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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2303.09094 | Masod Sadipour | Masod Sadipour, Ali N. Azadani | The measurement of bovine pericardium density and its implications on
leaflet stress distribution in bioprosthetic heart valves | 13 pages, 7 figures | null | 10.1007/s13239-023-00692-0 | null | q-bio.TO | http://creativecommons.org/publicdomain/zero/1.0/ | Purpose: Bioprosthetic Heart Valves (BHVs) are currently in widespread use
with promising outcomes. Computational modeling provides a framework for
quantitatively describing BHVs in the preclinical phase. To obtain reliable
solutions in computational modeling, it is essential to consider accurate
leaflet properties such as mechanical properties and density. Bovine
pericardium (BP) is widely used as BHV leaflets. Previous computational studies
assume BP density to be close to the density of water or blood. However, BP
leaflets undergo multiple treatments such as fixation and anti-calcification.
The present study aims to measure the density of the BP used in BHVs and
determine its effect on leaflet stress distribution.
Methods: We determined the density of eight square BP samples laser cut from
Edwards BP patches. The weight of specimens was measured using an A&D
Analytical Balance, and volume was measured by high-resolution imaging. Finite
element models of a BHV similar to PERIMOUNT Magna were developed in ABAQUS.
Results: The average density value of the BP samples was 1410 kg/m3. In the
acceleration phase of a cardiac cycle, the maximum stress value reached 1.89
MPa for a density value of 1410 kg/m3 , and 2.47 MPa for a density of 1000
kg/m3(30.7% difference). In the deceleration, the maximum stress value reached
713 and 669 kPa, respectively.
Conclusion: Stress distribution and deformation of BHV leaflets are dependent
upon the magnitude of density. Ascertaining an accurate value for the density
of BHV leaflets is essential for computational models.
| [
{
"created": "Thu, 16 Mar 2023 05:38:54 GMT",
"version": "v1"
}
] | 2024-01-23 | [
[
"Sadipour",
"Masod",
""
],
[
"Azadani",
"Ali N.",
""
]
] | Purpose: Bioprosthetic Heart Valves (BHVs) are currently in widespread use with promising outcomes. Computational modeling provides a framework for quantitatively describing BHVs in the preclinical phase. To obtain reliable solutions in computational modeling, it is essential to consider accurate leaflet properties such as mechanical properties and density. Bovine pericardium (BP) is widely used as BHV leaflets. Previous computational studies assume BP density to be close to the density of water or blood. However, BP leaflets undergo multiple treatments such as fixation and anti-calcification. The present study aims to measure the density of the BP used in BHVs and determine its effect on leaflet stress distribution. Methods: We determined the density of eight square BP samples laser cut from Edwards BP patches. The weight of specimens was measured using an A&D Analytical Balance, and volume was measured by high-resolution imaging. Finite element models of a BHV similar to PERIMOUNT Magna were developed in ABAQUS. Results: The average density value of the BP samples was 1410 kg/m3. In the acceleration phase of a cardiac cycle, the maximum stress value reached 1.89 MPa for a density value of 1410 kg/m3 , and 2.47 MPa for a density of 1000 kg/m3(30.7% difference). In the deceleration, the maximum stress value reached 713 and 669 kPa, respectively. Conclusion: Stress distribution and deformation of BHV leaflets are dependent upon the magnitude of density. Ascertaining an accurate value for the density of BHV leaflets is essential for computational models. |
2009.11241 | Xuan Guo | Xuan Guo, Shichao Feng | Deep learning for peptide identification from metaproteomics datasets | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Metaproteomics are becoming widely used in microbiome research for gaining
insights into the functional state of the microbial community. Current
metaproteomics studies are generally based on high-throughput tandem mass
spectrometry (MS/MS) coupled with liquid chromatography. The identification of
peptides and proteins from MS data involves the computational procedure of
searching MS/MS spectra against a predefined protein sequence database and
assigning top-scored peptides to spectra. Existing computational tools are
still far from being able to extract all the information out of large MS/MS
datasets acquired from metaproteome samples. In this paper, we proposed a
deep-learning-based algorithm, called DeepFilter, for improving the rate of
confident peptide identifications from a collection of tandem mass spectra.
Compared with other post-processing tools, including Percolator, Q-ranker,
PeptideProphet, and Iprophet, DeepFilter identified 20% and 10% more
peptide-spectrum-matches and proteins, respectively, on marine microbial and
soil microbial metaproteome samples with false discovery rate at 1%.
| [
{
"created": "Wed, 23 Sep 2020 16:25:22 GMT",
"version": "v1"
}
] | 2020-09-24 | [
[
"Guo",
"Xuan",
""
],
[
"Feng",
"Shichao",
""
]
] | Metaproteomics are becoming widely used in microbiome research for gaining insights into the functional state of the microbial community. Current metaproteomics studies are generally based on high-throughput tandem mass spectrometry (MS/MS) coupled with liquid chromatography. The identification of peptides and proteins from MS data involves the computational procedure of searching MS/MS spectra against a predefined protein sequence database and assigning top-scored peptides to spectra. Existing computational tools are still far from being able to extract all the information out of large MS/MS datasets acquired from metaproteome samples. In this paper, we proposed a deep-learning-based algorithm, called DeepFilter, for improving the rate of confident peptide identifications from a collection of tandem mass spectra. Compared with other post-processing tools, including Percolator, Q-ranker, PeptideProphet, and Iprophet, DeepFilter identified 20% and 10% more peptide-spectrum-matches and proteins, respectively, on marine microbial and soil microbial metaproteome samples with false discovery rate at 1%. |
2101.01752 | Giuseppe Tronci | Heather E. Owston, Katrina M. Moisley, Giuseppe Tronci, Stephen J.
Russell, Peter V. Giannoudis, Elena Jones | Induced Periosteum-Mimicking Membrane with Cell Barrier and
Multipotential Stromal Cell (MSC) Homing Functionalities | null | null | 10.3390/ijms21155233 | null | q-bio.TO | http://creativecommons.org/licenses/by/4.0/ | The current management of critical size bone defects (CSBDs) remains
challenging and requires multiple surgeries. To reduce the number of surgeries,
wrapping a biodegradable fibrous membrane around the defect to contain the
graft and carry biological stimulants for repair is highly desirable.
Poly(epsilon-caprolactone) (PCL) can be utilised to realise nonwoven fibrous
barrier-like structures through free surface electrospinning (FSE). Human
periosteum and induced membrane (IM) samples informed the development of an FSE
membrane to support platelet lysate (PL) absorption, multipotential stromal
cells (MSC) growth, and the prevention of cell migration. Although thinner than
IM, periosteum presented a more mature vascular system with a significantly
larger blood vessel diameter. The electrospun membrane (PCL3%-E) exhibited
randomly configured nanoscale fibres that were successfully customised to
introduce pores of increased diameter, without compromising tensile properties.
Additional to the PL absorption and release capabilities needed for MSC
attraction and growth, PCL3%-E also provided a favourable surface for the
proliferation and alignment of periosteum- and bone marrow derived-MSCs, whilst
possessing a barrier function to cell migration. These results demonstrate the
development of a promising biodegradable barrier membrane enabling PL release
and MSC colonisation, two key functionalities needed for the in situ formation
of a transitional periosteum-like structure, enabling movement towards
single-surgery CSBD reconstruction.
| [
{
"created": "Tue, 5 Jan 2021 19:36:50 GMT",
"version": "v1"
}
] | 2021-01-07 | [
[
"Owston",
"Heather E.",
""
],
[
"Moisley",
"Katrina M.",
""
],
[
"Tronci",
"Giuseppe",
""
],
[
"Russell",
"Stephen J.",
""
],
[
"Giannoudis",
"Peter V.",
""
],
[
"Jones",
"Elena",
""
]
] | The current management of critical size bone defects (CSBDs) remains challenging and requires multiple surgeries. To reduce the number of surgeries, wrapping a biodegradable fibrous membrane around the defect to contain the graft and carry biological stimulants for repair is highly desirable. Poly(epsilon-caprolactone) (PCL) can be utilised to realise nonwoven fibrous barrier-like structures through free surface electrospinning (FSE). Human periosteum and induced membrane (IM) samples informed the development of an FSE membrane to support platelet lysate (PL) absorption, multipotential stromal cells (MSC) growth, and the prevention of cell migration. Although thinner than IM, periosteum presented a more mature vascular system with a significantly larger blood vessel diameter. The electrospun membrane (PCL3%-E) exhibited randomly configured nanoscale fibres that were successfully customised to introduce pores of increased diameter, without compromising tensile properties. Additional to the PL absorption and release capabilities needed for MSC attraction and growth, PCL3%-E also provided a favourable surface for the proliferation and alignment of periosteum- and bone marrow derived-MSCs, whilst possessing a barrier function to cell migration. These results demonstrate the development of a promising biodegradable barrier membrane enabling PL release and MSC colonisation, two key functionalities needed for the in situ formation of a transitional periosteum-like structure, enabling movement towards single-surgery CSBD reconstruction. |
1909.00404 | Alexander Spirov | Victoria Yu. Samuta, Alexander V. Spirov | Quantitative analysis of the dynamics of maternal gradients of the early
Drosophila embryo | 19 pages, in russian | null | null | null | q-bio.QM q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The predetermination, formation and maintenance of the primary morphogenetic
gradient (bicoid gradient) of the early Drosophila embryo involves many
interrelated processes. Here we focus on a system-biological analysis of the
processes of redistribution of bicoid mRNA in an early embryo. The results of a
quantitative analysis of experimental data, together with the results of their
dynamic modeling, substantiate the role of active transport in the
redistribution of bicoid mRNA.
| [
{
"created": "Sun, 1 Sep 2019 14:00:30 GMT",
"version": "v1"
}
] | 2019-09-04 | [
[
"Samuta",
"Victoria Yu.",
""
],
[
"Spirov",
"Alexander V.",
""
]
] | The predetermination, formation and maintenance of the primary morphogenetic gradient (bicoid gradient) of the early Drosophila embryo involves many interrelated processes. Here we focus on a system-biological analysis of the processes of redistribution of bicoid mRNA in an early embryo. The results of a quantitative analysis of experimental data, together with the results of their dynamic modeling, substantiate the role of active transport in the redistribution of bicoid mRNA. |
2104.11852 | Tiberiu Tesileanu | Tiberiu Tesileanu, Siavash Golkar, Samaneh Nasiri, Anirvan M.
Sengupta, Dmitri B. Chklovskii | Neural circuits for dynamics-based segmentation of time series | v2.1; 34 pages, 14 figures | null | null | null | q-bio.NC physics.bio-ph | http://creativecommons.org/licenses/by/4.0/ | The brain must extract behaviorally relevant latent variables from the
signals streamed by the sensory organs. Such latent variables are often encoded
in the dynamics that generated the signal rather than in the specific
realization of the waveform. Therefore, one problem faced by the brain is to
segment time series based on underlying dynamics. We present two algorithms for
performing this segmentation task that are biologically plausible, which we
define as acting in a streaming setting and all learning rules being local. One
algorithm is model-based and can be derived from an optimization problem
involving a mixture of autoregressive processes. This algorithm relies on
feedback in the form of a prediction error, and can also be used for
forecasting future samples. In some brain regions, such as the retina, the
feedback connections necessary to use the prediction error for learning are
absent. For this case, we propose a second, model-free algorithm that uses a
running estimate of the autocorrelation structure of the signal to perform the
segmentation. We show that both algorithms do well when tasked with segmenting
signals drawn from autoregressive models with piecewise-constant parameters. In
particular, the segmentation accuracy is similar to that obtained from
oracle-like methods in which the ground-truth parameters of the autoregressive
models are known. We also test our methods on datasets generated by alternating
snippets of voice recordings. We provide implementations of our algorithms at
https://github.com/ttesileanu/bio-time-series.
| [
{
"created": "Sat, 24 Apr 2021 01:54:27 GMT",
"version": "v1"
},
{
"created": "Wed, 29 Sep 2021 18:59:27 GMT",
"version": "v2"
},
{
"created": "Tue, 5 Oct 2021 21:11:50 GMT",
"version": "v3"
}
] | 2021-10-07 | [
[
"Tesileanu",
"Tiberiu",
""
],
[
"Golkar",
"Siavash",
""
],
[
"Nasiri",
"Samaneh",
""
],
[
"Sengupta",
"Anirvan M.",
""
],
[
"Chklovskii",
"Dmitri B.",
""
]
] | The brain must extract behaviorally relevant latent variables from the signals streamed by the sensory organs. Such latent variables are often encoded in the dynamics that generated the signal rather than in the specific realization of the waveform. Therefore, one problem faced by the brain is to segment time series based on underlying dynamics. We present two algorithms for performing this segmentation task that are biologically plausible, which we define as acting in a streaming setting and all learning rules being local. One algorithm is model-based and can be derived from an optimization problem involving a mixture of autoregressive processes. This algorithm relies on feedback in the form of a prediction error, and can also be used for forecasting future samples. In some brain regions, such as the retina, the feedback connections necessary to use the prediction error for learning are absent. For this case, we propose a second, model-free algorithm that uses a running estimate of the autocorrelation structure of the signal to perform the segmentation. We show that both algorithms do well when tasked with segmenting signals drawn from autoregressive models with piecewise-constant parameters. In particular, the segmentation accuracy is similar to that obtained from oracle-like methods in which the ground-truth parameters of the autoregressive models are known. We also test our methods on datasets generated by alternating snippets of voice recordings. We provide implementations of our algorithms at https://github.com/ttesileanu/bio-time-series. |
1806.11557 | Francis Aweda | O.A. Falaiye and F. O Aweda | Mineralogical Characteristics of Harmattan Dust Across Jos North Central
and Potiskum North Earthern Cities of Nigeria | 18 pqges, 7 figures | null | null | null | q-bio.OT astro-ph.EP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The trace metals and mineralogical composition of harmattan dust carried out
on the samples collected at Jos ((9 55'N, 8 55'E)) and Potiskum ((11 43'N, 11
02'E) as revealed by PIXE and AAS machine using clean Petri Dishes and Plastic
bowls of 10 cm in diameter aimed on the characteristics of the mineralogical
and elemental composition of the harmattan dust carried out in Nigeria.
Thirteen trace elements, Na, K, Ca, Mg, Fe, Cd, Zn, Mn, Cu, Si, Al, Ti, and Zr
were determined and their concentrations were evaluated in different
proportion. Minerals such as Quartz [SiO2], Corundum [Al2O3], Hematite [Fe2O3],
Lime [CaO], Periclase [MgO], Rutile [TiO2], Zincite [MnO], Bunsenite [NiO],
Cuprite [Cu2O], Zincite [ZnO], Baddeleyite [ZrO2], Litharge [PbO], Monazite
[P2O5], Montrodydite [HgO] and Petzite [Au2O3] were also determined in
different concentrations. The particle weight of the sample for the residential
and commercial areas were calculated to be Jos (18.95g/m2, 19.25g/m2), Potiskum
(24.24 g/m2, 2515g/m2) respectively. The results shows that the harmattan dust
that blows across the two stations in Nigeria comprise of high elements and
more minerals.
| [
{
"created": "Tue, 19 Jun 2018 21:14:03 GMT",
"version": "v1"
}
] | 2018-07-02 | [
[
"Falaiye",
"O. A.",
""
],
[
"Aweda",
"F. O",
""
]
] | The trace metals and mineralogical composition of harmattan dust carried out on the samples collected at Jos ((9 55'N, 8 55'E)) and Potiskum ((11 43'N, 11 02'E) as revealed by PIXE and AAS machine using clean Petri Dishes and Plastic bowls of 10 cm in diameter aimed on the characteristics of the mineralogical and elemental composition of the harmattan dust carried out in Nigeria. Thirteen trace elements, Na, K, Ca, Mg, Fe, Cd, Zn, Mn, Cu, Si, Al, Ti, and Zr were determined and their concentrations were evaluated in different proportion. Minerals such as Quartz [SiO2], Corundum [Al2O3], Hematite [Fe2O3], Lime [CaO], Periclase [MgO], Rutile [TiO2], Zincite [MnO], Bunsenite [NiO], Cuprite [Cu2O], Zincite [ZnO], Baddeleyite [ZrO2], Litharge [PbO], Monazite [P2O5], Montrodydite [HgO] and Petzite [Au2O3] were also determined in different concentrations. The particle weight of the sample for the residential and commercial areas were calculated to be Jos (18.95g/m2, 19.25g/m2), Potiskum (24.24 g/m2, 2515g/m2) respectively. The results shows that the harmattan dust that blows across the two stations in Nigeria comprise of high elements and more minerals. |
1908.01876 | Patrick Holmes | Patrick D. Holmes, Shannon M. Danforth, Xiao-Yu Fu, Talia Y. Moore,
and Ram Vasudevan | Characterizing the limits of human stability during motion: perturbative
experiment validates a model-based approach for the Sit-to-Stand task | 19 pages, 9 figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Falls affect a growing number of the population each year. Clinical methods
to identify those at greatest risk for falls usually evaluate individuals while
they perform specific motions such as balancing or Sit-to-Stand (STS).
Unfortunately these techniques have been shown to have poor predictive power
and are unable to identify the magnitude, direction, and timing of
perturbations that can cause an individual to lose stability during motion. To
address this limitation, the recently proposed Stability Basin (SB) aims to
characterize the set of perturbations that will cause an individual to fall
under a specific motor control strategy. The SB is defined as the set of
configurations that do not lead to failure for an individual under their chosen
control strategy. This paper presents a novel method to compute the SB and the
first experimental validation of the SB with an 11-person perturbative STS
experiment involving forwards or backwards pulls from a motor-driven cable. The
individually-constructed SBs are used to identify when a trial fails, i.e.,
when an individual must switch control strategies (indicated by a step or sit)
to recover from a perturbation. The constructed SBs correctly predict the
outcome of trials where failure was observed with over 90% accuracy, and
correctly predict the outcome of successful trials with over 95% accuracy. The
SB was compared to three other methods and was found to estimate the stable
region with over 45% more accuracy in all cases. This study demonstrates that
SBs offer a novel model-based approach for quantifying stability during motion,
which could be used in physical therapy for individuals at risk of falling.
| [
{
"created": "Mon, 5 Aug 2019 21:54:52 GMT",
"version": "v1"
}
] | 2019-08-07 | [
[
"Holmes",
"Patrick D.",
""
],
[
"Danforth",
"Shannon M.",
""
],
[
"Fu",
"Xiao-Yu",
""
],
[
"Moore",
"Talia Y.",
""
],
[
"Vasudevan",
"Ram",
""
]
] | Falls affect a growing number of the population each year. Clinical methods to identify those at greatest risk for falls usually evaluate individuals while they perform specific motions such as balancing or Sit-to-Stand (STS). Unfortunately these techniques have been shown to have poor predictive power and are unable to identify the magnitude, direction, and timing of perturbations that can cause an individual to lose stability during motion. To address this limitation, the recently proposed Stability Basin (SB) aims to characterize the set of perturbations that will cause an individual to fall under a specific motor control strategy. The SB is defined as the set of configurations that do not lead to failure for an individual under their chosen control strategy. This paper presents a novel method to compute the SB and the first experimental validation of the SB with an 11-person perturbative STS experiment involving forwards or backwards pulls from a motor-driven cable. The individually-constructed SBs are used to identify when a trial fails, i.e., when an individual must switch control strategies (indicated by a step or sit) to recover from a perturbation. The constructed SBs correctly predict the outcome of trials where failure was observed with over 90% accuracy, and correctly predict the outcome of successful trials with over 95% accuracy. The SB was compared to three other methods and was found to estimate the stable region with over 45% more accuracy in all cases. This study demonstrates that SBs offer a novel model-based approach for quantifying stability during motion, which could be used in physical therapy for individuals at risk of falling. |
2007.02855 | Gilberto Nakamura | Gilberto Nakamura, Basil Grammaticos, Christophe Deroulers, Mathilde
Badoual | Effective epidemic model for COVID-19 using accumulated deaths | 20 pages, 7 figures | null | 10.1016/j.chaos.2021.110667 | null | q-bio.PE physics.bio-ph physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The severe acute respiratory syndrome COVID-19 has been in the center of the
ongoing global health crisis in 2020. The high prevalence of mild cases
facilitates sub-notification outside hospital environments and the number of
those who are or have been infected remains largely unknown, leading to poor
estimates of the crude mortality rate of the disease. Here we use a simple
model to describe the number of accumulated deaths caused by COVID-19. The
close connection between the proposed model and an approximate solution of the
SIR model provides a system of equations whose solutions are robust estimates
of epidemiological parameters. We find that the crude mortality varies between
$10^{-4}$ and $10^{-3}$ depending on the severity of the outbreak which is
lower than previous estimates obtained from laboratory confirmed patients. We
also estimate quantities of practical interest such as the basic reproduction
number and the expected number of deaths in the asymptotic limit with and
without social distancing measures and lockdowns, which allow us to measure the
efficiency of these interventions.
| [
{
"created": "Mon, 6 Jul 2020 16:13:45 GMT",
"version": "v1"
}
] | 2021-05-26 | [
[
"Nakamura",
"Gilberto",
""
],
[
"Grammaticos",
"Basil",
""
],
[
"Deroulers",
"Christophe",
""
],
[
"Badoual",
"Mathilde",
""
]
] | The severe acute respiratory syndrome COVID-19 has been in the center of the ongoing global health crisis in 2020. The high prevalence of mild cases facilitates sub-notification outside hospital environments and the number of those who are or have been infected remains largely unknown, leading to poor estimates of the crude mortality rate of the disease. Here we use a simple model to describe the number of accumulated deaths caused by COVID-19. The close connection between the proposed model and an approximate solution of the SIR model provides a system of equations whose solutions are robust estimates of epidemiological parameters. We find that the crude mortality varies between $10^{-4}$ and $10^{-3}$ depending on the severity of the outbreak which is lower than previous estimates obtained from laboratory confirmed patients. We also estimate quantities of practical interest such as the basic reproduction number and the expected number of deaths in the asymptotic limit with and without social distancing measures and lockdowns, which allow us to measure the efficiency of these interventions. |
2402.17252 | Thomas-Otavio Peulen | Thomas-Otavio Peulen (1,2,3,4), Katherina Hemmen (4), Annemarie Greife
(5), Benjamin M. Webb (1,2,3), Suren Felekyan (5), Andrej Sali (1,2,3), Claus
A. M. Seidel (5), Hugo Sanabria (6), Katrin G. Heinze (4) ((1) Department of
Bioengineering and Therapeutic Sciences, University of California, San
Francisco, (2) Department of Pharmaceutical Chemistry, University of
California, San Francisco, San Francisco, California, United States, (3)
Quantitative Biosciences Institute (QBI), University of California, San
Francisco, San Francisco, California, United States, (4) Rudolf Virchow
Center for Integrative and Translational Bioimaging, University of
W\"urzburg, W\"urzburg, Germany, (5) Chair of Molecular Physical Chemistry,
Heinrich-Heine University, D\"usseldorf, Germany, (6) Department of Physics &
Astronomy, Clemson University, Clemson, United States) | tttrlib: modular software for integrating fluorescence spectroscopy,
imaging, and molecular modeling | null | null | null | null | q-bio.QM physics.bio-ph | http://creativecommons.org/licenses/by-sa/4.0/ | We introduce software for reading, writing and processing fluorescence
single-molecule and image spectroscopy data and developing analysis pipelines
that unifies various spectroscopic analysis tools. Our software can be used for
processing multiple experiment types, e.g., for time-resolved single-molecule
(sm) spectroscopy, laser scanning microscopy, fluorescence correlation
spectroscopy, and image correlation spectroscopy. The software is file format
agnostic, processes and outputs multiple time-resolved data formats. Thereby
our software eliminates the need for data conversion and mitigates data
archiving issues.
| [
{
"created": "Tue, 27 Feb 2024 06:53:18 GMT",
"version": "v1"
}
] | 2024-02-28 | [
[
"Peulen",
"Thomas-Otavio",
""
],
[
"Hemmen",
"Katherina",
""
],
[
"Greife",
"Annemarie",
""
],
[
"Webb",
"Benjamin M.",
""
],
[
"Felekyan",
"Suren",
""
],
[
"Sali",
"Andrej",
""
],
[
"Seidel",
"Claus A. M.",
""
],
[
"Sanabria",
"Hugo",
""
],
[
"Heinze",
"Katrin G.",
""
]
] | We introduce software for reading, writing and processing fluorescence single-molecule and image spectroscopy data and developing analysis pipelines that unifies various spectroscopic analysis tools. Our software can be used for processing multiple experiment types, e.g., for time-resolved single-molecule (sm) spectroscopy, laser scanning microscopy, fluorescence correlation spectroscopy, and image correlation spectroscopy. The software is file format agnostic, processes and outputs multiple time-resolved data formats. Thereby our software eliminates the need for data conversion and mitigates data archiving issues. |
1912.08735 | Can Firtina | Jeremie S. Kim, Can Firtina, Meryem Banu Cavlak, Damla Senol Cali,
Mohammed Alser, Nastaran Hajinazar, Can Alkan, Onur Mutlu | AirLift: A Fast and Comprehensive Technique for Remapping Alignments
between Reference Genomes | null | null | null | null | q-bio.GN cs.CE | http://creativecommons.org/licenses/by/4.0/ | As genome sequencing tools and techniques improve, researchers are able to
incrementally assemble more accurate reference genomes, which enable
sensitivity in read mapping and downstream analysis such as variant calling. A
more sensitive downstream analysis is critical for a better understanding of
the genome donor (e.g., health characteristics). Therefore, read sets from
sequenced samples should ideally be mapped to the latest available reference
genome that represents the most relevant population. Unfortunately, the
increasingly large amount of available genomic data makes it prohibitively
expensive to fully re-map each read set to its respective reference genome
every time the reference is updated. There are several tools that attempt to
accelerate the process of updating a read data set from one reference to
another (i.e., remapping). However, if a read maps to a region in the old
reference that does not appear with a reasonable degree of similarity in the
new reference, the read cannot be remapped. We find that, as a result of this
drawback, a significant portion of annotations are lost when using
state-of-the-art remapping tools. To address this major limitation in existing
tools, we propose AirLift, a fast and comprehensive technique for remapping
alignments from one genome to another. Compared to the state-of-the-art method
for remapping reads (i.e., full mapping), AirLift reduces the overall execution
time to remap read sets between two reference genome versions by up to 27.4x.
We validate our remapping results with GATK and find that AirLift provides high
accuracy in identifying ground truth SNP/INDEL variants.
| [
{
"created": "Wed, 18 Dec 2019 16:58:27 GMT",
"version": "v1"
},
{
"created": "Wed, 17 Feb 2021 00:07:40 GMT",
"version": "v2"
},
{
"created": "Fri, 12 Aug 2022 04:38:54 GMT",
"version": "v3"
},
{
"created": "Mon, 21 Nov 2022 13:12:27 GMT",
"version": "v4"
}
] | 2022-11-22 | [
[
"Kim",
"Jeremie S.",
""
],
[
"Firtina",
"Can",
""
],
[
"Cavlak",
"Meryem Banu",
""
],
[
"Cali",
"Damla Senol",
""
],
[
"Alser",
"Mohammed",
""
],
[
"Hajinazar",
"Nastaran",
""
],
[
"Alkan",
"Can",
""
],
[
"Mutlu",
"Onur",
""
]
] | As genome sequencing tools and techniques improve, researchers are able to incrementally assemble more accurate reference genomes, which enable sensitivity in read mapping and downstream analysis such as variant calling. A more sensitive downstream analysis is critical for a better understanding of the genome donor (e.g., health characteristics). Therefore, read sets from sequenced samples should ideally be mapped to the latest available reference genome that represents the most relevant population. Unfortunately, the increasingly large amount of available genomic data makes it prohibitively expensive to fully re-map each read set to its respective reference genome every time the reference is updated. There are several tools that attempt to accelerate the process of updating a read data set from one reference to another (i.e., remapping). However, if a read maps to a region in the old reference that does not appear with a reasonable degree of similarity in the new reference, the read cannot be remapped. We find that, as a result of this drawback, a significant portion of annotations are lost when using state-of-the-art remapping tools. To address this major limitation in existing tools, we propose AirLift, a fast and comprehensive technique for remapping alignments from one genome to another. Compared to the state-of-the-art method for remapping reads (i.e., full mapping), AirLift reduces the overall execution time to remap read sets between two reference genome versions by up to 27.4x. We validate our remapping results with GATK and find that AirLift provides high accuracy in identifying ground truth SNP/INDEL variants. |
2004.14787 | Biman Bagchi - | Saumyak Mukherjee, Sayantan Mondal and Biman Bagchi | Dynamical Theory and Cellular Automata Simulations of Pandemic Spread:
Understanding Different Temporal Patterns of Infections | 11 pages, 11 figures, 3 tables | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Here we propose and implement a generalized mathematical model to find the
time evolution of population in infectious diseases and apply the model to
study the recent COVID-19 pandemic. Our model at the core is a non-local
generalization of the widely used Kermack-McKendrick(KM) model where the
susceptible(S) population evolves into two other categories, namely
infectives(I) and removed(R). This is the well-known SIR model in which we
further divide both S and I into high and low risk categories. We first
formulate a set of non-local dynamical equations for the time evolution of
distinct population distributions under this categorization in an attempt to
describe the general scenario of infectious disease progression. We then solve
the non-linear coupled differential equations-(i) numerically by the method of
propagation, and (ii) a more flexible and versatile cellular automata (CA)
simulation which provides a coarse-grained description of the generalized
non-local model. In order to account for multiple factors such as role of
spreaders before containment, we introduce a time dependent rate which appears
to be essential to explain the sudden spikes before the plateau observed in
many cases (for example like China). We demonstrate how this generalized
approach allows us to handle the effects of (i) time-dependence of the
rate-constants of spread, (ii) different population density, (iii) the age
ratio, (iv) quarantine, (v) lockdown, and (vi) social distancing. Our study
allows us to make certain predictions regarding the nature of spread with
respect to several external parameters, treated as control variables. Analysis
of the model clearly shows that due to the strong heterogeneity in the epidemic
process originating from the distribution of initial infectives, the theory
must be local in character but at the same time connect to a global
perspective.
| [
{
"created": "Thu, 30 Apr 2020 14:02:49 GMT",
"version": "v1"
}
] | 2020-05-01 | [
[
"Mukherjee",
"Saumyak",
""
],
[
"Mondal",
"Sayantan",
""
],
[
"Bagchi",
"Biman",
""
]
] | Here we propose and implement a generalized mathematical model to find the time evolution of population in infectious diseases and apply the model to study the recent COVID-19 pandemic. Our model at the core is a non-local generalization of the widely used Kermack-McKendrick(KM) model where the susceptible(S) population evolves into two other categories, namely infectives(I) and removed(R). This is the well-known SIR model in which we further divide both S and I into high and low risk categories. We first formulate a set of non-local dynamical equations for the time evolution of distinct population distributions under this categorization in an attempt to describe the general scenario of infectious disease progression. We then solve the non-linear coupled differential equations-(i) numerically by the method of propagation, and (ii) a more flexible and versatile cellular automata (CA) simulation which provides a coarse-grained description of the generalized non-local model. In order to account for multiple factors such as role of spreaders before containment, we introduce a time dependent rate which appears to be essential to explain the sudden spikes before the plateau observed in many cases (for example like China). We demonstrate how this generalized approach allows us to handle the effects of (i) time-dependence of the rate-constants of spread, (ii) different population density, (iii) the age ratio, (iv) quarantine, (v) lockdown, and (vi) social distancing. Our study allows us to make certain predictions regarding the nature of spread with respect to several external parameters, treated as control variables. Analysis of the model clearly shows that due to the strong heterogeneity in the epidemic process originating from the distribution of initial infectives, the theory must be local in character but at the same time connect to a global perspective. |
1706.05568 | Mareike Fischer | Michelle Galla and Kristina Wicke and Mareike Fischer | On the statistical inconsistency of Maximum Parsimony for $k$-tuple-site
data | null | null | null | null | q-bio.PE math.CO math.PR stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One of the main aims of phylogenetics is to reconstruct the \enquote{Tree of
Life}. In this respect, different methods and criteria are used to analyze DNA
sequences of different species and to compare them in order to derive the
evolutionary relationships of these species. Maximum Parsimony is one such
criterion for tree reconstruction and, it is the one which we will use in this
paper. However, it is well-known that tree reconstruction methods can lead to
wrong relationship estimates. One typical problem of Maximum Parsimony is long
branch attraction, which can lead to statistical inconsistency. In this work,
we will consider a blockwise approach to alignment analysis, namely so-called
$k$-tuple analyses. For four taxa it has already been shown that
$k$-tuple-based analyses are statistically inconsistent if and only if the
standard character-based (site-based) analyses are statistically inconsistent.
