand Modes of the DNA as a Probe into MW-Radiation | 13 pages | null | null | null | q-bio.BM | null | We consider the regime in which the bands of the torsional acoustic (TA) and
the hydrogen-bond-stretch (HBS) modes of the DNA interpenetrate each other.
Within the framework of a model that accommodates the structure of the double
helix, we find the three-wave interaction between the TA- and the HBS-modes,
and show that microwave radiation could bring about torsional vibrations that
could serve as a pump mode for maintaining the HBS-one. Rayleigh's threshold
condition for the parametric resonance provides an estimate for the power
density of the mw-field necessary for generating the HBS-mode.
| [
{
"created": "Fri, 19 Sep 2003 05:55:55 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Golo",
"Voislav",
""
]
] | We consider the regime in which the bands of the torsional acoustic (TA) and the hydrogen-bond-stretch (HBS) modes of the DNA interpenetrate each other. Within the framework of a model that accommodates the structure of the double helix, we find the three-wave interaction between the TA- and the HBS-modes, and show that microwave radiation could bring about torsional vibrations that could serve as a pump mode for maintaining the HBS-one. Rayleigh's threshold condition for the parametric resonance provides an estimate for the power density of the mw-field necessary for generating the HBS-mode. |
1707.08337 | Daniel Mart\'i | Daniel Mart\'i, Nicolas Brunel, Srdjan Ostojic | Correlations between synapses in pairs of neurons slow down dynamics in
randomly connected neural networks | 17 pages, 7 figures | Phys. Rev. E 97, 062314 (2018) | 10.1103/PhysRevE.97.062314 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Networks of randomly connected neurons are among the most popular models in
theoretical neuroscience. The connectivity between neurons in the cortex is
however not fully random, the simplest and most prominent deviation from
randomness found in experimental data being the overrepresentation of
bidirectional connections among pyramidal cells. Using numerical and analytical
methods, we investigated the effects of partially symmetric connectivity on
dynamics in networks of rate units. We considered the two dynamical regimes
exhibited by random neural networks: the weak-coupling regime, where the firing
activity decays to a single fixed point unless the network is stimulated, and
the strong-coupling or chaotic regime, characterized by internally generated
fluctuating firing rates. In the weak-coupling regime, we computed analytically
for an arbitrary degree of symmetry the auto-correlation of network activity in
presence of external noise. In the chaotic regime, we performed simulations to
determine the timescale of the intrinsic fluctuations. In both cases, symmetry
increases the characteristic asymptotic decay time of the autocorrelation
function and therefore slows down the dynamics in the network.
| [
{
"created": "Wed, 26 Jul 2017 09:41:25 GMT",
"version": "v1"
},
{
"created": "Tue, 22 May 2018 20:36:52 GMT",
"version": "v2"
},
{
"created": "Fri, 6 Jul 2018 08:17:33 GMT",
"version": "v3"
}
] | 2018-07-09 | [
[
"Martí",
"Daniel",
""
],
[
"Brunel",
"Nicolas",
""
],
[
"Ostojic",
"Srdjan",
""
]
] | Networks of randomly connected neurons are among the most popular models in theoretical neuroscience. The connectivity between neurons in the cortex is however not fully random, the simplest and most prominent deviation from randomness found in experimental data being the overrepresentation of bidirectional connections among pyramidal cells. Using numerical and analytical methods, we investigated the effects of partially symmetric connectivity on dynamics in networks of rate units. We considered the two dynamical regimes exhibited by random neural networks: the weak-coupling regime, where the firing activity decays to a single fixed point unless the network is stimulated, and the strong-coupling or chaotic regime, characterized by internally generated fluctuating firing rates. In the weak-coupling regime, we computed analytically for an arbitrary degree of symmetry the auto-correlation of network activity in presence of external noise. In the chaotic regime, we performed simulations to determine the timescale of the intrinsic fluctuations. In both cases, symmetry increases the characteristic asymptotic decay time of the autocorrelation function and therefore slows down the dynamics in the network. |
0906.0886 | Mikko Tuomi | M. Tuomi, T. Thum, H. J\"arvinen, S. Fronzek, B. Berg, M. Harmon, J.
A. Trofymow, S. Sevanto, J. Liski | Leaf litter decomposition -- Estimates of global variability based on
Yasso07 model | 19 Pages, to appear in Ecological Modelling | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Litter decomposition is an important process in the global carbon cycle. It
accounts for most of the heterotrophic soil respiration and results in
formation of more stable soil organic carbon (SOC) which is the largest
terrestrial carbon stock. Litter decomposition may induce remarkable feedbacks
to climate change because it is a climate-dependent process. To investigate the
global patterns of litter decomposition, we developed a description of this
process and tested the validity of this description using a large set of foliar
litter mass loss measurements (nearly 10 000 data points derived from
approximately 70 000 litter bags). We applied the Markov chain Monte Carlo
method to estimate uncertainty in the parameter values and results of our model
called Yasso07. The model appeared globally applicable. It estimated the
effects of litter type (plant species) and climate on mass loss with little
systematic error over the first 10 decomposition years, using only initial
litter chemistry, air temperature and precipitation as input variables.
Illustrative of the global variability in litter mass loss rates, our example
calculations showed that a typical conifer litter had 68% of its initial mass
still remaining after two decomposition years in tundra while a deciduous
litter had only 15% remaining in the tropics. Uncertainty in these estimates, a
direct result of the uncertainty of the parameter values of the model, varied
according to the distribution of the litter bag data among climate conditions
and ranged from 2% in tundra to 4% in the tropics. This reliability was
adequate to use the model and distinguish the effects of even small differences
in litter quality or climate conditions on litter decomposition as
statistically significant.
| [
{
"created": "Thu, 4 Jun 2009 11:35:07 GMT",
"version": "v1"
}
] | 2009-06-05 | [
[
"Tuomi",
"M.",
""
],
[
"Thum",
"T.",
""
],
[
"Järvinen",
"H.",
""
],
[
"Fronzek",
"S.",
""
],
[
"Berg",
"B.",
""
],
[
"Harmon",
"M.",
""
],
[
"Trofymow",
"J. A.",
""
],
[
"Sevanto",
"S.",
""
],
[
"Liski",
"J.",
""
]
] | Litter decomposition is an important process in the global carbon cycle. It accounts for most of the heterotrophic soil respiration and results in formation of more stable soil organic carbon (SOC) which is the largest terrestrial carbon stock. Litter decomposition may induce remarkable feedbacks to climate change because it is a climate-dependent process. To investigate the global patterns of litter decomposition, we developed a description of this process and tested the validity of this description using a large set of foliar litter mass loss measurements (nearly 10 000 data points derived from approximately 70 000 litter bags). We applied the Markov chain Monte Carlo method to estimate uncertainty in the parameter values and results of our model called Yasso07. The model appeared globally applicable. It estimated the effects of litter type (plant species) and climate on mass loss with little systematic error over the first 10 decomposition years, using only initial litter chemistry, air temperature and precipitation as input variables. Illustrative of the global variability in litter mass loss rates, our example calculations showed that a typical conifer litter had 68% of its initial mass still remaining after two decomposition years in tundra while a deciduous litter had only 15% remaining in the tropics. Uncertainty in these estimates, a direct result of the uncertainty of the parameter values of the model, varied according to the distribution of the litter bag data among climate conditions and ranged from 2% in tundra to 4% in the tropics. This reliability was adequate to use the model and distinguish the effects of even small differences in litter quality or climate conditions on litter decomposition as statistically significant. |
1305.0758 | Jean-Beno\^it Lalanne | Jean-Beno\^it Lalanne and Paul Fran\c{c}ois | Principles of Adaptive Sorting Revealed by In Silico Evolution | 50 pages, 28 figures, including supplementary information | null | 10.1103/PhysRevLett.110.218102 | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Many biological networks have to filter out useful information from a vast
excess of spurious interactions. We use computational evolution to predict
design features of networks processing ligand categorization. The important
problem of early immune response is considered as a case-study. Rounds of
evolution with different constraints uncover elaborations of the same network
motif we name adaptive sorting. Corresponding network substructures can be
identified in current models of immune recognition. Our work draws a deep
analogy between immune recognition and biochemical adaptation.
| [
{
"created": "Fri, 3 May 2013 15:52:08 GMT",
"version": "v1"
}
] | 2013-05-27 | [
[
"Lalanne",
"Jean-Benoît",
""
],
[
"François",
"Paul",
""
]
] | Many biological networks have to filter out useful information from a vast excess of spurious interactions. We use computational evolution to predict design features of networks processing ligand categorization. The important problem of early immune response is considered as a case-study. Rounds of evolution with different constraints uncover elaborations of the same network motif we name adaptive sorting. Corresponding network substructures can be identified in current models of immune recognition. Our work draws a deep analogy between immune recognition and biochemical adaptation. |
1109.5681 | Valerie Hower | Valerie Hower, Richard Starfield, Adam Roberts, Lior Pachter | Quantifying uniformity of mapped reads | withdrawing based on the journal's policy | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Summary: We describe a tool for quantifying the uniformity of mapped reads in
high-throughput sequencing experiments. Our statistic directly measures the
uniformity of both read position and fragment length, and we explain how to
compute a p-value that can be used to quantify biases arising from experimental
protocols and mapping procedures. Our method is useful for comparing different
protocols in experiments such as RNA-Seq.
Availability and Implementation: We provide a freely available and open
source python script that can be used to analyze raw read data or reads mapped
to transcripts in BAM format at http://www.math.miami.edu/~vhower/ReadSpy.html .
Contact: lpachter@math.berkeley.edu
| [
{
"created": "Mon, 26 Sep 2011 19:33:37 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Jul 2012 20:41:08 GMT",
"version": "v2"
},
{
"created": "Tue, 17 Jul 2012 18:51:26 GMT",
"version": "v3"
}
] | 2013-10-22 | [
[
"Hower",
"Valerie",
""
],
[
"Starfield",
"Richard",
""
],
[
"Roberts",
"Adam",
""
],
[
"Pachter",
"Lior",
""
]
] | Summary: We describe a tool for quantifying the uniformity of mapped reads in high-throughput sequencing experiments. Our statistic directly measures the uniformity of both read position and fragment length, and we explain how to compute a p-value that can be used to quantify biases arising from experimental protocols and mapping procedures. Our method is useful for comparing different protocols in experiments such as RNA-Seq. Availability and Implementation: We provide a freely available and open source python script that can be used to analyze raw read data or reads mapped to transcripts in BAM format at http://www.math.miami.edu/~vhower/ReadSpy.html . Contact: lpachter@math.berkeley.edu |
1312.7735 | Jens Christian Claussen | Arne Weigenand, Thomas Martinetz and Jens Christian Claussen | The phase response of the cortical slow oscillation | null | Cognitive Neurodynamics 6(4), 367-375 (2012) | 10.1007/s11571-012-9207-z | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cortical slow oscillations occur in the mammalian brain during deep sleep and
have been shown to contribute to memory consolidation, an effect that can be
enhanced by electrical stimulation. As the precise underlying working
mechanisms are not known it is desired to develop and analyze computational
models of slow oscillations and to study the response to electrical stimuli. In
this paper we employ the conductance based model of Compte et al. [J
Neurophysiol 89, 2707] to study the effect of electrical stimulation. The
population response to electrical stimulation depends on the timing of the
stimulus with respect to the state of the slow oscillation. First, we reproduce
the experimental results of electrical stimulation in ferret brain slices by
Shu et al. [Nature 423, 288] from the conductance based model. We then
numerically obtain the phase response curve for the conductance based network
model to quantify the network's response to weak stimuli. Our results agree
with experiments in vivo and in vitro that show that sensitivity to stimulation
is weaker in the up than in the down state. However, we also find that within
the up state stimulation leads to a shortening of the up state, or phase
advance, whereas during the up-down transition a prolongation of up states is
possible, resulting in a phase delay. Finally, we compute the phase response
curve for the simple mean-field model by Ngo et al. [Europhys Lett 89, 68002]
and find that the qualitative shape of the PRC is preserved, despite its
different mechanism for the generation of slow oscillations.
| [
{
"created": "Mon, 30 Dec 2013 15:15:28 GMT",
"version": "v1"
}
] | 2013-12-31 | [
[
"Weigenand",
"Arne",
""
],
[
"Martinetz",
"Thomas",
""
],
[
"Claussen",
"Jens Christian",
""
]
] | Cortical slow oscillations occur in the mammalian brain during deep sleep and have been shown to contribute to memory consolidation, an effect that can be enhanced by electrical stimulation. As the precise underlying working mechanisms are not known it is desired to develop and analyze computational models of slow oscillations and to study the response to electrical stimuli. In this paper we employ the conductance based model of Compte et al. [J Neurophysiol 89, 2707] to study the effect of electrical stimulation. The population response to electrical stimulation depends on the timing of the stimulus with respect to the state of the slow oscillation. First, we reproduce the experimental results of electrical stimulation in ferret brain slices by Shu et al. [Nature 423, 288] from the conductance based model. We then numerically obtain the phase response curve for the conductance based network model to quantify the network's response to weak stimuli. Our results agree with experiments in vivo and in vitro that show that sensitivity to stimulation is weaker in the up than in the down state. However, we also find that within the up state stimulation leads to a shortening of the up state, or phase advance, whereas during the up-down transition a prolongation of up states is possible, resulting in a phase delay. Finally, we compute the phase response curve for the simple mean-field model by Ngo et al. [Europhys Lett 89, 68002] and find that the qualitative shape of the PRC is preserved, despite its different mechanism for the generation of slow oscillations. |
q-bio/0411046 | Patricia Faisca | P.F.N. Faisca, M.M. Telo da Gama, A. Nunes | The Go model revisited: Native structure and the geometric coupling
between local and long-range contacts | 12 pages, 26 figures, RevTex. Accepted in Proteins: Structure,
Function and Bioinformatics | Proteins: Structure, Function and Bioinformatics 60, 712-722
(2005) | 10.1002/prot.20521 | null | q-bio.BM | null | Monte Carlo simulations show that long-range interactions play a major role
in determining the folding rates of 48-mer three-dimensional lattice polymers
modelled by the Go potential. For three target structures with different native
geometries we found a sharp increase in the folding time when the relative
contribution of the long-range interactions to the native state's energy is
decreased from ~50% towards zero. However, the dispersion of the simulated
folding times depends strongly on the native geometry and Go polymers folding
to one of the target structures exhibit folding times spanning three orders of
magnitude. We have also found that, depending on the target geometry, a strong
geometric coupling may exist between local and long-range contacts meaning
that, when this coupling exists, the formation of long-range contacts is forced
by the previous formation of local contacts. The absence of a strong geometric
coupling leads to kinetics that are more sensitive to the interaction energy
parameters; in this case the formation of local contacts is not sufficient to
promote the establishment of long-range ones when these are strongly penalized
energetically, leading to longer folding times.