So, in the four-taxon case, going from individual sites to $k$-tuples does not
lead to any improvement. However, real biological analyses often consider more
than only four taxa. Therefore, we analyze the case of five taxa for $2$- and
$3$-tuple-site data and consider alphabets with two and four elements. We show
that the equivalence of single-site data and $k$-tuple-site data then no longer
holds. Even so, we can show that Maximum Parsimony is statistically
inconsistent for $k$-tuple site data and five taxa.
| [
{
"created": "Sat, 17 Jun 2017 18:03:27 GMT",
"version": "v1"
},
{
"created": "Thu, 14 Dec 2017 21:32:47 GMT",
"version": "v2"
},
{
"created": "Thu, 4 Oct 2018 07:58:45 GMT",
"version": "v3"
}
] | 2018-10-05 | [
[
"Galla",
"Michelle",
""
],
[
"Wicke",
"Kristina",
""
],
[
"Fischer",
"Mareike",
""
]
] | One of the main aims of phylogenetics is to reconstruct the \enquote{Tree of Life}. In this respect, different methods and criteria are used to analyze DNA sequences of different species and to compare them in order to derive the evolutionary relationships of these species. Maximum Parsimony is one such criterion for tree reconstruction and, it is the one which we will use in this paper. However, it is well-known that tree reconstruction methods can lead to wrong relationship estimates. One typical problem of Maximum Parsimony is long branch attraction, which can lead to statistical inconsistency. In this work, we will consider a blockwise approach to alignment analysis, namely so-called $k$-tuple analyses. For four taxa it has already been shown that $k$-tuple-based analyses are statistically inconsistent if and only if the standard character-based (site-based) analyses are statistically inconsistent. So, in the four-taxon case, going from individual sites to $k$-tuples does not lead to any improvement. However, real biological analyses often consider more than only four taxa. Therefore, we analyze the case of five taxa for $2$- and $3$-tuple-site data and consider alphabets with two and four elements. We show that the equivalence of single-site data and $k$-tuple-site data then no longer holds. Even so, we can show that Maximum Parsimony is statistically inconsistent for $k$-tuple site data and five taxa. |
q-bio/0506018 | Antonio T. Costa Jr | Monica F. B. Moreira, Marcio P. Dantas, A. T. Costa Jr | Spontaneous natural selection in a model for spatially distributed
interacting populations | RevTeX4, 8 figures | null | null | null | q-bio.PE | null | We present an individual-based model for two interacting populations
diffusing on lattices in which a strong natural selection develops
spontaneously. The models combine traditional local predator-prey dynamics with
random walks. Individual's mobility is considered as an inherited trait. Small
variations upon inheritance, mimicking mutations, provide variability on which
natural selection may act. Although the dynamic rules defining the models do
not explicitly favor any mobility values, we found that the average mobility of
both populations tend to be maximized in various situations. In some situations
there is evidence of polymorphism, indicated by an adaptive landscape with many
local maxima. We provide evidence relating selective pressure for high mobility
with pattern formation.
| [
{
"created": "Wed, 15 Jun 2005 21:39:33 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Moreira",
"Monica F. B.",
""
],
[
"Dantas",
"Marcio P.",
""
],
[
"Costa",
"A. T.",
"Jr"
]
] | We present an individual-based model for two interacting populations diffusing on lattices in which a strong natural selection develops spontaneously. The models combine traditional local predator-prey dynamics with random walks. Individual's mobility is considered as an inherited trait. Small variations upon inheritance, mimicking mutations, provide variability on which natural selection may act. Although the dynamic rules defining the models do not explicitly favor any mobility values, we found that the average mobility of both populations tend to be maximized in various situations. In some situations there is evidence of polymorphism, indicated by an adaptive landscape with many local maxima. We provide evidence relating selective pressure for high mobility with pattern formation. |
1902.01257 | Vesna Vuksanovic | Vesna Vuksanovi\'c | Cortical thickness and functional networks modules by cortical lobes | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | This study aims to investigate topological organization of cortical thickness
and functional networks by cortical lobes. First, I demonstrated modular
organization of these networks by the cortical surface frontal, temporal,
parietal and occipital divisions. Secondly, I mapped the overlapping edges of
cortical thickness and functional networks for positive and negative
correlations. Finally, I showed that overlapping positive edges map onto
within-lobe cortical interactions and negative onto between-lobes interactions.
| [
{
"created": "Mon, 4 Feb 2019 15:39:10 GMT",
"version": "v1"
},
{
"created": "Thu, 13 Jun 2019 09:16:27 GMT",
"version": "v2"
}
] | 2019-06-14 | [
[
"Vuksanović",
"Vesna",
""
]
] | This study aims to investigate topological organization of cortical thickness and functional networks by cortical lobes. First, I demonstrated modular organization of these networks by the cortical surface frontal, temporal, parietal and occipital divisions. Secondly, I mapped the overlapping edges of cortical thickness and functional networks for positive and negative correlations. Finally, I showed that overlapping positive edges map onto within-lobe cortical interactions and negative onto between-lobes interactions. |
2006.03420 | Robert Worden | R.P. Worden | Is there a wave excitation in the Thalamus? | 11 pages | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper proposes that the thalamus is the site of a wave excitation, whose
function is to represent the locations of things around the animal. Neurons
couple to the wave as transmitters and receivers. The wave acts as an analogue
representation of local space. This has benefits over a purely neural
representation of space. Several lines of evidence support this hypothesis;
both theoretical, concerning efficient Bayesian inference in the brain, and
empirical, concerning the neuro-anatomy of the thalamus. Across all species,
the most basic function of the brain is to coordinate movements in space. To
represent positions in space only by neural firing rates would be complex and
inefficient. It is possible that that the brain represents 3D space in a direct
and natural way, by a 3D wave
| [
{
"created": "Wed, 20 May 2020 14:28:02 GMT",
"version": "v1"
}
] | 2020-06-08 | [
[
"Worden",
"R. P.",
""
]
] | This paper proposes that the thalamus is the site of a wave excitation, whose function is to represent the locations of things around the animal. Neurons couple to the wave as transmitters and receivers. The wave acts as an analogue representation of local space. This has benefits over a purely neural representation of space. Several lines of evidence support this hypothesis; both theoretical, concerning efficient Bayesian inference in the brain, and empirical, concerning the neuro-anatomy of the thalamus. Across all species, the most basic function of the brain is to coordinate movements in space. To represent positions in space only by neural firing rates would be complex and inefficient. It is possible that that the brain represents 3D space in a direct and natural way, by a 3D wave |
2404.09059 | Rayanne Luke | Prajakta Bedekar and Rayanne A. Luke and Anthony J. Kearsley | Prevalence estimation methods for time-dependent antibody kinetics of
infected and vaccinated individuals: a graph-theoretic approach | 27 pages, 7 figures | null | null | null | q-bio.PE math.PR physics.bio-ph q-bio.QM stat.ME | http://creativecommons.org/licenses/by/4.0/ | Immune events such as infection, vaccination, and a combination of the two
result in distinct time-dependent antibody responses in affected individuals.
These responses and event prevalences combine non-trivially to govern antibody
levels sampled from a population. Time-dependence and disease prevalence pose
considerable modeling challenges that need to be addressed to provide a
rigorous mathematical underpinning of the underlying biology. We propose a
time-inhomogeneous Markov chain model for event-to-event transitions coupled
with a probabilistic framework for anti-body kinetics and demonstrate its use
in a setting in which individuals can be infected or vaccinated but not both.
We prove the equivalency of this approach to the framework developed in our
previous work. Synthetic data are used to demonstrate the modeling process and
conduct prevalence estimation via transition probability matrices. This
approach is ideal to model sequences of infections and vaccinations, or
personal trajectories in a population, making it an important first step
towards a mathematical characterization of reinfection, vaccination boosting,
and cross-events of infection after vaccination or vice versa.
| [
{
"created": "Sat, 13 Apr 2024 18:43:59 GMT",
"version": "v1"
}
] | 2024-04-16 | [
[
"Bedekar",
"Prajakta",
""
],
[
"Luke",
"Rayanne A.",
""
],
[
"Kearsley",
"Anthony J.",
""
]
] | Immune events such as infection, vaccination, and a combination of the two result in distinct time-dependent antibody responses in affected individuals. These responses and event prevalences combine non-trivially to govern antibody levels sampled from a population. Time-dependence and disease prevalence pose considerable modeling challenges that need to be addressed to provide a rigorous mathematical underpinning of the underlying biology. We propose a time-inhomogeneous Markov chain model for event-to-event transitions coupled with a probabilistic framework for anti-body kinetics and demonstrate its use in a setting in which individuals can be infected or vaccinated but not both. We prove the equivalency of this approach to the framework developed in our previous work. Synthetic data are used to demonstrate the modeling process and conduct prevalence estimation via transition probability matrices. This approach is ideal to model sequences of infections and vaccinations, or personal trajectories in a population, making it an important first step towards a mathematical characterization of reinfection, vaccination boosting, and cross-events of infection after vaccination or vice versa. |
1706.02327 | Christian Negre | Christian F. A. Negre, Uriel N. Morzan, Heidi Hendrickson, Rhitankar
Pal, George P. Lisi, J. Patrick Loria, Ivan Rivalta, Junming Ho, Victor S.
Batista | Eigenvector Centrality Distribution for Characterization of Protein
Allosteric Pathways | null | null | 10.1073/pnas.1810452115 | null | q-bio.BM cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Determining the principal energy pathways for allosteric communication in
biomolecules, that occur as a result of thermal motion, remains challenging due
to the intrinsic complexity of the systems involved. Graph theory provides an
approach for making sense of such complexity, where allosteric proteins can be
represented as networks of amino acids. In this work, we establish the
eigenvector centrality metric in terms of the mutual information, as a mean of
elucidating the allosteric mechanism that regulates the enzymatic activity of
proteins. Moreover, we propose a strategy to characterize the range of the
physical interactions that underlie the allosteric process. In particular, the
well known enzyme, imidazol glycerol phosphate synthase (IGPS), is utilized to
test the proposed methodology. The eigenvector centrality measurement
successfully describes the allosteric pathways of IGPS, and allows to pinpoint
key amino acids in terms of their relevance in the momentum transfer process.
The resulting insight can be utilized for refining the control of IGPS
activity, widening the scope for its engineering. Furthermore, we propose a new
centrality metric quantifying the relevance of the surroundings of each
residue. In addition, the proposed technique is validated against experimental
solution NMR measurements yielding fully consistent results. Overall, the
methodologies proposed in the present work constitute a powerful and cost
effective strategy to gain insight on the allosteric mechanism of proteins.
| [
{
"created": "Wed, 7 Jun 2017 18:32:59 GMT",
"version": "v1"
},
{
"created": "Mon, 25 Jun 2018 15:33:04 GMT",
"version": "v2"
}
] | 2022-05-04 | [
[
"Negre",
"Christian F. A.",
""
],
[
"Morzan",
"Uriel N.",
""
],
[
"Hendrickson",
"Heidi",
""
],
[
"Pal",
"Rhitankar",
""
],
[
"Lisi",
"George P.",
""
],
[
"Loria",
"J. Patrick",
""
],
[
"Rivalta",
"Ivan",
""
],
[
"Ho",
"Junming",
""
],
[
"Batista",
"Victor S.",
""
]
] | Determining the principal energy pathways for allosteric communication in biomolecules, that occur as a result of thermal motion, remains challenging due to the intrinsic complexity of the systems involved. Graph theory provides an approach for making sense of such complexity, where allosteric proteins can be represented as networks of amino acids. In this work, we establish the eigenvector centrality metric in terms of the mutual information, as a mean of elucidating the allosteric mechanism that regulates the enzymatic activity of proteins. Moreover, we propose a strategy to characterize the range of the physical interactions that underlie the allosteric process. In particular, the well known enzyme, imidazol glycerol phosphate synthase (IGPS), is utilized to test the proposed methodology. The eigenvector centrality measurement successfully describes the allosteric pathways of IGPS, and allows to pinpoint key amino acids in terms of their relevance in the momentum transfer process. The resulting insight can be utilized for refining the control of IGPS activity, widening the scope for its engineering. Furthermore, we propose a new centrality metric quantifying the relevance of the surroundings of each residue. In addition, the proposed technique is validated against experimental solution NMR measurements yielding fully consistent results. Overall, the methodologies proposed in the present work constitute a powerful and cost effective strategy to gain insight on the allosteric mechanism of proteins. |
2002.10372 | Mauro Mobilia | Ami Taitelbaum, Robert West, Michael Assaf, Mauro Mobilia | Population Dynamics in a Changing Environment: Random versus Periodic
Switching | 22 pages, 7 figures: main text (6 pages, 3 figures) followed by
Supplementary Material (16 pages, 4 figures). Published in Physical Review
Letters. Additional supporting resources available at
https://figshare.com/articles/Supplementary_Material/12613370 | Phys. Rev. Lett. 125, 048105 (2020) | 10.1103/PhysRevLett.125.048105 | null | q-bio.PE cond-mat.stat-mech nlin.AO physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Environmental changes greatly influence the evolution of populations. Here,
we study the dynamics of a population of two strains, one growing slightly
faster than the other, competing for resources in a time-varying binary
environment modeled by a carrying capacity switching either randomly or
periodically between states of abundance and scarcity. The population dynamics
is characterized by demographic noise (birth and death events) coupled to a
varying environment. We elucidate the similarities and differences of the
evolution subject to a stochastically- and periodically-varying environment.
Importantly, the population size distribution is generally found to be broader
under intermediate and fast random switching than under periodic variations,
which results in markedly different asymptotic behaviors between the fixation
probability of random and periodic switching. We also determine the detailed
conditions under which the fixation probability of the slow strain is maximal.
| [
{
"created": "Mon, 24 Feb 2020 16:57:17 GMT",
"version": "v1"
},
{
"created": "Thu, 9 Jul 2020 00:22:13 GMT",
"version": "v2"
},
{
"created": "Mon, 27 Jul 2020 14:26:40 GMT",
"version": "v3"
}
] | 2020-07-28 | [
[
"Taitelbaum",
"Ami",
""
],
[
"West",
"Robert",
""
],
[
"Assaf",
"Michael",
""
],
[
"Mobilia",
"Mauro",
""
]
] | Environmental changes greatly influence the evolution of populations. Here, we study the dynamics of a population of two strains, one growing slightly faster than the other, competing for resources in a time-varying binary environment modeled by a carrying capacity switching either randomly or periodically between states of abundance and scarcity. The population dynamics is characterized by demographic noise (birth and death events) coupled to a varying environment. We elucidate the similarities and differences of the evolution subject to a stochastically- and periodically-varying environment. Importantly, the population size distribution is generally found to be broader under intermediate and fast random switching than under periodic variations, which results in markedly different asymptotic behaviors between the fixation probability of random and periodic switching. We also determine the detailed conditions under which the fixation probability of the slow strain is maximal. |
1205.6867 | Frederick Matsen IV | Frederick A. Matsen, Aaron Gallagher, Connor McCoy | Minimizing the average distance to a closest leaf in a phylogenetic tree | Please contact us with any comments or questions! | null | null | null | q-bio.PE cs.DM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | When performing an analysis on a collection of molecular sequences, it can be
convenient to reduce the number of sequences under consideration while
maintaining some characteristic of a larger collection of sequences. For
example, one may wish to select a subset of high-quality sequences that
represent the diversity of a larger collection of sequences. One may also wish
to specialize a large database of characterized "reference sequences" to a
smaller subset that is as close as possible on average to a collection of
"query sequences" of interest. Such a representative subset can be useful
whenever one wishes to find a set of reference sequences that is appropriate to
use for comparative analysis of environmentally-derived sequences, such as for
selecting "reference tree" sequences for phylogenetic placement of metagenomic
reads. In this paper we formalize these problems in terms of the minimization
of the Average Distance to the Closest Leaf (ADCL) and investigate algorithms
to perform the relevant minimization. We show that the greedy algorithm is not
effective, show that a variant of the Partitioning Among Medoids (PAM)
heuristic gets stuck in local minima, and develop an exact dynamic programming
approach. Using this exact program we note that the performance of PAM appears
to be good for simulated trees, and is faster than the exact algorithm for
small trees. On the other hand, the exact program gives solutions for all
numbers of leaves less than or equal to the given desired number of leaves,
while PAM only gives a solution for the pre-specified number of leaves. Via
application to real data, we show that the ADCL criterion chooses chimeric
sequences less often than random subsets, while the maximization of
phylogenetic diversity chooses them more often than random. These algorithms
have been implemented in publicly available software.
| [
{
"created": "Thu, 31 May 2012 01:41:37 GMT",
"version": "v1"
},
{
"created": "Fri, 31 Aug 2012 18:05:58 GMT",
"version": "v2"
}
] | 2012-09-03 | [
[
"Matsen",
"Frederick A.",
""
],
[
"Gallagher",
"Aaron",
""
],
[
"McCoy",
"Connor",
""
]
] | When performing an analysis on a collection of molecular sequences, it can be convenient to reduce the number of sequences under consideration while maintaining some characteristic of a larger collection of sequences. For example, one may wish to select a subset of high-quality sequences that represent the diversity of a larger collection of sequences. One may also wish to specialize a large database of characterized "reference sequences" to a smaller subset that is as close as possible on average to a collection of "query sequences" of interest. Such a representative subset can be useful whenever one wishes to find a set of reference sequences that is appropriate to use for comparative analysis of environmentally-derived sequences, such as for selecting "reference tree" sequences for phylogenetic placement of metagenomic reads. In this paper we formalize these problems in terms of the minimization of the Average Distance to the Closest Leaf (ADCL) and investigate algorithms to perform the relevant minimization. We show that the greedy algorithm is not effective, show that a variant of the Partitioning Among Medoids (PAM) heuristic gets stuck in local minima, and develop an exact dynamic programming approach. Using this exact program we note that the performance of PAM appears to be good for simulated trees, and is faster than the exact algorithm for small trees. On the other hand, the exact program gives solutions for all numbers of leaves less than or equal to the given desired number of leaves, while PAM only gives a solution for the pre-specified number of leaves. Via application to real data, we show that the ADCL criterion chooses chimeric sequences less often than random subsets, while the maximization of phylogenetic diversity chooses them more often than random. These algorithms have been implemented in publicly available software. |
2404.10807 | Joseph Marsh | Benjamin J. Livesey, Mihaly Badonyi, Mafalda Dias, Jonathan Frazer,
Sushant Kumar, Kresten Lindorff-Larsen, David M. McCandlish, Rose Orenbuch,
Courtney A. Shearer, Lara Muffley, Julia Foreman, Andrew M. Glazer, Ben
Lehner, Debora S. Marks, Frederick P. Roth, Alan F. Rubin, Lea M. Starita and
Joseph A. Marsh | Guidelines for releasing a variant effect predictor | 14 pages, 1 figure | null | null | null | q-bio.OT | http://creativecommons.org/licenses/by/4.0/ | Computational methods for assessing the likely impacts of mutations, known as
variant effect predictors (VEPs), are widely used in the assessment and
interpretation of human genetic variation, as well as in other applications
like protein engineering. Many different VEPs have been released to date, and
there is tremendous variability in their underlying algorithms and outputs, and
in the ways in which the methodologies and predictions are shared. This leads
to considerable challenges for end users in knowing which VEPs to use and how
to use them. Here, to address these issues, we provide guidelines and
recommendations for the release of novel VEPs. Emphasising open-source
availability, transparent methodologies, clear variant effect score
interpretations, standardised scales, accessible predictions, and rigorous
training data disclosure, we aim to improve the usability and interpretability
of VEPs, and promote their integration into analysis and evaluation pipelines.
We also provide a large, categorised list of currently available VEPs, aiming
to facilitate the discovery and encourage the usage of novel methods within the
scientific community.
| [
{
"created": "Tue, 16 Apr 2024 13:37:07 GMT",
"version": "v1"
}
] | 2024-04-18 | [
[
"Livesey",
"Benjamin J.",
""
],
[
"Badonyi",
"Mihaly",
""
],
[
"Dias",
"Mafalda",
""
],
[
"Frazer",
"Jonathan",
""
],
[
"Kumar",
"Sushant",
""
],
[
"Lindorff-Larsen",
"Kresten",
""
],
[
"McCandlish",
"David M.",
""
],
[
"Orenbuch",
"Rose",
""
],
[
"Shearer",
"Courtney A.",
""
],
[
"Muffley",
"Lara",
""
],
[
"Foreman",
"Julia",
""
],
[
"Glazer",
"Andrew M.",
""
],
[
"Lehner",
"Ben",
""
],
[
"Marks",
"Debora S.",
""
],
[
"Roth",
"Frederick P.",
""
],
[
"Rubin",
"Alan F.",
""
],
[
"Starita",
"Lea M.",
""
],
[
"Marsh",
"Joseph A.",
""
]
] | Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs. Emphasising open-source availability, transparent methodologies, clear variant effect score interpretations, standardised scales, accessible predictions, and rigorous training data disclosure, we aim to improve the usability and interpretability of VEPs, and promote their integration into analysis and evaluation pipelines. We also provide a large, categorised list of currently available VEPs, aiming to facilitate the discovery and encourage the usage of novel methods within the scientific community. |
1503.00529 | Sergei Maslov | Sergei Maslov and Kim Sneppen | Diversity waves in collapse-driven population dynamics | 15 pages (including SI), 6 figures + 7 supplementary figures | null | 10.1371/journal.pcbi.1004440 | null | q-bio.PE nlin.AO physics.soc-ph q-fin.EC q-fin.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Populations of species in ecosystems are often constrained by availability of
resources within their environment. In effect this means that a growth of one
population, needs to be balanced by comparable reduction in populations of
others. In neutral models of biodiversity all populations are assumed to change
incrementally due to stochastic births and deaths of individuals. Here we
propose and model another redistribution mechanism driven by abrupt and severe
collapses of the entire population of a single species freeing up resources for
the remaining ones. This mechanism may be relevant e.g. for communities of
bacteria, with strain-specific collapses caused e.g. by invading
bacteriophages, or for other ecosystems where infectious diseases play an
important role.
The emergent dynamics of our system is cyclic "diversity waves" triggered by
collapses of globally dominating populations. The population diversity peaks at
the beginning of each wave and exponentially decreases afterwards. Species
abundances are characterized by a bimodal time-aggregated distribution with the
lower peak formed by populations of recently collapsed or newly introduced
species, while the upper peak - species that has not yet collapsed in the
current wave. In most waves both upper and lower peaks are composed of several
smaller peaks. This self-organized hierarchical peak structure has a long-term
memory transmitted across several waves. It gives rise to a scale-free tail of
the time-aggregated population distribution with a universal exponent of 1.7.
We show that diversity wave dynamics is robust with respect to variations in
the rules of our model such as diffusion between multiple environments,
species-specific growth and extinction rates, and bet-hedging strategies.
| [
{
"created": "Mon, 2 Mar 2015 14:03:39 GMT",
"version": "v1"
},
{
"created": "Tue, 14 Jul 2015 18:39:20 GMT",
"version": "v2"
}
] | 2016-02-17 | [
[
"Maslov",
"Sergei",
""
],
[
"Sneppen",
"Kim",
""
]
] | Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe collapses of the entire population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is cyclic "diversity waves" triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances are characterized by a bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species, while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies. |
2004.07440 | Masaki Watabe | Masaki Watabe, Hideaki Yoshimura, Satya N. V. Arjunan, Kazunari Kaizu,
and Koichi Takahashi | Signaling activations through G-protein-coupled-receptor aggregations | 6 pages, 4 figures | Phys. Rev. E 102, 032413 (2020) | 10.1103/PhysRevE.102.032413 | null | q-bio.MN q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Eukaryotic cells transmit extracellular signal information to cellular
interiors through the formation of a ternary complex made up of a ligand (or
agonist), G-protein, and G-protein coupled receptor (GPCR). Previously
formalized theories of ternary complex formation have mainly assumed that
observable states of receptors can only take the form of monomers. Here, we
propose a multiary complex model of GPCR signaling activations via the vector
representation of various unobserved aggregated receptor states. Our results
from model simulations imply that receptor aggregation processes can govern
cooperative effects in a regime inaccessible by previous theories. In
particular, we show how the affinity of ligand-receptor binding can be largely
varied by various oligomer formations in the low concentration range of
G-protein stimulus.
| [
{
"created": "Thu, 16 Apr 2020 03:51:21 GMT",
"version": "v1"
},
{
"created": "Tue, 22 Sep 2020 23:10:22 GMT",
"version": "v2"
}
] | 2020-09-24 | [
[
"Watabe",
"Masaki",
""
],
[
"Yoshimura",
"Hideaki",
""
],
[
"Arjunan",
"Satya N. V.",
""
],
[
"Kaizu",
"Kazunari",
""
],
[
"Takahashi",
"Koichi",
""
]
] | Eukaryotic cells transmit extracellular signal information to cellular interiors through the formation of a ternary complex made up of a ligand (or agonist), G-protein, and G-protein coupled receptor (GPCR). Previously formalized theories of ternary complex formation have mainly assumed that observable states of receptors can only take the form of monomers. Here, we propose a multiary complex model of GPCR signaling activations via the vector representation of various unobserved aggregated receptor states. Our results from model simulations imply that receptor aggregation processes can govern cooperative effects in a regime inaccessible by previous theories. In particular, we show how the affinity of ligand-receptor binding can be largely varied by various oligomer formations in the low concentration range of G-protein stimulus. |
q-bio/0611024 | Iraziet Charret | I. C. Charret and M. V. Carneiro | Spontaneous emergence of spatial patterns ina a predator-prey model | 17 pages and 15 figures | PRE v.76. e061902, 2007 | 10.1103/PhysRevE.76.061902 | null | q-bio.PE | null | We present studies for an individual based model of three interacting
populations whose individuals are mobile in a 2D-lattice. We focus on the
pattern formation in the spatial distributions of the populations. Also
relevant is the relationship between pattern formation and features of the
populations' time series. Our model displays travelling waves solutions,
clustering and uniform distributions, all related to the parameters values. We
also observed that the regeneration rate, the parameter associated to the
primary level of trophic chain, the plants, regulated the presence of
predators, as well as the type of spatial configuration.
| [
{
"created": "Tue, 7 Nov 2006 13:37:35 GMT",
"version": "v1"
}
] | 2007-12-18 | [
[
"Charret",
"I. C.",
""
],
[
"Carneiro",
"M. V.",
""
]
] | We present studies for an individual based model of three interacting populations whose individuals are mobile in a 2D-lattice. We focus on the pattern formation in the spatial distributions of the populations. Also relevant is the relationship between pattern formation and features of the populations' time series. Our model displays travelling waves solutions, clustering and uniform distributions, all related to the parameters values. We also observed that the regeneration rate, the parameter associated to the primary level of trophic chain, the plants, regulated the presence of predators, as well as the type of spatial configuration. |
2003.00009 | Carlo Vittorio Cannistraci | Yan Ge, Philipp Rosendahl, Claudio Dur\'an, Nicole T\"opfner, Sara
Ciucci, Jochen Guck, and Carlo Vittorio Cannistraci | Cell Mechanics Based Computational Classification of Red Blood Cells Via
Machine Intelligence Applied to Morpho-Rheological Markers | 13 pages, 3 figures, 4 tables | IEEE/ACM Trans. Comput. Biol. Bioinform (2019) | 10.1109/TCBB.2019.2945762 | null | q-bio.QM cs.LG stat.ML | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Despite fluorescent cell-labelling being widely employed in biomedical
studies, some of its drawbacks are inevitable, with unsuitable fluorescent
probes or probes inducing a functional change being the main limitations.
Consequently, the demand for and development of label-free methodologies to
classify cells is strong and its impact on precision medicine is relevant.
Towards this end, high-throughput techniques for cell mechanical phenotyping
have been proposed to get a multidimensional biophysical characterization of
single cells. With this motivation, our goal here is to investigate the extent
to which an unsupervised machine learning methodology, which is applied
exclusively on morpho-rheological markers obtained by real-time deformability
and fluorescence cytometry (RT-FDC), can address the difficult task of
providing label-free discrimination of reticulocytes from mature red blood
cells. We focused on this problem, since the characterization of reticulocytes
(their percentage and cellular features) in the blood is vital in multiple
human disease conditions, especially bone-marrow disorders such as anemia and
leukemia. Our approach reports promising label-free results in the
classification of reticulocytes from mature red blood cells, and it represents
a step forward in the development of high-throughput morpho-rheological-based
methodologies for the computational categorization of single cells. Besides,
our methodology can be an alternative but also a complementary method to
integrate with existing cell-labelling techniques.
| [
{
"created": "Mon, 2 Mar 2020 15:11:46 GMT",
"version": "v1"
}
] | 2020-03-03 | [
[
"Ge",
"Yan",
""
],
[
"Rosendahl",
"Philipp",
""
],
[
"Durán",
"Claudio",
""
],
[
"Töpfner",
"Nicole",
""
],
[
"Ciucci",
"Sara",
""
],
[
"Guck",
"Jochen",
""
],
[
"Cannistraci",
"Carlo Vittorio",
""
]
] | Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawbacks are inevitable, with unsuitable fluorescent probes or probes inducing a functional change being the main limitations. Consequently, the demand for and development of label-free methodologies to classify cells is strong and its impact on precision medicine is relevant. Towards this end, high-throughput techniques for cell mechanical phenotyping have been proposed to get a multidimensional biophysical characterization of single cells. With this motivation, our goal here is to investigate the extent to which an unsupervised machine learning methodology, which is applied exclusively on morpho-rheological markers obtained by real-time deformability and fluorescence cytometry (RT-FDC), can address the difficult task of providing label-free discrimination of reticulocytes from mature red blood cells. We focused on this problem, since the characterization of reticulocytes (their percentage and cellular features) in the blood is vital in multiple human disease conditions, especially bone-marrow disorders such as anemia and leukemia. Our approach reports promising label-free results in the classification of reticulocytes from mature red blood cells, and it represents a step forward in the development of high-throughput morpho-rheological-based methodologies for the computational categorization of single cells. Besides, our methodology can be an alternative but also a complementary method to integrate with existing cell-labelling techniques. |
2401.06294 | Clement Soubrier | Cl\'ement Soubrier, Eric Foxall, Luca Ciandrini, Khanh Dao Duc | Optimal control of ribosome population for gene expression under
periodic nutrient intake | 16 pages (plus 13 pages of appendices). 4 figures (plus 1 figure and
1 table in appendices). Submitted to the Journal of The Royal Society
Interface | J. R. Soc. Interface. 2120230652 | 10.1098/rsif.2023.0652 | null | q-bio.SC | http://creativecommons.org/licenses/by/4.0/ | Translation of proteins is a fundamental part of gene expression that is
mediated by ribosomes. As ribosomes significantly contribute to both cellular
mass and energy consumption, achieving efficient management of the ribosome
population is also crucial to metabolism and growth. Inspired by biological
evidence for nutrient-dependent mechanisms that control both ribosome active
degradation and genesis, we introduce a dynamical model of protein production,
that includes the dynamics of resources and control over the ribosome
population. Under the hypothesis that active degradation and biogenesis are
optimal for maximizing and maintaining protein production, we aim to
qualitatively reproduce empirical observations of the ribosome population
dynamics. Upon formulating the associated optimization problem, we first
analytically study the stability and global behaviour of solutions under
constant resource input, and characterize the extent of oscillations and
convergence rate to a global equilibrium. We further use these results to
simplify and solve the problem under a quasi-static approximation. Using
biophysical parameter values, we find that optimal control solutions lead to
both control mechanisms and the ribosome population switching between periods
of feeding and fasting, suggesting that the intense regulation of ribosome
population observed in experiments allows to maximize and maintain protein
production. Finally, we find some range for the control values over which such
a regime can be observed, depending on the intensity of fasting.
| [
{
"created": "Thu, 11 Jan 2024 23:27:13 GMT",
"version": "v1"
}
] | 2024-04-18 | [
[
"Soubrier",
"Clément",
""
],
[
"Foxall",
"Eric",
""
],
[
"Ciandrini",
"Luca",
""
],
[
"Duc",
"Khanh Dao",
""
]
] | Translation of proteins is a fundamental part of gene expression that is mediated by ribosomes. As ribosomes significantly contribute to both cellular mass and energy consumption, achieving efficient management of the ribosome population is also crucial to metabolism and growth. Inspired by biological evidence for nutrient-dependent mechanisms that control both ribosome active degradation and genesis, we introduce a dynamical model of protein production, that includes the dynamics of resources and control over the ribosome population. Under the hypothesis that active degradation and biogenesis are optimal for maximizing and maintaining protein production, we aim to qualitatively reproduce empirical observations of the ribosome population dynamics. Upon formulating the associated optimization problem, we first analytically study the stability and global behaviour of solutions under constant resource input, and characterize the extent of oscillations and convergence rate to a global equilibrium. We further use these results to simplify and solve the problem under a quasi-static approximation. Using biophysical parameter values, we find that optimal control solutions lead to both control mechanisms and the ribosome population switching between periods of feeding and fasting, suggesting that the intense regulation of ribosome population observed in experiments allows to maximize and maintain protein production. Finally, we find some range for the control values over which such a regime can be observed, depending on the intensity of fasting. |
2311.17066 | Ke Yuhe | Yuhe Ke, Matilda Swee Sun Tang, Celestine Jia Ling Loh, Hairil Rizal
Abdullah, Nicholas Brian Shannon | Cluster trajectory of SOFA score in predicting mortality in sepsis | 26 pages, 4 figures, 2 tables | null | null | null | q-bio.QM cs.AI | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Objective: Sepsis is a life-threatening condition. Sequential Organ Failure
Assessment (SOFA) score is commonly used to assess organ dysfunction and
predict ICU mortality, but it is taken as a static measurement and fails to
capture dynamic changes. This study aims to investigate the relationship
between dynamic changes in SOFA scores over the first 72 hours of ICU admission
and patient outcomes.
Design, setting, and participants: 3,253 patients in the Medical Information
Mart for Intensive Care IV database who met the sepsis-3 criteria and were
admitted from the emergency department with at least 72 hours of ICU admission
and full-active resuscitation status were analysed. Group-based trajectory
modelling with dynamic time warping and k-means clustering identified distinct
trajectory patterns in dynamic SOFA scores. They were subsequently compared
using Python.
Main outcome measures: Outcomes including hospital and ICU mortality, length
of stay in hospital and ICU, and readmission during hospital stay, were
collected. Discharge time from ICU to wards and cut-offs at 7-day and 14-day
were taken.
Results: Four clusters were identified: A (consistently low SOFA scores), B
(rapid increase followed by a decline in SOFA scores), C (higher baseline
scores with gradual improvement), and D (persistently elevated scores). Cluster
D had the longest ICU and hospital stays, highest ICU and hospital mortality.
Discharge rates from ICU were similar for Clusters A and B, while Cluster C had
initially comparable rates but a slower transition to ward.
Conclusion: Monitoring dynamic changes in SOFA score is valuable for
assessing sepsis severity and treatment responsiveness.
| [
{
"created": "Thu, 23 Nov 2023 12:29:00 GMT",
"version": "v1"
}
] | 2023-11-30 | [
[
"Ke",
"Yuhe",
""
],
[
"Tang",
"Matilda Swee Sun",
""
],
[
"Loh",
"Celestine Jia Ling",
""
],
[
"Abdullah",
"Hairil Rizal",
""
],
[
"Shannon",
"Nicholas Brian",
""
]
] | Objective: Sepsis is a life-threatening condition. Sequential Organ Failure Assessment (SOFA) score is commonly used to assess organ dysfunction and predict ICU mortality, but it is taken as a static measurement and fails to capture dynamic changes. This study aims to investigate the relationship between dynamic changes in SOFA scores over the first 72 hours of ICU admission and patient outcomes. Design, setting, and participants: 3,253 patients in the Medical Information Mart for Intensive Care IV database who met the sepsis-3 criteria and were admitted from the emergency department with at least 72 hours of ICU admission and full-active resuscitation status were analysed. Group-based trajectory modelling with dynamic time warping and k-means clustering identified distinct trajectory patterns in dynamic SOFA scores. They were subsequently compared using Python. Main outcome measures: Outcomes including hospital and ICU mortality, length of stay in hospital and ICU, and readmission during hospital stay, were collected. Discharge time from ICU to wards and cut-offs at 7-day and 14-day were taken. Results: Four clusters were identified: A (consistently low SOFA scores), B (rapid increase followed by a decline in SOFA scores), C (higher baseline scores with gradual improvement), and D (persistently elevated scores). Cluster D had the longest ICU and hospital stays, highest ICU and hospital mortality. Discharge rates from ICU were similar for Clusters A and B, while Cluster C had initially comparable rates but a slower transition to ward. Conclusion: Monitoring dynamic changes in SOFA score is valuable for assessing sepsis severity and treatment responsiveness. |
1401.1755 | Tobias Reichenbach | Alexander Dobrinevski, Mikko Alava, Tobias Reichenbach, Erwin Frey | Mobility-Dependent Selection of Competing Strategy Associations | 9 pages, six figures; accepted in Physical Review E | Phys. Rev. E 89, 012721 (2014) | 10.1103/PhysRevE.89.012721 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Standard models of population dynamics focus on the the interaction,
survival, and extinction of the competing species individually. Real ecological
systems, however, are characterized by an abundance of species (or strategies,
in the terminology of evolutionary-game theory) that form intricate, complex
interaction networks. The description of the ensuing dynamics may be aided by
studying associations of certain strategies rather than individual ones. Here
we show how such a higher-level description can bear fruitful insight.
Motivated from different strains of colicinogenic Escherichia coli bacteria, we
investigate a four-strategy system which contains a three-strategy cycle and a
neutral alliance of two strategies. We find that the stochastic, spatial model
exhibits a mobility-dependent selection of either the three-strategy cycle or
of the neutral pair. We analyze this intriguing phenomenon numerically and
analytically.
| [
{
"created": "Wed, 8 Jan 2014 17:11:20 GMT",
"version": "v1"
}
] | 2014-05-27 | [
[
"Dobrinevski",
"Alexander",
""
],
[
"Alava",
"Mikko",
""
],
[
"Reichenbach",
"Tobias",
""
],
[
"Frey",
"Erwin",
""
]
] | Standard models of population dynamics focus on the the interaction, survival, and extinction of the competing species individually. Real ecological systems, however, are characterized by an abundance of species (or strategies, in the terminology of evolutionary-game theory) that form intricate, complex interaction networks. The description of the ensuing dynamics may be aided by studying associations of certain strategies rather than individual ones. Here we show how such a higher-level description can bear fruitful insight. Motivated from different strains of colicinogenic Escherichia coli bacteria, we investigate a four-strategy system which contains a three-strategy cycle and a neutral alliance of two strategies. We find that the stochastic, spatial model exhibits a mobility-dependent selection of either the three-strategy cycle or of the neutral pair. We analyze this intriguing phenomenon numerically and analytically. |
2011.10126 | Brandon Hayes | Brandon H Hayes, Mathieu Andraud, Luis G Salazar, Nicolas Rose, and
Timothee Vergne | Mechanistic modeling of African swine fever: A systematic review | 19 pages, 3 figures, 4 tables. Accepted to Preventive Veterinary
Medicine. Revised from previous preprint to include models published through
Dec 2020 | null | 10.1016/j.prevetmed.2021.105358 | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | The spread of African swine fever (ASF) poses a grave threat to the global
swine industry. Understanding transmission dynamics, such as through
mechanistic modeling, is critical for designing effective control strategies.
Articles were examined across multiple epidemiological and model
characteristics. Model filiation was determined through creation of a
neighbor-joined tree using phylogenetic software. Of 34 four articles
qualifying for inclusion, four main modelling objectives were identified:
estimating transmission parameters (11 studies), assessing determinants of
transmission (7), examining consequences of hypothetical outbreaks (5), and
assessing alternative control strategies (11). Estimated transmission
parameters varied widely as did parameter assumptions between models.
Uncertainties on epidemiological and ecological parameters were usually
accounted for to assess the impact on the modeled infection trajectory. Almost
all models are host specific, being developed for either domestic pigs or wild
boar despite the fact that spillover events between domestic pigs and wild boar
are evidenced to play an important role in ASF outbreaks. The development of
models incorporating such transmission routes is crucial. All compared control
strategies were defined a priori, and future models should be built to identify
optimal contributions across many control methods. Further, control strategies
were examined in competition, opposed to how they would be synergistically
implemented. While comparing strategies is beneficial for identifying a
rank-order efficacy of control methods, this structure does not necessarily
determine the most effective combination of all available strategies. In order
for ASFV models to effectively support decision-making in controlling ASFV
globally, these modelling limitations need to be addressed.
| [
{
"created": "Thu, 19 Nov 2020 22:11:14 GMT",
"version": "v1"
},
{
"created": "Thu, 29 Apr 2021 07:44:11 GMT",
"version": "v2"
}
] | 2021-04-30 | [
[
"Hayes",
"Brandon H",
""
],
[
"Andraud",
"Mathieu",
""
],
[
"Salazar",
"Luis G",
""
],
[
"Rose",
"Nicolas",
""
],
[
"Vergne",
"Timothee",
""
]
] | The spread of African swine fever (ASF) poses a grave threat to the global swine industry. Understanding transmission dynamics, such as through mechanistic modeling, is critical for designing effective control strategies. Articles were examined across multiple epidemiological and model characteristics. Model filiation was determined through creation of a neighbor-joined tree using phylogenetic software. Of 34 four articles qualifying for inclusion, four main modelling objectives were identified: estimating transmission parameters (11 studies), assessing determinants of transmission (7), examining consequences of hypothetical outbreaks (5), and assessing alternative control strategies (11). Estimated transmission parameters varied widely as did parameter assumptions between models. Uncertainties on epidemiological and ecological parameters were usually accounted for to assess the impact on the modeled infection trajectory. Almost all models are host specific, being developed for either domestic pigs or wild boar despite the fact that spillover events between domestic pigs and wild boar are evidenced to play an important role in ASF outbreaks. The development of models incorporating such transmission routes is crucial. All compared control strategies were defined a priori, and future models should be built to identify optimal contributions across many control methods. Further, control strategies were examined in competition, opposed to how they would be synergistically implemented. While comparing strategies is beneficial for identifying a rank-order efficacy of control methods, this structure does not necessarily determine the most effective combination of all available strategies. In order for ASFV models to effectively support decision-making in controlling ASFV globally, these modelling limitations need to be addressed. |
1208.0029 | Tobias Reichenbach | Tobias Reichenbach, Aleksandra Stefanovic, Fumiaki Nin, A. J. Hudspeth | Waves on Reissner's membrane: a mechanism for the propagation of
otoacoustic emissions from the cochlea | 30 pages, 6 figures, and Supplemental information | Cell Reports 1, 374-384 (2012) | 10.1016/j.celrep.2012.02.013 | null | q-bio.TO physics.bio-ph physics.comp-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sound is detected and converted into electrical signals within the ear. The
cochlea not only acts as a passive detector of sound, however, but can also
produce tones itself. These otoacoustic emissions are a striking manifestation
of the cochlea's mechanical active process. A controversy remains of how these
mechanical signals propagate back to the middle ear, from which they are
emitted as sound. Here we combine theoretical and experimental studies to show
that mechanical signals can be transmitted by waves on Reissner's membrane, an
elastic structure within the cochea. We develop a theory for wave propagation
on Reissner's membrane and its role in otoacoustic emissions. Employing a
scanning laser interferometer, we measure traveling waves on Reissner's
membrane in the gerbil, guinea pig, and chinchilla. The results accord with the
theory and thus support a role for Reissner's membrane in otoacoustic
emissions.
| [
{
"created": "Tue, 31 Jul 2012 20:49:32 GMT",
"version": "v1"
}
] | 2012-08-02 | [
[
"Reichenbach",
"Tobias",
""
],
[
"Stefanovic",
"Aleksandra",
""
],
[
"Nin",
"Fumiaki",
""
],
[
"Hudspeth",
"A. J.",
""
]
] | Sound is detected and converted into electrical signals within the ear. The cochlea not only acts as a passive detector of sound, however, but can also produce tones itself. These otoacoustic emissions are a striking manifestation of the cochlea's mechanical active process. A controversy remains of how these mechanical signals propagate back to the middle ear, from which they are emitted as sound. Here we combine theoretical and experimental studies to show that mechanical signals can be transmitted by waves on Reissner's membrane, an elastic structure within the cochea. We develop a theory for wave propagation on Reissner's membrane and its role in otoacoustic emissions. Employing a scanning laser interferometer, we measure traveling waves on Reissner's membrane in the gerbil, guinea pig, and chinchilla. The results accord with the theory and thus support a role for Reissner's membrane in otoacoustic emissions. |
2003.01409 | Niceto R. Luque | Francisco Naveros, Niceto R. Luque, Eduardo Ros, Angelo Arleo | VOR Adaptation on a Humanoid iCub Robot Using a Spiking Cerebellar Model | null | null | 10.1109/TCYB.2019.2899246 | null | q-bio.NC cs.NE cs.RO cs.SY eess.SY | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We embed a spiking cerebellar model within an adaptive real-time (RT) control
loop that is able to operate a real robotic body (iCub) when performing
different vestibulo-ocular reflex (VOR) tasks. The spiking neural network
computation, including event- and time-driven neural dynamics, neural activity,
and spike-timing dependent plasticity (STDP) mechanisms, leads to a
nondeterministic computation time caused by the neural activity volleys
encountered during cerebellar simulation. This nondeterministic computation
time motivates the integration of an RT supervisor module that is able to
ensure a well-orchestrated neural computation time and robot operation.
Actually, our neurorobotic experimental setup (VOR) benefits from the
biological sensory motor delay between the cerebellum and the body to buffer
the computational overloads as well as providing flexibility in adjusting the
neural computation time and RT operation. The RT supervisor module provides for
incremental countermeasures that dynamically slow down or speed up the
cerebellar simulation by either halting the simulation or disabling certain
neural computation features (i.e., STDP mechanisms, spike propagation, and
neural updates) to cope with the RT constraints imposed by the real robot
operation. This neurorobotic experimental setup is applied to different
horizontal and vertical VOR adaptive tasks that are widely used by the
neuroscientific community to address cerebellar functioning. We aim to
elucidate the manner in which the combination of the cerebellar neural
substrate and the distributed plasticity shapes the cerebellar neural activity
to mediate motor adaptation. This paper underlies the need for a two-stage
learning process to facilitate VOR acquisition.
| [
{
"created": "Tue, 3 Mar 2020 09:48:15 GMT",
"version": "v1"
},
{
"created": "Tue, 31 Mar 2020 07:26:00 GMT",
"version": "v2"
}
] | 2020-04-01 | [
[
"Naveros",
"Francisco",
""
],
[
"Luque",
"Niceto R.",
""
],
[
"Ros",
"Eduardo",
""
],
[
"Arleo",
"Angelo",
""
]
] | We embed a spiking cerebellar model within an adaptive real-time (RT) control loop that is able to operate a real robotic body (iCub) when performing different vestibulo-ocular reflex (VOR) tasks. The spiking neural network computation, including event- and time-driven neural dynamics, neural activity, and spike-timing dependent plasticity (STDP) mechanisms, leads to a nondeterministic computation time caused by the neural activity volleys encountered during cerebellar simulation. This nondeterministic computation time motivates the integration of an RT supervisor module that is able to ensure a well-orchestrated neural computation time and robot operation. Actually, our neurorobotic experimental setup (VOR) benefits from the biological sensory motor delay between the cerebellum and the body to buffer the computational overloads as well as providing flexibility in adjusting the neural computation time and RT operation. The RT supervisor module provides for incremental countermeasures that dynamically slow down or speed up the cerebellar simulation by either halting the simulation or disabling certain neural computation features (i.e., STDP mechanisms, spike propagation, and neural updates) to cope with the RT constraints imposed by the real robot operation. This neurorobotic experimental setup is applied to different horizontal and vertical VOR adaptive tasks that are widely used by the neuroscientific community to address cerebellar functioning. We aim to elucidate the manner in which the combination of the cerebellar neural substrate and the distributed plasticity shapes the cerebellar neural activity to mediate motor adaptation. This paper underlies the need for a two-stage learning process to facilitate VOR acquisition. |
1311.2665 | Chen Jia | Chen Jia, Daquan Jiang, Minping Qian | An allosteric model of the inositol trisphosphate receptor with
nonequilibrium binding | 23 pages, 5 figures | Physical Biology, 11(5):056001, 2014 | 10.1088/1478-3975/11/5/056001 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The inositol trisphosphate receptor (IPR) is a crucial ion channel that
regulates the Ca$^{2+}$ influx from the endoplasmic reticulum (ER) to the
cytoplasm. A thorough study of the IPR channel contributes to a better
understanding of calcium oscillations and waves. It has long been observed that
the IPR channel is a typical biological system which performs adaptation.
However, recent advances on the physical essence of adaptation show that
adaptation systems with a negative feedback mechanism, such as the IPR channel,
must break detailed balance and always operate out of equilibrium with energy
dissipation. Almost all previous IPR models are equilibrium models assuming
detailed balance and thus violate the physical essence of adaptation. In this
article, we constructed a nonequilibrium allosteric model of single IPR
channels based on the patch-clamp experimental data obtained from the IPR in
the outer membranes of isolated nuclei of the \emph{Xenopus} oocyte. It turns
out that our model reproduces the patch-clamp experimental data reasonably well
and produces both the correct steady-state and dynamic properties of the
channel. Particularly, our model successfully describes the complicated bimodal
[Ca$^{2+}$] dependence of the mean open duration at high [IP$_3$], a
steady-state behavior which fails to be correctly described in previous IPR
models. Finally, we used the patch-clamp experimental data to validate that the
IPR channel indeed breaks detailed balance and thus is a nonequilibrium system
which consumes energy.
| [
{
"created": "Tue, 12 Nov 2013 03:23:05 GMT",
"version": "v1"
},
{
"created": "Fri, 4 Jul 2014 15:21:35 GMT",
"version": "v2"
}
] | 2014-08-28 | [
[
"Jia",
"Chen",
""
],
[
"Jiang",
"Daquan",
""
],
[
"Qian",
"Minping",
""
]
] | The inositol trisphosphate receptor (IPR) is a crucial ion channel that regulates the Ca$^{2+}$ influx from the endoplasmic reticulum (ER) to the cytoplasm. A thorough study of the IPR channel contributes to a better understanding of calcium oscillations and waves. It has long been observed that the IPR channel is a typical biological system which performs adaptation. However, recent advances on the physical essence of adaptation show that adaptation systems with a negative feedback mechanism, such as the IPR channel, must break detailed balance and always operate out of equilibrium with energy dissipation. Almost all previous IPR models are equilibrium models assuming detailed balance and thus violate the physical essence of adaptation. In this article, we constructed a nonequilibrium allosteric model of single IPR channels based on the patch-clamp experimental data obtained from the IPR in the outer membranes of isolated nuclei of the \emph{Xenopus} oocyte. It turns out that our model reproduces the patch-clamp experimental data reasonably well and produces both the correct steady-state and dynamic properties of the channel. Particularly, our model successfully describes the complicated bimodal [Ca$^{2+}$] dependence of the mean open duration at high [IP$_3$], a steady-state behavior which fails to be correctly described in previous IPR models. Finally, we used the patch-clamp experimental data to validate that the IPR channel indeed breaks detailed balance and thus is a nonequilibrium system which consumes energy. |
2102.12602 | Guillermo Lorenzo | Guillermo Lorenzo, David A. Hormuth II, Angela M. Jarrett, Ernesto A.
B. F. Lima, Shashank Subramanian, George Biros, J. Tinsley Oden, Thomas J. R.
Hughes, and Thomas E. Yankeelov | Quantitative in vivo imaging to enable tumor forecasting and treatment
optimization | null | null | null | null | q-bio.TO cs.CE q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Current clinical decision-making in oncology relies on averages of large
patient populations to both assess tumor status and treatment outcomes.
However, cancers exhibit an inherent evolving heterogeneity that requires an
individual approach based on rigorous and precise predictions of cancer growth
and treatment response. To this end, we advocate the use of quantitative in
vivo imaging data to calibrate mathematical models for the personalized
forecasting of tumor development. In this chapter, we summarize the main data
types available from both common and emerging in vivo medical imaging
technologies, and how these data can be used to obtain patient-specific
parameters for common mathematical models of cancer. We then outline
computational methods designed to solve these models, thereby enabling their
use for producing personalized tumor forecasts in silico, which, ultimately,
can be used to not only predict response, but also optimize treatment. Finally,
we discuss the main barriers to making the above paradigm a clinical reality.
| [
{
"created": "Wed, 24 Feb 2021 23:32:48 GMT",
"version": "v1"
}
] | 2021-02-26 | [
[
"Lorenzo",
"Guillermo",
""
],
[
"Hormuth",
"David A.",
"II"
],
[
"Jarrett",
"Angela M.",
""
],
[
"Lima",
"Ernesto A. B. F.",
""
],
[
"Subramanian",
"Shashank",
""
],
[
"Biros",
"George",
""
],
[
"Oden",
"J. Tinsley",
""
],
[
"Hughes",
"Thomas J. R.",
""
],
[
"Yankeelov",
"Thomas E.",
""
]
] | Current clinical decision-making in oncology relies on averages of large patient populations to both assess tumor status and treatment outcomes. However, cancers exhibit an inherent evolving heterogeneity that requires an individual approach based on rigorous and precise predictions of cancer growth and treatment response. To this end, we advocate the use of quantitative in vivo imaging data to calibrate mathematical models for the personalized forecasting of tumor development. In this chapter, we summarize the main data types available from both common and emerging in vivo medical imaging technologies, and how these data can be used to obtain patient-specific parameters for common mathematical models of cancer. We then outline computational methods designed to solve these models, thereby enabling their use for producing personalized tumor forecasts in silico, which, ultimately, can be used to not only predict response, but also optimize treatment. Finally, we discuss the main barriers to making the above paradigm a clinical reality. |
1802.00102 | Laura Schaposnik | Laura P. Schaposnik, Anlin Zhang | Modeling epidemics on d-cliqued graphs | 11 pages, 16 figures | Letters in Biomathematics, Vol. 5, Iss. 1, 2018 | 10.1080/23737867.2017.1419080 | null | q-bio.PE cs.SI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Since social interactions have been shown to lead to symmetric clusters, we
propose here that symmetries play a key role in epidemic modeling. Mathematical
models on d-ary tree graphs were recently shown to be particularly effective
for modeling epidemics in simple networks [Seibold & Callender, 2016]. To
account for symmetric relations, we generalize this to a new type of networks
modeled on d-cliqued tree graphs, which are obtained by adding edges to regular
d-trees to form d-cliques. This setting gives a more realistic model for
epidemic outbreaks originating, for example, within a family or classroom and
which could reach a population by transmission via children in schools.
Specifically, we quantify how an infection starting in a clique (e.g. family)
can reach other cliques through the body of the graph (e.g. public places).
Moreover, we propose and study the notion of a safe zone, a subset that has a
negligible probability of infection.
| [
{
"created": "Wed, 31 Jan 2018 23:35:04 GMT",
"version": "v1"
}
] | 2019-05-24 | [
[
"Schaposnik",
"Laura P.",
""
],
[
"Zhang",
"Anlin",
""
]
] | Since social interactions have been shown to lead to symmetric clusters, we propose here that symmetries play a key role in epidemic modeling. Mathematical models on d-ary tree graphs were recently shown to be particularly effective for modeling epidemics in simple networks [Seibold & Callender, 2016]. To account for symmetric relations, we generalize this to a new type of networks modeled on d-cliqued tree graphs, which are obtained by adding edges to regular d-trees to form d-cliques. This setting gives a more realistic model for epidemic outbreaks originating, for example, within a family or classroom and which could reach a population by transmission via children in schools. Specifically, we quantify how an infection starting in a clique (e.g. family) can reach other cliques through the body of the graph (e.g. public places). Moreover, we propose and study the notion of a safe zone, a subset that has a negligible probability of infection. |
2109.01571 | Karl Grieshop | Karl Grieshop, Eddie K.H. Ho, Katja R. Kasimatis | Dominance reversals: The resolution of genetic conflict and maintenance
of genetic variation | Review paper with some original theory, 1 Figure, 1 table, 1 box, and
Supporting Information (including 11 Figures and 2 tables) | Proceedings of the Royal Society B, 291(2018), p.20232816 (2024) | 10.1098/rspb.2023.2816 | null | q-bio.PE q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Beneficial reversals of dominance reduce the costs of genetic trade-offs and
can enable selection to maintain genetic variation for fitness. Beneficial
dominance reversals are characterized by the beneficial allele for a given
context (e.g. habitat, developmental stage, trait, or sex) being dominant in
that context but recessive where deleterious. This context-dependence at least
partially mitigates the fitness consequence of heterozygotes carrying one
non-beneficial allele for their context and can result in balancing selection
that maintains alternative alleles. Dominance reversals are theoretically
plausible and are supported by mounting empirical evidence. Here we highlight
the importance of beneficial dominance reversals as a mechanism for the
mitigation of genetic conflict and review the theory and empirical evidence for
them. We identify some areas in need of further research and development and
outline three methods (dominance ordination, allele-specific expression, and
allele-specific ATAC-Seq) that could facilitate the identification of
antagonistic genetic variation. There is ample scope for the development of new
empirical methods as well as reanalysis of existing data through the lens of
dominance reversals. A greater focus on this topic will expand our
understanding of the mechanisms that resolve genetic conflict and whether they
maintain genetic variation.
| [
{
"created": "Fri, 3 Sep 2021 14:52:31 GMT",
"version": "v1"
},
{
"created": "Sat, 15 Oct 2022 16:15:07 GMT",
"version": "v2"
},
{
"created": "Wed, 13 Dec 2023 13:08:56 GMT",
"version": "v3"
},
{
"created": "Fri, 26 Jan 2024 09:32:50 GMT",
"version": "v4"
}
] | 2024-03-28 | [
[
"Grieshop",
"Karl",
""
],
[
"Ho",
"Eddie K. H.",
""
],
[
"Kasimatis",
"Katja R.",
""
]
] | Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g. habitat, developmental stage, trait, or sex) being dominant in that context but recessive where deleterious. This context-dependence at least partially mitigates the fitness consequence of heterozygotes carrying one non-beneficial allele for their context and can result in balancing selection that maintains alternative alleles. Dominance reversals are theoretically plausible and are supported by mounting empirical evidence. Here we highlight the importance of beneficial dominance reversals as a mechanism for the mitigation of genetic conflict and review the theory and empirical evidence for them. We identify some areas in need of further research and development and outline three methods (dominance ordination, allele-specific expression, and allele-specific ATAC-Seq) that could facilitate the identification of antagonistic genetic variation. There is ample scope for the development of new empirical methods as well as reanalysis of existing data through the lens of dominance reversals. A greater focus on this topic will expand our understanding of the mechanisms that resolve genetic conflict and whether they maintain genetic variation. |
2201.11748 | Roberto Rojas-Cessa | Jorge Medina, Roberto Rojas-Cessa, and Vatcharapan Umpaichitra | Reducing COVID-19 Cases and Deaths by Applying Blockchain in Vaccination
Rollout Management | Peer reviewed | in IEEE Open Journal of Engineering in Medicine and Biology, vol.