| [
{
"created": "Fri, 26 Nov 2004 17:23:52 GMT",
"version": "v1"
},
{
"created": "Wed, 9 Mar 2005 16:07:31 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Faisca",
"P. F. N.",
""
],
[
"da Gama",
"M. M. Telo",
""
],
[
"Nunes",
"A.",
""
]
] | Monte Carlo simulations show that long-range interactions play a major role in determining the folding rates of 48-mer three-dimensional lattice polymers modelled by the Go potential. For three target structures with different native geometries we found a sharp increase in the folding time when the relative contribution of the long-range interactions to the native state's energy is decreased from ~50% towards zero. However, the dispersion of the simulated folding times depends strongly on the native geometry and Go polymers folding to one of the target structures exhibit folding times spanning three orders of magnitude. We have also found that, depending on the target geometry, a strong geometric coupling may exist between local and long-range contacts meaning that, when this coupling exists, the formation of long-range contacts is forced by the previous formation of local contacts. The absence of a strong geometric coupling leads to kinetics that are more sensitive to the interaction energy parameters; in this case the formation of local contacts is not sufficient to promote the establishment of long-range ones when these are strongly penalized energetically, leading to longer folding times. |
0812.3276 | Luis G. Morelli | Luis G. Morelli, Saul Ares, Leah Herrgen, Christian Schroeter, Frank
Julicher, and Andrew C. Oates | Delayed coupling theory of vertebrate segmentation | published online 10 December 2008, Adv. Online Pub. HFSP Journal
(free access) | null | 10.2976/1.3027088 | null | q-bio.MN nlin.AO physics.bio-ph q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Rhythmic and sequential subdivision of the elongating vertebrate embryonic
body axis into morphological somites is controlled by an oscillating
multicellular genetic network termed the segmentation clock. This clock
operates in the presomitic mesoderm (PSM), generating dynamic stripe patterns
of oscillatory gene-expression across the field of PSM cells. How these spatial
patterns, the clock's collective period, and the underlying cellular-level
interactions are related is not understood. A theory encompassing temporal and
spatial domains of local and collective aspects of the system is essential to
tackle these questions. Our delayed coupling theory achieves this by
representing the PSM as an array of phase oscillators, combining four key
elements: a frequency profile of oscillators slowing across the PSM; coupling
between neighboring oscillators; delay in coupling; and a moving boundary
describing embryonic axis elongation. This theory predicts that the
segmentation clock's collective period depends on delayed coupling. We derive
an expression for pattern wavelength across the PSM and show how this can be
used to fit dynamic wildtype gene-expression patterns, revealing the
quantitative values of parameters controlling spatial and temporal organization
of the oscillators in the system. Our theory can be used to analyze
experimental perturbations, thereby identifying roles of genes involved in
segmentation.
| [
{
"created": "Wed, 17 Dec 2008 14:02:19 GMT",
"version": "v1"
}
] | 2009-01-08 | [
[
"Morelli",
"Luis G.",
""
],
[
"Ares",
"Saul",
""
],
[
"Herrgen",
"Leah",
""
],
[
"Schroeter",
"Christian",
""
],
[
"Julicher",
"Frank",
""
],
[
"Oates",
"Andrew C.",
""
]
] | Rhythmic and sequential subdivision of the elongating vertebrate embryonic body axis into morphological somites is controlled by an oscillating multicellular genetic network termed the segmentation clock. This clock operates in the presomitic mesoderm (PSM), generating dynamic stripe patterns of oscillatory gene-expression across the field of PSM cells. How these spatial patterns, the clock's collective period, and the underlying cellular-level interactions are related is not understood. A theory encompassing temporal and spatial domains of local and collective aspects of the system is essential to tackle these questions. Our delayed coupling theory achieves this by representing the PSM as an array of phase oscillators, combining four key elements: a frequency profile of oscillators slowing across the PSM; coupling between neighboring oscillators; delay in coupling; and a moving boundary describing embryonic axis elongation. This theory predicts that the segmentation clock's collective period depends on delayed coupling. We derive an expression for pattern wavelength across the PSM and show how this can be used to fit dynamic wildtype gene-expression patterns, revealing the quantitative values of parameters controlling spatial and temporal organization of the oscillators in the system. Our theory can be used to analyze experimental perturbations, thereby identifying roles of genes involved in segmentation. |
2210.03910 | Sat Byul Seo | Sat byul Seo, Jianzhong Su | Quantifying constraints determining independent activation on NMDA
receptors mediated currents from evoked and spontaneous synaptic transmission
at an individual synapse | null | null | null | null | q-bio.NC math.DS | http://creativecommons.org/licenses/by/4.0/ | A synapse acts on neural transmission through a chemical process called
synapses fusion between pre-synaptic and post-synaptic terminals. Presynaptic
terminals release neurotransmitters either in response to action potential or
spontaneously independent of presynaptic activity. However, it is still unclear
the mechanism of evoked and spontaneous neuro-transmission that activate on
postsynaptic terminals. To address this question, we examined the possibility
that spontaneous and evoked neurotransmissions using mathematical simulations.
We aimed to address the biophysical constraints that may determine independent
activation on N-methyl-D-asparate (NMDA) receptor mediated currents in response
to evoked and spontaneous glutamate molecules releases. In order to identify
the spatial relation between spontaneous and evoked glutamate release, we
considered quantitative factors, such as size of synapses, inhomogeneity of
diffusion mobility, geometry of synaptic cleft, and release rate of
neurotransmitter. Simulation results showed that as a synaptic size is smaller
and if the cleft space is more cohesive in the peripheral area than the centre
area, then there is high possibility of having crosstalk of two signals
released from center and edge. When a synaptic size is larger, the cleft space
is more affinity in the central area than the external area, and if the
geometry of fusion has a narrower space, then those produce more chances of
independence of two modes of currents released from center and edge. The
computed results match well with existing experimental findings and serve as a
road map for further exploration to identify independence of evoked and
spontaneous releases.
| [
{
"created": "Sat, 8 Oct 2022 04:20:10 GMT",
"version": "v1"
}
] | 2022-10-11 | [
[
"Seo",
"Sat byul",
""
],
[
"Su",
"Jianzhong",
""
]
] | A synapse acts on neural transmission through a chemical process called synapses fusion between pre-synaptic and post-synaptic terminals. Presynaptic terminals release neurotransmitters either in response to action potential or spontaneously independent of presynaptic activity. However, it is still unclear the mechanism of evoked and spontaneous neuro-transmission that activate on postsynaptic terminals. To address this question, we examined the possibility that spontaneous and evoked neurotransmissions using mathematical simulations. We aimed to address the biophysical constraints that may determine independent activation on N-methyl-D-asparate (NMDA) receptor mediated currents in response to evoked and spontaneous glutamate molecules releases. In order to identify the spatial relation between spontaneous and evoked glutamate release, we considered quantitative factors, such as size of synapses, inhomogeneity of diffusion mobility, geometry of synaptic cleft, and release rate of neurotransmitter. Simulation results showed that as a synaptic size is smaller and if the cleft space is more cohesive in the peripheral area than the centre area, then there is high possibility of having crosstalk of two signals released from center and edge. When a synaptic size is larger, the cleft space is more affinity in the central area than the external area, and if the geometry of fusion has a narrower space, then those produce more chances of independence of two modes of currents released from center and edge. The computed results match well with existing experimental findings and serve as a road map for further exploration to identify independence of evoked and spontaneous releases. |
1505.05983 | Yann Ponty | Cedric Chauve, Julien Courtiel, Yann Ponty (LIX, AMIB) | Counting, generating and sampling tree alignments | ALCOB - 3rd International Conference on Algorithms for Computational
Biology - 2016, Jun 2016, Trujillo, Spain. 2016 | null | null | null | q-bio.QM cs.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Pairwise ordered tree alignment are combinatorial objects that appear in RNA
secondary structure comparison. However, the usual representation of tree
alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce
identical sets of matches between identical pairs of trees. This ambiguity is
uninformative, and detrimental to any probabilistic analysis.In this work, we
consider tree alignments up to equivalence. Our first result is a precise
asymptotic enumeration of tree alignments, obtained from a context-free grammar
by mean of basic analytic combinatorics. Our second result focuses on
alignments between two given ordered trees $S$ and $T$. By refining our grammar
to align specific trees, we obtain a decomposition scheme for the space of
alignments, and use it to design an efficient dynamic programming algorithm for
sampling alignments under the Gibbs-Boltzmann probability distribution. This
generalizes existing tree alignment algorithms, and opens the door for a
probabilistic analysis of the space of suboptimal RNA secondary structures
alignments.
| [
{
"created": "Fri, 22 May 2015 08:25:05 GMT",
"version": "v1"
},
{
"created": "Tue, 22 Dec 2015 13:03:28 GMT",
"version": "v2"
},
{
"created": "Mon, 7 Mar 2016 19:44:22 GMT",
"version": "v3"
}
] | 2016-03-08 | [
[
"Chauve",
"Cedric",
"",
"LIX, AMIB"
],
[
"Courtiel",
"Julien",
"",
"LIX, AMIB"
],
[
"Ponty",
"Yann",
"",
"LIX, AMIB"
]
] | Pairwise ordered tree alignment are combinatorial objects that appear in RNA secondary structure comparison. However, the usual representation of tree alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce identical sets of matches between identical pairs of trees. This ambiguity is uninformative, and detrimental to any probabilistic analysis.In this work, we consider tree alignments up to equivalence. Our first result is a precise asymptotic enumeration of tree alignments, obtained from a context-free grammar by mean of basic analytic combinatorics. Our second result focuses on alignments between two given ordered trees $S$ and $T$. By refining our grammar to align specific trees, we obtain a decomposition scheme for the space of alignments, and use it to design an efficient dynamic programming algorithm for sampling alignments under the Gibbs-Boltzmann probability distribution. This generalizes existing tree alignment algorithms, and opens the door for a probabilistic analysis of the space of suboptimal RNA secondary structures alignments. |
2201.07879 | Jacominus van Baalen | Robert Penner (IHES), Minus van Baalen (CNRS, IBENS) | On the origins of the Omicron variant of the SARS-CoV-2 virus | null | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A possible explanation based on first principles for the appearance of the
Omicron variant of the SARS-CoV-2 virus is proposed involving coinfection with
HIV. The gist is that the resultant HIV-induced immunocompromise allows
SARS-CoV-2 greater latitude to explore its own mutational space. This latitude
is not withoutr estriction, and a specific biophysical constraint is explored.
Specifically, a nearly two- to five-fold discrepancy in backbone hydrogen
bonding is observed between sub-molecules in Protein Data Bank files of the
spike glycoprotein yielding two conclusions: mutagenic residues in the
receptor-binding subunit of the spike much more frequently do not participate
in backbone hydrogen bonds; and a technique of viral escape is therefore to
remove such bonds within physico-chemical and functional constraints. Earlier
work, from which the previous discussion is entirely independent, explains
these phenomena from general principles of free energy, namely, the
metastability of the glycoprotein. The conclusions therefore likely hold more
generally as principles in virology.
| [
{
"created": "Wed, 8 Dec 2021 13:51:47 GMT",
"version": "v1"
}
] | 2022-01-21 | [
[
"Penner",
"Robert",
"",
"IHES"
],
[
"van Baalen",
"Minus",
"",
"CNRS, IBENS"
]
] | A possible explanation based on first principles for the appearance of the Omicron variant of the SARS-CoV-2 virus is proposed involving coinfection with HIV. The gist is that the resultant HIV-induced immunocompromise allows SARS-CoV-2 greater latitude to explore its own mutational space. This latitude is not withoutr estriction, and a specific biophysical constraint is explored. Specifically, a nearly two- to five-fold discrepancy in backbone hydrogen bonding is observed between sub-molecules in Protein Data Bank files of the spike glycoprotein yielding two conclusions: mutagenic residues in the receptor-binding subunit of the spike much more frequently do not participate in backbone hydrogen bonds; and a technique of viral escape is therefore to remove such bonds within physico-chemical and functional constraints. Earlier work, from which the previous discussion is entirely independent, explains these phenomena from general principles of free energy, namely, the metastability of the glycoprotein. The conclusions therefore likely hold more generally as principles in virology. |
1704.03525 | Hidenori Tanaka | Hidenori Tanaka, Howard A. Stone, David R. Nelson | Spatial gene drives and pushed genetic waves | null | PNAS, vol. 114 no. 32, 8452-8457 (2017) | 10.1073/pnas.1705868114 | null | q-bio.PE cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Gene drives have the potential to rapidly replace a harmful wild-type allele
with a gene drive allele engineered to have desired functionalities. However,
an accidental or premature release of a gene drive construct to the natural
environment could damage an ecosystem irreversibly. Thus, it is important to
understand the spatiotemporal consequences of the super-Mendelian population
genetics prior to potential applications. Here, we employ a reaction-diffusion
model for sexually reproducing diploid organisms to study how a locally
introduced gene drive allele spreads to replace the wild-type allele, even
though it possesses a selective disadvantage $s>0$. Using methods developed by
N. Barton and collaborators, we show that socially responsible gene drives
require $0.5<s<0.697$, a rather narrow range. In this "pushed wave" regime, the
spatial spreading of gene drives will be initiated only when the initial
frequency distribution is above a threshold profile called "critical
propagule", which acts as a safeguard against accidental release. We also study
how the spatial spread of the pushed wave can be stopped by making gene drives
uniquely vulnerable ("sensitizing drive") in a way that is harmless for a
wild-type allele. Finally, we show that appropriately sensitized drives in two
dimensions can be stopped even by imperfect barriers perforated by a series of
gaps.