2, pp. 249-255, 2021 | 10.1109/OJEMB.2021.3093774 | null | q-bio.QM cs.CY | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Because a fast vaccination rollout against coronavirus disease 2019
(COVID-19) is critical to restore daily life and avoid virus mutations, it is
tempting to have a relaxed vaccination-administration management system.
However, a robust management system can support the enforcement of preventive
measures, and in turn, reduce incidence and deaths. Here, we model a trustable
and reliable management system based on blockchain for vaccine distribution by
extending the Susceptible-Exposed-Infected-Recovery (SEIR) model. The model
includes prevention measures such as mask-wearing, social distance, vaccination
rate, and vaccination efficiency. It also considers negative social behavior,
such as violations of social distance and attempts of using illegitimate
vaccination proofs. By evaluating the model, we show that the proposed system
can reduce up to 2.5 million cases and half a million deaths in the most
demanding scenarios.
| [
{
"created": "Thu, 27 Jan 2022 18:31:41 GMT",
"version": "v1"
},
{
"created": "Wed, 16 Mar 2022 13:29:18 GMT",
"version": "v2"
}
] | 2022-03-17 | [
[
"Medina",
"Jorge",
""
],
[
"Rojas-Cessa",
"Roberto",
""
],
[
"Umpaichitra",
"Vatcharapan",
""
]
] | Because a fast vaccination rollout against coronavirus disease 2019 (COVID-19) is critical to restore daily life and avoid virus mutations, it is tempting to have a relaxed vaccination-administration management system. However, a robust management system can support the enforcement of preventive measures, and in turn, reduce incidence and deaths. Here, we model a trustable and reliable management system based on blockchain for vaccine distribution by extending the Susceptible-Exposed-Infected-Recovery (SEIR) model. The model includes prevention measures such as mask-wearing, social distance, vaccination rate, and vaccination efficiency. It also considers negative social behavior, such as violations of social distance and attempts of using illegitimate vaccination proofs. By evaluating the model, we show that the proposed system can reduce up to 2.5 million cases and half a million deaths in the most demanding scenarios. |
1907.04953 | Da-Young Lee | Da-Young Lee, Dong-Yeop Na, Yong Seok Heo, and Guo-Liang Wang | Digital image quantification of rice sheath blight: Optimized
segmentation and automatic classification | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Rapid and accurate phenotypic screening of rice germplasms is crucial in
screening for sources of rice sheath blight resistance. However, visual and/or
caliper-based estimations of coalescing, necrotic, ShB disease lesions are
time-consuming, labor-intensive and exposed to human rater subjectivity. Here,
we propose the use of RGB images and image processing techniques to quantify
ShB disease progression in terms of lesion height and diseased area. To be
specific, we developed a pixel color- and coordinate-based K-Means Clustering
(PCC-KMC) algorithm utilizing Mahalanobis metric aimed at accurate segmentation
of symptomatic and non-symptomatic regions within rice stem images. The
performance of PCC-KMC was evaluated using Lin's concordance correlation
coefficient by comparing its results to visual measurements of ShB lesion
height and to lesion/diseased area measured using ImageJ. Low bias and high
precision were observed for absolute lesion height (bias=0.93, precision=0.94)
and absolute symptomatic area (bias=0.98, precision=0.97) studies. Moreover, we
introduced a convolutional neural network (CNN) for the automatic annotation on
clusters, termed PCC-KMC-CNN. Our CNN was trained based on 85%:15% of
composition for training and testing dataset from total 168 ShB-infected stem
sample images, recording 92% accuracy and 0.21 loss. PCC-KMC-CNN also showed
high accuracy and precision for the absolute lesion height (bias=0.86,
precision=0.90) and absolute diseased area (bias=0.99, precision=0.97) studies.
These results demonstrate that the present methodology has great potential and
promise to substitute the traditional visual-based ShB disease severity
assessment.
| [
{
"created": "Wed, 10 Jul 2019 23:11:27 GMT",
"version": "v1"
},
{
"created": "Tue, 13 Apr 2021 06:04:03 GMT",
"version": "v2"
}
] | 2021-04-14 | [
[
"Lee",
"Da-Young",
""
],
[
"Na",
"Dong-Yeop",
""
],
[
"Heo",
"Yong Seok",
""
],
[
"Wang",
"Guo-Liang",
""
]
] | Rapid and accurate phenotypic screening of rice germplasms is crucial in screening for sources of rice sheath blight resistance. However, visual and/or caliper-based estimations of coalescing, necrotic, ShB disease lesions are time-consuming, labor-intensive and exposed to human rater subjectivity. Here, we propose the use of RGB images and image processing techniques to quantify ShB disease progression in terms of lesion height and diseased area. To be specific, we developed a pixel color- and coordinate-based K-Means Clustering (PCC-KMC) algorithm utilizing Mahalanobis metric aimed at accurate segmentation of symptomatic and non-symptomatic regions within rice stem images. The performance of PCC-KMC was evaluated using Lin's concordance correlation coefficient by comparing its results to visual measurements of ShB lesion height and to lesion/diseased area measured using ImageJ. Low bias and high precision were observed for absolute lesion height (bias=0.93, precision=0.94) and absolute symptomatic area (bias=0.98, precision=0.97) studies. Moreover, we introduced a convolutional neural network (CNN) for the automatic annotation on clusters, termed PCC-KMC-CNN. Our CNN was trained based on 85%:15% of composition for training and testing dataset from total 168 ShB-infected stem sample images, recording 92% accuracy and 0.21 loss. PCC-KMC-CNN also showed high accuracy and precision for the absolute lesion height (bias=0.86, precision=0.90) and absolute diseased area (bias=0.99, precision=0.97) studies. These results demonstrate that the present methodology has great potential and promise to substitute the traditional visual-based ShB disease severity assessment. |
2006.09818 | Nathaniel Barlow | Steven J. Weinstein, Morgan S. Holland, Kelly E. Rogers, Nathaniel S.
Barlow | Analytic solution of the SEIR epidemic model via asymptotic approximant | original version had substantial text overlap with arXiv:2004.07833;
this is now less so | null | 10.1016/j.physd.2020.132633 | null | q-bio.PE physics.soc-ph | http://creativecommons.org/licenses/by-sa/4.0/ | An analytic solution is obtained to the SEIR Epidemic Model. The solution is
created by constructing a single second-order nonlinear differential equation
in $\ln S$ and analytically continuing its divergent power series solution such
that it matches the correct long-time exponential damping of the epidemic
model. This is achieved through an asymptotic approximant (Barlow et. al, 2017,
Q. Jl Mech. Appl. Math, 70 (1), 21-48) in the form of a modified symmetric
Pad\'e approximant that incorporates this damping. The utility of the
analytical form is demonstrated through its application to the COVID-19
pandemic.
| [
{
"created": "Fri, 12 Jun 2020 20:18:44 GMT",
"version": "v1"
},
{
"created": "Tue, 30 Jun 2020 01:52:51 GMT",
"version": "v2"
}
] | 2020-07-01 | [
[
"Weinstein",
"Steven J.",
""
],
[
"Holland",
"Morgan S.",
""
],
[
"Rogers",
"Kelly E.",
""
],
[
"Barlow",
"Nathaniel S.",
""
]
] | An analytic solution is obtained to the SEIR Epidemic Model. The solution is created by constructing a single second-order nonlinear differential equation in $\ln S$ and analytically continuing its divergent power series solution such that it matches the correct long-time exponential damping of the epidemic model. This is achieved through an asymptotic approximant (Barlow et. al, 2017, Q. Jl Mech. Appl. Math, 70 (1), 21-48) in the form of a modified symmetric Pad\'e approximant that incorporates this damping. The utility of the analytical form is demonstrated through its application to the COVID-19 pandemic. |
1108.4642 | Steven Kelk | Steven Kelk | A note on efficient computation of hybridization number via softwired
clusters | null | null | null | null | q-bio.PE cs.DS | 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 binary phylogenetic trees on taxon set X
in time (6r)^r.poly(n), where n=|X|. The novelty of this approach is that it
avoids the use of Maximum Acyclic Agreement Forests (MAAFs) and instead
exploits the equivalence of the problem with a related problem from the
softwired clusters literature. This offers an alternative perspective on the
underlying combinatorial structure of the hybridization number problem.
| [
{
"created": "Tue, 23 Aug 2011 15:54:02 GMT",
"version": "v1"
}
] | 2011-08-24 | [
[
"Kelk",
"Steven",
""
]
] | Here we present a new fixed parameter tractable algorithm to compute the hybridization number r of two rooted binary phylogenetic trees on taxon set X in time (6r)^r.poly(n), where n=|X|. The novelty of this approach is that it avoids the use of Maximum Acyclic Agreement Forests (MAAFs) and instead exploits the equivalence of the problem with a related problem from the softwired clusters literature. This offers an alternative perspective on the underlying combinatorial structure of the hybridization number problem. |
2102.06490 | Michael Grinfeld | Michael Grinfeld, Nigel Mottram and Jozsef Farkas | A General Model of Structured Cell Kinetics | 8 pages, 1 figure | null | null | null | q-bio.CB nlin.PS | http://creativecommons.org/licenses/by/4.0/ | We present a modelling framework for the dynamics of cells structured by the
concentration of a micromolecule they contain. We derive general equations for
the evolution of the cell population and of the extra-cellular concentration of
the molecule and apply this approach to models of silicosis and quorum sensing
in Gram-negative bacteria
| [
{
"created": "Fri, 12 Feb 2021 12:44:56 GMT",
"version": "v1"
}
] | 2021-02-15 | [
[
"Grinfeld",
"Michael",
""
],
[
"Mottram",
"Nigel",
""
],
[
"Farkas",
"Jozsef",
""
]
] | We present a modelling framework for the dynamics of cells structured by the concentration of a micromolecule they contain. We derive general equations for the evolution of the cell population and of the extra-cellular concentration of the molecule and apply this approach to models of silicosis and quorum sensing in Gram-negative bacteria |
1703.10677 | Yang Chen | Yang Chen, Dong-Jie Zhao, Chao Song, Wei-He Liu, Zi-Yang Wang,
Zhong-Yi Wang, Guiliang Tang, and Lan Huang | Detecting causality in Plant electrical signal by a hybrid causal
analysis approach | 12 figures | null | null | null | q-bio.NC q-bio.TO | http://creativecommons.org/licenses/by-nc-sa/4.0/ | At present, multi-electrode array (MEA) approach and optical recording allow
us to acquire plant electrical activity with higher spatio-temporal resolution.
To understand the dynamic information flow of the electrical signaling system
and estimate the effective connectivity, we proposed a solution to combine the
two casualty analysis approaches, i.e. Granger causality and transfer entropy,
which they complement each other to measure dynamics effective connectivity of
the complex system. Our findings in three qualitatively different levels of
plant bioelectrical activities revealed direction of information flow and
dynamic complex causal connectives by using the two causal analysis approaches,
especially indicated that the direction of information flow is not only along
the longitudinal section but also spreading in transection.
| [
{
"created": "Wed, 22 Mar 2017 02:11:45 GMT",
"version": "v1"
}
] | 2017-04-03 | [
[
"Chen",
"Yang",
""
],
[
"Zhao",
"Dong-Jie",
""
],
[
"Song",
"Chao",
""
],
[
"Liu",
"Wei-He",
""
],
[
"Wang",
"Zi-Yang",
""
],
[
"Wang",
"Zhong-Yi",
""
],
[
"Tang",
"Guiliang",
""
],
[
"Huang",
"Lan",
""
]
] | At present, multi-electrode array (MEA) approach and optical recording allow us to acquire plant electrical activity with higher spatio-temporal resolution. To understand the dynamic information flow of the electrical signaling system and estimate the effective connectivity, we proposed a solution to combine the two casualty analysis approaches, i.e. Granger causality and transfer entropy, which they complement each other to measure dynamics effective connectivity of the complex system. Our findings in three qualitatively different levels of plant bioelectrical activities revealed direction of information flow and dynamic complex causal connectives by using the two causal analysis approaches, especially indicated that the direction of information flow is not only along the longitudinal section but also spreading in transection. |
0811.3464 | Elfi Kraka | Sushilee Ranganathan, Dmitry Izotov, Elfi Kraka, and Dieter Cremer | Classification of Supersecondary Structures in Proteins Using the
Automated Protein Structure Analysis Method | 40 pages, 5 figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Automated Protein Structure Analysis (APSA) method is used for the
classification of supersecondary structures. Basis for the classification is
the encoding of three-dimensional (3D) residue conformations into a 16-letter
code (3D-1D projection). It is shown that the letter code of the protein makes
it possible to reconstruct its overall shape without ambiguity (1D-3D
translation). Accordingly, the letter code is used for the development of
classification rules that distinguish supersecondary structures by the
properties of their turns and the orientation of the flanking helix or strand
structures. The orientations of turn and flanking structures are collected in
an octant system that helps to specify 196 supersecondary groups for
(alpha,alpha)-, (alpha,beta)-, (beta,alpha)-, (beta,beta)-class. 391 protein
chains leading to 2499 super secondary structures were analyzed. Frequently
occurring super secondary structures are identified with the help of the octant
classification system and explained on the basis of their letter and
classification codes.
| [
{
"created": "Fri, 21 Nov 2008 04:24:40 GMT",
"version": "v1"
},
{
"created": "Mon, 24 Nov 2008 20:52:14 GMT",
"version": "v2"
}
] | 2008-11-24 | [
[
"Ranganathan",
"Sushilee",
""
],
[
"Izotov",
"Dmitry",
""
],
[
"Kraka",
"Elfi",
""
],
[
"Cremer",
"Dieter",
""
]
] | The Automated Protein Structure Analysis (APSA) method is used for the classification of supersecondary structures. Basis for the classification is the encoding of three-dimensional (3D) residue conformations into a 16-letter code (3D-1D projection). It is shown that the letter code of the protein makes it possible to reconstruct its overall shape without ambiguity (1D-3D translation). Accordingly, the letter code is used for the development of classification rules that distinguish supersecondary structures by the properties of their turns and the orientation of the flanking helix or strand structures. The orientations of turn and flanking structures are collected in an octant system that helps to specify 196 supersecondary groups for (alpha,alpha)-, (alpha,beta)-, (beta,alpha)-, (beta,beta)-class. 391 protein chains leading to 2499 super secondary structures were analyzed. Frequently occurring super secondary structures are identified with the help of the octant classification system and explained on the basis of their letter and classification codes. |
1205.2358 | Thomas R. Weikl | Thomas R. Weikl and David D. Boehr | Conformational selection and induced changes along the catalytic cycle
of E. coli DHFR | 14 pages, 8 figures, 2 tables | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Protein function often involves changes between different conformations.
Central questions are how these conformational changes are coupled to the
binding or catalytic processes during which they occur, and how they affect the
catalytic rates of enzymes. An important model system is the enzyme
dihydrofolate reductase (DHFR) from E. coli, which exhibits characteristic
conformational changes of the active-site loop during the catalytic step and
during unbinding of the product. In this article, we present a general kinetic
framework that can be used (1) to identify the ordering of events in the
coupling of conformational changes, binding and catalysis and (2) to determine
the rates of the substeps of coupled processes from a combined analysis of NMR
R2 relaxation dispersion experiments and traditional enzyme kinetics
measurements. We apply this framework to E. coli DHFR and find that the
conformational change during product unbinding follows a
conformational-selection mechanism, i.e. the conformational change occurs
predominantly prior to unbinding. The conformational change during the
catalytic step, in contrast, is an induced change, i.e. the change occurs after
the chemical reaction. We propose that the reason for these conformational
changes, which are absent in human and other vertebrate DHFRs, is robustness of
the catalytic rate against large pH variations and changes to substrate/product
concentrations in E. coli.
| [
{
"created": "Thu, 10 May 2012 19:25:53 GMT",
"version": "v1"
}
] | 2012-05-11 | [
[
"Weikl",
"Thomas R.",
""
],
[
"Boehr",
"David D.",
""
]
] | Protein function often involves changes between different conformations. Central questions are how these conformational changes are coupled to the binding or catalytic processes during which they occur, and how they affect the catalytic rates of enzymes. An important model system is the enzyme dihydrofolate reductase (DHFR) from E. coli, which exhibits characteristic conformational changes of the active-site loop during the catalytic step and during unbinding of the product. In this article, we present a general kinetic framework that can be used (1) to identify the ordering of events in the coupling of conformational changes, binding and catalysis and (2) to determine the rates of the substeps of coupled processes from a combined analysis of NMR R2 relaxation dispersion experiments and traditional enzyme kinetics measurements. We apply this framework to E. coli DHFR and find that the conformational change during product unbinding follows a conformational-selection mechanism, i.e. the conformational change occurs predominantly prior to unbinding. The conformational change during the catalytic step, in contrast, is an induced change, i.e. the change occurs after the chemical reaction. We propose that the reason for these conformational changes, which are absent in human and other vertebrate DHFRs, is robustness of the catalytic rate against large pH variations and changes to substrate/product concentrations in E. coli. |
2311.12080 | Alaa Sadiq | Alaa M. Sadeq | Exploring the Relationship Between COVID-19 Induced Economic Downturn
and Women's Nutritional Health Disparities | null | null | null | null | q-bio.OT | http://creativecommons.org/licenses/by/4.0/ | This study explores how the COVID-19 pandemic's economic impact has
exacerbated nutritional health disparities among women. It sought to understand
the effects of economic challenges on women's dietary choices and access to
nutritious food across different socioeconomic groups. Using a mixed-methods
approach, the research combined quantitative data from health and economic
records with qualitative insights from interviews with diverse women. The study
analyzed trends in nutritional health and economic factors before and after the
pandemic and gathered personal accounts regarding nutrition and economic
difficulties during this period. Findings showed a clear link between the
economic downturn and deteriorating nutritional health, particularly in
low-income and marginalized groups. These women reported decreased access to
healthy foods and an increased dependence on less nutritious options due to
budget constraints, leading to a decline in dietary quality. This trend was
less evident in higher-income groups, highlighting stark disparities. The
pandemic intensified pre-existing nutritional inequalities, with the most
vulnerable groups facing greater adverse effects. However, community support
and public health measures provided some relief. In summary, the pandemic's
economic repercussions have indirectly impaired women's nutritional health,
especially among the socioeconomically disadvantaged. This highlights the
necessity for tailored nutritional interventions and economic policies focused
on safeguarding women's health.
| [
{
"created": "Mon, 20 Nov 2023 09:10:25 GMT",
"version": "v1"
}
] | 2023-11-22 | [
[
"Sadeq",
"Alaa M.",
""
]
] | This study explores how the COVID-19 pandemic's economic impact has exacerbated nutritional health disparities among women. It sought to understand the effects of economic challenges on women's dietary choices and access to nutritious food across different socioeconomic groups. Using a mixed-methods approach, the research combined quantitative data from health and economic records with qualitative insights from interviews with diverse women. The study analyzed trends in nutritional health and economic factors before and after the pandemic and gathered personal accounts regarding nutrition and economic difficulties during this period. Findings showed a clear link between the economic downturn and deteriorating nutritional health, particularly in low-income and marginalized groups. These women reported decreased access to healthy foods and an increased dependence on less nutritious options due to budget constraints, leading to a decline in dietary quality. This trend was less evident in higher-income groups, highlighting stark disparities. The pandemic intensified pre-existing nutritional inequalities, with the most vulnerable groups facing greater adverse effects. However, community support and public health measures provided some relief. In summary, the pandemic's economic repercussions have indirectly impaired women's nutritional health, especially among the socioeconomically disadvantaged. This highlights the necessity for tailored nutritional interventions and economic policies focused on safeguarding women's health. |
1307.7872 | Claudius Gros | Claudius Gros | Generating functionals for guided self-organization | To be published in "Guided Self-Organization: Inception", Springer
Series on Emergence, Complexity and Computation, M. Prokopenko (ed),
Proceedings of Fifth International Workshop on Guided Self-Organization,
Sydney 2012 | M. Prokopenko (ed.), Guided Self-Organization: Inception, 53-66,
Springer (2014) | null | null | q-bio.NC nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Time evolution equations for dynamical systems can often be derived from
generating functionals. Examples are Newton's equations of motion in classical
dynamics which can be generated within the Lagrange or the Hamiltonian
formalism. We propose that generating functionals for self-organizing complex
systems offer several advantages. Generating functionals allow to formulate
complex dynamical systems systematically and the results obtained are typically
valid for classes of complex systems, as defined by the type of their
respective generating functionals. The generated dynamical systems tend, in
addition, to be minimal, containing only few free and undetermined parameters.
We point out that two or more generating functionals may be used to define a
complex system and that multiple generating function may not, and should not,
be combined into a single overall objective function. We provide and discuss
examples in terms of adapting neural networks.
| [
{
"created": "Tue, 30 Jul 2013 08:53:04 GMT",
"version": "v1"
}
] | 2014-04-23 | [
[
"Gros",
"Claudius",
""
]
] | Time evolution equations for dynamical systems can often be derived from generating functionals. Examples are Newton's equations of motion in classical dynamics which can be generated within the Lagrange or the Hamiltonian formalism. We propose that generating functionals for self-organizing complex systems offer several advantages. Generating functionals allow to formulate complex dynamical systems systematically and the results obtained are typically valid for classes of complex systems, as defined by the type of their respective generating functionals. The generated dynamical systems tend, in addition, to be minimal, containing only few free and undetermined parameters. We point out that two or more generating functionals may be used to define a complex system and that multiple generating function may not, and should not, be combined into a single overall objective function. We provide and discuss examples in terms of adapting neural networks. |
1211.2458 | Paul H\'eroux | Su Dong, Paul Heroux | Survey of Extra-Low Frequency and Very-Low Frequency Magnetic Fields in
Cell Culture Incubators | 59 pages, 20 figures, 7 appendices | null | null | null | q-bio.QM physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A typical cell culture CO2 incubator was probed in detail to document the
pattern of 60-Hz magnetic fields (MFs) inside the unit, as well as the ability
of the incubator to attenuate environmental MFs. Subsequently, a survey of 46
cell culture incubators was performed. The survey measured MFs outside and
inside the incubators, the frequency spectrum between 5 and 2000 Hz, and
variations over time of the 60-Hz MF. Our measurements show an uneven spatial
distribution, reflecting electronic and electrical components hidden within the
walls. Attenuation of environmental MFs varied between 18 % and 33 %,
signalling easy penetration into the units. MF levels, frequency spectra and
variations over time were very different from one unit to the next. All 46
incubators surveyed had an average field greater than 0.2 microT; among them,
39 (85 %) had an average field greater than 1 microT. There is substantial work
to be done in improving control over the MF environment of in vitro experiments
in bio-medicine, particularly if they involve cancer cells.
| [
{
"created": "Sun, 11 Nov 2012 20:40:00 GMT",
"version": "v1"
}
] | 2012-11-13 | [
[
"Dong",
"Su",
""
],
[
"Heroux",
"Paul",
""
]
] | A typical cell culture CO2 incubator was probed in detail to document the pattern of 60-Hz magnetic fields (MFs) inside the unit, as well as the ability of the incubator to attenuate environmental MFs. Subsequently, a survey of 46 cell culture incubators was performed. The survey measured MFs outside and inside the incubators, the frequency spectrum between 5 and 2000 Hz, and variations over time of the 60-Hz MF. Our measurements show an uneven spatial distribution, reflecting electronic and electrical components hidden within the walls. Attenuation of environmental MFs varied between 18 % and 33 %, signalling easy penetration into the units. MF levels, frequency spectra and variations over time were very different from one unit to the next. All 46 incubators surveyed had an average field greater than 0.2 microT; among them, 39 (85 %) had an average field greater than 1 microT. There is substantial work to be done in improving control over the MF environment of in vitro experiments in bio-medicine, particularly if they involve cancer cells. |
2406.15987 | Francis Motta | Francis C. Motta, Kevin McGoff, Breschine Cummins, Steven B. Haase | Generalized Measures of Population Synchrony | null | null | null | null | q-bio.PE math.PR q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Synchronized behavior among individuals is a ubiquitous feature of
populations. Understanding mechanisms of (de)synchronization demands
meaningful, interpretable, computable quantifications of synchrony, relevant to
measurements that can be made of dynamic populations. Despite the importance to
analyzing and modeling populations, existing notions of synchrony often lack
rigorous definitions, may be specialized to a particular experimental system
and/or measurement, or may have undesirable properties that limit their
utility. We introduce a notion of synchrony for populations of individuals
occupying a compact metric space that depends on the Fr\'{e}chet variance of
the distribution of individuals. We establish several fundamental and desirable
mathematical properties of this synchrony measure, including continuity and
invariance to metric scaling. We establish a general approximation result that
controls the disparity between synchrony in the true space and the synchrony
observed through a discretization of state space, as may occur when observable
states are limited by measurement constraints. We develop efficient algorithms
to compute synchrony in a variety of state spaces, including all finite state
spaces and empirical distributions on the circle, and provide accessible
implementations in an open-source Python module. To demonstrate the usefulness
of the synchrony measure in biological applications, we investigate several
biologically relevant models of mechanisms that can alter the dynamics of
synchrony over time, and reanalyze published data concerning the dynamics of
the intraerythrocytic developmental cycles of $\textit{Plasmodium}$ parasites.
We anticipate that the rigorous definition of population synchrony and the
mathematical and biological results presented here will be broadly useful in
analyzing and modeling populations in a variety of contexts.
| [
{
"created": "Sun, 23 Jun 2024 02:46:43 GMT",
"version": "v1"
}
] | 2024-06-25 | [
[
"Motta",
"Francis C.",
""
],
[
"McGoff",
"Kevin",
""
],
[
"Cummins",
"Breschine",
""
],
[
"Haase",
"Steven B.",
""
]
] | Synchronized behavior among individuals is a ubiquitous feature of populations. Understanding mechanisms of (de)synchronization demands meaningful, interpretable, computable quantifications of synchrony, relevant to measurements that can be made of dynamic populations. Despite the importance to analyzing and modeling populations, existing notions of synchrony often lack rigorous definitions, may be specialized to a particular experimental system and/or measurement, or may have undesirable properties that limit their utility. We introduce a notion of synchrony for populations of individuals occupying a compact metric space that depends on the Fr\'{e}chet variance of the distribution of individuals. We establish several fundamental and desirable mathematical properties of this synchrony measure, including continuity and invariance to metric scaling. We establish a general approximation result that controls the disparity between synchrony in the true space and the synchrony observed through a discretization of state space, as may occur when observable states are limited by measurement constraints. We develop efficient algorithms to compute synchrony in a variety of state spaces, including all finite state spaces and empirical distributions on the circle, and provide accessible implementations in an open-source Python module. To demonstrate the usefulness of the synchrony measure in biological applications, we investigate several biologically relevant models of mechanisms that can alter the dynamics of synchrony over time, and reanalyze published data concerning the dynamics of the intraerythrocytic developmental cycles of $\textit{Plasmodium}$ parasites. We anticipate that the rigorous definition of population synchrony and the mathematical and biological results presented here will be broadly useful in analyzing and modeling populations in a variety of contexts. |
2106.10234 | Yingce Xia | Jinhua Zhu, Yingce Xia, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan
Liu | Dual-view Molecule Pre-training | Add new results of retrosynthesis | null | null | null | q-bio.QM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Inspired by its success in natural language processing and computer vision,
pre-training has attracted substantial attention in cheminformatics and
bioinformatics, especially for molecule based tasks. A molecule can be
represented by either a graph (where atoms are connected by bonds) or a SMILES
sequence (where depth-first-search is applied to the molecular graph with
specific rules). Existing works on molecule pre-training use either graph
representations only or SMILES representations only. In this work, we propose
to leverage both the representations and design a new pre-training algorithm,
dual-view molecule pre-training (briefly, DMP), that can effectively combine
the strengths of both types of molecule representations. The model of DMP
consists of two branches: a Transformer branch that takes the SMILES sequence
of a molecule as input, and a GNN branch that takes a molecular graph as input.
The training of DMP contains three tasks: (1) predicting masked tokens in a
SMILES sequence by the Transformer branch, (2) predicting masked atoms in a
molecular graph by the GNN branch, and (3) maximizing the consistency between
the two high-level representations output by the Transformer and GNN branches
separately. After pre-training, we can use either the Transformer branch (this
one is recommended according to empirical results), the GNN branch, or both for
downstream tasks. DMP is tested on nine molecular property prediction tasks and
achieves state-of-the-art performances on seven of them. Furthermore, we test
DMP on three retrosynthesis tasks and achieve state-of-the-art results on them.
| [
{
"created": "Thu, 17 Jun 2021 03:58:38 GMT",
"version": "v1"
},
{
"created": "Wed, 13 Oct 2021 03:09:28 GMT",
"version": "v2"
}
] | 2021-10-14 | [
[
"Zhu",
"Jinhua",
""
],
[
"Xia",
"Yingce",
""
],
[
"Qin",
"Tao",
""
],
[
"Zhou",
"Wengang",
""
],
[
"Li",
"Houqiang",
""
],
[
"Liu",
"Tie-Yan",
""
]
] | Inspired by its success in natural language processing and computer vision, pre-training has attracted substantial attention in cheminformatics and bioinformatics, especially for molecule based tasks. A molecule can be represented by either a graph (where atoms are connected by bonds) or a SMILES sequence (where depth-first-search is applied to the molecular graph with specific rules). Existing works on molecule pre-training use either graph representations only or SMILES representations only. In this work, we propose to leverage both the representations and design a new pre-training algorithm, dual-view molecule pre-training (briefly, DMP), that can effectively combine the strengths of both types of molecule representations. The model of DMP consists of two branches: a Transformer branch that takes the SMILES sequence of a molecule as input, and a GNN branch that takes a molecular graph as input. The training of DMP contains three tasks: (1) predicting masked tokens in a SMILES sequence by the Transformer branch, (2) predicting masked atoms in a molecular graph by the GNN branch, and (3) maximizing the consistency between the two high-level representations output by the Transformer and GNN branches separately. After pre-training, we can use either the Transformer branch (this one is recommended according to empirical results), the GNN branch, or both for downstream tasks. DMP is tested on nine molecular property prediction tasks and achieves state-of-the-art performances on seven of them. Furthermore, we test DMP on three retrosynthesis tasks and achieve state-of-the-art results on them. |
2002.09062 | Weiqi Ji | Weiqi Ji and Sili Deng | Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical
Reaction Neural Network | null | The Journal of Physical Chemistry A, 2021 | 10.1021/acs.jpca.0c09316 | null | q-bio.MN cs.LG physics.chem-ph stat.ML | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Chemical reactions occur in energy, environmental, biological, and many other
natural systems, and the inference of the reaction networks is essential to
understand and design the chemical processes in engineering and life sciences.
Yet, revealing the reaction pathways for complex systems and processes is still
challenging due to the lack of knowledge of the involved species and reactions.
Here, we present a neural network approach that autonomously discovers reaction
pathways from the time-resolved species concentration data. The proposed
Chemical Reaction Neural Network (CRNN), by design, satisfies the fundamental
physics laws, including the Law of Mass Action and the Arrhenius Law.
Consequently, the CRNN is physically interpretable such that the reaction
pathways can be interpreted, and the kinetic parameters can be quantified
simultaneously from the weights of the neural network. The inference of the
chemical pathways is accomplished by training the CRNN with species
concentration data via stochastic gradient descent. We demonstrate the
successful implementations and the robustness of the approach in elucidating
the chemical reaction pathways of several chemical engineering and biochemical
systems. The autonomous inference by the CRNN approach precludes the need for
expert knowledge in proposing candidate networks and addresses the curse of
dimensionality in complex systems. The physical interpretability also makes the
CRNN capable of not only fitting the data for a given system but also
developing knowledge of unknown pathways that could be generalized to similar
chemical systems.
| [
{
"created": "Thu, 20 Feb 2020 23:36:46 GMT",
"version": "v1"
},
{
"created": "Fri, 8 Jan 2021 22:18:36 GMT",
"version": "v2"
}
] | 2021-01-22 | [
[
"Ji",
"Weiqi",
""
],
[
"Deng",
"Sili",
""
]
] | Chemical reactions occur in energy, environmental, biological, and many other natural systems, and the inference of the reaction networks is essential to understand and design the chemical processes in engineering and life sciences. Yet, revealing the reaction pathways for complex systems and processes is still challenging due to the lack of knowledge of the involved species and reactions. Here, we present a neural network approach that autonomously discovers reaction pathways from the time-resolved species concentration data. The proposed Chemical Reaction Neural Network (CRNN), by design, satisfies the fundamental physics laws, including the Law of Mass Action and the Arrhenius Law. Consequently, the CRNN is physically interpretable such that the reaction pathways can be interpreted, and the kinetic parameters can be quantified simultaneously from the weights of the neural network. The inference of the chemical pathways is accomplished by training the CRNN with species concentration data via stochastic gradient descent. We demonstrate the successful implementations and the robustness of the approach in elucidating the chemical reaction pathways of several chemical engineering and biochemical systems. The autonomous inference by the CRNN approach precludes the need for expert knowledge in proposing candidate networks and addresses the curse of dimensionality in complex systems. The physical interpretability also makes the CRNN capable of not only fitting the data for a given system but also developing knowledge of unknown pathways that could be generalized to similar chemical systems. |
1607.08552 | Tobias K\"uhn | Tobias K\"uhn, Moritz Helias | Locking of correlated neural activity to ongoing oscillations | 57 pages, 12 figures, published version | PLoS Comput Biol 13(6): e1005534 (2017) | 10.1371/journal.pcbi.1005534 | null | q-bio.NC cond-mat.dis-nn | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Population-wide oscillations are ubiquitously observed in mesoscopic signals
of cortical activity. In these network states a global oscillatory cycle
modulates the propensity of neurons to fire. Synchronous activation of neurons
has been hypothesized to be a separate channel of signal processing information
in the brain. A salient question is therefore if and how oscillations interact
with spike synchrony and in how far these channels can be considered separate.
Experiments indeed showed that correlated spiking co-modulates with the static
firing rate and is also tightly locked to the phase of beta-oscillations. While
the dependence of correlations on the mean rate is well understood in
feed-forward networks, it remains unclear why and by which mechanisms
correlations tightly lock to an oscillatory cycle. We here demonstrate that
such correlated activation of pairs of neurons is qualitatively explained by
periodically-driven random networks. We identify the mechanisms by which
covariances depend on a driving periodic stimulus. Mean-field theory combined
with linear response theory yields closed-form expressions for the
cyclostationary mean activities and pairwise zero-time-lag covariances of
binary recurrent random networks. Two distinct mechanisms cause time-dependent
covariances: the modulation of the susceptibility of single neurons (via the
external input and network feedback) and the time-varying variances of single
unit activities. For some parameters, the effectively inhibitory recurrent
feedback leads to resonant covariances even if mean activities show
non-resonant behavior. Our analytical results open the question of
time-modulated synchronous activity to a quantitative analysis.
| [
{
"created": "Thu, 28 Jul 2016 18:09:49 GMT",
"version": "v1"
},
{
"created": "Fri, 21 Oct 2016 09:58:28 GMT",
"version": "v2"
},
{
"created": "Mon, 3 Jul 2017 15:25:12 GMT",
"version": "v3"
}
] | 2017-07-04 | [
[
"Kühn",
"Tobias",
""
],
[
"Helias",
"Moritz",
""
]
] | Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain. A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate. Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations. While the dependence of correlations on the mean rate is well understood in feed-forward networks, it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle. We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks. We identify the mechanisms by which covariances depend on a driving periodic stimulus. Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks. Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons (via the external input and network feedback) and the time-varying variances of single unit activities. For some parameters, the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior. Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis. |
1811.08068 | Xiaochen Liu | X. Liu, P. Sanz-Leon, P. A. Robinson | Gamma-Band Correlations in Primary Visual Cortex | 23 pages; 12 figures | Phys. Rev. E 101, 042406 (2020) | 10.1103/PhysRevE.101.042406 | null | q-bio.NC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Neural field theory is used to quantitatively analyze the two-dimensional
spatiotemporal correlation properties of gamma-band (30 -- 70 Hz) oscillations
evoked by stimuli arriving at the primary visual cortex (V1), and modulated by
patchy connectivities that depend on orientation preference (OP). Correlation
functions are derived analytically under different stimulus and measurement
conditions. The predictions reproduce a range of published experimental
results, including the existence of two-point oscillatory temporal
cross-correlations with zero time-lag between neurons with similar OP, the
influence of spatial separation of neurons on the strength of the correlations,
and the effects of differing stimulus orientations.
| [
{
"created": "Tue, 20 Nov 2018 04:28:28 GMT",
"version": "v1"
}
] | 2021-03-19 | [
[
"Liu",
"X.",
""
],
[
"Sanz-Leon",
"P.",
""
],
[
"Robinson",
"P. A.",
""
]
] | Neural field theory is used to quantitatively analyze the two-dimensional spatiotemporal correlation properties of gamma-band (30 -- 70 Hz) oscillations evoked by stimuli arriving at the primary visual cortex (V1), and modulated by patchy connectivities that depend on orientation preference (OP). Correlation functions are derived analytically under different stimulus and measurement conditions. The predictions reproduce a range of published experimental results, including the existence of two-point oscillatory temporal cross-correlations with zero time-lag between neurons with similar OP, the influence of spatial separation of neurons on the strength of the correlations, and the effects of differing stimulus orientations. |
2007.16018 | Daniele Marinazzo | Sebastiano Stramaglia, Tomas Scagliarini, Bryan C. Daniels, and
Daniele Marinazzo | Quantifying dynamical high-order interdependencies from the
O-information: an application to neural spiking dynamics | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | We address the problem of efficiently and informatively quantifying how
multiplets of variables carry information about the future of the dynamical
system they belong to. In particular we want to identify groups of variables
carrying redundant or synergistic information, and track how the size and the
composition of these multiplets changes as the collective behavior of the
system evolves. In order to afford a parsimonious expansion of shared
information, and at the same time control for lagged interactions and common
effect, we develop a dynamical, conditioned version of the O-information, a
framework recently proposed to quantify high-order interdependencies via
multivariate extension of the mutual information. We thus obtain an expansion
of the transfer entropy in which synergistic and redundant effects are
separated. We apply this framework to a dataset of spiking neurons from a
monkey performing a perceptual discrimination task. The method identifies
synergistic multiplets that include neurons previously categorized as
containing little relevant information individually.
| [
{
"created": "Fri, 31 Jul 2020 12:34:19 GMT",
"version": "v1"
}
] | 2020-08-03 | [
[
"Stramaglia",
"Sebastiano",
""
],
[
"Scagliarini",
"Tomas",
""
],
[
"Daniels",
"Bryan C.",
""
],
[
"Marinazzo",
"Daniele",
""
]
] | We address the problem of efficiently and informatively quantifying how multiplets of variables carry information about the future of the dynamical system they belong to. In particular we want to identify groups of variables carrying redundant or synergistic information, and track how the size and the composition of these multiplets changes as the collective behavior of the system evolves. In order to afford a parsimonious expansion of shared information, and at the same time control for lagged interactions and common effect, we develop a dynamical, conditioned version of the O-information, a framework recently proposed to quantify high-order interdependencies via multivariate extension of the mutual information. We thus obtain an expansion of the transfer entropy in which synergistic and redundant effects are separated. We apply this framework to a dataset of spiking neurons from a monkey performing a perceptual discrimination task. The method identifies synergistic multiplets that include neurons previously categorized as containing little relevant information individually. |
1706.03835 | Christian Meisel | Christian Meisel, Kimberlyn Bailey, Peter Achermann and Dietmar Plenz | Decline of long-range temporal correlations in the human brain during
sustained wakefulness | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sleep is crucial for daytime functioning, cognitive performance and general
well-being. These aspects of daily life are known to be impaired after extended
wake, yet, the underlying neuronal correlates have been difficult to identify.
Accumulating evidence suggests that normal functioning of the brain is
characterized by long-range temporal correlations (LRTCs) in cortex, which are
supportive for decision-making and working memory tasks.
Here we assess LRTCs in resting state human EEG data during a 40-hour sleep
deprivation experiment by evaluating the decay in autocorrelation and the
scaling exponent of the detrended fluctuation analysis from EEG amplitude
fluctuations. We find with both measures that LRTCs decline as sleep
deprivation progresses. This decline becomes evident when taking changes in
signal power into appropriate consideration.
Our results demonstrate the importance of sleep to maintain LRTCs in the
human brain. In complex networks, LRTCs naturally emerge in the vicinity of a
critical state. The observation of declining LRTCs during wake thus provides
additional support for our hypothesis that sleep reorganizes cortical networks
towards critical dynamics for optimal functioning.
| [
{
"created": "Mon, 12 Jun 2017 20:15:43 GMT",
"version": "v1"
}
] | 2017-06-14 | [
[
"Meisel",
"Christian",
""
],
[
"Bailey",
"Kimberlyn",
""
],
[
"Achermann",
"Peter",
""
],
[
"Plenz",
"Dietmar",
""
]
] | Sleep is crucial for daytime functioning, cognitive performance and general well-being. These aspects of daily life are known to be impaired after extended wake, yet, the underlying neuronal correlates have been difficult to identify. Accumulating evidence suggests that normal functioning of the brain is characterized by long-range temporal correlations (LRTCs) in cortex, which are supportive for decision-making and working memory tasks. Here we assess LRTCs in resting state human EEG data during a 40-hour sleep deprivation experiment by evaluating the decay in autocorrelation and the scaling exponent of the detrended fluctuation analysis from EEG amplitude fluctuations. We find with both measures that LRTCs decline as sleep deprivation progresses. This decline becomes evident when taking changes in signal power into appropriate consideration. Our results demonstrate the importance of sleep to maintain LRTCs in the human brain. In complex networks, LRTCs naturally emerge in the vicinity of a critical state. The observation of declining LRTCs during wake thus provides additional support for our hypothesis that sleep reorganizes cortical networks towards critical dynamics for optimal functioning. |
q-bio/0504025 | Edwin Wang Dr. | Edwin Wang and Enrico Purisima | Self-organization of gene regulatory network motifs enriched with short
transcript's half-life transcription factors | Trends Genet (in press), main text 1, supplementary notes 1, 40
pages, 7 tables, 4 figs, minor modifications | Trends Genet, 21:492-495, 2005 | 10.1016/j.tig.2005.06.013 | null | q-bio.MN | null | Network motifs, the recurring regulatory structural patterns in networks, are
able to self-organize to produce networks. Three major motifs, feedforward
loop, single input modules and bi-fan are found in gene regulatory networks.
The large ratio of genes to transcription factors (TFs) in genomes leads to a
sharing of TFs by motifs and is sufficient to result in network
self-organization. We find a common design principle of these motifs: short
transcript's half-life (THL) TFs are significantly enriched in motifs and hubs.
This enrichment becomes one of the driving forces for the emergence of the
network scale-free topology and allows the network to quickly adapt to
environmental changes. Most feedforward loops and bi-fans contain at least one
short THL TF, which can be seen as a criterion for self-assembling these
motifs. We have classified the motifs according to their short THL TF content.
We show that the percentage of the different motif subtypes varies in different
cellular conditions.
| [
{
"created": "Mon, 18 Apr 2005 23:20:19 GMT",
"version": "v1"
},
{
"created": "Mon, 25 Apr 2005 22:36:25 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Wang",
"Edwin",
""
],
[
"Purisima",
"Enrico",
""
]
] | Network motifs, the recurring regulatory structural patterns in networks, are able to self-organize to produce networks. Three major motifs, feedforward loop, single input modules and bi-fan are found in gene regulatory networks. The large ratio of genes to transcription factors (TFs) in genomes leads to a sharing of TFs by motifs and is sufficient to result in network self-organization. We find a common design principle of these motifs: short transcript's half-life (THL) TFs are significantly enriched in motifs and hubs. This enrichment becomes one of the driving forces for the emergence of the network scale-free topology and allows the network to quickly adapt to environmental changes. Most feedforward loops and bi-fans contain at least one short THL TF, which can be seen as a criterion for self-assembling these motifs. We have classified the motifs according to their short THL TF content. We show that the percentage of the different motif subtypes varies in different cellular conditions. |
q-bio/0701031 | Miroslaw Dudek | Miroslaw R. Dudek | Lotka-Volterra population model of genetic evolution | 10 pages, 6 figures | null | null | null | q-bio.PE q-bio.OT | null | A deterministic model of an age-structured population with genetics analogous
to the discrete time Penna model of genetic evolution is constructed on the
basis of the Lotka-Volterra scheme. It is shown that if, as in the Penna model,
genetic information is represented by the fraction of defective genes in the
population, the population numbers for each specific individual's age are
represented by exactly the same functions of age in both models. This gives us
a new possibility to consider multi-species evolution without using detailed
microscopic Penna model.
We discuss a particular case of the predator-prey system representing an
ecosystem consisting of a limited amount of energy resources consumed by the
age-structured species living in this ecosystem. Then, the increase in number
of the individuals in the population under consideration depends on the
available energy resources, the shape of the distribution function of defective
genes in the population and the fertility age. We show that these parameters
determine the trend toward equilibrium of the whole ecosystem.
| [
{
"created": "Sat, 20 Jan 2007 15:54:21 GMT",
"version": "v1"
},
{
"created": "Sun, 28 Jan 2007 08:18:45 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Dudek",
"Miroslaw R.",
""
]
] | A deterministic model of an age-structured population with genetics analogous to the discrete time Penna model of genetic evolution is constructed on the basis of the Lotka-Volterra scheme. It is shown that if, as in the Penna model, genetic information is represented by the fraction of defective genes in the population, the population numbers for each specific individual's age are represented by exactly the same functions of age in both models. This gives us a new possibility to consider multi-species evolution without using detailed microscopic Penna model. We discuss a particular case of the predator-prey system representing an ecosystem consisting of a limited amount of energy resources consumed by the age-structured species living in this ecosystem. Then, the increase in number of the individuals in the population under consideration depends on the available energy resources, the shape of the distribution function of defective genes in the population and the fertility age. We show that these parameters determine the trend toward equilibrium of the whole ecosystem. |
1911.04585 | Ralf Engbert | Johan Chandra, Andre Kruegel, Ralf Engbert | Modulation of oculomotor control during reading of mirrored and inverted
texts | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The interplay between cognitive and oculomotor processes during reading can
be explored when the spatial layout of text deviates from the typical display.
In this study, we investigate various eye-movement measures during reading of
text with experimentally manipulated layout (word-wise and letter-wise
mirrored-reversed text as well as inverted and scrambled text). While typical
findings (e.g., longer mean fixation times, shorter mean saccades lengths) in
reading manipulated texts compared to normal texts were reported in earlier
work, little is known about changes of oculomotor targeting observed in
within-word landing positions under the above text layouts. Here we carry out
precise analyses of landing positions and find substantial changes in the
so-called launch-site effect in addition to the expected overall slow-down of
reading performance. Specifically, during reading of our manipulated text
conditions with reversed letter order (against overall reading direction), we
find a reduced launch-site effect, while in all other manipulated text
conditions, we observe an increased launch-site effect. Our results clearly
indicate that the oculomotor system is highly adaptive when confronted with
unusual reading conditions.
| [
{
"created": "Mon, 11 Nov 2019 22:21:22 GMT",
"version": "v1"
}
] | 2019-11-13 | [
[
"Chandra",
"Johan",
""
],
[
"Kruegel",
"Andre",
""
],
[
"Engbert",
"Ralf",
""
]
] | The interplay between cognitive and oculomotor processes during reading can be explored when the spatial layout of text deviates from the typical display. In this study, we investigate various eye-movement measures during reading of text with experimentally manipulated layout (word-wise and letter-wise mirrored-reversed text as well as inverted and scrambled text). While typical findings (e.g., longer mean fixation times, shorter mean saccades lengths) in reading manipulated texts compared to normal texts were reported in earlier work, little is known about changes of oculomotor targeting observed in within-word landing positions under the above text layouts. Here we carry out precise analyses of landing positions and find substantial changes in the so-called launch-site effect in addition to the expected overall slow-down of reading performance. Specifically, during reading of our manipulated text conditions with reversed letter order (against overall reading direction), we find a reduced launch-site effect, while in all other manipulated text conditions, we observe an increased launch-site effect. Our results clearly indicate that the oculomotor system is highly adaptive when confronted with unusual reading conditions. |
2102.00316 | Michael Wilkinson | Michael Wilkinson, David Yllanes and Greg Huber | Polysomally Protected Viruses | 14 pages, 4 figures, Physical Biology, in press | Phys. Biol. 18 046009 (2021) | 10.1088/1478-3975/abf5b5 | null | q-bio.SC q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It is conceivable that an RNA virus could use a polysome, that is, a string
of ribosomes covering the RNA strand, to protect the genetic material from
degradation inside a host cell. This paper discusses how such a virus might
operate, and how its presence might be detected by ribosome profiling. There
are two possible forms for such a polysomally protected virus, depending upon
whether just the forward strand or both the forward and complementary strands
can be encased by ribosomes (these will be termed type 1 and type 2,
respectively). It is argued that in the type 2 case the viral RNA would evolve
an ambigrammatic property, whereby the viral genes are free of stop codons in a
reverse reading frame (with forward and reverse codons aligned). Recent
observations of ribosome profiles of ambigrammatic narnavirus sequences are
consistent with our predictions for the type 2 case.
| [
{
"created": "Sat, 30 Jan 2021 21:34:11 GMT",
"version": "v1"
},
{
"created": "Thu, 8 Apr 2021 21:50:34 GMT",
"version": "v2"
}
] | 2021-06-24 | [
[
"Wilkinson",
"Michael",
""
],
[
"Yllanes",
"David",
""
],
[
"Huber",
"Greg",
""
]
] | It is conceivable that an RNA virus could use a polysome, that is, a string of ribosomes covering the RNA strand, to protect the genetic material from degradation inside a host cell. This paper discusses how such a virus might operate, and how its presence might be detected by ribosome profiling. There are two possible forms for such a polysomally protected virus, depending upon whether just the forward strand or both the forward and complementary strands can be encased by ribosomes (these will be termed type 1 and type 2, respectively). It is argued that in the type 2 case the viral RNA would evolve an ambigrammatic property, whereby the viral genes are free of stop codons in a reverse reading frame (with forward and reverse codons aligned). Recent observations of ribosome profiles of ambigrammatic narnavirus sequences are consistent with our predictions for the type 2 case. |
2104.04161 | Simone Pigolotti | Anzhelika Koldaeva, Hsieh-Fu Tsai, Amy Q. Shen, and Simone Pigolotti | Population genetics in microchannels | 20 pages, 9 figures, combined main text + SI | Proc. Natl. Acad. Sci. 119(12), e2120821119 (2022) | 10.1073/pnas.2120821119 | null | q-bio.PE cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Spatial constraints such as rigid barriers affect the dynamics of cell
populations, potentially altering the course of natural evolution. In this
paper, we investigate the population genetics of Escherichia coli proliferating
in microchannels with open ends. Our analysis is based on a population model in
which reproducing cells shift entire lanes of cells towards the open ends of
the channel. The model predicts that diversity is lost very rapidly within
lanes, but at a much slower pace among lanes. As a consequence, two mixed,
neutral E. coli strains competing in a microchannel must organize into an
ordered regular stripe pattern in the course of a few generations. These
predictions are in quantitative agreement with our experiments. We also
demonstrate that random mutations appearing in the middle of the channel are
much more likely to reach fixation than those occurring elsewhere. Our results
illustrate fundamental mechanisms of microbial evolution in spatially confined
space.
| [
{
"created": "Fri, 9 Apr 2021 02:33:01 GMT",
"version": "v1"
},
{
"created": "Tue, 28 Sep 2021 06:11:01 GMT",
"version": "v2"
},
{
"created": "Fri, 25 Mar 2022 08:02:11 GMT",
"version": "v3"
}
] | 2022-03-28 | [
[
"Koldaeva",
"Anzhelika",
""
],
[
"Tsai",
"Hsieh-Fu",
""
],
[
"Shen",
"Amy Q.",
""
],
[
"Pigolotti",
"Simone",
""
]
] | Spatial constraints such as rigid barriers affect the dynamics of cell populations, potentially altering the course of natural evolution. In this paper, we investigate the population genetics of Escherichia coli proliferating in microchannels with open ends. Our analysis is based on a population model in which reproducing cells shift entire lanes of cells towards the open ends of the channel. The model predicts that diversity is lost very rapidly within lanes, but at a much slower pace among lanes. As a consequence, two mixed, neutral E. coli strains competing in a microchannel must organize into an ordered regular stripe pattern in the course of a few generations. These predictions are in quantitative agreement with our experiments. We also demonstrate that random mutations appearing in the middle of the channel are much more likely to reach fixation than those occurring elsewhere. Our results illustrate fundamental mechanisms of microbial evolution in spatially confined space. |
2002.02642 | Narendra Dixit | Rajat Desikan, Rustom Antia, Narendra M. Dixit | The weakest link bridging germinal center B cells and follicular
dendritic cells limits antibody affinity maturation | null | BioEssays, 2021 | 10.1002/bies.202000159 | null | q-bio.PE q-bio.BM q-bio.CB | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The affinity of antibodies (Abs) produced in vivo for their target antigens
(Ags) is typically well below the maximum affinity possible. Nearly 25 years
ago, Foote and Eisen explained how an 'affinity ceiling' could arise from
constraints associated with the acquisition of soluble antigen by B cells.
However, recent studies have shown that B cells in germinal centers (where Ab
affinity maturation occurs) acquire Ag not in soluble form but presented as
receptor-bound immune complexes on follicular dendritic cells (FDCs). How the
affinity ceiling arises in such a scenario is unclear. Here, we argue that the
ceiling arises from the weakest link of the chain of protein complexes that
bridges B cells and FDCs and is broken during Ag acquisition. This hypothesis
explains the affinity ceiling realized in vivo and suggests that strengthening
the weakest link could raise the ceiling and improve Ab responses.
| [
{
"created": "Fri, 7 Feb 2020 06:47:25 GMT",
"version": "v1"
}
] | 2021-02-16 | [
[
"Desikan",
"Rajat",
""
],
[
"Antia",
"Rustom",
""
],
[
"Dixit",
"Narendra M.",
""
]
] | The affinity of antibodies (Abs) produced in vivo for their target antigens (Ags) is typically well below the maximum affinity possible. Nearly 25 years ago, Foote and Eisen explained how an 'affinity ceiling' could arise from constraints associated with the acquisition of soluble antigen by B cells. However, recent studies have shown that B cells in germinal centers (where Ab affinity maturation occurs) acquire Ag not in soluble form but presented as receptor-bound immune complexes on follicular dendritic cells (FDCs). How the affinity ceiling arises in such a scenario is unclear. Here, we argue that the ceiling arises from the weakest link of the chain of protein complexes that bridges B cells and FDCs and is broken during Ag acquisition. This hypothesis explains the affinity ceiling realized in vivo and suggests that strengthening the weakest link could raise the ceiling and improve Ab responses. |
1605.01219 | Michele Caselle | Antonio Rosanova, Alberto Colliva, Matteo Osella, Michele Caselle | Modelling the evolution of transcription factor binding preferences in
complex eukaryotes | 14 pages, 5 figures. Minor changes. Final version, accepted for
publication | Sci Rep. 2017 Aug 8;7(1):7596 | 10.1038/s41598-017-07761-0. | null | q-bio.GN q-bio.MN q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Transcription factors (TFs) exert their regulatory action by binding to DNA
with specific sequence preferences. However, different TFs can partially share
their binding sequences due to their common evolutionary origin. This
`redundancy' of binding defines a way of organizing TFs in `motif families' by
grouping TFs with similar binding preferences. Since these ultimately define
the TF target genes, the motif family organization entails information about
the structure of transcriptional regulation as it has been shaped by evolution.