| [
{
"created": "Tue, 11 Apr 2017 20:26:03 GMT",
"version": "v1"
},
{
"created": "Tue, 22 Aug 2017 03:24:37 GMT",
"version": "v2"
}
] | 2017-08-23 | [
[
"Tanaka",
"Hidenori",
""
],
[
"Stone",
"Howard A.",
""
],
[
"Nelson",
"David R.",
""
]
] | Gene drives have the potential to rapidly replace a harmful wild-type allele with a gene drive allele engineered to have desired functionalities. However, an accidental or premature release of a gene drive construct to the natural environment could damage an ecosystem irreversibly. Thus, it is important to understand the spatiotemporal consequences of the super-Mendelian population genetics prior to potential applications. Here, we employ a reaction-diffusion model for sexually reproducing diploid organisms to study how a locally introduced gene drive allele spreads to replace the wild-type allele, even though it possesses a selective disadvantage $s>0$. Using methods developed by N. Barton and collaborators, we show that socially responsible gene drives require $0.5<s<0.697$, a rather narrow range. In this "pushed wave" regime, the spatial spreading of gene drives will be initiated only when the initial frequency distribution is above a threshold profile called "critical propagule", which acts as a safeguard against accidental release. We also study how the spatial spread of the pushed wave can be stopped by making gene drives uniquely vulnerable ("sensitizing drive") in a way that is harmless for a wild-type allele. Finally, we show that appropriately sensitized drives in two dimensions can be stopped even by imperfect barriers perforated by a series of gaps. |
1902.07601 | Hugh Trenchard Mr. | Hugh Trenchard | Cell pelotons: a model of early evolutionary cell sorting, with
application to slime mold D. discoideum | 41 pages, 8 figures, 1 appendix, accepted manuscript in press | null | 10.1016/j.jtbi.2019.02.011 | null | q-bio.PE q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A theoretical model is presented for early evolutionary cell sorting within
cellular aggregates. The model involves an energy-saving mechanism and
principles of collective self-organization analogous to those observed in
bicycle pelotons (groups of cyclists). The theoretical framework is applied to
slime-mold slugs (Dictyostelium discoideum) and incorporated into a computer
simulation which demonstrates principally the sorting of cells between the
anterior and posterior slug regions. The simulation relies on an existing
simulation of bicycle peloton dynamics which is modified to incorporate a
limited range of cell metabolic capacities among heterogeneous cells, along
with a tunable energy-expenditure parameter, referred to as an 'output-level'
or 'starvation-level' to reflect diminishing energetic supply, proto-cellular
dynamics are modelled for three output phases: 'active', 'suffering', and
'dying or dead.' Adjusting the starvation parameter causes cell differentiation
and sorting into sub-groups within the cellular aggregate. Tuning of the
starvation parameter demonstrates how weak or expired cells shuffle backward
within the cellular aggregate.
| [
{
"created": "Wed, 20 Feb 2019 15:39:30 GMT",
"version": "v1"
}
] | 2019-02-21 | [
[
"Trenchard",
"Hugh",
""
]
] | A theoretical model is presented for early evolutionary cell sorting within cellular aggregates. The model involves an energy-saving mechanism and principles of collective self-organization analogous to those observed in bicycle pelotons (groups of cyclists). The theoretical framework is applied to slime-mold slugs (Dictyostelium discoideum) and incorporated into a computer simulation which demonstrates principally the sorting of cells between the anterior and posterior slug regions. The simulation relies on an existing simulation of bicycle peloton dynamics which is modified to incorporate a limited range of cell metabolic capacities among heterogeneous cells, along with a tunable energy-expenditure parameter, referred to as an 'output-level' or 'starvation-level' to reflect diminishing energetic supply, proto-cellular dynamics are modelled for three output phases: 'active', 'suffering', and 'dying or dead.' Adjusting the starvation parameter causes cell differentiation and sorting into sub-groups within the cellular aggregate. Tuning of the starvation parameter demonstrates how weak or expired cells shuffle backward within the cellular aggregate. |
1710.08405 | Peter Foster | Bryan Kaye, Olivia Stiehl, Peter J. Foster, Michael J. Shelley, Daniel
J. Needleman, Sebastian F\"urthauer | Measuring and modeling polymer gradients argues that spindle
microtubules regulate their own nucleation | null | null | 10.1088/1367-2630/aac2a5 | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Spindles are self-organized microtubule-based structures that segregate
chromosomes during cell division. The mass of the spindle is controlled by the
balance between microtubule turnover and nucleation. The mechanisms that
control the spatial regulation of microtubule nucleation remain poorly
understood. Previous work has found that microtubule nucleators bind to
microtubules in the spindle, but it is unclear if this binding regulates the
activity of those nucleators. Here we use a combination of experiments and
mathematical modeling to investigate this issue. We measure the concentration
of tubulin and microtubules in and around the spindle. We found a very sharp
decay in microtubules at the spindle interface, which is inconsistent with the
activity of microtubule nucleators being independent of their association with
microtubules and consistent with a model in which microtubule nucleators are
only active when bound to a microtubule. This strongly argues that the activity
of microtubule nucleators is greatly enhanced when bound to microtubules. Thus,
microtubule nucleators are both localized and activated by the microtubules
they generate.
| [
{
"created": "Mon, 23 Oct 2017 17:54:21 GMT",
"version": "v1"
}
] | 2018-06-13 | [
[
"Kaye",
"Bryan",
""
],
[
"Stiehl",
"Olivia",
""
],
[
"Foster",
"Peter J.",
""
],
[
"Shelley",
"Michael J.",
""
],
[
"Needleman",
"Daniel J.",
""
],
[
"Fürthauer",
"Sebastian",
""
]
] | Spindles are self-organized microtubule-based structures that segregate chromosomes during cell division. The mass of the spindle is controlled by the balance between microtubule turnover and nucleation. The mechanisms that control the spatial regulation of microtubule nucleation remain poorly understood. Previous work has found that microtubule nucleators bind to microtubules in the spindle, but it is unclear if this binding regulates the activity of those nucleators. Here we use a combination of experiments and mathematical modeling to investigate this issue. We measure the concentration of tubulin and microtubules in and around the spindle. We found a very sharp decay in microtubules at the spindle interface, which is inconsistent with the activity of microtubule nucleators being independent of their association with microtubules and consistent with a model in which microtubule nucleators are only active when bound to a microtubule. This strongly argues that the activity of microtubule nucleators is greatly enhanced when bound to microtubules. Thus, microtubule nucleators are both localized and activated by the microtubules they generate. |
1205.0381 | Sayantari Ghosh | Indrani Bose and Sayantari Ghosh | Origins of Binary Gene Expression in Post-transcriptional Regulation by
MicroRNAs | 10 Pages, 5 Figures | Eur. Phys. J. E (2012) 35:102 | null | null | q-bio.QM q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | MicroRNA-mediated regulation of gene expression is characterised by some
distinctive features that set it apart from unregulated and transcription
factor-regulated gene expression. Recently, a mathematical model has been
proposed to describe the dynamics of post-transcriptional regulation by
microRNAs. The model explains the observations made in single cell experiments
quite well. In this paper, we introduce some additional features into the model
and consider two specific cases. In the first case, a non-cooperative positive
feedback loop is included in the transcriptional regulation of the target gene
expression. In the second case, a stochastic version of the original model is
considered in which there are random transitions between the inactive and
active expression states of the gene. In the first case we show that
bistability is possible in a parameter regime, due to the presence of a
non-linear protein decay term in the gene expression dynamics. In the second
case, we derive the conditions for obtaining stochastic binary gene expression.
We find that this type of gene expression is more favourable in the case of
regulation by microRNAs as compared to the case of unregulated gene expression.
The theoretical predictions relating to binary gene expression are
experimentally testable.
| [
{
"created": "Wed, 2 May 2012 11:08:36 GMT",
"version": "v1"
},
{
"created": "Wed, 13 Jun 2012 09:32:02 GMT",
"version": "v2"
},
{
"created": "Thu, 18 Oct 2012 10:09:55 GMT",
"version": "v3"
}
] | 2012-10-19 | [
[
"Bose",
"Indrani",
""
],
[
"Ghosh",
"Sayantari",
""
]
] | MicroRNA-mediated regulation of gene expression is characterised by some distinctive features that set it apart from unregulated and transcription factor-regulated gene expression. Recently, a mathematical model has been proposed to describe the dynamics of post-transcriptional regulation by microRNAs. The model explains the observations made in single cell experiments quite well. In this paper, we introduce some additional features into the model and consider two specific cases. In the first case, a non-cooperative positive feedback loop is included in the transcriptional regulation of the target gene expression. In the second case, a stochastic version of the original model is considered in which there are random transitions between the inactive and active expression states of the gene. In the first case we show that bistability is possible in a parameter regime, due to the presence of a non-linear protein decay term in the gene expression dynamics. In the second case, we derive the conditions for obtaining stochastic binary gene expression. We find that this type of gene expression is more favourable in the case of regulation by microRNAs as compared to the case of unregulated gene expression. The theoretical predictions relating to binary gene expression are experimentally testable. |
2210.02366 | Rayanne Luke | Rayanne A. Luke and Anthony J. Kearsley and Paul N. Patrone | Optimal classification and generalized prevalence estimates for
diagnostic settings with more than two classes | 28 pages, 8 figures, 4 tables, 4 supplemental figures | null | 10.1016/j.mbs.2023.108982 | null | q-bio.QM math.OC math.PR physics.bio-ph stat.ME | http://creativecommons.org/licenses/by/4.0/ | An accurate multiclass classification strategy is crucial to interpreting
antibody tests. However, traditional methods based on confidence intervals or
receiver operating characteristics lack clear extensions to settings with more
than two classes. We address this problem by developing a multiclass
classification based on probabilistic modeling and optimal decision theory that
minimizes the convex combination of false classification rates. The
classification process is challenging when the relative fraction of the
population in each class, or generalized prevalence, is unknown. Thus, we also
develop a method for estimating the generalized prevalence of test data that is
independent of classification. We validate our approach on serological data
with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) na\"ive,
previously infected, and vaccinated classes. Synthetic data are used to
demonstrate that (i) prevalence estimates are unbiased and converge to true
values and (ii) our procedure applies to arbitrary measurement dimensions. In
contrast to the binary problem, the multiclass setting offers wide-reaching
utility as the most general framework and provides new insight into prevalence
estimation best practices.
| [
{
"created": "Wed, 5 Oct 2022 16:13:42 GMT",
"version": "v1"
}
] | 2024-05-07 | [
[
"Luke",
"Rayanne A.",
""
],
[
"Kearsley",
"Anthony J.",
""
],
[
"Patrone",
"Paul N.",
""
]
] | An accurate multiclass classification strategy is crucial to interpreting antibody tests. However, traditional methods based on confidence intervals or receiver operating characteristics lack clear extensions to settings with more than two classes. We address this problem by developing a multiclass classification based on probabilistic modeling and optimal decision theory that minimizes the convex combination of false classification rates. The classification process is challenging when the relative fraction of the population in each class, or generalized prevalence, is unknown. Thus, we also develop a method for estimating the generalized prevalence of test data that is independent of classification. We validate our approach on serological data with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) na\"ive, previously infected, and vaccinated classes. Synthetic data are used to demonstrate that (i) prevalence estimates are unbiased and converge to true values and (ii) our procedure applies to arbitrary measurement dimensions. In contrast to the binary problem, the multiclass setting offers wide-reaching utility as the most general framework and provides new insight into prevalence estimation best practices. |
1602.01876 | Christophe Dessimoz | Pascale Gaudet, Nives \v{S}kunca, James C. Hu, Christophe Dessimoz | Primer on the Gene Ontology | to appear in forthcoming book "The Gene Ontology Handbook" (Springer
Humana) | The Gene Ontology Handbook (Springer, New York), 25-37 (2016) | 10.1007/978-1-4939-3743-1_3 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Gene Ontology (GO) project is the largest resource for cataloguing gene
function. The combination of solid conceptual underpinnings and a practical set
of features have made the GO a widely adopted resource in the research
community and an essential resource for data analysis. In this chapter, we
provide a concise primer for all users of the GO. We briefly introduce the
structure of the ontology and explain how to interpret annotations associated
with the GO.
| [
{
"created": "Thu, 4 Feb 2016 22:55:46 GMT",
"version": "v1"
}
] | 2016-12-07 | [
[
"Gaudet",
"Pascale",
""
],
[
"Škunca",
"Nives",
""
],
[
"Hu",
"James C.",
""
],
[
"Dessimoz",
"Christophe",
""
]
] | The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essential resource for data analysis. In this chapter, we provide a concise primer for all users of the GO. We briefly introduce the structure of the ontology and explain how to interpret annotations associated with the GO. |
1712.02851 | Mario V Balzan | M V Balzan, J Caruana, A Zammit | Assessing the capacity and flow of ecosystem services in multifunctional
landscapes: evidence of a rural-urban gradient in a Mediterranean small
island state | null | null | 10.1016/j.landusepol.2017.08.025 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Distinguishing between the capacity of ecosystems to generate ecosystem
services (ES) and the actual use of these service (ES flow) in ES assessment
and mapping is important to develop an understanding of the sustainability of
ES use. This study assesses the spatial variation in ES capacity and flow in
the Mediterranean small island state of Malta. The services included in this
study were crop provisioning, beekeeping and honey production, fodder and
livestock production, crop pollination, air quality regulation, and aesthetic
ES. This assessment develops different spatial models, which make use of
available datasets, causal relationships between datasets, including a
generated land use land cover (LULC) map, and statistical models and indicators
based on direct measurements. Individual ES indicators were mapped to visualise
and compare their spatial patterns across the case study area. Subsequently, an
analysis of ES associations and bundles was carried out using Pearson
parametric correlation test, for both ES capacity and flow indicators generated
from this study, and through Principal Component Analysis. Results demonstrate
several significant synergistic interactions between ES capacity and flow in
rural landscapes characterised with agricultural and semi-natural LULC
categories, indicating high landscape multifunctionality. In contrast,
predominantly urban areas tend to be characterised with a low ecosystem
capacity and ES flow, suggesting that ES delivery in the landscapes of the
study area is determined by land use intensity. These findings support the
notion that multifunctional rural landscapes provide multiple ES, making an
important contribution to human well-being, and that land use planning that
develops green infrastructure in urban areas can significantly contribute to
support biodiversity and ES delivery.
| [
{
"created": "Thu, 7 Dec 2017 20:10:50 GMT",
"version": "v1"
}
] | 2018-03-21 | [
[
"Balzan",
"M V",
""
],
[
"Caruana",
"J",
""
],
[
"Zammit",
"A",
""
]
] | Distinguishing between the capacity of ecosystems to generate ecosystem services (ES) and the actual use of these service (ES flow) in ES assessment and mapping is important to develop an understanding of the sustainability of ES use. This study assesses the spatial variation in ES capacity and flow in the Mediterranean small island state of Malta. The services included in this study were crop provisioning, beekeeping and honey production, fodder and livestock production, crop pollination, air quality regulation, and aesthetic ES. This assessment develops different spatial models, which make use of available datasets, causal relationships between datasets, including a generated land use land cover (LULC) map, and statistical models and indicators based on direct measurements. Individual ES indicators were mapped to visualise and compare their spatial patterns across the case study area. Subsequently, an analysis of ES associations and bundles was carried out using Pearson parametric correlation test, for both ES capacity and flow indicators generated from this study, and through Principal Component Analysis. Results demonstrate several significant synergistic interactions between ES capacity and flow in rural landscapes characterised with agricultural and semi-natural LULC categories, indicating high landscape multifunctionality. In contrast, predominantly urban areas tend to be characterised with a low ecosystem capacity and ES flow, suggesting that ES delivery in the landscapes of the study area is determined by land use intensity. These findings support the notion that multifunctional rural landscapes provide multiple ES, making an important contribution to human well-being, and that land use planning that develops green infrastructure in urban areas can significantly contribute to support biodiversity and ES delivery. |
1411.1553 | Vadim Volkov S | Vadim Volkov | Salinity tolerance in plants: attempts to manipulate ion transport | 67 pages, 9 figures | null | null | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Ion transport is the major determining factor of salinity tolerance in
plants. A simple scheme of a plant cell with ion fluxes provides basic
understanding of ion transport and the corresponding changes of ion
concentrations under salinity. The review describes in detail basic principles
of ion transport for a plant cell, introduces set of transporters essential for
sodium and potassium uptake and efflux, analyses driving forces of ion
transport and compares ion fluxes measured by several techniques. Study of
differences in ion transport between salt tolerant halophytes and
salt-sensitive plants with an emphasis on transport of potassium and sodium via
plasma membranes offers knowledge for increasing salinity tolerance. Effects of
salt stress on ion transport properties of membranes show huge opportunities
for manipulating ion transport. Several attempts to overexpress or knockout ion
transporters for changing salinity tolerance are described. Future perspectives
are questioned with more attention given to potential candidate ion channels
and transporters for altered expression. The potential direction of increasing
salinity tolerance by modifying ion channels and transporters is discussed and
questioned. An alternative approach from synthetic biology is to modify the
existing membrane transport proteins or create new ones with desired properties
for transforming agricultural crops. The approach had not been widely used
earlier and leads also to theoretical and pure scientific aspects of protein
chemistry, structure-function relations of membrane proteins, systems biology
and physiology of stress and ion homeostasis.
| [
{
"created": "Thu, 6 Nov 2014 10:24:21 GMT",
"version": "v1"
}
] | 2014-11-07 | [
[
"Volkov",
"Vadim",
""
]
] | Ion transport is the major determining factor of salinity tolerance in plants. A simple scheme of a plant cell with ion fluxes provides basic understanding of ion transport and the corresponding changes of ion concentrations under salinity. The review describes in detail basic principles of ion transport for a plant cell, introduces set of transporters essential for sodium and potassium uptake and efflux, analyses driving forces of ion transport and compares ion fluxes measured by several techniques. Study of differences in ion transport between salt tolerant halophytes and salt-sensitive plants with an emphasis on transport of potassium and sodium via plasma membranes offers knowledge for increasing salinity tolerance. Effects of salt stress on ion transport properties of membranes show huge opportunities for manipulating ion transport. Several attempts to overexpress or knockout ion transporters for changing salinity tolerance are described. Future perspectives are questioned with more attention given to potential candidate ion channels and transporters for altered expression. The potential direction of increasing salinity tolerance by modifying ion channels and transporters is discussed and questioned. An alternative approach from synthetic biology is to modify the existing membrane transport proteins or create new ones with desired properties for transforming agricultural crops. The approach had not been widely used earlier and leads also to theoretical and pure scientific aspects of protein chemistry, structure-function relations of membrane proteins, systems biology and physiology of stress and ion homeostasis. |
1704.05687 | Sayan Nag | Archi Banerjee, Shankha Sanyal, Souparno Roy, Sourya Sengupta, Sayan
Biswas, Sayan Nag, Ranjan Sengupta and Dipak Ghosh | Neural (EEG) Response during Creation and Appreciation: A Novel Study
with Hindustani Raga Music | 14 pages, 5 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | What happens inside the performers brain when he is performing and composing
a particular raga. Are there some specific regions in brain which are activated
when an artist is creating or imaging a raga in his brain. Do the regions
remain the same when the artist is listening to the same raga sung by him.
These are the questions that perplexed neuroscientists for a long time. In this
study we strive to answer these questions by using latest state of the art
techniques to assess brain response. An EEG experiment was conducted for two
eminent performers of Indian classical music, when they mentally created the
imagery of a raga Jay Jayanti in their mind, as well as when they listened to
the same raga. The beauty of Hindustani music lies in the fact that the
musician is himself the composer and recreates the imagery of the raga in his
mind while performing, hence the scope of creative improvisations are immense.
The alpha and theta frequency rhythms were segregated from each of the time
series data and analyzed using robust non MFDXA technique to quantitatively
assess the degree of cross-correlation of each EEG frequency rhythm in
different combination of electrodes from frontal, occipital and temporal lobes.
A strong response was found in the occipital and fronto occipital region during
mental improvisation of the raga, which is an interesting revelation of this
study. Strong retentive features were obtained in regard to both alpha and
theta rhythms in musical listening in the fronto temporal and occipital
temporal region while the features were almost absent in the thinking part.
Further, other specific regions have been identified separately for the two
separate conditions in which the correlations among the different lobes were
the strongest.
| [
{
"created": "Wed, 19 Apr 2017 11:01:20 GMT",
"version": "v1"
}
] | 2017-04-20 | [
[
"Banerjee",
"Archi",
""
],
[
"Sanyal",
"Shankha",
""
],
[
"Roy",
"Souparno",
""
],
[
"Sengupta",
"Sourya",
""
],
[
"Biswas",
"Sayan",
""
],
[
"Nag",
"Sayan",
""
],
[
"Sengupta",
"Ranjan",
""
],
[
"Ghosh",
"Dipak",
""
]
] | What happens inside the performers brain when he is performing and composing a particular raga. Are there some specific regions in brain which are activated when an artist is creating or imaging a raga in his brain. Do the regions remain the same when the artist is listening to the same raga sung by him. These are the questions that perplexed neuroscientists for a long time. In this study we strive to answer these questions by using latest state of the art techniques to assess brain response. An EEG experiment was conducted for two eminent performers of Indian classical music, when they mentally created the imagery of a raga Jay Jayanti in their mind, as well as when they listened to the same raga. The beauty of Hindustani music lies in the fact that the musician is himself the composer and recreates the imagery of the raga in his mind while performing, hence the scope of creative improvisations are immense. The alpha and theta frequency rhythms were segregated from each of the time series data and analyzed using robust non MFDXA technique to quantitatively assess the degree of cross-correlation of each EEG frequency rhythm in different combination of electrodes from frontal, occipital and temporal lobes. A strong response was found in the occipital and fronto occipital region during mental improvisation of the raga, which is an interesting revelation of this study. Strong retentive features were obtained in regard to both alpha and theta rhythms in musical listening in the fronto temporal and occipital temporal region while the features were almost absent in the thinking part. Further, other specific regions have been identified separately for the two separate conditions in which the correlations among the different lobes were the strongest. |
1708.01280 | Sa\'ul Buitrago Boret | Sa\'ul E. Buitrago Boret and Ren\'e Escalante and Minaya Villasana | Mathematical modelling of zika virus in Brazil | null | null | null | null | q-bio.PE q-bio.QM | http://creativecommons.org/licenses/by-sa/4.0/ | In this paper we study some deterministic mathematical models that seek to
explain the expansion of zika virus, as a viral epidemic, using published data
for Brazil. SIR type models are proposed and validated using the epidemic data
found, considering several aspects in the spread of the disease. Finally, we
confirmed that the crucial epidemic parameter such as $R_0$ is consistent with
those previously reported in the literature for other areas. We also explored
variations of the parameters within Brazil for different federal entities. We
concluded that a parsimonious model that includes both human and vector
populations best describe the epidemic parameters.
| [
{
"created": "Thu, 3 Aug 2017 18:58:39 GMT",
"version": "v1"
},
{
"created": "Mon, 23 Jan 2023 02:32:27 GMT",
"version": "v2"
}
] | 2023-01-24 | [
[
"Boret",
"Saúl E. Buitrago",
""
],
[
"Escalante",
"René",
""
],
[
"Villasana",
"Minaya",
""
]
] | In this paper we study some deterministic mathematical models that seek to explain the expansion of zika virus, as a viral epidemic, using published data for Brazil. SIR type models are proposed and validated using the epidemic data found, considering several aspects in the spread of the disease. Finally, we confirmed that the crucial epidemic parameter such as $R_0$ is consistent with those previously reported in the literature for other areas. We also explored variations of the parameters within Brazil for different federal entities. We concluded that a parsimonious model that includes both human and vector populations best describe the epidemic parameters. |
2108.08143 | Imdadullah Khan | Sarwan Ali, Tamkanat-E-Ali, Muhammad Asad Khan, Imdadullah Khan,
Murray Patterson | Effective and scalable clustering of SARS-CoV-2 sequences | To Appear in: International Conference on Big Data Research (ICBDR) | null | null | null | q-bio.PE cs.LG | http://creativecommons.org/publicdomain/zero/1.0/ | SARS-CoV-2, like any other virus, continues to mutate as it spreads,
according to an evolutionary process. Unlike any other virus, the number of
currently available sequences of SARS-CoV-2 in public databases such as GISAID
is already several million. This amount of data has the potential to uncover
the evolutionary dynamics of a virus like never before. However, a million is
already several orders of magnitude beyond what can be processed by the
traditional methods designed to reconstruct a virus's evolutionary history,
such as those that build a phylogenetic tree. Hence, new and scalable methods
will need to be devised in order to make use of the ever increasing number of
viral sequences being collected.
Since identifying variants is an important part of understanding the
evolution of a virus, in this paper, we propose an approach based on clustering
sequences to identify the current major SARS-CoV-2 variants. Using a $k$-mer
based feature vector generation and efficient feature selection methods, our
approach is effective in identifying variants, as well as being efficient and
scalable to millions of sequences. Such a clustering method allows us to show
the relative proportion of each variant over time, giving the rate of spread of
each variant in different locations -- something which is important for vaccine
development and distribution. We also compute the importance of each amino acid
position of the spike protein in identifying a given variant in terms of
information gain. Positions of high variant-specific importance tend to agree
with those reported by the USA's Centers for Disease Control and Prevention
(CDC), further demonstrating our approach.
| [
{
"created": "Wed, 18 Aug 2021 13:32:43 GMT",
"version": "v1"
},
{
"created": "Wed, 25 Aug 2021 07:32:11 GMT",
"version": "v2"
},
{
"created": "Mon, 6 Sep 2021 13:13:57 GMT",
"version": "v3"
},
{
"created": "Fri, 10 Sep 2021 01:22:08 GMT",
"version": "v4"
},
{
"created": "Tue, 12 Oct 2021 14:33:37 GMT",
"version": "v5"
}
] | 2021-10-13 | [
[
"Ali",
"Sarwan",
""
],
[
"Tamkanat-E-Ali",
"",
""
],
[
"Khan",
"Muhammad Asad",
""
],
[
"Khan",
"Imdadullah",
""
],
[
"Patterson",
"Murray",
""
]
] | SARS-CoV-2, like any other virus, continues to mutate as it spreads, according to an evolutionary process. Unlike any other virus, the number of currently available sequences of SARS-CoV-2 in public databases such as GISAID is already several million. This amount of data has the potential to uncover the evolutionary dynamics of a virus like never before. However, a million is already several orders of magnitude beyond what can be processed by the traditional methods designed to reconstruct a virus's evolutionary history, such as those that build a phylogenetic tree. Hence, new and scalable methods will need to be devised in order to make use of the ever increasing number of viral sequences being collected. Since identifying variants is an important part of understanding the evolution of a virus, in this paper, we propose an approach based on clustering sequences to identify the current major SARS-CoV-2 variants. Using a $k$-mer based feature vector generation and efficient feature selection methods, our approach is effective in identifying variants, as well as being efficient and scalable to millions of sequences. Such a clustering method allows us to show the relative proportion of each variant over time, giving the rate of spread of each variant in different locations -- something which is important for vaccine development and distribution. We also compute the importance of each amino acid position of the spike protein in identifying a given variant in terms of information gain. Positions of high variant-specific importance tend to agree with those reported by the USA's Centers for Disease Control and Prevention (CDC), further demonstrating our approach. |
1303.6737 | Elisenda Feliu | Elisenda Feliu and Carsten Wiuf | Simplifying Biochemical Models With Intermediate Species | Published in the Journal of the Royal Society Interace. The proof of
Proposition 2 in the originally published file was erroneus. The result is
though correct and the proof has now been fixed. We thank Magali Giaroli from
the University of Buenos Aires for pointing out the error in the proof | null | 10.1098/rsif.2013.0484 | null | q-bio.MN math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mathematical models are increasingly being used to understand complex
biochemical systems, to analyze experimental data and make predictions about
unobserved quantities. However, we rarely know how robust our conclusions are
with respect to the choice and uncertainties of the model. Using algebraic
techniques we study systematically the effects of intermediate, or transient,
species in biochemical systems and provide a simple, yet rigorous mathematical
classification of all models obtained from a core model by including
intermediates. Main examples include enzymatic and post-translational
modification systems, where intermediates often are considered insignificant
and neglected in a model, or they are not included because we are unaware of
their existence. All possible models obtained from the core model are
classified into a finite number of classes. Each class is defined by a
mathematically simple canonical model that characterizes crucial dynamical
properties, such as mono- and multistationarity and stability of steady states,
of all models in the class. We show that if the core model does not have
conservation laws, then the introduction of intermediates does not change the
steady-state concentrations of the species in the core model, after suitable
matching of parameters. Importantly, our results provide guidelines to the
modeler in choosing between models and in distinguishing their properties.