Focusing on the human TF repertoire, we show that a one-parameter evolutionary
model of the Birth-Death-Innovation type can explain the TF empirical
ripartition in motif families, and allows to highlight the relevant
evolutionary forces at the origin of this organization. Moreover, the model
allows to pinpoint few deviations from the neutral scenario it assumes: three
over-expanded families (including HOX and FOX genes), a set of `singleton' TFs
for which duplication seems to be selected against, and a higher-than-average
rate of diversification of the binding preferences of TFs with a Zinc Finger
DNA binding domain. Finally, a comparison of the TF motif family organization
in different eukaryotic species suggests an increase of redundancy of binding
with organism complexity.
| [
{
"created": "Wed, 4 May 2016 10:52:25 GMT",
"version": "v1"
},
{
"created": "Tue, 4 Dec 2018 16:05:21 GMT",
"version": "v2"
}
] | 2018-12-05 | [
[
"Rosanova",
"Antonio",
""
],
[
"Colliva",
"Alberto",
""
],
[
"Osella",
"Matteo",
""
],
[
"Caselle",
"Michele",
""
]
] | Transcription factors (TFs) exert their regulatory action by binding to DNA with specific sequence preferences. However, different TFs can partially share their binding sequences due to their common evolutionary origin. This `redundancy' of binding defines a way of organizing TFs in `motif families' by grouping TFs with similar binding preferences. Since these ultimately define the TF target genes, the motif family organization entails information about the structure of transcriptional regulation as it has been shaped by evolution. Focusing on the human TF repertoire, we show that a one-parameter evolutionary model of the Birth-Death-Innovation type can explain the TF empirical ripartition in motif families, and allows to highlight the relevant evolutionary forces at the origin of this organization. Moreover, the model allows to pinpoint few deviations from the neutral scenario it assumes: three over-expanded families (including HOX and FOX genes), a set of `singleton' TFs for which duplication seems to be selected against, and a higher-than-average rate of diversification of the binding preferences of TFs with a Zinc Finger DNA binding domain. Finally, a comparison of the TF motif family organization in different eukaryotic species suggests an increase of redundancy of binding with organism complexity. |
0901.1598 | Frederick Matsen IV | Frederick A. Matsen | constNJ: an algorithm to reconstruct sets of phylogenetic trees
satisfying pairwise topological constraints | Please contact me with any questions or comments! | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper introduces constNJ, the first algorithm for phylogenetic
reconstruction of sets of trees with constrained pairwise rooted subtree-prune
regraft (rSPR) distance. We are motivated by the problem of constructing sets
of trees which must fit into a recombination, hybridization, or similar
network. Rather than first finding a set of trees which are optimal according
to a phylogenetic criterion (e.g. likelihood or parsimony) and then attempting
to fit them into a network, constNJ estimates the trees while enforcing
specified rSPR distance constraints. The primary input for constNJ is a
collection of distance matrices derived from sequence blocks which are assumed
to have evolved in a tree-like manner, such as blocks of an alignment which do
not contain any recombination breakpoints. The other input is a set of rSPR
constraints for any set of pairs of trees. ConstNJ is consistent and a strict
generalization of the neighbor-joining algorithm; it uses the new notion of
"maximum agreement partitions" to assure that the resulting trees satisfy the
given rSPR distance constraints.
| [
{
"created": "Mon, 12 Jan 2009 15:46:13 GMT",
"version": "v1"
},
{
"created": "Tue, 20 Jan 2009 19:41:29 GMT",
"version": "v2"
}
] | 2009-09-30 | [
[
"Matsen",
"Frederick A.",
""
]
] | This paper introduces constNJ, the first algorithm for phylogenetic reconstruction of sets of trees with constrained pairwise rooted subtree-prune regraft (rSPR) distance. We are motivated by the problem of constructing sets of trees which must fit into a recombination, hybridization, or similar network. Rather than first finding a set of trees which are optimal according to a phylogenetic criterion (e.g. likelihood or parsimony) and then attempting to fit them into a network, constNJ estimates the trees while enforcing specified rSPR distance constraints. The primary input for constNJ is a collection of distance matrices derived from sequence blocks which are assumed to have evolved in a tree-like manner, such as blocks of an alignment which do not contain any recombination breakpoints. The other input is a set of rSPR constraints for any set of pairs of trees. ConstNJ is consistent and a strict generalization of the neighbor-joining algorithm; it uses the new notion of "maximum agreement partitions" to assure that the resulting trees satisfy the given rSPR distance constraints. |
1812.02467 | Jessie Renton | Jessie Renton and Karen M. Page | Evolution of cooperation on an epithelium | 19 pages, 8 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cooperation is prevalent in nature, not only in the context of social
interactions within the animal kingdom, but also on the cellular level. In
cancer for example, tumour cells can cooperate by producing growth factors. The
evolution of cooperation has traditionally been studied for well-mixed
populations under the framework of evolutionary game theory, and more recently
for structured populations using evolutionary graph theory. The population
structures arising due to cellular arrangement in tissues however are dynamic
and thus cannot be accurately represented by either of these frameworks. In
this work we compare the conditions for cooperative success in an epithelium
modelled using evolutionary graph theory, to those in a mechanical model of an
epithelium =- the Voronoi tessellation model. Crucially, in this latter model
cells are able to move, and birth and death are not spatially coupled. We
calculate fixation probabilities in the Voronoi tessellation model through
simulation and an approximate analytic technique and show that this leads to
stronger promotion of cooperation in comparison with the evolutionary graph
theory model.
| [
{
"created": "Thu, 6 Dec 2018 11:22:28 GMT",
"version": "v1"
}
] | 2018-12-07 | [
[
"Renton",
"Jessie",
""
],
[
"Page",
"Karen M.",
""
]
] | Cooperation is prevalent in nature, not only in the context of social interactions within the animal kingdom, but also on the cellular level. In cancer for example, tumour cells can cooperate by producing growth factors. The evolution of cooperation has traditionally been studied for well-mixed populations under the framework of evolutionary game theory, and more recently for structured populations using evolutionary graph theory. The population structures arising due to cellular arrangement in tissues however are dynamic and thus cannot be accurately represented by either of these frameworks. In this work we compare the conditions for cooperative success in an epithelium modelled using evolutionary graph theory, to those in a mechanical model of an epithelium =- the Voronoi tessellation model. Crucially, in this latter model cells are able to move, and birth and death are not spatially coupled. We calculate fixation probabilities in the Voronoi tessellation model through simulation and an approximate analytic technique and show that this leads to stronger promotion of cooperation in comparison with the evolutionary graph theory model. |
2005.11454 | Aydogan Ozcan | Calvin Brown, Derek Tseng, Paige M. K. Larkin, Susan Realegeno, Leanne
Mortimer, Arjun Subramonian, Dino Di Carlo, Omai B. Garner, Aydogan Ozcan | An Automated, Cost-Effective Optical System for Accelerated
Anti-microbial Susceptibility Testing (AST) using Deep Learning | 13 Pages, 6 Figures, 1 Table | ACS Photonics (2020) | 10.1021/acsphotonics.0c00841 | null | q-bio.QM physics.app-ph physics.ins-det physics.med-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Antimicrobial susceptibility testing (AST) is a standard clinical procedure
used to quantify antimicrobial resistance (AMR). Currently, the gold standard
method requires incubation for 18-24 h and subsequent inspection for growth by
a trained medical technologist. We demonstrate an automated, cost-effective
optical system that delivers early AST results, minimizing incubation time and
eliminating human errors, while remaining compatible with standard phenotypic
assay workflow. The system is composed of cost-effective components and
eliminates the need for optomechanical scanning. A neural network processes the
captured optical intensity information from an array of fiber optic cables to
determine whether bacterial growth has occurred in each well of a 96-well
microplate. When the system was blindly tested on isolates from 33 patients
with Staphylococcus aureus infections, 95.03% of all the wells containing
growth were correctly identified using our neural network, with an average of
5.72 h of incubation time required to identify growth. 90% of all wells (growth
and no-growth) were correctly classified after 7 h, and 95% after 10.5 h. Our
deep learning-based optical system met the FDA-defined criteria for essential
and categorical agreements for all 14 antibiotics tested after an average of
6.13 h and 6.98 h, respectively. Furthermore, our system met the FDA criteria
for major and very major error rates for 11 of 12 possible drugs after an
average of 4.02 h, and 9 of 13 possible drugs after an average of 9.39 h,
respectively. This system could enable faster, inexpensive, automated AST,
especially in resource limited settings, helping to mitigate the rise of global
AMR.
| [
{
"created": "Sat, 23 May 2020 02:38:26 GMT",
"version": "v1"
}
] | 2020-07-17 | [
[
"Brown",
"Calvin",
""
],
[
"Tseng",
"Derek",
""
],
[
"Larkin",
"Paige M. K.",
""
],
[
"Realegeno",
"Susan",
""
],
[
"Mortimer",
"Leanne",
""
],
[
"Subramonian",
"Arjun",
""
],
[
"Di Carlo",
"Dino",
""
],
[
"Garner",
"Omai B.",
""
],
[
"Ozcan",
"Aydogan",
""
]
] | Antimicrobial susceptibility testing (AST) is a standard clinical procedure used to quantify antimicrobial resistance (AMR). Currently, the gold standard method requires incubation for 18-24 h and subsequent inspection for growth by a trained medical technologist. We demonstrate an automated, cost-effective optical system that delivers early AST results, minimizing incubation time and eliminating human errors, while remaining compatible with standard phenotypic assay workflow. The system is composed of cost-effective components and eliminates the need for optomechanical scanning. A neural network processes the captured optical intensity information from an array of fiber optic cables to determine whether bacterial growth has occurred in each well of a 96-well microplate. When the system was blindly tested on isolates from 33 patients with Staphylococcus aureus infections, 95.03% of all the wells containing growth were correctly identified using our neural network, with an average of 5.72 h of incubation time required to identify growth. 90% of all wells (growth and no-growth) were correctly classified after 7 h, and 95% after 10.5 h. Our deep learning-based optical system met the FDA-defined criteria for essential and categorical agreements for all 14 antibiotics tested after an average of 6.13 h and 6.98 h, respectively. Furthermore, our system met the FDA criteria for major and very major error rates for 11 of 12 possible drugs after an average of 4.02 h, and 9 of 13 possible drugs after an average of 9.39 h, respectively. This system could enable faster, inexpensive, automated AST, especially in resource limited settings, helping to mitigate the rise of global AMR. |
1007.5022 | Tsvi Tlusty | Ilan Breskin, Jordi Soriano, Elisha Moses, and Tsvi Tlusty | Percolation in living neural networks | PACS numbers: 87.18.Sn, 87.19.La, 64.60.Ak
http://www.weizmann.ac.il/complex/tlusty/papers/PhysRevLett2006.pdf | Breskin I Soriano J Moses E & Tlusty T Percolation in Living
Neural Networks Phys Rev Lett 97 188102-4 (2006) | 10.1103/PhysRevLett.97.188102 | null | q-bio.NC cond-mat.dis-nn physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study living neural networks by measuring the neurons' response to a
global electrical stimulation. Neural connectivity is lowered by reducing the
synaptic strength, chemically blocking neurotransmitter receptors. We use a
graph-theoretic approach to show that the connectivity undergoes a percolation
transition. This occurs as the giant component disintegrates, characterized by
a power law with critical exponent $\beta \simeq 0.65$ is independent of the
balance between excitatory and inhibitory neurons and indicates that the degree
distribution is gaussian rather than scale free
| [
{
"created": "Wed, 28 Jul 2010 16:12:39 GMT",
"version": "v1"
}
] | 2010-07-30 | [
[
"Breskin",
"Ilan",
""
],
[
"Soriano",
"Jordi",
""
],
[
"Moses",
"Elisha",
""
],
[
"Tlusty",
"Tsvi",
""
]
] | We study living neural networks by measuring the neurons' response to a global electrical stimulation. Neural connectivity is lowered by reducing the synaptic strength, chemically blocking neurotransmitter receptors. We use a graph-theoretic approach to show that the connectivity undergoes a percolation transition. This occurs as the giant component disintegrates, characterized by a power law with critical exponent $\beta \simeq 0.65$ is independent of the balance between excitatory and inhibitory neurons and indicates that the degree distribution is gaussian rather than scale free |
1910.05881 | Taiping Zeng | Taiping Zeng, XiaoLi Li, and Bailu Si | Bayesian Integration of Multi-resolutional Grid Codes for Spatial
Cognition | arXiv admin note: text overlap with arXiv:1910.04590 | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Fourier-like summation of several grid cell modules with different spatial
frequencies in the medial entorhinal cortex (MEC) has long been proposed to
form the contours of place firing fields. Recent experiments largely, but not
completely, support this theory. Place fields are obviously expanded by
inactivation of dorsal MEC, which fits the hypothesis. However, contrary to the
prediction, inactivation of ventral MEC is also weakly broaden the spatial
place firing patterns. In this study, we derive the model from grid spatial
frequencies represented by Gaussian profiles to a 1D place field by Bayesian
inference, and further provide completely theoretical explanations for
expansion of place fields and predictions for alignments of grid components. To
understand the information transform across between neocortex, entorhinal
cortex, and hippocampus, we propose spatial memory indexing theory from
hippocampal indexing theory to investigate how neural dynamics work in the
entorhinal-hippocampal circuit. The inputs of place cells in CA3 are converged
from three grid modules with different grid spacings layer II of MEC by
Bayesian mechanism. We resort to the robot system to test Fourier hypothesis
and spatial memory indexing theory, and validate our proposed
entorhinal-hippocampal model. And then we demonstrate its cognitive mapping
capability on the KITTI odometry benchmark dataset. Results suggest that our
model provides a rational theoretical explanation for the biological
experimental results. Results also show that the proposed model is robust for
simultaneous localization and mapping (SLAM) in the large-scale environment.
Our proposed model theoretically supports for Fourier hypothesis in a general
Bayesian mechanism, which may pertain to other neural systems in addition to
spatial cognition.
| [
{
"created": "Mon, 14 Oct 2019 01:43:11 GMT",
"version": "v1"
}
] | 2019-10-15 | [
[
"Zeng",
"Taiping",
""
],
[
"Li",
"XiaoLi",
""
],
[
"Si",
"Bailu",
""
]
] | Fourier-like summation of several grid cell modules with different spatial frequencies in the medial entorhinal cortex (MEC) has long been proposed to form the contours of place firing fields. Recent experiments largely, but not completely, support this theory. Place fields are obviously expanded by inactivation of dorsal MEC, which fits the hypothesis. However, contrary to the prediction, inactivation of ventral MEC is also weakly broaden the spatial place firing patterns. In this study, we derive the model from grid spatial frequencies represented by Gaussian profiles to a 1D place field by Bayesian inference, and further provide completely theoretical explanations for expansion of place fields and predictions for alignments of grid components. To understand the information transform across between neocortex, entorhinal cortex, and hippocampus, we propose spatial memory indexing theory from hippocampal indexing theory to investigate how neural dynamics work in the entorhinal-hippocampal circuit. The inputs of place cells in CA3 are converged from three grid modules with different grid spacings layer II of MEC by Bayesian mechanism. We resort to the robot system to test Fourier hypothesis and spatial memory indexing theory, and validate our proposed entorhinal-hippocampal model. And then we demonstrate its cognitive mapping capability on the KITTI odometry benchmark dataset. Results suggest that our model provides a rational theoretical explanation for the biological experimental results. Results also show that the proposed model is robust for simultaneous localization and mapping (SLAM) in the large-scale environment. Our proposed model theoretically supports for Fourier hypothesis in a general Bayesian mechanism, which may pertain to other neural systems in addition to spatial cognition. |
1405.1610 | Nico Riedel | Nico Riedel, Bhavin S. Khatri, Michael L\"assig, Johannes Berg | Multiple-line inference of selection on quantitative traits | 21 pages, 11 figures; to appear in Genetics | Genetics 201 (1), 305-322 (2015) | 10.1534/genetics.115.178988 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Trait differences between species may be attributable to natural selection.
However, quantifying the strength of evidence for selection acting on a
particular trait is a difficult task. Here we develop a population-genetic test
for selection acting on a quantitative trait which is based on multiple-line
crosses. We show that using multiple lines increases both the power and the
scope of selection inference. First, a test based on three or more lines
detects selection with strongly increased statistical significance, and we show
explicitly how the sensitivity of the test depends on the number of lines.
Second, a multiple-line test allows to distinguish different lineage-specific
selection scenarios. Our analytical results are complemented by extensive
numerical simulations. We then apply the multiple-line test to QTL data on
floral character traits in plant species of the Mimulus genus and on
photoperiodic traits in different maize strains, where we find a signatures of
lineage-specific selection not seen in a two-line test.
| [
{
"created": "Wed, 7 May 2014 14:10:29 GMT",
"version": "v1"
},
{
"created": "Mon, 6 Jul 2015 09:28:36 GMT",
"version": "v2"
}
] | 2017-08-09 | [
[
"Riedel",
"Nico",
""
],
[
"Khatri",
"Bhavin S.",
""
],
[
"Lässig",
"Michael",
""
],
[
"Berg",
"Johannes",
""
]
] | Trait differences between species may be attributable to natural selection. However, quantifying the strength of evidence for selection acting on a particular trait is a difficult task. Here we develop a population-genetic test for selection acting on a quantitative trait which is based on multiple-line crosses. We show that using multiple lines increases both the power and the scope of selection inference. First, a test based on three or more lines detects selection with strongly increased statistical significance, and we show explicitly how the sensitivity of the test depends on the number of lines. Second, a multiple-line test allows to distinguish different lineage-specific selection scenarios. Our analytical results are complemented by extensive numerical simulations. We then apply the multiple-line test to QTL data on floral character traits in plant species of the Mimulus genus and on photoperiodic traits in different maize strains, where we find a signatures of lineage-specific selection not seen in a two-line test. |
1810.12016 | Mattia Bramini | Mattia Bramini, Silvio Sacchetti, Andrea Armirotti, Anna Rocchi, Ester
V\'azquez, Ver\'onica Le\'on Castellanos, Tiziano Bandiera, Fabrizia Cesca
and Fabio Benfenati | Graphene oxide nanosheets disrupt lipid composition, Ca2+ homeostasis
and synaptic transmission in primary cortical neurons | This document is the unedited Author's version of a Submitted Work
that was subsequently accepted for publication in ACS Nano. To access the
final edited and published work see
https://pubs.acs.org/articlesonrequest/AOR-MGXEfuAxY43fnrHfBEuQ | ACS Nano 2016, 10, 7, 7154-7171 | 10.1021/acsnano.6b03438 | null | q-bio.NC physics.bio-ph | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Graphene has the potential to make a very significant impact on society, with
important applications in the biomedical field. The possibility to engineer
graphene-based medical devices at the neuronal interface is of particular
interest, making it imperative to determine the biocompatibility of graphene
materials with neuronal cells. Here we conducted a comprehensive analysis of
the effects of chronic and acute exposure of rat primary cortical neurons to
few-layers pristine graphene (GR) and monolayer graphene oxide (GO) flakes. By
combining a range of cell biology, microscopy, electrophysiology and omics
approaches we characterized the graphene neuron interaction from the first
steps of membrane contact and internalization to the long-term effects on cell
viability, synaptic transmission and cell metabolism. GR/GO flakes are found in
contact with the neuronal membrane, free in the cytoplasm and internalized
through the endolysosomal pathway, with no significant impact on neuron
viability. However, GO exposure selectively caused the inhibition of excitatory
transmission, paralleled by a reduction in the number of excitatory synaptic
contacts, and a concomitant enhancement of the inhibitory activity. This was
accompanied by induction of autophagy, altered Ca2+ dynamics and by a
downregulation of some of the main players in the regulation of Ca2+
homeostasis in both excitatory and inhibitory neurons. Our results show that,
although graphene exposure does not impact on neuron viability, it does
nevertheless have important effects on neuronal transmission and network
functionality, thus warranting caution when planning to employ this material
for neuro-biological applications.
| [
{
"created": "Mon, 29 Oct 2018 09:23:01 GMT",
"version": "v1"
}
] | 2018-10-30 | [
[
"Bramini",
"Mattia",
""
],
[
"Sacchetti",
"Silvio",
""
],
[
"Armirotti",
"Andrea",
""
],
[
"Rocchi",
"Anna",
""
],
[
"Vázquez",
"Ester",
""
],
[
"Castellanos",
"Verónica León",
""
],
[
"Bandiera",
"Tiziano",
""
],
[
"Cesca",
"Fabrizia",
""
],
[
"Benfenati",
"Fabio",
""
]
] | Graphene has the potential to make a very significant impact on society, with important applications in the biomedical field. The possibility to engineer graphene-based medical devices at the neuronal interface is of particular interest, making it imperative to determine the biocompatibility of graphene materials with neuronal cells. Here we conducted a comprehensive analysis of the effects of chronic and acute exposure of rat primary cortical neurons to few-layers pristine graphene (GR) and monolayer graphene oxide (GO) flakes. By combining a range of cell biology, microscopy, electrophysiology and omics approaches we characterized the graphene neuron interaction from the first steps of membrane contact and internalization to the long-term effects on cell viability, synaptic transmission and cell metabolism. GR/GO flakes are found in contact with the neuronal membrane, free in the cytoplasm and internalized through the endolysosomal pathway, with no significant impact on neuron viability. However, GO exposure selectively caused the inhibition of excitatory transmission, paralleled by a reduction in the number of excitatory synaptic contacts, and a concomitant enhancement of the inhibitory activity. This was accompanied by induction of autophagy, altered Ca2+ dynamics and by a downregulation of some of the main players in the regulation of Ca2+ homeostasis in both excitatory and inhibitory neurons. Our results show that, although graphene exposure does not impact on neuron viability, it does nevertheless have important effects on neuronal transmission and network functionality, thus warranting caution when planning to employ this material for neuro-biological applications. |
2111.04326 | Felix Kramer | Felix Kramer, Carl D. Modes | On biological flow networks: Antagonism between hydrodynamic and
metabolic stimuli as driver of topological transitions | null | null | null | null | q-bio.TO nlin.AO physics.bio-ph | http://creativecommons.org/licenses/by-nc-sa/4.0/ | A plethora of computational models have been developed in recent decades to
account for the morphogenesis of complex biological fluid networks, such as
capillary beds. Contemporary adaptation models are based on optimization
schemes where networks react and adapt toward given flow patterns. Doing so, a
system reduces dissipation and network volume, thereby altering its final form.
Yet, recent numeric studies on network morphogenesis, incorporating uptake of
metabolites by the embedding tissue, have indicated the conventional approach
to be insufficient. Here, we systematically study a hybrid-model which combines
the network adaptation schemes intended to generate space-filling perfusion as
well as optimal filtration of metabolites. As a result, we find hydrodynamic
stimuli (wall-shear stress) and filtration based stimuli (uptake of
metabolites) to be antagonistic as hydrodynamically optimized systems have
suboptimal uptake qualities and vice versa. We show that a switch between
different optimization regimes is typically accompanied with a complex
transition between topologically redundant meshes and spanning trees. Depending
on the metabolite demand and uptake capabilities of the adaptating networks, we
are further able to demonstrate the existence of nullity re-entrant behavior
and the development of compromised phenotypes such as dangling non-perfused
vessels and bottlenecks.
| [
{
"created": "Mon, 8 Nov 2021 08:37:35 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Nov 2021 10:25:33 GMT",
"version": "v2"
},
{
"created": "Mon, 15 Nov 2021 18:36:53 GMT",
"version": "v3"
}
] | 2021-11-16 | [
[
"Kramer",
"Felix",
""
],
[
"Modes",
"Carl D.",
""
]
] | A plethora of computational models have been developed in recent decades to account for the morphogenesis of complex biological fluid networks, such as capillary beds. Contemporary adaptation models are based on optimization schemes where networks react and adapt toward given flow patterns. Doing so, a system reduces dissipation and network volume, thereby altering its final form. Yet, recent numeric studies on network morphogenesis, incorporating uptake of metabolites by the embedding tissue, have indicated the conventional approach to be insufficient. Here, we systematically study a hybrid-model which combines the network adaptation schemes intended to generate space-filling perfusion as well as optimal filtration of metabolites. As a result, we find hydrodynamic stimuli (wall-shear stress) and filtration based stimuli (uptake of metabolites) to be antagonistic as hydrodynamically optimized systems have suboptimal uptake qualities and vice versa. We show that a switch between different optimization regimes is typically accompanied with a complex transition between topologically redundant meshes and spanning trees. Depending on the metabolite demand and uptake capabilities of the adaptating networks, we are further able to demonstrate the existence of nullity re-entrant behavior and the development of compromised phenotypes such as dangling non-perfused vessels and bottlenecks. |
2404.04300 | Michael Plank | Caleb Sullivan, Pubudu Senanayake, Michael J. Plank | Quantifying age-specific household contacts in Aotearoa New Zealand for
infectious disease modelling | null | null | null | null | q-bio.PE physics.soc-ph | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Accounting for population age structure and age-specific contact patterns is
crucial for accurate modelling of human infectious disease dynamics and impact.
A common approach is to use synthetic contact matrices, which estimate the
number of contacts between individuals of different ages in specific settings.
These contact matrices are frequently based on data collected from populations
with very different demographic and socioeconomic characteristics from the
population of interest. Here we use a comprehensive household composition
dataset based on New Zealand census and administrative data to construct
household contact matrices and a synthetic population that can be used for
modelling. We investigate the behaviour of a compartment-based and an
agent-based epidemic model parameterised using this data, compared to a
commonly used synthetic contact matrix. We find that using the household
composition data leads to lower attack rates in older age groups compared to
using the synthetic contact matrix. This difference becomes larger when
household transmission is more dominant relative to non-household transmission.
In addition, explicitly account for household structure in an agent-based
models leads to lower attack rates at all ages. We provide electronic versions
of the synthetic population and household contact matrix for other researchers
to use in infectious disease models.
| [
{
"created": "Thu, 4 Apr 2024 21:25:53 GMT",
"version": "v1"
}
] | 2024-04-09 | [
[
"Sullivan",
"Caleb",
""
],
[
"Senanayake",
"Pubudu",
""
],
[
"Plank",
"Michael J.",
""
]
] | Accounting for population age structure and age-specific contact patterns is crucial for accurate modelling of human infectious disease dynamics and impact. A common approach is to use synthetic contact matrices, which estimate the number of contacts between individuals of different ages in specific settings. These contact matrices are frequently based on data collected from populations with very different demographic and socioeconomic characteristics from the population of interest. Here we use a comprehensive household composition dataset based on New Zealand census and administrative data to construct household contact matrices and a synthetic population that can be used for modelling. We investigate the behaviour of a compartment-based and an agent-based epidemic model parameterised using this data, compared to a commonly used synthetic contact matrix. We find that using the household composition data leads to lower attack rates in older age groups compared to using the synthetic contact matrix. This difference becomes larger when household transmission is more dominant relative to non-household transmission. In addition, explicitly account for household structure in an agent-based models leads to lower attack rates at all ages. We provide electronic versions of the synthetic population and household contact matrix for other researchers to use in infectious disease models. |
1110.2519 | Michele Bellingeri | Michele Bellingeri | Threshold Extinction in Food Webs | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Understanding how an extinction event affects ecosystem is fundamental to
biodiversity conservation. For this reason, food web response to species loss
has been investigated in several ways in the last years. Several studies
focused on secondary extinction due to biodiversity loss in a bottom-up
perspective using in-silico extinction experiments in which a single species is
removed at each step and the number of secondary extinctions is recorded. In
these binary simulations a species goes secondarily extinct if it loses all its
resource species, that is, when the energy intake is zero. This pure
topological statement represents the best case scenario. In fact a consumer
species could go extinct losing a certain fraction of the energy intake and the
response of quantitative food webs to node loss could be very different with
respect to simple binary predictions. The goal of this paper is to analyze how
patterns of secondary extinctions change when higher species sensitivity are
included in the analyses. In particular, we explored how food web secondary
extinction, triggered by the removal of most connected nodes, varies as a
function of the energy intake threshold assumed as the minimum needed for
species persistence. As we will show, a very low increase of energy intake
threshold stimulates a disproportionate growth of secondary extinction.
| [
{
"created": "Tue, 11 Oct 2011 22:14:05 GMT",
"version": "v1"
},
{
"created": "Fri, 4 Nov 2011 13:53:51 GMT",
"version": "v2"
}
] | 2011-11-07 | [
[
"Bellingeri",
"Michele",
""
]
] | Understanding how an extinction event affects ecosystem is fundamental to biodiversity conservation. For this reason, food web response to species loss has been investigated in several ways in the last years. Several studies focused on secondary extinction due to biodiversity loss in a bottom-up perspective using in-silico extinction experiments in which a single species is removed at each step and the number of secondary extinctions is recorded. In these binary simulations a species goes secondarily extinct if it loses all its resource species, that is, when the energy intake is zero. This pure topological statement represents the best case scenario. In fact a consumer species could go extinct losing a certain fraction of the energy intake and the response of quantitative food webs to node loss could be very different with respect to simple binary predictions. The goal of this paper is to analyze how patterns of secondary extinctions change when higher species sensitivity are included in the analyses. In particular, we explored how food web secondary extinction, triggered by the removal of most connected nodes, varies as a function of the energy intake threshold assumed as the minimum needed for species persistence. As we will show, a very low increase of energy intake threshold stimulates a disproportionate growth of secondary extinction. |
0709.4200 | Philip M. Kim | Philip M. Kim, Jan O. Korbel, Xueying Chen, Mark B. Gerstein | Copy Number Variants and Segmental Duplications Show Different Formation
Signatures | 13 pages | null | null | null | q-bio.GN q-bio.QM | null | In addition to variation in terms of single nucleotide polymorphisms (SNPs),
whole regions ranging from several kilobases up to a megabase in length differ
in copy number among individuals. These differences are referred to as Copy
Number Variants (CNVs) and extensive mapping of these is underway. Recent
studies have highlighted their great prevalence in the human genome. Segmental
Duplications (SDs) are long (>1kb) stretches of duplicated DNA with high
sequence identity. First, we analyzed the co-localization of SDs and find that
SDs are significantly co-localized with each other, resulting in a power-law
distribution, which suggests a preferential attachment mechanism, i.e. existing
SDs are likely to be involved in creating new ones nearby. Second, we look at
the relationship of CNVs/SDs with various types of repeats. We we find that the
previously recognized association of SDs with Alu elements is significantly
stronger for older SDs and is sharply decreasing for younger ones. While it
might be expected that the patterns should be similar for SDs and CNVs, we
find, surprisingly, no association of CNVs with Alu elements. This trend is
consistent with the decreasing correlation between Alu elements and younger
SDs, the activity of Alu elements has been decreasing and by now it they seem
no longer active. Furthermore, we find a striking association of SDs with
processed pseudogenes suggesting that they may also have mediated SD formation.
Moreover, find strong association with microsatellites for both SDs and CNVs
that suggests a role for satellites in the formation of both.
| [
{
"created": "Wed, 26 Sep 2007 15:53:40 GMT",
"version": "v1"
}
] | 2007-09-27 | [
[
"Kim",
"Philip M.",
""
],
[
"Korbel",
"Jan O.",
""
],
[
"Chen",
"Xueying",
""
],
[
"Gerstein",
"Mark B.",
""
]
] | In addition to variation in terms of single nucleotide polymorphisms (SNPs), whole regions ranging from several kilobases up to a megabase in length differ in copy number among individuals. These differences are referred to as Copy Number Variants (CNVs) and extensive mapping of these is underway. Recent studies have highlighted their great prevalence in the human genome. Segmental Duplications (SDs) are long (>1kb) stretches of duplicated DNA with high sequence identity. First, we analyzed the co-localization of SDs and find that SDs are significantly co-localized with each other, resulting in a power-law distribution, which suggests a preferential attachment mechanism, i.e. existing SDs are likely to be involved in creating new ones nearby. Second, we look at the relationship of CNVs/SDs with various types of repeats. We we find that the previously recognized association of SDs with Alu elements is significantly stronger for older SDs and is sharply decreasing for younger ones. While it might be expected that the patterns should be similar for SDs and CNVs, we find, surprisingly, no association of CNVs with Alu elements. This trend is consistent with the decreasing correlation between Alu elements and younger SDs, the activity of Alu elements has been decreasing and by now it they seem no longer active. Furthermore, we find a striking association of SDs with processed pseudogenes suggesting that they may also have mediated SD formation. Moreover, find strong association with microsatellites for both SDs and CNVs that suggests a role for satellites in the formation of both. |
2401.00562 | Tim Sziburis | Tim Sziburis, Susanne Blex, Tobias Glasmachers, Ioannis Iossifidis | Ruhr Hand Motion Catalog of Human Center-Out Transport Trajectories in
3D Task-Space Captured by a Redundant Measurement System | null | null | null | null | q-bio.QM eess.SP | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Neurological conditions are a major source of movement disorders. Motion
modelling and variability analysis have the potential to identify pathology but
require profound data. We introduce a systematic dataset of 3D center-out
task-space trajectories of human hand transport movements in a natural setting.