Further, our work provides a formal way of comparing models that share a common
skeleton.
| [
{
"created": "Wed, 27 Mar 2013 04:07:34 GMT",
"version": "v1"
},
{
"created": "Mon, 1 Jul 2013 14:35:07 GMT",
"version": "v2"
},
{
"created": "Wed, 4 Nov 2015 21:49:09 GMT",
"version": "v3"
}
] | 2015-11-06 | [
[
"Feliu",
"Elisenda",
""
],
[
"Wiuf",
"Carsten",
""
]
] | Mathematical models are increasingly being used to understand complex biochemical systems, to analyze experimental data and make predictions about unobserved quantities. However, we rarely know how robust our conclusions are with respect to the choice and uncertainties of the model. Using algebraic techniques we study systematically the effects of intermediate, or transient, species in biochemical systems and provide a simple, yet rigorous mathematical classification of all models obtained from a core model by including intermediates. Main examples include enzymatic and post-translational modification systems, where intermediates often are considered insignificant and neglected in a model, or they are not included because we are unaware of their existence. All possible models obtained from the core model are classified into a finite number of classes. Each class is defined by a mathematically simple canonical model that characterizes crucial dynamical properties, such as mono- and multistationarity and stability of steady states, of all models in the class. We show that if the core model does not have conservation laws, then the introduction of intermediates does not change the steady-state concentrations of the species in the core model, after suitable matching of parameters. Importantly, our results provide guidelines to the modeler in choosing between models and in distinguishing their properties. Further, our work provides a formal way of comparing models that share a common skeleton. |
q-bio/0609013 | Per Arne Rikvold | Per Arne Rikvold | Complex Behavior in Simple Models of Biological Coevolution | 8 pages, 5 figures | Int. J. Mod. Phys. C 20, 1387-1397 (2009) | 10.1142/S012918310901445X | null | q-bio.PE cond-mat.stat-mech nlin.AO | null | We explore the complex dynamical behavior of simple predator-prey models of
biological coevolution that account for interspecific and intraspecific
competition for resources, as well as adaptive foraging behavior. In long
kinetic Monte Carlo simulations of these models we find quite robust 1/f-like
noise in species diversity and population sizes, as well as power-law
distributions for the lifetimes of individual species and the durations of
quiet periods of relative evolutionary stasis. In one model, based on the
Holling Type II functional response, adaptive foraging produces a metastable
low-diversity phase and a stable high-diversity phase.
| [
{
"created": "Fri, 8 Sep 2006 19:59:45 GMT",
"version": "v1"
}
] | 2009-10-26 | [
[
"Rikvold",
"Per Arne",
""
]
] | We explore the complex dynamical behavior of simple predator-prey models of biological coevolution that account for interspecific and intraspecific competition for resources, as well as adaptive foraging behavior. In long kinetic Monte Carlo simulations of these models we find quite robust 1/f-like noise in species diversity and population sizes, as well as power-law distributions for the lifetimes of individual species and the durations of quiet periods of relative evolutionary stasis. In one model, based on the Holling Type II functional response, adaptive foraging produces a metastable low-diversity phase and a stable high-diversity phase. |
q-bio/0703067 | Emilio Hernandez-Garcia | E. Hernandez-Garcia, E. A. Herrada, A. F. Rozenfeld, C. J. Tessone, V.
M. Eguiluz, C. M. Duarte, S. Arnaud-Haond, and E. Serrao | Evolutionary and Ecological Trees and Networks | 6 pages, 5 figures. To appear in Proceedings of the Medyfinol06
Conference | in Nonequilibrium Statistical Mechanics and Nonlinear Physics, Ed.
by O. Descalzi, O.A. Rosso and H.A. Larrondo. AIP Conference Proceedings
Volume 913, American Institute of Physics (New York, 2007), pp. 78-83 | 10.1063/1.2746728 | null | q-bio.PE cond-mat.stat-mech q-bio.QM | null | Evolutionary relationships between species are usually represented in
phylogenies, i.e. evolutionary trees, which are a type of networks. The
terminal nodes of these trees represent species, which are made of individuals
and populations among which gene flow occurs. This flow can also be represented
as a network. In this paper we briefly show some properties of these complex
networks of evolutionary and ecological relationships. First, we characterize
large scale evolutionary relationships in the Tree of Life by a degree
distribution. Second, we represent genetic relationships between individuals of
a Mediterranean marine plant, Posidonia oceanica, in terms of a Minimum
Spanning Tree. Finally, relationships among plant shoots inside populations are
represented as networks of genetic similarity.
| [
{
"created": "Fri, 30 Mar 2007 13:54:45 GMT",
"version": "v1"
}
] | 2007-07-11 | [
[
"Hernandez-Garcia",
"E.",
""
],
[
"Herrada",
"E. A.",
""
],
[
"Rozenfeld",
"A. F.",
""
],
[
"Tessone",
"C. J.",
""
],
[
"Eguiluz",
"V. M.",
""
],
[
"Duarte",
"C. M.",
""
],
[
"Arnaud-Haond",
"S.",
""
],
[
"Serrao",
"E.",
""
]
] | Evolutionary relationships between species are usually represented in phylogenies, i.e. evolutionary trees, which are a type of networks. The terminal nodes of these trees represent species, which are made of individuals and populations among which gene flow occurs. This flow can also be represented as a network. In this paper we briefly show some properties of these complex networks of evolutionary and ecological relationships. First, we characterize large scale evolutionary relationships in the Tree of Life by a degree distribution. Second, we represent genetic relationships between individuals of a Mediterranean marine plant, Posidonia oceanica, in terms of a Minimum Spanning Tree. Finally, relationships among plant shoots inside populations are represented as networks of genetic similarity. |
q-bio/0401026 | Yisroel Brumer | Yisroel Brumer and Eugene I. Shakhnovich | Host-Parasite Co-evolution and Optimal Mutation Rates for
Semi-conservative Quasispecies | null | null | 10.1103/PhysRevE.69.061909 | null | q-bio.PE cond-mat.soft | null | In this paper, we extend a model of host-parasite co-evolution to incorporate
the semi-conservative nature of DNA replication for both the host and the
parasite. We find that the optimal mutation rate for the semi-conservative and
conservative hosts converge for realistic genome lengths, thus maintaining the
admirable agreement between theory and experiment found previously for the
conservative model and justifying the conservative approximation in some cases.
We demonstrate that, while the optimal mutation rate for a conservative and
semi-conservative parasite interacting with a given immune system is similar to
that of a conservative parasite, the properties away from this optimum differ
significantly. We suspect that this difference, coupled with the requirement
that a parasite optimize survival in a range of viable hosts, may help explain
why semi-conservative viruses are known to have significantly lower mutation
rates than their conservative counterparts.
| [
{
"created": "Tue, 20 Jan 2004 22:27:39 GMT",
"version": "v1"
}
] | 2009-11-10 | [
[
"Brumer",
"Yisroel",
""
],
[
"Shakhnovich",
"Eugene I.",
""
]
] | In this paper, we extend a model of host-parasite co-evolution to incorporate the semi-conservative nature of DNA replication for both the host and the parasite. We find that the optimal mutation rate for the semi-conservative and conservative hosts converge for realistic genome lengths, thus maintaining the admirable agreement between theory and experiment found previously for the conservative model and justifying the conservative approximation in some cases. We demonstrate that, while the optimal mutation rate for a conservative and semi-conservative parasite interacting with a given immune system is similar to that of a conservative parasite, the properties away from this optimum differ significantly. We suspect that this difference, coupled with the requirement that a parasite optimize survival in a range of viable hosts, may help explain why semi-conservative viruses are known to have significantly lower mutation rates than their conservative counterparts. |
q-bio/0401019 | Henry Stapp | J.M. Schwartz, H.P. Stapp, M. Beauregard | Quantum Physics in Neuroscience and Psychology: A New Theory With
Respect to Mind/Brain Interaction | 72 pages. Submitted to Behavior and Brain Sciences | null | null | LBNL 54290 | q-bio.NC | null | The cognitive frame in which most neuropsychological research on the neural
basis of behavior is conducted contains the assumption that brain mechanisms
per se fully suffice to explain all psychologically described phenomena. This
assumption stems from the idea that the brain is made up entirely of material
particles and fields, and that all causal mechanisms must therefore be
formulated solely in terms of properties of these elements. One consequence of
this stance is that psychological terms having intrinsic mentalistic and/or
experiential content (terms such as "feeling," "knowing," and "effort") have
not been included as primary causal factors in neuropsychological research:
insofar as properties are not described in material terms they are deemed
irrelevant to the causal mechanisms underlying brain function. However, the
origin of this demand that experiential realities be excluded from the causal
base is a theory of nature that has been known for more that three quarters of
a century to be fundamentally incorrect. It is explained here why it is
consequently scientifically unwarranted to assume that material factors alone
can in principle explain all causal mechanisms relevant to neuroscience. More
importantly, it is explained how a key quantum effect can be introduced into
brain dynamics in a simple and practical way that provides a rationally
coherent, causally formulated, physics-based way of understanding and using the
psychological and physical data derived from the growing set of studies of the
capacity of directed attention and mental effort to systematically alter brain
function.
| [
{
"created": "Wed, 14 Jan 2004 22:23:39 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Schwartz",
"J. M.",
""
],
[
"Stapp",
"H. P.",
""
],
[
"Beauregard",
"M.",
""
]
] | The cognitive frame in which most neuropsychological research on the neural basis of behavior is conducted contains the assumption that brain mechanisms per se fully suffice to explain all psychologically described phenomena. This assumption stems from the idea that the brain is made up entirely of material particles and fields, and that all causal mechanisms must therefore be formulated solely in terms of properties of these elements. One consequence of this stance is that psychological terms having intrinsic mentalistic and/or experiential content (terms such as "feeling," "knowing," and "effort") have not been included as primary causal factors in neuropsychological research: insofar as properties are not described in material terms they are deemed irrelevant to the causal mechanisms underlying brain function. However, the origin of this demand that experiential realities be excluded from the causal base is a theory of nature that has been known for more that three quarters of a century to be fundamentally incorrect. It is explained here why it is consequently scientifically unwarranted to assume that material factors alone can in principle explain all causal mechanisms relevant to neuroscience. More importantly, it is explained how a key quantum effect can be introduced into brain dynamics in a simple and practical way that provides a rationally coherent, causally formulated, physics-based way of understanding and using the psychological and physical data derived from the growing set of studies of the capacity of directed attention and mental effort to systematically alter brain function. |
1611.04781 | Bashar Ibrahim | Bashar Ibrahim | Modeling potent pathways for APC/C inhibition: pivotal roles for MCC and
BubR1 | Journal article as preprint | OMICS: A Journal of Integrative Biology. May 2015, 19(5): 294-305 | 10.1089/omi.2015.0027 | null | q-bio.MN math.AP math.DS q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The highly conserved spindle assembly checkpoint (SAC) ensures that the
sister chromatids of the duplicated genome are not separated and distributed to
the spindle poles before all chromosomes have been properly linked to the
microtubules of the mitotic spindle. Biochemically, the SAC delays cell cycle
progression by preventing activation of the anaphase-promoting complex (APC/C)
or cyclosome; whose activation by Cdc20 is required for sister-chromatid
separation, which marks the transition into anaphase. In response to activation
of the checkpoint, various species control the activity of both APC/C and
Cdc20. However, the underlying regulatory pathways remain largely elusive. In
this study, five possible model variants of APC/C regulation were constructed,
namely BubR1, Mad2, MCC, MCF2 and an all-pathways model variant. These models
are validated with experimental data from the literature. A wide range of
parameter values have been tested to find critical values of the APC binding
rate. The results show that all variants are able to capture the wild type
behaviour of the APC. However, only one model variant, which included both MCC
as well as BubR1 as potent inhibitors of the APC, was able to reproduce both
wild type and mutant type behaviour of APC regulation. The presented work has
successfully distinguished between five competing dynamical models of the same
biological system using a systems biology approach. Furthermore, the results
suggest that systems-level approach is vital for molecular biology and could
also be used for compare the pathways of relevance with the objective to
generate hypotheses and improve our understanding.
| [
{
"created": "Tue, 15 Nov 2016 10:41:05 GMT",
"version": "v1"
}
] | 2016-11-18 | [
[
"Ibrahim",
"Bashar",
""
]
] | The highly conserved spindle assembly checkpoint (SAC) ensures that the sister chromatids of the duplicated genome are not separated and distributed to the spindle poles before all chromosomes have been properly linked to the microtubules of the mitotic spindle. Biochemically, the SAC delays cell cycle progression by preventing activation of the anaphase-promoting complex (APC/C) or cyclosome; whose activation by Cdc20 is required for sister-chromatid separation, which marks the transition into anaphase. In response to activation of the checkpoint, various species control the activity of both APC/C and Cdc20. However, the underlying regulatory pathways remain largely elusive. In this study, five possible model variants of APC/C regulation were constructed, namely BubR1, Mad2, MCC, MCF2 and an all-pathways model variant. These models are validated with experimental data from the literature. A wide range of parameter values have been tested to find critical values of the APC binding rate. The results show that all variants are able to capture the wild type behaviour of the APC. However, only one model variant, which included both MCC as well as BubR1 as potent inhibitors of the APC, was able to reproduce both wild type and mutant type behaviour of APC regulation. The presented work has successfully distinguished between five competing dynamical models of the same biological system using a systems biology approach. Furthermore, the results suggest that systems-level approach is vital for molecular biology and could also be used for compare the pathways of relevance with the objective to generate hypotheses and improve our understanding. |
2011.10301 | Maarten Wensink | M. J. Wensink | Perturbations of lifespan inequality in natural populations | 14 pages, 0 figures | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Correlations between high life expectancy and low lifespan inequality are
frequently observed. A recent article seeks to explain this phenomenon by
proposing that a mortality improvement maps to life expectancy and relative
lifespan equality through the same weights w(x), with an extra weight W(x)
applied for relative lifespan equality, specific for the equality indicator
used. From statistical theory, the claim that changes of life expectancy and
lifespan (in)equality map through the same weights is unexpected.