The transport tasks of this study consist of grasping a cylindric object from a
unified start position and transporting it to one of nine target locations in
unconstrained operational space. The measurement procedure is automatized to
record ten trials per target location. With that, the dataset consists of 90
movement trajectories for each hand of 31 participants without known movement
disorders. The participants are aged between 21 and 78 years, covering a wide
range. Data are recorded redundantly by both an optical tracking system and an
IMU sensor. As opposed to the stationary capturing system, the IMU can be
considered as a portable, low-cost and energy-efficient alternative to be
implemented on embedded systems.
| [
{
"created": "Sun, 31 Dec 2023 18:39:42 GMT",
"version": "v1"
}
] | 2024-01-02 | [
[
"Sziburis",
"Tim",
""
],
[
"Blex",
"Susanne",
""
],
[
"Glasmachers",
"Tobias",
""
],
[
"Iossifidis",
"Ioannis",
""
]
] | Neurological conditions are a major source of movement disorders. Motion modelling and variability analysis have the potential to identify pathology but require profound data. We introduce a systematic dataset of 3D center-out task-space trajectories of human hand transport movements in a natural setting. The transport tasks of this study consist of grasping a cylindric object from a unified start position and transporting it to one of nine target locations in unconstrained operational space. The measurement procedure is automatized to record ten trials per target location. With that, the dataset consists of 90 movement trajectories for each hand of 31 participants without known movement disorders. The participants are aged between 21 and 78 years, covering a wide range. Data are recorded redundantly by both an optical tracking system and an IMU sensor. As opposed to the stationary capturing system, the IMU can be considered as a portable, low-cost and energy-efficient alternative to be implemented on embedded systems. |
2104.02604 | Mar\'ia Virginia Sabando Miss | Mar\'ia Virginia Sabando, Ignacio Ponzoni, Evangelos E. Milios, Axel
J. Soto | Using Molecular Embeddings in QSAR Modeling: Does it Make a Difference? | null | Briefings in Bioinformatics, Volume 23, Issue 1, January 2022,
bbab365 | 10.1093/bib/bbab365 | null | q-bio.BM cs.LG q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | With the consolidation of deep learning in drug discovery, several novel
algorithms for learning molecular representations have been proposed. Despite
the interest of the community in developing new methods for learning molecular
embeddings and their theoretical benefits, comparing molecular embeddings with
each other and with traditional representations is not straightforward, which
in turn hinders the process of choosing a suitable representation for QSAR
modeling. A reason behind this issue is the difficulty of conducting a fair and
thorough comparison of the different existing embedding approaches, which
requires numerous experiments on various datasets and training scenarios. To
close this gap, we reviewed the literature on methods for molecular embeddings
and reproduced three unsupervised and two supervised molecular embedding
techniques recently proposed in the literature. We compared these five methods
concerning their performance in QSAR scenarios using different classification
and regression datasets. We also compared these representations to traditional
molecular representations, namely molecular descriptors and fingerprints. As
opposed to the expected outcome, our experimental setup consisting of over
25,000 trained models and statistical tests revealed that the predictive
performance using molecular embeddings did not significantly surpass that of
traditional representations. While supervised embeddings yielded competitive
results compared to those using traditional molecular representations,
unsupervised embeddings tended to perform worse than traditional
representations. Our results highlight the need for conducting a careful
comparison and analysis of the different embedding techniques prior to using
them in drug design tasks, and motivate a discussion about the potential of
molecular embeddings in computer-aided drug design.
| [
{
"created": "Sat, 20 Mar 2021 21:45:22 GMT",
"version": "v1"
},
{
"created": "Wed, 28 Jul 2021 15:30:22 GMT",
"version": "v2"
}
] | 2022-05-09 | [
[
"Sabando",
"María Virginia",
""
],
[
"Ponzoni",
"Ignacio",
""
],
[
"Milios",
"Evangelos E.",
""
],
[
"Soto",
"Axel J.",
""
]
] | With the consolidation of deep learning in drug discovery, several novel algorithms for learning molecular representations have been proposed. Despite the interest of the community in developing new methods for learning molecular embeddings and their theoretical benefits, comparing molecular embeddings with each other and with traditional representations is not straightforward, which in turn hinders the process of choosing a suitable representation for QSAR modeling. A reason behind this issue is the difficulty of conducting a fair and thorough comparison of the different existing embedding approaches, which requires numerous experiments on various datasets and training scenarios. To close this gap, we reviewed the literature on methods for molecular embeddings and reproduced three unsupervised and two supervised molecular embedding techniques recently proposed in the literature. We compared these five methods concerning their performance in QSAR scenarios using different classification and regression datasets. We also compared these representations to traditional molecular representations, namely molecular descriptors and fingerprints. As opposed to the expected outcome, our experimental setup consisting of over 25,000 trained models and statistical tests revealed that the predictive performance using molecular embeddings did not significantly surpass that of traditional representations. While supervised embeddings yielded competitive results compared to those using traditional molecular representations, unsupervised embeddings tended to perform worse than traditional representations. Our results highlight the need for conducting a careful comparison and analysis of the different embedding techniques prior to using them in drug design tasks, and motivate a discussion about the potential of molecular embeddings in computer-aided drug design. |
1911.01174 | Alexander L\"uck | Alexander L\"uck, Verena Wolf | Generalized Method of Moments Estimation for Stochastic Models of DNA
Methylation Patterns | 12 pages, 3 figures, 1 table | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | With recent advances in sequencing technologies, large amounts of epigenomic
data have become available and computational methods are contributing
significantly to the progress of epigenetic research. As an orthogonal approach
to methods based on machine learning, mechanistic modeling aims at a
description of the mechanisms underlying epigenetic changes. Here, we propose
an efficient method for parameter estimation for stochastic models that
describe the dynamics of DNA methylation patterns over time. Our method is
based on the Generalized Method of Moments (GMM) and gives results with an
accuracy similar to that of maximum likelihood-based estimation approaches.
However, in contrast to the latter, the GMM still allows an efficient and
accurate calibration of parameters even if the complexity of the model is
increased by considering longer methylation patterns. We show the usefulness of
our method by applying it to hairpin bisulfite sequencing data from mouse ESCs
for varying pattern lengths.
| [
{
"created": "Mon, 4 Nov 2019 13:01:24 GMT",
"version": "v1"
}
] | 2019-11-05 | [
[
"Lück",
"Alexander",
""
],
[
"Wolf",
"Verena",
""
]
] | With recent advances in sequencing technologies, large amounts of epigenomic data have become available and computational methods are contributing significantly to the progress of epigenetic research. As an orthogonal approach to methods based on machine learning, mechanistic modeling aims at a description of the mechanisms underlying epigenetic changes. Here, we propose an efficient method for parameter estimation for stochastic models that describe the dynamics of DNA methylation patterns over time. Our method is based on the Generalized Method of Moments (GMM) and gives results with an accuracy similar to that of maximum likelihood-based estimation approaches. However, in contrast to the latter, the GMM still allows an efficient and accurate calibration of parameters even if the complexity of the model is increased by considering longer methylation patterns. We show the usefulness of our method by applying it to hairpin bisulfite sequencing data from mouse ESCs for varying pattern lengths. |
2405.07123 | Jordan Rozum | Austin M. Marcus, Jordan Rozum, Herbert Sizek, and Luis M. Rocha | CANA v1.0.0 and schematodes: efficient quantification of symmetry in
Boolean automata | 5 pages 1 figure (two images in figure) | null | null | null | q-bio.MN q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | The biomolecular networks underpinning cell function exhibit canalization, or
the buffering of fluctuations required to function in a noisy environment. One
understudied putative mechanism for canalization is the functional equivalence
of a biomolecular entity's regulators (e.g., among the transcription factors
for a gene). In these discrete dynamical systems, activation and inhibition of
biomolecular entities (e.g., transcription of genes) are modeled as the
activity of coupled 2-state automata, and thus the equivalence of regulators
can be studied using the theory of symmetry in discrete functions. To this end,
we present a new exact algorithm for finding maximal symmetry groups among the
inputs to discrete functions. We implement this algorithm in Rust as a Python
package, schematodes. We include schematodes in the new CANA v1.0.0 release, an
open source Python library for analyzing canalization in Boolean networks,
which we also present here. We compare our exact method implemented in
schematodes to the previously published inexact method used in earlier releases
of CANA and find that schematodes significantly outperforms the prior method
both in speed and accuracy. We also apply CANA v1.0.0 to study the symmetry
properties of regulatory function from an ensemble of experimentally-supported
Boolean networks from the Cell Collective. Using CANA v1.0.0, we find that the
distribution of a previously reported symmetry parameter, $k_s/k$, is
statistically significantly different in the Cell Collective than in random
automata with the same in-degree and activation bias (Kolmogorov-Smirnov test,
$p<0.001$). In particular, its spread is much wider than in our null model (IQR
0.31 vs IQR 0.20 with equal medians), demonstrating that the Cell Collective is
enriched in functions with extreme symmetry or asymmetry.
| [
{
"created": "Sun, 12 May 2024 01:14:00 GMT",
"version": "v1"
}
] | 2024-05-14 | [
[
"Marcus",
"Austin M.",
""
],
[
"Rozum",
"Jordan",
""
],
[
"Sizek",
"Herbert",
""
],
[
"Rocha",
"Luis M.",
""
]
] | The biomolecular networks underpinning cell function exhibit canalization, or the buffering of fluctuations required to function in a noisy environment. One understudied putative mechanism for canalization is the functional equivalence of a biomolecular entity's regulators (e.g., among the transcription factors for a gene). In these discrete dynamical systems, activation and inhibition of biomolecular entities (e.g., transcription of genes) are modeled as the activity of coupled 2-state automata, and thus the equivalence of regulators can be studied using the theory of symmetry in discrete functions. To this end, we present a new exact algorithm for finding maximal symmetry groups among the inputs to discrete functions. We implement this algorithm in Rust as a Python package, schematodes. We include schematodes in the new CANA v1.0.0 release, an open source Python library for analyzing canalization in Boolean networks, which we also present here. We compare our exact method implemented in schematodes to the previously published inexact method used in earlier releases of CANA and find that schematodes significantly outperforms the prior method both in speed and accuracy. We also apply CANA v1.0.0 to study the symmetry properties of regulatory function from an ensemble of experimentally-supported Boolean networks from the Cell Collective. Using CANA v1.0.0, we find that the distribution of a previously reported symmetry parameter, $k_s/k$, is statistically significantly different in the Cell Collective than in random automata with the same in-degree and activation bias (Kolmogorov-Smirnov test, $p<0.001$). In particular, its spread is much wider than in our null model (IQR 0.31 vs IQR 0.20 with equal medians), demonstrating that the Cell Collective is enriched in functions with extreme symmetry or asymmetry. |
2106.13202 | Ju An Park | Ju An Park, Vikram Voleti, Kathryn E. Thomas, Alexander Wong and Jason
L. Deglint | SALT: Sea lice Adaptive Lattice Tracking -- An Unsupervised Approach to
Generate an Improved Ocean Model | 5 pages, 3 figures, 3 tables | null | null | null | q-bio.QM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Warming oceans due to climate change are leading to increased numbers of
ectoparasitic copepods, also known as sea lice, which can cause significant
ecological loss to wild salmon populations and major economic loss to
aquaculture sites. The main transport mechanism driving the spread of sea lice
populations are near-surface ocean currents. Present strategies to estimate the
distribution of sea lice larvae are computationally complex and limit
full-scale analysis. Motivated to address this challenge, we propose SALT: Sea
lice Adaptive Lattice Tracking approach for efficient estimation of sea lice
dispersion and distribution in space and time. Specifically, an adaptive
spatial mesh is generated by merging nodes in the lattice graph of the Ocean
Model based on local ocean properties, thus enabling highly efficient graph
representation. SALT demonstrates improved efficiency while maintaining
consistent results with the standard method, using near-surface current data
for Hardangerfjord, Norway. The proposed SALT technique shows promise for
enhancing proactive aquaculture management through predictive modelling of sea
lice infestation pressure maps in a changing climate.
| [
{
"created": "Thu, 24 Jun 2021 17:29:42 GMT",
"version": "v1"
}
] | 2021-06-25 | [
[
"Park",
"Ju An",
""
],
[
"Voleti",
"Vikram",
""
],
[
"Thomas",
"Kathryn E.",
""
],
[
"Wong",
"Alexander",
""
],
[
"Deglint",
"Jason L.",
""
]
] | Warming oceans due to climate change are leading to increased numbers of ectoparasitic copepods, also known as sea lice, which can cause significant ecological loss to wild salmon populations and major economic loss to aquaculture sites. The main transport mechanism driving the spread of sea lice populations are near-surface ocean currents. Present strategies to estimate the distribution of sea lice larvae are computationally complex and limit full-scale analysis. Motivated to address this challenge, we propose SALT: Sea lice Adaptive Lattice Tracking approach for efficient estimation of sea lice dispersion and distribution in space and time. Specifically, an adaptive spatial mesh is generated by merging nodes in the lattice graph of the Ocean Model based on local ocean properties, thus enabling highly efficient graph representation. SALT demonstrates improved efficiency while maintaining consistent results with the standard method, using near-surface current data for Hardangerfjord, Norway. The proposed SALT technique shows promise for enhancing proactive aquaculture management through predictive modelling of sea lice infestation pressure maps in a changing climate. |
1503.07116 | Bartlomiej Waclaw Dr | Bartlomiej Waclaw, Ivana Bozic, Meredith E. Pittman, Ralph H. Hruban,
Bert Vogelstein, Martin A. Nowak | Spatial model predicts dispersal and cell turnover cause reduced
intra-tumor heterogeneity | 37 pages, 14 figures | null | 10.1038/nature14971 | null | q-bio.PE q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Most cancers in humans are large, measuring centimeters in diameter, composed
of many billions of cells. An equivalent mass of normal cells would be highly
heterogeneous as a result of the mutations that occur during each cell
division. What is remarkable about cancers is their homogeneity - virtually
every neoplastic cell within a large cancer contains the same core set of
genetic alterations, with heterogeneity confined to mutations that have emerged
after the last clonal expansions. How such clones expand within the
spatially-constrained three dimensional architecture of a tumor, and come to
dominate a large, pre-existing lesion, has never been explained. We here
describe a model for tumor evolution that shows how short-range migration and
cell turnover can account for rapid cell mixing inside the tumor. With it, we
show that even a small selective advantage of a single cell within a large
tumor allows the descendants of that cell to replace the precursor mass in a
clinically relevant time frame. We also demonstrate that the same mechanisms
can be responsible for the rapid onset of resistance to chemotherapy. Our model
not only provides novel insights into spatial and temporal aspects of tumor
growth but also suggests that targeting short range cellular migratory activity
could have dramatic effects on tumor growth rates.
| [
{
"created": "Tue, 24 Mar 2015 17:22:54 GMT",
"version": "v1"
}
] | 2016-02-17 | [
[
"Waclaw",
"Bartlomiej",
""
],
[
"Bozic",
"Ivana",
""
],
[
"Pittman",
"Meredith E.",
""
],
[
"Hruban",
"Ralph H.",
""
],
[
"Vogelstein",
"Bert",
""
],
[
"Nowak",
"Martin A.",
""
]
] | Most cancers in humans are large, measuring centimeters in diameter, composed of many billions of cells. An equivalent mass of normal cells would be highly heterogeneous as a result of the mutations that occur during each cell division. What is remarkable about cancers is their homogeneity - virtually every neoplastic cell within a large cancer contains the same core set of genetic alterations, with heterogeneity confined to mutations that have emerged after the last clonal expansions. How such clones expand within the spatially-constrained three dimensional architecture of a tumor, and come to dominate a large, pre-existing lesion, has never been explained. We here describe a model for tumor evolution that shows how short-range migration and cell turnover can account for rapid cell mixing inside the tumor. With it, we show that even a small selective advantage of a single cell within a large tumor allows the descendants of that cell to replace the precursor mass in a clinically relevant time frame. We also demonstrate that the same mechanisms can be responsible for the rapid onset of resistance to chemotherapy. Our model not only provides novel insights into spatial and temporal aspects of tumor growth but also suggests that targeting short range cellular migratory activity could have dramatic effects on tumor growth rates. |
1301.1590 | Hamidreza Chitsaz | Hamidreza Chitsaz and Elmirasadat Forouzmand and Gholamreza Haffari | An Efficient Algorithm for Upper Bound on the Partition Function of
Nucleic Acids | null | null | null | null | q-bio.BM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It has been shown that minimum free energy structure for RNAs and RNA-RNA
interaction is often incorrect due to inaccuracies in the energy parameters and
inherent limitations of the energy model. In contrast, ensemble based
quantities such as melting temperature and equilibrium concentrations can be
more reliably predicted. Even structure prediction by sampling from the
ensemble and clustering those structures by Sfold [7] has proven to be more
reliable than minimum free energy structure prediction. The main obstacle for
ensemble based approaches is the computational complexity of the partition
function and base pairing probabilities. For instance, the space complexity of
the partition function for RNA-RNA interaction is $O(n^4)$ and the time
complexity is $O(n^6)$ which are prohibitively large [4,12]. Our goal in this
paper is to give a fast algorithm, based on sparse folding, to calculate an
upper bound on the partition function. Our work is based on the recent
algorithm of Hazan and Jaakkola [10]. The space complexity of our algorithm is
the same as that of sparse folding algorithms, and the time complexity of our
algorithm is $O(MFE(n)\ell)$ for single RNA and $O(MFE(m, n)\ell)$ for RNA-RNA
interaction in practice, in which $MFE$ is the running time of sparse folding
and $\ell \leq n$ ($\ell \leq n + m$) is a sequence dependent parameter.
| [
{
"created": "Tue, 8 Jan 2013 16:58:28 GMT",
"version": "v1"
}
] | 2013-01-09 | [
[
"Chitsaz",
"Hamidreza",
""
],
[
"Forouzmand",
"Elmirasadat",
""
],
[
"Haffari",
"Gholamreza",
""
]
] | It has been shown that minimum free energy structure for RNAs and RNA-RNA interaction is often incorrect due to inaccuracies in the energy parameters and inherent limitations of the energy model. In contrast, ensemble based quantities such as melting temperature and equilibrium concentrations can be more reliably predicted. Even structure prediction by sampling from the ensemble and clustering those structures by Sfold [7] has proven to be more reliable than minimum free energy structure prediction. The main obstacle for ensemble based approaches is the computational complexity of the partition function and base pairing probabilities. For instance, the space complexity of the partition function for RNA-RNA interaction is $O(n^4)$ and the time complexity is $O(n^6)$ which are prohibitively large [4,12]. Our goal in this paper is to give a fast algorithm, based on sparse folding, to calculate an upper bound on the partition function. Our work is based on the recent algorithm of Hazan and Jaakkola [10]. The space complexity of our algorithm is the same as that of sparse folding algorithms, and the time complexity of our algorithm is $O(MFE(n)\ell)$ for single RNA and $O(MFE(m, n)\ell)$ for RNA-RNA interaction in practice, in which $MFE$ is the running time of sparse folding and $\ell \leq n$ ($\ell \leq n + m$) is a sequence dependent parameter. |
1807.07566 | Yu-Cheng Chen | Yu-Cheng Chen, Qiushu Chen, Xiaotain Tan, Grace Chen, Ingrid Bergin,
Muhammad Nadeem Aslam, and Xudong Fan | Chromatin Laser Imaging Reveals Abnormal Nuclear Changes for Early
Cancer Detection | null | null | null | null | q-bio.TO physics.bio-ph physics.optics q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We developed and applied rapid scanning laser-emission microscopy to detect
abnormal changes in cell nuclei for early diagnosis of cancer and cancer
precursors. Regulation of chromatins is essential for genetic development and
normal cell functions, while abnormal nuclear changes may lead to many
diseases, in particular, cancer. The capability to detect abnormal changes in
apparently normal tissues at a stage earlier than tumor development is critical
for cancer prevention. Here we report using LEM to analyze colonic tissues from
mice at-risk for colon cancer by detecting prepolyp nuclear abnormality. By
imaging the lasing emissions from chromatins, we discovered that, despite the
absence of observable lesions, polyps, or tumors under stereoscope, high-fat
mice exhibited significantly lower lasing thresholds than low-fat mice. The low
lasing threshold is, in fact, very similar to that of adenomas and is caused by
abnormal cell proliferation and chromatin deregulation that can potentially
lead to cancer. Our findings suggest that conventional methods, such as
colonoscopy, may be insufficient to reveal hidden or early tumors under
development. We envision that this work will provide new insights into LEM for
early tumor detection in clinical diagnosis and fundamental biological and
biomedical research of chromatin changes at the biomolecular level of cancer
development.
| [
{
"created": "Thu, 19 Jul 2018 11:08:10 GMT",
"version": "v1"
}
] | 2018-07-23 | [
[
"Chen",
"Yu-Cheng",
""
],
[
"Chen",
"Qiushu",
""
],
[
"Tan",
"Xiaotain",
""
],
[
"Chen",
"Grace",
""
],
[
"Bergin",
"Ingrid",
""
],
[
"Aslam",
"Muhammad Nadeem",
""
],
[
"Fan",
"Xudong",
""
]
] | We developed and applied rapid scanning laser-emission microscopy to detect abnormal changes in cell nuclei for early diagnosis of cancer and cancer precursors. Regulation of chromatins is essential for genetic development and normal cell functions, while abnormal nuclear changes may lead to many diseases, in particular, cancer. The capability to detect abnormal changes in apparently normal tissues at a stage earlier than tumor development is critical for cancer prevention. Here we report using LEM to analyze colonic tissues from mice at-risk for colon cancer by detecting prepolyp nuclear abnormality. By imaging the lasing emissions from chromatins, we discovered that, despite the absence of observable lesions, polyps, or tumors under stereoscope, high-fat mice exhibited significantly lower lasing thresholds than low-fat mice. The low lasing threshold is, in fact, very similar to that of adenomas and is caused by abnormal cell proliferation and chromatin deregulation that can potentially lead to cancer. Our findings suggest that conventional methods, such as colonoscopy, may be insufficient to reveal hidden or early tumors under development. We envision that this work will provide new insights into LEM for early tumor detection in clinical diagnosis and fundamental biological and biomedical research of chromatin changes at the biomolecular level of cancer development. |
1902.08555 | Jes\'us Fern\'andez-S\'anchez | Marta Casanellas, Jes\'us Fern\'andez-S\'anchez, Jordi Roca-Lacostena | Embeddability and rate identifiability of Kimura 2-parameter matrices | 20 pages; 10 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deciding whether a Markov matrix is embeddable (i.e. can be written as the
exponential of a rate matrix) is an open problem even for $4\times 4$ matrices.
We study the embedding problem and rate identifiability for the K80 model of
nucleotide substitution. For these $4\times 4$ matrices, we fully characterize
the set of embeddable K80 Markov matrices and the set of embeddable matrices
for which rates are identifiable. In particular, we describe an open subset of
embeddable matrices with non-identifiable rates. This set contains matrices
with positive eigenvalues and also diagonal largest in column matrices, which
might lead to consequences in parameter estimation in phylogenetics. Finally,
we compute the relative volumes of embeddable K80 matrices and of embeddable
matrices with identifiable rates. This study concludes the embedding problem
for the more general model K81 and its submodels, which had been initiated by
the last two authors in a separate work.
| [
{
"created": "Fri, 22 Feb 2019 16:43:07 GMT",
"version": "v1"
},
{
"created": "Wed, 27 Nov 2019 09:53:46 GMT",
"version": "v2"
}
] | 2019-11-28 | [
[
"Casanellas",
"Marta",
""
],
[
"Fernández-Sánchez",
"Jesús",
""
],
[
"Roca-Lacostena",
"Jordi",
""
]
] | Deciding whether a Markov matrix is embeddable (i.e. can be written as the exponential of a rate matrix) is an open problem even for $4\times 4$ matrices. We study the embedding problem and rate identifiability for the K80 model of nucleotide substitution. For these $4\times 4$ matrices, we fully characterize the set of embeddable K80 Markov matrices and the set of embeddable matrices for which rates are identifiable. In particular, we describe an open subset of embeddable matrices with non-identifiable rates. This set contains matrices with positive eigenvalues and also diagonal largest in column matrices, which might lead to consequences in parameter estimation in phylogenetics. Finally, we compute the relative volumes of embeddable K80 matrices and of embeddable matrices with identifiable rates. This study concludes the embedding problem for the more general model K81 and its submodels, which had been initiated by the last two authors in a separate work. |
2106.05783 | Leonardo Dalla Porta | Leonardo Dalla Porta, Daniel M. Castro, Mauro Copelli, Pedro V.
Carelli, and Fernanda S. Matias | Feedforward and feedback influences through distinct frequency bands
between two spiking-neuron networks | null | null | 10.1103/PhysRevE.104.054404 | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Several studies with brain signals suggested that bottom-up and top-down
influences are exerted through distinct frequency bands among visual cortical
areas. It has been recently shown that theta and gamma rhythms subserve
feedforward, whereas the feedback influence is dominated by the alpha-beta
rhythm in primates. A few theoretical models for reproducing these effects have
been proposed so far. Here we show that a simple but biophysically plausible
two-network motif composed of spiking-neuron models and chemical synapses can
exhibit feedforward and feedback influences through distinct frequency bands.