The current note explains this phenomenon by showing that W(x) undoes (part
of) w(x). Thus, while the change in relative lifespan equality is proportional
to the product of both weights, w(x)W(x), it is proportional to neither w(x)
nor W(x). As a result, some simplification is possible that gives way to an
intuitive understanding and a more direct interpretation of the perturbation
analysis proposed.
| [
{
"created": "Fri, 20 Nov 2020 09:52:30 GMT",
"version": "v1"
}
] | 2020-11-23 | [
[
"Wensink",
"M. J.",
""
]
] | Correlations between high life expectancy and low lifespan inequality are frequently observed. A recent article seeks to explain this phenomenon by proposing that a mortality improvement maps to life expectancy and relative lifespan equality through the same weights w(x), with an extra weight W(x) applied for relative lifespan equality, specific for the equality indicator used. From statistical theory, the claim that changes of life expectancy and lifespan (in)equality map through the same weights is unexpected. The current note explains this phenomenon by showing that W(x) undoes (part of) w(x). Thus, while the change in relative lifespan equality is proportional to the product of both weights, w(x)W(x), it is proportional to neither w(x) nor W(x). As a result, some simplification is possible that gives way to an intuitive understanding and a more direct interpretation of the perturbation analysis proposed. |
1902.07650 | Maria Florencia Noriega Romero Vargas | Florencia Noriega, Adolfo Christian Montes-Medina, and Marc Timme | Quantitative analysis of timing in animal vocal sequences | 10 pages, 10 figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Timing features such as the silence gaps between vocal units -- inter-call
intervals (ICIs) -- often correlate with biological information such as context
or genetic information. Such correlates between the ICIs and biological
information have been reported for a diversity of animals. Yet, few
quantitative approaches for investigating timing exist to date. Here, we
propose a novel approach for quantitatively comparing timing in animal
vocalisations in terms of the typical ICIs. As features, we use the
distribution of silence gaps parametrised with a kernel density estimate (KDE)
and compare the distributions with the symmetric Kullback-Leibler divergence
(sKL-divergence). We use this technique to compare timing in vocalisations of
two frog species, a group of zebra finches and calls from parrots of the same
species. As a main finding, we demonstrate that in our dataset, closely related
species have more similar distributions than species genetically more distant,
with sKL-divergences across-species larger than within-species distances.
Compared with more standard methods such as Fourier analysis, the proposed
method is more robust to different durations present in the data samples,
flexibly applicable to different species and easy to interpret. Investigating
timing in animal vocalisations may thus contribute to taxonomy, support
conservation efforts by helping monitoring animals in the wild and may shed
light onto the origins of timing structures in animal vocal communication.
| [
{
"created": "Wed, 20 Feb 2019 17:05:36 GMT",
"version": "v1"
}
] | 2019-02-21 | [
[
"Noriega",
"Florencia",
""
],
[
"Montes-Medina",
"Adolfo Christian",
""
],
[
"Timme",
"Marc",
""
]
] | Timing features such as the silence gaps between vocal units -- inter-call intervals (ICIs) -- often correlate with biological information such as context or genetic information. Such correlates between the ICIs and biological information have been reported for a diversity of animals. Yet, few quantitative approaches for investigating timing exist to date. Here, we propose a novel approach for quantitatively comparing timing in animal vocalisations in terms of the typical ICIs. As features, we use the distribution of silence gaps parametrised with a kernel density estimate (KDE) and compare the distributions with the symmetric Kullback-Leibler divergence (sKL-divergence). We use this technique to compare timing in vocalisations of two frog species, a group of zebra finches and calls from parrots of the same species. As a main finding, we demonstrate that in our dataset, closely related species have more similar distributions than species genetically more distant, with sKL-divergences across-species larger than within-species distances. Compared with more standard methods such as Fourier analysis, the proposed method is more robust to different durations present in the data samples, flexibly applicable to different species and easy to interpret. Investigating timing in animal vocalisations may thus contribute to taxonomy, support conservation efforts by helping monitoring animals in the wild and may shed light onto the origins of timing structures in animal vocal communication. |
2006.15385 | Stavros Maltezos | S. Maltezos | Methodology for Modelling the new COVID-19 Pandemic Spread and
Implementation to European Countries | 8 pages, 6 figures and 2 tables | null | null | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | After the breakout of the disease caused by the new virus COVID-19, the
mitigation stage has been reached in most of the countries in the world. During
this stage, a more accurate data analysis of the daily reported cases and other
parameters became possible for the European countries and has been performed in
this work. Based on a proposed parametrization model appropriate for
implementation to an epidemic in a large population, we focused on the disease
spread and we studied the obtained curves, as well as, we investigated probable
correlations between the country's characteristics and the parameters of the
parametrization. We have also developed a methodology for coupling our model to
the SIR-based models determining the basic and the effective reproductive
number referring to the parameter space. The obtained results and conclusions
could be useful in the case of a recurrence of this repulsive disease in the
future.
| [
{
"created": "Sat, 27 Jun 2020 15:25:32 GMT",
"version": "v1"
},
{
"created": "Tue, 30 Jun 2020 08:47:30 GMT",
"version": "v2"
}
] | 2020-07-01 | [
[
"Maltezos",
"S.",
""
]
] | After the breakout of the disease caused by the new virus COVID-19, the mitigation stage has been reached in most of the countries in the world. During this stage, a more accurate data analysis of the daily reported cases and other parameters became possible for the European countries and has been performed in this work. Based on a proposed parametrization model appropriate for implementation to an epidemic in a large population, we focused on the disease spread and we studied the obtained curves, as well as, we investigated probable correlations between the country's characteristics and the parameters of the parametrization. We have also developed a methodology for coupling our model to the SIR-based models determining the basic and the effective reproductive number referring to the parameter space. The obtained results and conclusions could be useful in the case of a recurrence of this repulsive disease in the future. |
q-bio/0410006 | Salvatore Miccich\`e | M. Spano, F. Lillo, S. Micciche, R. N. Mantegna | Inverted Repeats in Viral Genomes | 8 pages, 3 figures | Fluctuation and Noise Letters 5(2), L193-L200, (2005) | 10.1142/S0219477505002550 | null | q-bio.QM cond-mat.stat-mech q-bio.GN | null | We investigate 738 complete genomes of viruses to detect the presence of
short inverted repeats. The number of inverted repeats found is compared with
the prediction obtained for a Bernoullian and for a Markovian control model. We
find as a statistical regularity that the number of observed inverted repeats
is often greater than the one expected in terms of a Bernoullian or Markovian
model in several of the viruses and in almost all those with a genome longer
than 30,000 bp.
| [
{
"created": "Tue, 5 Oct 2004 13:32:54 GMT",
"version": "v1"
}
] | 2021-08-25 | [
[
"Spano",
"M.",
""
],
[
"Lillo",
"F.",
""
],
[
"Micciche",
"S.",
""
],
[
"Mantegna",
"R. N.",
""
]
] | We investigate 738 complete genomes of viruses to detect the presence of short inverted repeats. The number of inverted repeats found is compared with the prediction obtained for a Bernoullian and for a Markovian control model. We find as a statistical regularity that the number of observed inverted repeats is often greater than the one expected in terms of a Bernoullian or Markovian model in several of the viruses and in almost all those with a genome longer than 30,000 bp. |
1707.05182 | Robert Legenstein | Robert Legenstein, Zeno Jonke, Stefan Habenschuss and Wolfgang Maass | A probabilistic model for learning in cortical microcircuit motifs with
data-based divisive inhibition | 24 pages, 5 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Previous theoretical studies on the interaction of excitatory and inhibitory
neurons proposed to model this cortical microcircuit motif as a so-called
Winner-Take-All (WTA) circuit. A recent modeling study however found that the
WTA model is not adequate for data-based softer forms of divisive inhibition as
found in a microcircuit motif in cortical layer 2/3. We investigate here
through theoretical analysis the role of such softer divisive inhibition for
the emergence of computational operations and neural codes under spike-timing
dependent plasticity (STDP). We show that in contrast to WTA models - where the
network activity has been interpreted as probabilistic inference in a
generative mixture distribution - this network dynamics approximates inference
in a noisy-OR-like generative model that explains the network input based on
multiple hidden causes. Furthermore, we show that STDP optimizes the parameters
of this model by approximating online the expectation maximization (EM)
algorithm. This theoretical analysis corroborates a preceding modelling study
which suggested that the learning dynamics of this layer 2/3 microcircuit motif
extracts a specific modular representation of the input and thus performs blind
source separation on the input statistics.
| [
{
"created": "Mon, 17 Jul 2017 14:33:14 GMT",
"version": "v1"
}
] | 2018-03-27 | [
[
"Legenstein",
"Robert",
""
],
[
"Jonke",
"Zeno",
""
],
[
"Habenschuss",
"Stefan",
""
],
[
"Maass",
"Wolfgang",
""
]
] | Previous theoretical studies on the interaction of excitatory and inhibitory neurons proposed to model this cortical microcircuit motif as a so-called Winner-Take-All (WTA) circuit. A recent modeling study however found that the WTA model is not adequate for data-based softer forms of divisive inhibition as found in a microcircuit motif in cortical layer 2/3. We investigate here through theoretical analysis the role of such softer divisive inhibition for the emergence of computational operations and neural codes under spike-timing dependent plasticity (STDP). We show that in contrast to WTA models - where the network activity has been interpreted as probabilistic inference in a generative mixture distribution - this network dynamics approximates inference in a noisy-OR-like generative model that explains the network input based on multiple hidden causes. Furthermore, we show that STDP optimizes the parameters of this model by approximating online the expectation maximization (EM) algorithm. This theoretical analysis corroborates a preceding modelling study which suggested that the learning dynamics of this layer 2/3 microcircuit motif extracts a specific modular representation of the input and thus performs blind source separation on the input statistics. |
1409.1683 | Ugo Bastolla | Alberto Pascual-Garc\'ia, Antonio Ferrera and Ugo Bastolla | Does mutualism hinder biodiversity? | Submitted on October 2012 as a Brief Communication Arising from James
et al. Nature 487, 227-230 (2012) | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A recent paper by James et al. finds that mutualistic interactions decrease
the biodiversity of model ecosystems. However, this result can be reverted if
we consider ecological trade-offs and choose parameters suitable for sparse
mutualistic networks instead of fully connected networks.
| [
{
"created": "Fri, 5 Sep 2014 08:20:30 GMT",
"version": "v1"
}
] | 2014-09-08 | [
[
"Pascual-García",
"Alberto",
""
],
[
"Ferrera",
"Antonio",
""
],
[
"Bastolla",
"Ugo",
""
]
] | A recent paper by James et al. finds that mutualistic interactions decrease the biodiversity of model ecosystems. However, this result can be reverted if we consider ecological trade-offs and choose parameters suitable for sparse mutualistic networks instead of fully connected networks. |
1308.0699 | Ruth Nussinov | Ruth Nussinov | The spatial structure of cell signaling systems | 28 pages | Physical Biology 2013; 10(4) | 10.1088/1478-3975/10/4/045004 | null | q-bio.BM q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The spatial structure of the cell is highly organized at all levels: from
small complexes and assemblies, to local nano- and micro-clusters, to global,
micrometer scales across and between cells. We suggest that this multiscale
spatial cell organization also organizes signaling and coordinates cellular
behavior. We propose a new view of the spatial structure of cell signaling
systems. This new view describes cell signaling in terms of dynamic allosteric
interactions within and among distinct, spatially organized transient clusters.
The clusters vary over time and space and are on length scales from nanometers
to micrometers. When considered across these length-scales, primary factors in
the spatial organization are cell membrane domains and the actin cytoskeleton,
both also highly dynamic. A key challenge is to understand the interplay across
these multiple scales, link it to the physicochemical basis of the
conformational behavior of single molecules, and ultimately relate it to
cellular function. Overall, our premise is that at these scales, cell signaling
should be thought of not primarily as a sequence of diffusion-controlled
molecular collisions, but instead transient, allostery-driven cluster
re-forming interactions.
| [
{
"created": "Sat, 3 Aug 2013 14:09:42 GMT",
"version": "v1"
}
] | 2013-08-06 | [
[
"Nussinov",
"Ruth",
""
]
] | The spatial structure of the cell is highly organized at all levels: from small complexes and assemblies, to local nano- and micro-clusters, to global, micrometer scales across and between cells. We suggest that this multiscale spatial cell organization also organizes signaling and coordinates cellular behavior. We propose a new view of the spatial structure of cell signaling systems. This new view describes cell signaling in terms of dynamic allosteric interactions within and among distinct, spatially organized transient clusters. The clusters vary over time and space and are on length scales from nanometers to micrometers. When considered across these length-scales, primary factors in the spatial organization are cell membrane domains and the actin cytoskeleton, both also highly dynamic. A key challenge is to understand the interplay across these multiple scales, link it to the physicochemical basis of the conformational behavior of single molecules, and ultimately relate it to cellular function. Overall, our premise is that at these scales, cell signaling should be thought of not primarily as a sequence of diffusion-controlled molecular collisions, but instead transient, allostery-driven cluster re-forming interactions. |
2006.04954 | D. Delepine | Jose de Jesus Bernal-Alvarado and David Delepine (Guanajuato
University) | Morphology and numerical characteristics of epidemic curves for
SARS-Cov-II using Moyal distribution | 8 pages, 5 figures | null | null | null | q-bio.PE physics.med-ph physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, it is shown that the Moyal distribution is an excelent tool to
study the SARS-Cov-II (Covid-19) epidemiological associated curves and its
propagation. The Moyal parameters give all the information to describe the form
and the impact of the illness outbreak in the different affected countries and
its global impact. We checked that the Moyal distribution can accurately fit
the daily report of {\it{new confirmed cases of infected people}} (NCC) per
country, in that places where the contagion is reaching their final phase,
describing the beginning, the most intense phase and the descend of the
contagion, simultaneously . In order to achieve the purpose of this work, it is
important to work with a complete and well compilated set of the data to be
used to fit the curves. Data from European countries like France, Spain, Italy
Belgium, Sweden, United Kingdom, Denmark and others like USA and China, have
been used. Also, the correlation between the parameters of the Moyal
distribution fitting and the general public health measures imposed in each
country, have been discussed. A relation between those policies and the
features of the Moyal distribution, in terms of their parameters and critical
points, is shown; from that, it can be seen that the knowledge of the time
evolution of the epidemiological curve, their critical points, superposition
properties and rates of the rising and the ending, could help to find a way to
estimate the efficiency of social distancing measures, imposed in each country,
and anticipate the different phases of the pandemic.
| [
{
"created": "Mon, 8 Jun 2020 21:20:17 GMT",
"version": "v1"
}
] | 2020-06-11 | [
[
"Bernal-Alvarado",
"Jose de Jesus",
"",
"Guanajuato\n University"
],
[
"Delepine",
"David",
"",
"Guanajuato\n University"
]
] | In this paper, it is shown that the Moyal distribution is an excelent tool to study the SARS-Cov-II (Covid-19) epidemiological associated curves and its propagation. The Moyal parameters give all the information to describe the form and the impact of the illness outbreak in the different affected countries and its global impact. We checked that the Moyal distribution can accurately fit the daily report of {\it{new confirmed cases of infected people}} (NCC) per country, in that places where the contagion is reaching their final phase, describing the beginning, the most intense phase and the descend of the contagion, simultaneously . In order to achieve the purpose of this work, it is important to work with a complete and well compilated set of the data to be used to fit the curves. Data from European countries like France, Spain, Italy Belgium, Sweden, United Kingdom, Denmark and others like USA and China, have been used. Also, the correlation between the parameters of the Moyal distribution fitting and the general public health measures imposed in each country, have been discussed. A relation between those policies and the features of the Moyal distribution, in terms of their parameters and critical points, is shown; from that, it can be seen that the knowledge of the time evolution of the epidemiological curve, their critical points, superposition properties and rates of the rising and the ending, could help to find a way to estimate the efficiency of social distancing measures, imposed in each country, and anticipate the different phases of the pandemic. |
2005.12165 | Diego Ferreiro | Federico Coscio, Alejandro D. Nadra and Diego U. Ferreiro | A structural model for the Coronavirus Nucleocapsid | 13 pages, 5 figures | null | null | null | q-bio.BM | http://creativecommons.org/licenses/by-nc-sa/4.0/ | We propose a mesoscale model structure for the coronavirus nucleocapsid,
assembled from the high resolution structures of the basic building blocks of
the N-protein, CryoEM imaging and mathematical constraints for an overall
quasi-spherical particle. The structure is a truncated octahedron that
accommodates two layers: an outer shell composed of triangular and quadrangular
lattices of the N-terminal domain and an inner shell of equivalent lattices of
coiled parallel helices of the C-terminal domain. The model is consistent with
the dimensions expected for packaging large viral genomes and provides a
rationale to interpret the apparent pleomorphic nature of coronaviruses.
| [
{
"created": "Mon, 25 May 2020 15:22:04 GMT",
"version": "v1"
}
] | 2020-05-26 | [
[
"Coscio",
"Federico",
""
],
[
"Nadra",
"Alejandro D.",
""
],
[
"Ferreiro",
"Diego U.",
""
]
] | We propose a mesoscale model structure for the coronavirus nucleocapsid, assembled from the high resolution structures of the basic building blocks of the N-protein, CryoEM imaging and mathematical constraints for an overall quasi-spherical particle. The structure is a truncated octahedron that accommodates two layers: an outer shell composed of triangular and quadrangular lattices of the N-terminal domain and an inner shell of equivalent lattices of coiled parallel helices of the C-terminal domain. The model is consistent with the dimensions expected for packaging large viral genomes and provides a rationale to interpret the apparent pleomorphic nature of coronaviruses. |
2002.00070 | Cristhian Montoya | Cristhian Montoya and Jhoana P. Romero-Leiton | Analysis and optimal control of a malaria mathematical model under
resistance and population movement | null | null | null | null | q-bio.PE math.OC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work, two mathematical models for malaria under resistance are
presented. More precisely, the first model shows the interaction between humans
and mosquitoes inside a patch under infection of malaria when the human
population is resistant to antimalarial drug and mosquitoes population is
resistant to insecticides. For the second model, human-mosquitoes population
movements in two patches is analyzed under the same malaria transmission
dynamic established in one patch. For a single patch, existence and stability
conditions for the equilibrium solutions in terms of the local basic
reproductive number are developed. These results reveal the existence of a
forward bifurcation and the global stability of disease-free equilibrium. In
the case of two patches, a theoretical and numerical framework on sensitivity
analysis of parameters is presented. After that, the use of antimalarial drugs
and insecticides are incorporated as control strategies and an optimal control
problem is formulated. Numerical experiments are carried out in both models to
show the feasibility of our theoretical results.
| [
{
"created": "Fri, 31 Jan 2020 21:46:18 GMT",
"version": "v1"
}
] | 2020-02-04 | [
[
"Montoya",
"Cristhian",
""
],
[
"Romero-Leiton",
"Jhoana P.",
""
]
] | In this work, two mathematical models for malaria under resistance are presented. More precisely, the first model shows the interaction between humans and mosquitoes inside a patch under infection of malaria when the human population is resistant to antimalarial drug and mosquitoes population is resistant to insecticides. For the second model, human-mosquitoes population movements in two patches is analyzed under the same malaria transmission dynamic established in one patch. For a single patch, existence and stability conditions for the equilibrium solutions in terms of the local basic reproductive number are developed. These results reveal the existence of a forward bifurcation and the global stability of disease-free equilibrium. In the case of two patches, a theoretical and numerical framework on sensitivity analysis of parameters is presented. After that, the use of antimalarial drugs and insecticides are incorporated as control strategies and an optimal control problem is formulated. Numerical experiments are carried out in both models to show the feasibility of our theoretical results. |
1607.06225 | Rodrigo Rocha Pereira | Rodrigo P. Rocha, Wagner Figueiredo, Samir Suweis, and Amos Maritan | Species survival and scaling laws in hostile and disordered environments | 20 pages, 5 Figures | Phys. Rev. E 94, 042404 (2016) | 10.1103/PhysRevE.94.042404 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this work we study the likelihood of survival of single-species in the
context of hostile and disordered environments. Population dynamics in this
environment, as modeled by the Fisher equation, is characterized by negative
average growth rate, except in some random spatially distributed patches that
may support life. In particular, we are interested in the phase diagram of the
survival probability and in the critical size problem, i.e., the minimum patch
size required for surviving in the long time dynamics. We propose a measure for
the critical patch size as being proportional to the participation ratio (PR)
of the eigenvector corresponding to the largest eigenvalue of the linearized
Fisher dynamics. We obtain the (extinction-survival) phase diagram and the
probability distribution function (PDF) of the critical patch sizes for two
topologies, namely, the one-dimensional system and the fractal Peano basin. We
show that both topologies share the same qualitative features, but the fractal
topology requires higher spatial fluctuations to guarantee species survival. We
perform a finite-size scaling and we obtain the associated scaling exponents.
In addition, we show that the PDF of the critical patch sizes has an universal
shape for the 1D case in terms of the model parameters (diffusion, growth rate,
etc.). In contrast, the diffusion coefficient has a drastic effect on the PDF
of the critical patch sizes of the fractal Peano basin, and it does not obey
the same scaling law of the 1D case.
| [
{
"created": "Thu, 21 Jul 2016 08:03:34 GMT",
"version": "v1"
},
{
"created": "Tue, 11 Oct 2016 12:50:31 GMT",
"version": "v2"
}
] | 2018-10-25 | [
[
"Rocha",
"Rodrigo P.",
""
],
[
"Figueiredo",
"Wagner",
""
],
[
"Suweis",
"Samir",
""
],
[
"Maritan",
"Amos",
""
]
] | In this work we study the likelihood of survival of single-species in the context of hostile and disordered environments. Population dynamics in this environment, as modeled by the Fisher equation, is characterized by negative average growth rate, except in some random spatially distributed patches that may support life. In particular, we are interested in the phase diagram of the survival probability and in the critical size problem, i.e., the minimum patch size required for surviving in the long time dynamics. We propose a measure for the critical patch size as being proportional to the participation ratio (PR) of the eigenvector corresponding to the largest eigenvalue of the linearized Fisher dynamics. We obtain the (extinction-survival) phase diagram and the probability distribution function (PDF) of the critical patch sizes for two topologies, namely, the one-dimensional system and the fractal Peano basin. We show that both topologies share the same qualitative features, but the fractal topology requires higher spatial fluctuations to guarantee species survival. We perform a finite-size scaling and we obtain the associated scaling exponents. In addition, we show that the PDF of the critical patch sizes has an universal shape for the 1D case in terms of the model parameters (diffusion, growth rate, etc.). In contrast, the diffusion coefficient has a drastic effect on the PDF of the critical patch sizes of the fractal Peano basin, and it does not obey the same scaling law of the 1D case. |
1807.08900 | Hideaki Shimazaki | Jimmy Gaudreault and Hideaki Shimazaki | State-space analysis of an Ising model reveals contributions of pairwise
interactions to sparseness, fluctuation, and stimulus coding of monkey V1
neurons | 10 pages, 4 figures, ICANN2018 | null | null | null | q-bio.NC cond-mat.dis-nn stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this study, we analyzed the activity of monkey V1 neurons responding to
grating stimuli of different orientations using inference methods for a
time-dependent Ising model. The method provides optimal estimation of
time-dependent neural interactions with credible intervals according to the
sequential Bayes estimation algorithm. Furthermore, it allows us to trace
dynamics of macroscopic network properties such as entropy, sparseness, and
fluctuation. Here we report that, in all examined stimulus conditions, pairwise
interactions contribute to increasing sparseness and fluctuation. We then
demonstrate that the orientation of the grating stimulus is in part encoded in
the pairwise interactions of the neural populations. These results demonstrate
the utility of the state-space Ising model in assessing contributions of neural
interactions during stimulus processing.
| [
{
"created": "Tue, 24 Jul 2018 04:12:58 GMT",
"version": "v1"
}
] | 2018-07-25 | [
[
"Gaudreault",
"Jimmy",
""
],
[
"Shimazaki",
"Hideaki",
""
]
] | In this study, we analyzed the activity of monkey V1 neurons responding to grating stimuli of different orientations using inference methods for a time-dependent Ising model. The method provides optimal estimation of time-dependent neural interactions with credible intervals according to the sequential Bayes estimation algorithm. Furthermore, it allows us to trace dynamics of macroscopic network properties such as entropy, sparseness, and fluctuation. Here we report that, in all examined stimulus conditions, pairwise interactions contribute to increasing sparseness and fluctuation. We then demonstrate that the orientation of the grating stimulus is in part encoded in the pairwise interactions of the neural populations. These results demonstrate the utility of the state-space Ising model in assessing contributions of neural interactions during stimulus processing. |
1712.07491 | Junzhe Zhao | Junzhe Zhao | Kinetic Modelling and Inference of Hyperpolarized 13C Molecules in
Cancer Metabolism | Use of data not accredited in full; did not obtain full approval from
the laboratory | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Hyperpolarized 13C-MRI allows real time observation of metabolism in vivo.
Imaging sequences have been developed to follow the metabolism of [1-13C]
pyruvate and extract reaction kinetics, which can show tumour treatment
response. We applied the fitting model and algorithm for the imaging data of
mice tumour models and determined error estimates for the parameters of
interest. Data was least-squares fitted onto a two-site exchange model in
MATLAB, followed by statistic computation to assess model performance.
Inference through the application of MCMC was also performed. The modelling and
inference process extracted quantitative information satisfactorily and
reproducibly, demonstrating metabolic activity and intratumour heterogeneity.
Finally, novel fitting methods were evaluated and further recommendations were
made.
| [
{
"created": "Wed, 20 Dec 2017 14:15:49 GMT",
"version": "v1"
},
{
"created": "Thu, 21 Dec 2017 02:46:01 GMT",
"version": "v2"
},
{
"created": "Fri, 5 Jan 2018 01:18:58 GMT",
"version": "v3"
}
] | 2018-01-08 | [
[
"Zhao",
"Junzhe",
""
]
] | Hyperpolarized 13C-MRI allows real time observation of metabolism in vivo. Imaging sequences have been developed to follow the metabolism of [1-13C] pyruvate and extract reaction kinetics, which can show tumour treatment response. We applied the fitting model and algorithm for the imaging data of mice tumour models and determined error estimates for the parameters of interest. Data was least-squares fitted onto a two-site exchange model in MATLAB, followed by statistic computation to assess model performance. Inference through the application of MCMC was also performed. The modelling and inference process extracted quantitative information satisfactorily and reproducibly, demonstrating metabolic activity and intratumour heterogeneity. Finally, novel fitting methods were evaluated and further recommendations were made. |
2006.09222 | Sebastian Bayerl | Sebastian P. Bayerl, Florian H\"onig, Joelle Reister and Korbinian
Riedhammer | Towards Automated Assessment of Stuttering and Stuttering Therapy | 10 pages, 3 figures, 1 table Accepted at TSD 2020, 23rd International
Conference on Text, Speech and Dialogue | null | null | null | q-bio.QM cs.CL cs.LG cs.SD eess.AS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Stuttering is a complex speech disorder that can be identified by
repetitions, prolongations of sounds, syllables or words, and blocks while
speaking. Severity assessment is usually done by a speech therapist. While
attempts at automated assessment were made, it is rarely used in therapy.
Common methods for the assessment of stuttering severity include percent
stuttered syllables (% SS), the average of the three longest stuttering
symptoms during a speech task, or the recently introduced Speech Efficiency
Score (SES). This paper introduces the Speech Control Index (SCI), a new method
to evaluate the severity of stuttering. Unlike SES, it can also be used to
assess therapy success for fluency shaping. We evaluate both SES and SCI on a
new comprehensively labeled dataset containing stuttered German speech of
clients prior to, during, and after undergoing stuttering therapy. Phone
alignments of an automatic speech recognition system are statistically
evaluated in relation to their relative position to labeled stuttering events.
The results indicate that phone length distributions differ with respect to
their position in and around labeled stuttering events
| [
{
"created": "Tue, 16 Jun 2020 14:50:56 GMT",
"version": "v1"
}
] | 2020-06-17 | [
[
"Bayerl",
"Sebastian P.",
""
],
[
"Hönig",
"Florian",
""
],
[
"Reister",
"Joelle",
""
],
[
"Riedhammer",
"Korbinian",
""
]
] | Stuttering is a complex speech disorder that can be identified by repetitions, prolongations of sounds, syllables or words, and blocks while speaking. Severity assessment is usually done by a speech therapist. While attempts at automated assessment were made, it is rarely used in therapy. Common methods for the assessment of stuttering severity include percent stuttered syllables (% SS), the average of the three longest stuttering symptoms during a speech task, or the recently introduced Speech Efficiency Score (SES). This paper introduces the Speech Control Index (SCI), a new method to evaluate the severity of stuttering. Unlike SES, it can also be used to assess therapy success for fluency shaping. We evaluate both SES and SCI on a new comprehensively labeled dataset containing stuttered German speech of clients prior to, during, and after undergoing stuttering therapy. Phone alignments of an automatic speech recognition system are statistically evaluated in relation to their relative position to labeled stuttering events. The results indicate that phone length distributions differ with respect to their position in and around labeled stuttering events |
2009.12219 | Laura Schaposnik | Vishaal Ram and Laura P. Schaposnik | A modified age-structured SIR model for COVID-19 type viruses | 12 pages, 19 figures | Nature Sci Rep 11, 15194 (2021) | 10.1038/s41598-021-94609-3 | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present a modified age-structured SIR model based on known patterns of
social contact and distancing measures within Washington, USA. We find that
population age-distribution has a significant effect on disease spread and
mortality rate, and contribute to the efficacy of age-specific contact and
treatment measures. We consider the effect of relaxing restrictions across less
vulnerable age-brackets, comparing results across selected groups of varying
population parameters. Moreover, we analyze the mitigating effects of
vaccinations and examine the effectiveness of age-targeted distributions.
Lastly, we explore how our model can applied to other states to reflect
social-distancing policy based on different parameters and metrics.
| [
{
"created": "Wed, 23 Sep 2020 19:50:49 GMT",
"version": "v1"
}
] | 2022-10-18 | [
[
"Ram",
"Vishaal",
""
],
[
"Schaposnik",
"Laura P.",
""
]
] | We present a modified age-structured SIR model based on known patterns of social contact and distancing measures within Washington, USA. We find that population age-distribution has a significant effect on disease spread and mortality rate, and contribute to the efficacy of age-specific contact and treatment measures. We consider the effect of relaxing restrictions across less vulnerable age-brackets, comparing results across selected groups of varying population parameters. Moreover, we analyze the mitigating effects of vaccinations and examine the effectiveness of age-targeted distributions. Lastly, we explore how our model can applied to other states to reflect social-distancing policy based on different parameters and metrics. |
1308.6031 | Caterina La Porta AM | C.A.M. La Porta, S Zapperi | Do cancer cells undergo phenotypic switching? The case for imperfect
cancer stem cell markers | null | Scientific Reports | 2 : 441, 2012 | 10.1038/srep00441 | null | q-bio.PE q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The identification of cancer stem cells in vivo and in vitro relies on
specific surface markers that should allow to sort cancer cells in
phenotypically distinct subpopulations. Experiments report that sorted cancer
cell populations after some time tend to express again all the original
markers, leading to the hypothesis of phenotypic switching, according to which
cancer cells can transform stochastically into cancer stem cells. Here we
explore an alternative explanation based on the hypothesis that markers are not
perfect and are thus unable to identify all cancer stem cells. Our analysis is
based on a mathematical model for cancer cell proliferation that takes into
account phenotypic switching, imperfect markers and error in the sorting
process. Our conclusion is that the observation of reversible expression of
surface markers after sorting does not provide sufficient evidence in support
of phenotypic switching.
| [
{
"created": "Wed, 28 Aug 2013 02:18:02 GMT",
"version": "v1"
}
] | 2013-08-29 | [
[
"La Porta",
"C. A. M.",
""
],
[
"Zapperi",
"S",
""
]
] | The identification of cancer stem cells in vivo and in vitro relies on specific surface markers that should allow to sort cancer cells in phenotypically distinct subpopulations. Experiments report that sorted cancer cell populations after some time tend to express again all the original markers, leading to the hypothesis of phenotypic switching, according to which cancer cells can transform stochastically into cancer stem cells. Here we explore an alternative explanation based on the hypothesis that markers are not perfect and are thus unable to identify all cancer stem cells. Our analysis is based on a mathematical model for cancer cell proliferation that takes into account phenotypic switching, imperfect markers and error in the sorting process. Our conclusion is that the observation of reversible expression of surface markers after sorting does not provide sufficient evidence in support of phenotypic switching. |
1703.00940 | Nadav M. Shnerb | Yael Fried, Nadav M. Shnerb, David A. Kessler | Alternative steady states in random ecological networks | null | Phys. Rev. E 96, 012412 (2017) | 10.1103/PhysRevE.96.012412 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In many natural situations one observes a local system with many competing
species which is coupled by weak immigration to a regional species pool. The
dynamics of such a system is dominated by its stable and uninvadable (SU)
states. When the competition matrix is random, the number of SUs depends on the
average value of its entries and the variance. Here we consider the problem in
the limit of weak competition and large variance. Using a yes/no interaction
model, we show that the number of SUs corresponds to the number of maximum
cliques in a network close to its fully connected limit. The number of SUs
grows exponentially with the number of species in this limit, unless the
network is completely asymmetric. In the asymmetric limit the number of SUs is
${\cal O} (1)$. Numerical simulations suggest that these results are valid for
models with continuous distribution of competition terms.
| [
{
"created": "Thu, 2 Mar 2017 20:24:48 GMT",
"version": "v1"
}
] | 2017-07-26 | [
[
"Fried",
"Yael",
""
],
[
"Shnerb",
"Nadav M.",
""
],
[
"Kessler",
"David A.",
""
]
] | In many natural situations one observes a local system with many competing species which is coupled by weak immigration to a regional species pool. The dynamics of such a system is dominated by its stable and uninvadable (SU) states. When the competition matrix is random, the number of SUs depends on the average value of its entries and the variance. Here we consider the problem in the limit of weak competition and large variance. Using a yes/no interaction model, we show that the number of SUs corresponds to the number of maximum cliques in a network close to its fully connected limit. The number of SUs grows exponentially with the number of species in this limit, unless the network is completely asymmetric. In the asymmetric limit the number of SUs is ${\cal O} (1)$. Numerical simulations suggest that these results are valid for models with continuous distribution of competition terms. |
2310.04596 | Liang Chen | Liang Chen and Sue Ann Campbell | Synaptic delay induced macroscopic dynamics of the large-scale network
of Izhikevich neurons | 8 figures | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | We consider a large network of Izhikevich neurons. Each neuron has a
quadratic integrate-and-fire type model with a recovery variable modelling
spike frequency adaptation (SFA). We introduce a biologically motivated
synaptic current expression and a delay in the synaptic transmission. Following
the Ott-Antonsen theory, we reduce the network model to a mean-field system of
delayed differential equations. Numerical bifurcation analysis allows us to
locate higher-codimension bifurcations and to identify the regions in the
parameter space where the network exhibits changes in the macroscopic dynamics,
including transitions between states where the individual neurons exhibit
asynchronous tonic firing and different types of synchronous bursting. We
investigate the impact of the heterogeneity of the quenched input current, the
SFA mechanism and the synaptic delay on macroscopic dynamics. In the limit that
the heterogeneity goes to zero, our perturbation and bifurcation analysis shows
that the behaviour of the mean-field model remains consistent, although this
limit breaks an assumption of the model reduction. For a single population of
neurons with SFA, the synaptic delay has little effect on the generation of COs
for weak coupling, but favours their emergence beyond that, and even induces
new macroscopic dynamics. In particular, Torus bifurcations may occur, and
these are a crucial mechanism for the emergence of population bursting with two
nested frequencies. We discuss how these solutions may relate to
cross-frequency coupling which is potentially relevant for understanding
healthy and pathological brain functions.
| [
{
"created": "Fri, 6 Oct 2023 21:21:35 GMT",
"version": "v1"
}
] | 2023-10-10 | [
[
"Chen",
"Liang",
""
],
[
"Campbell",
"Sue Ann",
""
]
] | We consider a large network of Izhikevich neurons. Each neuron has a quadratic integrate-and-fire type model with a recovery variable modelling spike frequency adaptation (SFA). We introduce a biologically motivated synaptic current expression and a delay in the synaptic transmission. Following the Ott-Antonsen theory, we reduce the network model to a mean-field system of delayed differential equations. Numerical bifurcation analysis allows us to locate higher-codimension bifurcations and to identify the regions in the parameter space where the network exhibits changes in the macroscopic dynamics, including transitions between states where the individual neurons exhibit asynchronous tonic firing and different types of synchronous bursting. We investigate the impact of the heterogeneity of the quenched input current, the SFA mechanism and the synaptic delay on macroscopic dynamics. In the limit that the heterogeneity goes to zero, our perturbation and bifurcation analysis shows that the behaviour of the mean-field model remains consistent, although this limit breaks an assumption of the model reduction. For a single population of neurons with SFA, the synaptic delay has little effect on the generation of COs for weak coupling, but favours their emergence beyond that, and even induces new macroscopic dynamics. In particular, Torus bifurcations may occur, and these are a crucial mechanism for the emergence of population bursting with two nested frequencies. We discuss how these solutions may relate to cross-frequency coupling which is potentially relevant for understanding healthy and pathological brain functions. |
2109.13418 | Mara Freilich | Mara Freilich and Glenn Flierl and Amala Mahadevan | Diversity of growth rates maximizes phytoplankton productivity in an
eddying ocean | null | null | 10.1029/2021GL096180 | null | q-bio.PE physics.flu-dyn | http://creativecommons.org/licenses/by-nc-sa/4.0/ | In the subtropical gyres, phytoplankton rely on eddies for transporting
nutrients from depth to the euphotic zone. But, what controls the rate of
nutrient supply for new production? We show that vertical nutrient flux depends
both on the vertical motion within the eddying flow and varies nonlinearly with
the growth rate of the phytoplankton itself. Flux is maximized when the growth
rate matches the inverse of the decorrelation timescale for vertical motion.
Using a three-dimensional ocean model and a linear nutrient uptake model, we
find that phytoplankton productivity is maximized for a growth rate of 1/3
day$^{-1}$, which corresponds to the timescale of submesoscale dynamics.
Variability in the frequency of vertical motion across different physical
features of the flow favors phytoplankton production with different growth
rates. Such a growth-transport feedback can generate diversity in the
phytoplankton community structure at submesoscales and higher net productivity
in the presence of community diversity.
| [
{
"created": "Tue, 28 Sep 2021 01:12:23 GMT",
"version": "v1"
}
] | 2022-03-02 | [
[
"Freilich",
"Mara",
""
],
[
"Flierl",
"Glenn",
""
],
[
"Mahadevan",
"Amala",
""
]
] | In the subtropical gyres, phytoplankton rely on eddies for transporting nutrients from depth to the euphotic zone. But, what controls the rate of nutrient supply for new production? We show that vertical nutrient flux depends both on the vertical motion within the eddying flow and varies nonlinearly with the growth rate of the phytoplankton itself. Flux is maximized when the growth rate matches the inverse of the decorrelation timescale for vertical motion. Using a three-dimensional ocean model and a linear nutrient uptake model, we find that phytoplankton productivity is maximized for a growth rate of 1/3 day$^{-1}$, which corresponds to the timescale of submesoscale dynamics. Variability in the frequency of vertical motion across different physical features of the flow favors phytoplankton production with different growth rates. Such a growth-transport feedback can generate diversity in the phytoplankton community structure at submesoscales and higher net productivity in the presence of community diversity. |
2103.13920 | Mar\'ia Vallet-Regi | C. Heras, S. Sanchez-Salcedo, D. Lozano, J. Pe\~na, P. Esbrit, M.
Vallet-Regi, A.J. Salinas | Osteostatin potentiates the bioactivity of mesoporous glass scaffolds
containing Zn2+ ions in human mesenchymal stem cell cultures | 34 pages, 11 figures | Acta Biomaterialia. 89 (2019) 359-371 | 10.1016/j.actbio.2019.03.033 | null | q-bio.BM physics.bio-ph | http://creativecommons.org/licenses/by-nc-nd/4.0/ | There is an urgent need of biosynthetic bone grafts with enhanced osteogenic
capacity. In this study, we describe the design of hierarchical
meso-macroporous 3D-scaffolds based on mesoporous bioactive glasses (MBGs),
enriched with the peptide osteostatin and Zn2+ ions, and their osteogenic
effect on human mesenchymal stem cells (hMSCs) as a preclinical strategy in
bone regeneration. By using additive fabrication techniques, scaffolds
exhibiting hierarchical porosity: mesopores , macropores and big channels, were
prepared. These MBG scaffolds with or without osteostatin were evaluated in
cell cultures of hMSCs. Zinc promoted hMSCs colonization (both the surface and
inside) of MBG scaffolds. Moreover, Zn2+ ions and osteostatin together, but not
independently, in the scaffolds were found to induce the osteoblast
differentiation genes runt related transcription factor-2 (RUNX2) and alkaline
phosphatase (ALP) in hMSCs after 7 d of culture in the absence of an osteogenic
differentiation-promoting medium. These results add credence to the combined
use of zinc and osteostatin as an effective strategy for bone regeneration
applications.
| [
{
"created": "Tue, 23 Mar 2021 12:32:06 GMT",
"version": "v1"
}
] | 2021-03-26 | [
[
"Heras",
"C.",
""
],
[
"Sanchez-Salcedo",
"S.",
""
],
[
"Lozano",
"D.",
""
],
[
"Peña",
"J.",
""
],
[
"Esbrit",
"P.",
""
],
[
"Vallet-Regi",
"M.",
""
],
[
"Salinas",
"A. J.",
""
]
] | There is an urgent need of biosynthetic bone grafts with enhanced osteogenic capacity. In this study, we describe the design of hierarchical meso-macroporous 3D-scaffolds based on mesoporous bioactive glasses (MBGs), enriched with the peptide osteostatin and Zn2+ ions, and their osteogenic effect on human mesenchymal stem cells (hMSCs) as a preclinical strategy in bone regeneration. By using additive fabrication techniques, scaffolds exhibiting hierarchical porosity: mesopores , macropores and big channels, were prepared. These MBG scaffolds with or without osteostatin were evaluated in cell cultures of hMSCs. Zinc promoted hMSCs colonization (both the surface and inside) of MBG scaffolds. Moreover, Zn2+ ions and osteostatin together, but not independently, in the scaffolds were found to induce the osteoblast differentiation genes runt related transcription factor-2 (RUNX2) and alkaline phosphatase (ALP) in hMSCs after 7 d of culture in the absence of an osteogenic differentiation-promoting medium. These results add credence to the combined use of zinc and osteostatin as an effective strategy for bone regeneration applications. |
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