Differently from previous studies, this kind of model allows us to study
directed influences not only at the population level, by using a proxy for the
local field potential, but also at the cellular level, by using the neuronal
spiking series.
| [
{
"created": "Thu, 10 Jun 2021 14:34:03 GMT",
"version": "v1"
}
] | 2021-11-24 | [
[
"Porta",
"Leonardo Dalla",
""
],
[
"Castro",
"Daniel M.",
""
],
[
"Copelli",
"Mauro",
""
],
[
"Carelli",
"Pedro V.",
""
],
[
"Matias",
"Fernanda S.",
""
]
] | Several studies with brain signals suggested that bottom-up and top-down influences are exerted through distinct frequency bands among visual cortical areas. It has been recently shown that theta and gamma rhythms subserve feedforward, whereas the feedback influence is dominated by the alpha-beta rhythm in primates. A few theoretical models for reproducing these effects have been proposed so far. Here we show that a simple but biophysically plausible two-network motif composed of spiking-neuron models and chemical synapses can exhibit feedforward and feedback influences through distinct frequency bands. Differently from previous studies, this kind of model allows us to study directed influences not only at the population level, by using a proxy for the local field potential, but also at the cellular level, by using the neuronal spiking series. |
1807.07127 | Charo del Genio | Erin Connelly, Charo I. del Genio, Freya Harrison | Datamining a medieval medical text reveals patterns in ingredient choice
that reflect biological activity against the causative agents of specified
infections | 27 pages, 4 figures | null | null | null | q-bio.QM cs.SI physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The pharmacopeia used by physicians and lay people in medieval Europe has
largely been dismissed as placebo or superstition. While we now recognise that
some of the materia medica used by medieval physicians could have had useful
biological properties, research in this area is limited by the labour-intensive
process of searching and interpreting historical medical texts. Here, we
demonstrate the potential power of turning medieval medical texts into
contextualised electronic databases amenable to exploration by algorithm. We
use established methodologies from network science to reveal statistically
significant patterns in ingredient selection and usage in a key text, the
fifteenth-century Lylye of Medicynes, focusing on remedies to treat symptoms of
microbial infection. We discuss the potential that these patterns reflect
rational medical decisions. In providing a worked example of data-driven
textual analysis, we demonstrate the potential of this approach to encourage
interdisciplinary collaboration and to shine a new light on the
ethnopharmacology of historical medical texts.
| [
{
"created": "Wed, 18 Jul 2018 20:08:18 GMT",
"version": "v1"
}
] | 2018-07-20 | [
[
"Connelly",
"Erin",
""
],
[
"del Genio",
"Charo I.",
""
],
[
"Harrison",
"Freya",
""
]
] | The pharmacopeia used by physicians and lay people in medieval Europe has largely been dismissed as placebo or superstition. While we now recognise that some of the materia medica used by medieval physicians could have had useful biological properties, research in this area is limited by the labour-intensive process of searching and interpreting historical medical texts. Here, we demonstrate the potential power of turning medieval medical texts into contextualised electronic databases amenable to exploration by algorithm. We use established methodologies from network science to reveal statistically significant patterns in ingredient selection and usage in a key text, the fifteenth-century Lylye of Medicynes, focusing on remedies to treat symptoms of microbial infection. We discuss the potential that these patterns reflect rational medical decisions. In providing a worked example of data-driven textual analysis, we demonstrate the potential of this approach to encourage interdisciplinary collaboration and to shine a new light on the ethnopharmacology of historical medical texts. |
1109.5159 | Michael Knudsen | Michael Knudsen, Elisenda Feliu, Carsten Wiuf | Exact Analysis of Intrinsic Qualitative Features of Phosphorelays using
Mathematical Models | null | null | null | null | q-bio.MN q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Phosphorelays are a class of signaling mechanisms used by cells to respond to
changes in their environment. Phosphorelays (of which two-component systems
constitute a special case) are particularly abundant in prokaryotes and have
been shown to be involved in many fundamental processes such as stress
response, osmotic regulation, virulence, and chemotaxis. We develop a general
model of phosphorelays extending existing models of phosphorelays and
two-component systems. We analyze the model analytically under the assumption
of mass-action kinetics and prove that a phosphorelay has a unique stable
steady-state. Furthermore, we derive explicit functions relating stimulus to
the response in any layer of a phosphorelay and show that a limited degree of
ultrasensitivity (the ability to respond to changes in stimulus in a
switch-like manner) in the bottom layer of a phosphorelay is an intrinsic
feature which does not depend on any reaction rates or substrate amounts. On
the other hand, we show how adjusting reaction rates and substrate amounts may
lead to higher degrees of ultrasensitivity in intermediate layers. The explicit
formulas also enable us to prove how the response changes with alterations in
stimulus, kinetic parameters, and substrate amounts. Aside from providing
biological insight, the formulas may also be used to avoid time-consuming
simulations in numerical analyses and simulations.
| [
{
"created": "Fri, 23 Sep 2011 19:08:28 GMT",
"version": "v1"
}
] | 2011-09-26 | [
[
"Knudsen",
"Michael",
""
],
[
"Feliu",
"Elisenda",
""
],
[
"Wiuf",
"Carsten",
""
]
] | Phosphorelays are a class of signaling mechanisms used by cells to respond to changes in their environment. Phosphorelays (of which two-component systems constitute a special case) are particularly abundant in prokaryotes and have been shown to be involved in many fundamental processes such as stress response, osmotic regulation, virulence, and chemotaxis. We develop a general model of phosphorelays extending existing models of phosphorelays and two-component systems. We analyze the model analytically under the assumption of mass-action kinetics and prove that a phosphorelay has a unique stable steady-state. Furthermore, we derive explicit functions relating stimulus to the response in any layer of a phosphorelay and show that a limited degree of ultrasensitivity (the ability to respond to changes in stimulus in a switch-like manner) in the bottom layer of a phosphorelay is an intrinsic feature which does not depend on any reaction rates or substrate amounts. On the other hand, we show how adjusting reaction rates and substrate amounts may lead to higher degrees of ultrasensitivity in intermediate layers. The explicit formulas also enable us to prove how the response changes with alterations in stimulus, kinetic parameters, and substrate amounts. Aside from providing biological insight, the formulas may also be used to avoid time-consuming simulations in numerical analyses and simulations. |
1807.08686 | Anita Mehta | Anita Mehta | Storing and retrieving long-term memories: cooperation and competition
in synaptic dynamics | 34 pages, 7 figures | Advances in Physics: X, 3:1, 755-789, (2018) | 10.1080/23746149.2018.1480415 | null | q-bio.NC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We first review traditional approaches to memory storage and formation,
drawing on the literature of quantitative neuroscience as well as statistical
physics. These have generally focused on the fast dynamics of neurons; however,
there is now an increasing emphasis on the slow dynamics of synapses, whose
weight changes are held to be responsible for memory storage. An important
first step in this direction was taken in the context of Fusi's cascade model,
where complex synaptic architectures were invoked, in particular, to store
long-term memories. No explicit synaptic dynamics were, however, invoked in
that work. These were recently incorporated theoretically using the techniques
used in agent-based modelling, and subsequently, models of competing and
cooperating synapses were formulated. It was found that the key to the storage
of long-term memories lay in the competitive dynamics of synapses. In this
review, we focus on models of synaptic competition and cooperation, and look at
the outstanding challenges that remain.
| [
{
"created": "Mon, 23 Jul 2018 15:54:33 GMT",
"version": "v1"
}
] | 2018-07-24 | [
[
"Mehta",
"Anita",
""
]
] | We first review traditional approaches to memory storage and formation, drawing on the literature of quantitative neuroscience as well as statistical physics. These have generally focused on the fast dynamics of neurons; however, there is now an increasing emphasis on the slow dynamics of synapses, whose weight changes are held to be responsible for memory storage. An important first step in this direction was taken in the context of Fusi's cascade model, where complex synaptic architectures were invoked, in particular, to store long-term memories. No explicit synaptic dynamics were, however, invoked in that work. These were recently incorporated theoretically using the techniques used in agent-based modelling, and subsequently, models of competing and cooperating synapses were formulated. It was found that the key to the storage of long-term memories lay in the competitive dynamics of synapses. In this review, we focus on models of synaptic competition and cooperation, and look at the outstanding challenges that remain. |
2008.01237 | Haoyu Cheng | Haoyu Cheng, Gregory T Concepcion, Xiaowen Feng, Haowen Zhang and Heng
Li | Haplotype-resolved de novo assembly with phased assembly graphs | 11 pages, 3 figures, 3 tables | Nature Methods, 2021 | 10.1038/s41592-020-01056-5 | null | q-bio.GN q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Haplotype-resolved de novo assembly is the ultimate solution to the study of
sequence variations in a genome. However, existing algorithms either collapse
heterozygous alleles into one consensus copy or fail to cleanly separate the
haplotypes to produce high-quality phased assemblies. Here we describe hifiasm,
a new de novo assembler that takes advantage of long high-fidelity sequence
reads to faithfully represent the haplotype information in a phased assembly
graph. Unlike other graph-based assemblers that only aim to maintain the
contiguity of one haplotype, hifiasm strives to preserve the contiguity of all
haplotypes. This feature enables the development of a graph trio binning
algorithm that greatly advances over standard trio binning. On three human and
five non-human datasets, including California redwood with a $\sim$30-gigabase
hexaploid genome, we show that hifiasm frequently delivers better assemblies
than existing tools and consistently outperforms others on haplotype-resolved
assembly.
| [
{
"created": "Mon, 3 Aug 2020 23:10:44 GMT",
"version": "v1"
}
] | 2021-02-03 | [
[
"Cheng",
"Haoyu",
""
],
[
"Concepcion",
"Gregory T",
""
],
[
"Feng",
"Xiaowen",
""
],
[
"Zhang",
"Haowen",
""
],
[
"Li",
"Heng",
""
]
] | Haplotype-resolved de novo assembly is the ultimate solution to the study of sequence variations in a genome. However, existing algorithms either collapse heterozygous alleles into one consensus copy or fail to cleanly separate the haplotypes to produce high-quality phased assemblies. Here we describe hifiasm, a new de novo assembler that takes advantage of long high-fidelity sequence reads to faithfully represent the haplotype information in a phased assembly graph. Unlike other graph-based assemblers that only aim to maintain the contiguity of one haplotype, hifiasm strives to preserve the contiguity of all haplotypes. This feature enables the development of a graph trio binning algorithm that greatly advances over standard trio binning. On three human and five non-human datasets, including California redwood with a $\sim$30-gigabase hexaploid genome, we show that hifiasm frequently delivers better assemblies than existing tools and consistently outperforms others on haplotype-resolved assembly. |
0809.0391 | Masudul Haque | Alexey Mikaberidze, Masudul Haque | Survival benefits in mimicry: a quantitative framework | 9 pages, 7 figures | Journal of Theoretical Biology, Vol. 259, pages 462-468 (2009) | 10.1016/j.jtbi.2009.02.024 | null | q-bio.PE q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mimicry is a resemblance between species that benefits at least one of the
species. It is a ubiquitous evolutionary phenomenon particularly common among
prey species, in which case the advantage involves better protection from
predation. We formulate a mathematical description of mimicry among prey
species, to investigate benefits and disadvantages of mimicry. The basic setup
involves differential equations for quantities representing predator behavior,
namely, the probabilities for attacking prey at the next encounter. Using this
framework, we present new quantitative results, and also provide a unified
description of a significant fraction of the quantitative mimicry literature.
The new results include `temporary' mutualism between prey species, and an
optimal density at which the survival benefit is greatest for the mimic. The
formalism leads naturally to extensions in several directions, such as the
evolution of mimicry, the interplay of mimicry with population dynamics, etc.
We demonstrate this extensibility by presenting some explorations on
spatiotemporal pattern dynamics.
| [
{
"created": "Tue, 2 Sep 2008 10:19:34 GMT",
"version": "v1"
}
] | 2011-08-09 | [
[
"Mikaberidze",
"Alexey",
""
],
[
"Haque",
"Masudul",
""
]
] | Mimicry is a resemblance between species that benefits at least one of the species. It is a ubiquitous evolutionary phenomenon particularly common among prey species, in which case the advantage involves better protection from predation. We formulate a mathematical description of mimicry among prey species, to investigate benefits and disadvantages of mimicry. The basic setup involves differential equations for quantities representing predator behavior, namely, the probabilities for attacking prey at the next encounter. Using this framework, we present new quantitative results, and also provide a unified description of a significant fraction of the quantitative mimicry literature. The new results include `temporary' mutualism between prey species, and an optimal density at which the survival benefit is greatest for the mimic. The formalism leads naturally to extensions in several directions, such as the evolution of mimicry, the interplay of mimicry with population dynamics, etc. We demonstrate this extensibility by presenting some explorations on spatiotemporal pattern dynamics. |
1307.8407 | Ilya Zhbannikov | Ilya Y. Zhbannikov, Samuel S. Hunter, Matthew L. Settles and James A.
Foster | SlopMap: a software application tool for quick and flexible
identification of similar sequences using exact k-mer matching | null | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | With the advent of Next-Generation (NG) sequencing, it has become possible to
sequence an entire genome quickly and inexpensively. However, in some
experiments one only needs to extract and assembly a portion of the sequence
reads, for example when performing transcriptome studies, sequencing
mitochondrial genomes, or characterizing exomes. With the raw DNA-library of a
complete genome it would appear to be a trivial problem to identify reads of
interest. But it is not always easy to incorporate well-known tools such as
BLAST, BLAT, Bowtie, and SOAP directly into a bioinformatics pipelines before
the assembly stage, either due to in- compatibility with the assembler's file
inputs, or because it is desirable to incorporate information that must be
extracted separately. For example, in order to incorporate flowgrams from a
Roche 454 sequencer into the Newbler assembler it is necessary to first extract
them from the original SFF files. We present SlopMap, a bioinformatics software
utility which allows rapid identification similar to provided target sequences
from either Roche 454 or Illumnia DNA library. With a simple and intuitive
command- line interface along with file output formats compatible with assembly
programs, SlopMap can be directly embedded in biological data processing
pipeline without any additional programming work. In addition, SlopMap
preserves flowgram information needed for Roche 454 assembler.
| [
{
"created": "Wed, 31 Jul 2013 18:06:05 GMT",
"version": "v1"
}
] | 2013-08-01 | [
[
"Zhbannikov",
"Ilya Y.",
""
],
[
"Hunter",
"Samuel S.",
""
],
[
"Settles",
"Matthew L.",
""
],
[
"Foster",
"James A.",
""
]
] | With the advent of Next-Generation (NG) sequencing, it has become possible to sequence an entire genome quickly and inexpensively. However, in some experiments one only needs to extract and assembly a portion of the sequence reads, for example when performing transcriptome studies, sequencing mitochondrial genomes, or characterizing exomes. With the raw DNA-library of a complete genome it would appear to be a trivial problem to identify reads of interest. But it is not always easy to incorporate well-known tools such as BLAST, BLAT, Bowtie, and SOAP directly into a bioinformatics pipelines before the assembly stage, either due to in- compatibility with the assembler's file inputs, or because it is desirable to incorporate information that must be extracted separately. For example, in order to incorporate flowgrams from a Roche 454 sequencer into the Newbler assembler it is necessary to first extract them from the original SFF files. We present SlopMap, a bioinformatics software utility which allows rapid identification similar to provided target sequences from either Roche 454 or Illumnia DNA library. With a simple and intuitive command- line interface along with file output formats compatible with assembly programs, SlopMap can be directly embedded in biological data processing pipeline without any additional programming work. In addition, SlopMap preserves flowgram information needed for Roche 454 assembler. |
2212.11367 | Adam Tonks | Adam Tonks (1), Trevor Harris (2), Bo Li (1), William Brown (3),
Rebecca Smith (3) ((1) Department of Statistics, University of Illinois at
Urbana-Champaign, (2) Department of Statistics, Texas A&M University, (3)
Department of Pathobiology, University of Illinois at Urbana-Champaign) | Forecasting West Nile Virus with Graph Neural Networks: Harnessing
Spatial Dependence in Irregularly Sampled Geospatial Data | null | GeoHealth 8 (7), e2023GH000784 | 10.1029/2023GH000784 | null | q-bio.PE cs.LG q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Machine learning methods have seen increased application to geospatial
environmental problems, such as precipitation nowcasting, haze forecasting, and
crop yield prediction. However, many of the machine learning methods applied to
mosquito population and disease forecasting do not inherently take into account
the underlying spatial structure of the given data. In our work, we apply a
spatially aware graph neural network model consisting of GraphSAGE layers to
forecast the presence of West Nile virus in Illinois, to aid mosquito
surveillance and abatement efforts within the state. More generally, we show
that graph neural networks applied to irregularly sampled geospatial data can
exceed the performance of a range of baseline methods including logistic
regression, XGBoost, and fully-connected neural networks.
| [
{
"created": "Wed, 21 Dec 2022 21:08:45 GMT",
"version": "v1"
}
] | 2024-07-09 | [
[
"Tonks",
"Adam",
""
],
[
"Harris",
"Trevor",
""
],
[
"Li",
"Bo",
""
],
[
"Brown",
"William",
""
],
[
"Smith",
"Rebecca",
""
]
] | Machine learning methods have seen increased application to geospatial environmental problems, such as precipitation nowcasting, haze forecasting, and crop yield prediction. However, many of the machine learning methods applied to mosquito population and disease forecasting do not inherently take into account the underlying spatial structure of the given data. In our work, we apply a spatially aware graph neural network model consisting of GraphSAGE layers to forecast the presence of West Nile virus in Illinois, to aid mosquito surveillance and abatement efforts within the state. More generally, we show that graph neural networks applied to irregularly sampled geospatial data can exceed the performance of a range of baseline methods including logistic regression, XGBoost, and fully-connected neural networks. |
1105.0866 | Shivendra Tewari | Shivendra Tewari and Kaushik Majumdar | A Mathematical Model of Tripartite Synapse: Astrocyte Induced Synaptic
Plasticity | 42 pages, 14 figures, Journal of Biological Physics (to appear) | null | 10.1007/s10867-012-9267-7 | null | q-bio.NC math.DS q-bio.CB q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we present a biologically detailed mathematical model of
tripartite synapses, where astrocytes modulate short-term synaptic plasticity.
The model consists of a pre-synaptic bouton, a post-synaptic dendritic
spine-head, a synaptic cleft and a peri-synaptic astrocyte controlling Ca2+
dynamics inside the synaptic bouton. This in turn controls glutamate release
dynamics in the cleft. As a consequence of this, glutamate concentration in the
cleft has been modeled, in which glutamate reuptake by astrocytes has also been
incorporated. Finally, dendritic spine-head dynamics has been modeled. As an
application, this model clearly shows synaptic potentiation in the hippocampal
region, i.e., astrocyte Ca2+ mediates synaptic plasticity, which is in
conformity with the majority of the recent findings (Perea & Araque, 2007;
Henneberger et al., 2010; Navarrete et al., 2012).
| [
{
"created": "Wed, 4 May 2011 16:33:28 GMT",
"version": "v1"
},
{
"created": "Sat, 17 Dec 2011 16:43:50 GMT",
"version": "v2"
},
{
"created": "Mon, 12 Mar 2012 13:45:18 GMT",
"version": "v3"
}
] | 2012-06-05 | [
[
"Tewari",
"Shivendra",
""
],
[
"Majumdar",
"Kaushik",
""
]
] | In this paper we present a biologically detailed mathematical model of tripartite synapses, where astrocytes modulate short-term synaptic plasticity. The model consists of a pre-synaptic bouton, a post-synaptic dendritic spine-head, a synaptic cleft and a peri-synaptic astrocyte controlling Ca2+ dynamics inside the synaptic bouton. This in turn controls glutamate release dynamics in the cleft. As a consequence of this, glutamate concentration in the cleft has been modeled, in which glutamate reuptake by astrocytes has also been incorporated. Finally, dendritic spine-head dynamics has been modeled. As an application, this model clearly shows synaptic potentiation in the hippocampal region, i.e., astrocyte Ca2+ mediates synaptic plasticity, which is in conformity with the majority of the recent findings (Perea & Araque, 2007; Henneberger et al., 2010; Navarrete et al., 2012). |
1906.08317 | Jonathan Desponds | Jonathan Desponds, Massimo Vergassola and Aleksandra M. Walczak | Hunchback promoters can readout morphogenetic positional information in
less than a minute | null | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The first cell fate decisions in the developing fly embryo are made very
rapidly : hunchback genes decide in a few minutes whether a given nucleus
follows the anterior or the posterior developmental blueprint by reading out
the positional information encoded in the Bicoid morphogen. This developmental
system constitutes a prototypical instance of the broad spectrum of regulatory
decision processes that combine speed and accuracy. Traditional arguments based
on fixed-time sampling of Bicoid concentration indicate that an accurate
readout is not possible within the short times observed experimentally. This
raises the general issue of how speed-accuracy tradeoffs are achieved. Here, we
compare fixed-time sampling strategies to decisions made on-the-fly, which are
based on updating and comparing the likelihoods of being at an anterior or a
posterior location. We found that these more efficient schemes can complete
reliable cell fate decisions even within the very short embryological
timescales. We discuss the influence of promoter architectures on the mean
decision time and decision error rate and present concrete promoter
architectures that allow for the fast readout of the morphogen. Lastly, we
formulate explicit predictions for new experiments involving Bicoid mutants.
| [
{
"created": "Wed, 19 Jun 2019 19:20:11 GMT",
"version": "v1"
},
{
"created": "Fri, 21 Jun 2019 17:49:01 GMT",
"version": "v2"
}
] | 2019-06-24 | [
[
"Desponds",
"Jonathan",
""
],
[
"Vergassola",
"Massimo",
""
],
[
"Walczak",
"Aleksandra M.",
""
]
] | The first cell fate decisions in the developing fly embryo are made very rapidly : hunchback genes decide in a few minutes whether a given nucleus follows the anterior or the posterior developmental blueprint by reading out the positional information encoded in the Bicoid morphogen. This developmental system constitutes a prototypical instance of the broad spectrum of regulatory decision processes that combine speed and accuracy. Traditional arguments based on fixed-time sampling of Bicoid concentration indicate that an accurate readout is not possible within the short times observed experimentally. This raises the general issue of how speed-accuracy tradeoffs are achieved. Here, we compare fixed-time sampling strategies to decisions made on-the-fly, which are based on updating and comparing the likelihoods of being at an anterior or a posterior location. We found that these more efficient schemes can complete reliable cell fate decisions even within the very short embryological timescales. We discuss the influence of promoter architectures on the mean decision time and decision error rate and present concrete promoter architectures that allow for the fast readout of the morphogen. Lastly, we formulate explicit predictions for new experiments involving Bicoid mutants. |
1608.03047 | John Wentworth | Emma Wentworth and John Wentworth | Computational Limitations of First-Order Repressor Systems | null | null | null | null | q-bio.MN cs.SY math.DS q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Almost all current approaches for engineering modular logic components in
synthetic biology use first-order regulators, including most CRISPR/CAS, TAL,
zinc finger, and RNA interference systems. Many practitioners understand
intuitively that second and higher order binding is necessary for scalability,
and this is easy to show for single-input single-output systems. However, no
study to date has analysed whether a more complex system, utilizing e.g.
feedback or error correction, can produce scalable computation from first-order
regulators. We prove here that first order repressor systems cannot support
bistability. In the process, we introduce a function G to measure signal
quality in molecular systems, and we show that G always decreases in dynamic
feedback systems as well as static feed-forward logic cascades of first-order
repressors. As a result, first order repressors cannot build memory or signal
buffering elements. Finally, we suggest G as a potential new property for
characterization of standard biological parts.
| [
{
"created": "Wed, 10 Aug 2016 05:00:30 GMT",
"version": "v1"
}
] | 2016-08-11 | [
[
"Wentworth",
"Emma",
""
],
[
"Wentworth",
"John",
""
]
] | Almost all current approaches for engineering modular logic components in synthetic biology use first-order regulators, including most CRISPR/CAS, TAL, zinc finger, and RNA interference systems. Many practitioners understand intuitively that second and higher order binding is necessary for scalability, and this is easy to show for single-input single-output systems. However, no study to date has analysed whether a more complex system, utilizing e.g. feedback or error correction, can produce scalable computation from first-order regulators. We prove here that first order repressor systems cannot support bistability. In the process, we introduce a function G to measure signal quality in molecular systems, and we show that G always decreases in dynamic feedback systems as well as static feed-forward logic cascades of first-order repressors. As a result, first order repressors cannot build memory or signal buffering elements. Finally, we suggest G as a potential new property for characterization of standard biological parts. |
2010.00214 | Antoine Le Gall | B. Guilhas, J.C. Walter, J. Rech, G. David, N.-O. Walliser, J.
Palmeri, C. Mathieu-Demaziere, A. Parmeggiani, J.Y. Bouet, A. Le Gall, M.
Nollmann | ATP-driven separation of liquid phase condensates in bacteria | null | Molecular Cell, 2020, Pages 293-303.e4 | 10.1016/j.molcel.2020.06.034 | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Liquid-liquid phase separated (LLPS) states are key to compartmentalise
components in the absence of membranes, however it is unclear whether LLPS
condensates are actively and specifically organized in the sub-cellular space
and by which mechanisms. Here, we address this question by focusing on the
ParABS DNA segregation system, composed of a centromeric-like sequence (parS),
a DNA-binding protein (ParB) and a motor (ParA). We show that parS-ParB
associate to form nanometer-sized, round condensates. ParB molecules diffuse
rapidly within the nucleoid volume, but display confined motions when trapped
inside ParB condensates. Single ParB molecules are able to rapidly diffuse
between different condensates, and nucleation is strongly favoured by parS.
Notably, the ParA motor is required to prevent the fusion of ParB condensates.
These results describe a novel active mechanism that splits, segregates and
localises non-canonical LLPS condensates in the sub-cellular space.
| [
{
"created": "Thu, 1 Oct 2020 06:44:38 GMT",
"version": "v1"
}
] | 2020-10-02 | [
[
"Guilhas",
"B.",
""
],
[
"Walter",
"J. C.",
""
],
[
"Rech",
"J.",
""
],
[
"David",
"G.",
""
],
[
"Walliser",
"N. -O.",
""
],
[
"Palmeri",
"J.",
""
],
[
"Mathieu-Demaziere",
"C.",
""
],
[
"Parmeggiani",
"A.",
""
],
[
"Bouet",
"J. Y.",
""
],
[
"Gall",
"A. Le",
""
],
[
"Nollmann",
"M.",
""
]
] | Liquid-liquid phase separated (LLPS) states are key to compartmentalise components in the absence of membranes, however it is unclear whether LLPS condensates are actively and specifically organized in the sub-cellular space and by which mechanisms. Here, we address this question by focusing on the ParABS DNA segregation system, composed of a centromeric-like sequence (parS), a DNA-binding protein (ParB) and a motor (ParA). We show that parS-ParB associate to form nanometer-sized, round condensates. ParB molecules diffuse rapidly within the nucleoid volume, but display confined motions when trapped inside ParB condensates. Single ParB molecules are able to rapidly diffuse between different condensates, and nucleation is strongly favoured by parS. Notably, the ParA motor is required to prevent the fusion of ParB condensates. These results describe a novel active mechanism that splits, segregates and localises non-canonical LLPS condensates in the sub-cellular space. |
1310.4522 | Orjan Carlborg | Xia Shen, Simon Forsberg, Mats Pettersson, Zheya Sheng and Orjan
Carlborg | Natural CMT2 variation is associated with genome-wide methylation
changes and temperature adaptation | Rewrite to improve clarity of presentation. Results unchanged. 43 p,
3 main fig, 1 main table, 15 suppl fig, 2 suppl tables. Particular updates -
New title - More detailed abstract and introduction - Updated results section
for clarity and focus - Updated discussion connecting work to unpublished
work in other research groups - Corrected typos - Updated references and
acknowledgements | PLoS Genet 10(12): e1004842 | 10.1371/journal.pgen.1004842 | null | q-bio.PE q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A central problem when studying adaptation to a new environment is the
interplay between genetic variation and phenotypic plasticity. Arabidopsis
thaliana has colonized a wide range of habitats across the world and it is
therefore an attractive model for studying the genetic mechanisms underlying
environmental adaptation 4,5. Here, we used publicly available data from two
collections of A. thaliana accessions, covering the native range of the
species, to identify loci associated with differences in climates at the
sampling sites. To address the confounding between geographic location, climate
and population structure, a new genome-wide association analysis method was
developed that facilitates detection of potentially adaptive loci where the
alternative alleles display different tolerable climate ranges. Sixteen novel
such loci, many of which contained candidate genes with amino acid changes,
were found including a strong association between Chromomethylase 2 (CMT2) and
variability in seasonal temperatures. The reference allele dominated in areas
with less seasonal variability in temperature, and the alternative allele,
which disrupts genome-wide CHH-methylation, existed in both stable and variable
regions. Our results link natural variation in CMT2, and differential
genome-wide CHH methylation, to the distribution of A. thaliana accessions
across habitats with different seasonal temperature variability. They also
suggest a role for genetic regulation of epigenetic modifications in natural
adaptation, potentially through differential allelic plasticity, and illustrate
the importance of re-analyses of existing data using new analytical methods to
obtain a more complete understanding of the mechanisms contributing to
adaptation.
| [
{
"created": "Wed, 16 Oct 2013 21:27:07 GMT",
"version": "v1"
},
{
"created": "Thu, 9 Jan 2014 10:18:27 GMT",
"version": "v2"
}
] | 2014-12-22 | [
[
"Shen",
"Xia",
""
],
[
"Forsberg",
"Simon",
""
],
[
"Pettersson",
"Mats",
""
],
[
"Sheng",
"Zheya",
""
],
[
"Carlborg",
"Orjan",
""
]
] | A central problem when studying adaptation to a new environment is the interplay between genetic variation and phenotypic plasticity. Arabidopsis thaliana has colonized a wide range of habitats across the world and it is therefore an attractive model for studying the genetic mechanisms underlying environmental adaptation 4,5. Here, we used publicly available data from two collections of A. thaliana accessions, covering the native range of the species, to identify loci associated with differences in climates at the sampling sites. To address the confounding between geographic location, climate and population structure, a new genome-wide association analysis method was developed that facilitates detection of potentially adaptive loci where the alternative alleles display different tolerable climate ranges. Sixteen novel such loci, many of which contained candidate genes with amino acid changes, were found including a strong association between Chromomethylase 2 (CMT2) and variability in seasonal temperatures. The reference allele dominated in areas with less seasonal variability in temperature, and the alternative allele, which disrupts genome-wide CHH-methylation, existed in both stable and variable regions. Our results link natural variation in CMT2, and differential genome-wide CHH methylation, to the distribution of A. thaliana accessions across habitats with different seasonal temperature variability. They also suggest a role for genetic regulation of epigenetic modifications in natural adaptation, potentially through differential allelic plasticity, and illustrate the importance of re-analyses of existing data using new analytical methods to obtain a more complete understanding of the mechanisms contributing to adaptation. |
1310.6590 | Chuan-Chao Wang | Chuan-Chao Wang, Hui Li | Discovery of Phylogenetic Relevant Y-chromosome Variants in 1000 Genomes
Project Data | 11 pages, 14 figures | null | null | null | q-bio.PE q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Current Y chromosome research is limited in the poor resolution of Y
chromosome phylogenetic tree. Entirely sequenced Y chromosomes in numerous
human individuals have only recently become available by the advent of
next-generation sequencing technology. The 1000 Genomes Project has sequenced Y
chromosomes from more than 1000 males. Here, we analyzed 1000 Genomes Project Y
chromosome data of 1269 individuals and discovered about 25,000 phylogenetic
relevant SNPs. Those new markers are useful in the phylogeny of Y chromosome
and will lead to an increased phylogenetic resolution for many Y chromosome
studies.
| [
{
"created": "Thu, 24 Oct 2013 13:02:50 GMT",
"version": "v1"
}
] | 2013-10-25 | [
[
"Wang",
"Chuan-Chao",
""
],
[
"Li",
"Hui",
""
]
] | Current Y chromosome research is limited in the poor resolution of Y chromosome phylogenetic tree. Entirely sequenced Y chromosomes in numerous human individuals have only recently become available by the advent of next-generation sequencing technology. The 1000 Genomes Project has sequenced Y chromosomes from more than 1000 males. Here, we analyzed 1000 Genomes Project Y chromosome data of 1269 individuals and discovered about 25,000 phylogenetic relevant SNPs. Those new markers are useful in the phylogeny of Y chromosome and will lead to an increased phylogenetic resolution for many Y chromosome studies. |
2304.00148 | Samaila Jackson Yaga | S.J Yaga and F.W.O Saporu | A study of a deterministic model for meningitis epidemic | null | null | null | null | q-bio.PE stat.AP | http://creativecommons.org/licenses/by-nc-nd/4.0/ | A compartmental deterministic model that allows (1) immunity from two stages
of infection and carriage, and (2) disease induced death, is used in studying
the dynamics of meningitis epidemic process in a closed population. It allows
for difference in the transmission rate of infection to a susceptible by a
carrier and an infective. It is generalized to allow a proportion ({\phi}) of
those susceptibles infected to progress directly to infectives in stage I. Both
models are used in this study. The threshold conditions for the spread of
carrier and infectives in stage I are derived for the two models. Sensitivity
analysis is performed on the reproductive number derived from the next
generation matrix. The case-carrier ratio profile for various parameters and
threshold values are shown. So also are the graphs of the total number ever
infected as influenced by {\epsilon} and {\phi}. The infection transmission
rate (\b{eta}), the odds in favor of a carrier, over an infective, in
transmitting an infection to a susceptible ({\epsilon}) and the carrier
conversion rate ({\phi}) to an infective in stage I, are identified as key
parameters that should be subject of attention for any control intervention
strategy. The case-carrier ratio profiles provide evidence of a critical
case-carrier ratio attained before the number of reported cases grows to an
epidemic level. They also provide visual evidence of epidemiological context,
in this case, epidemic incidence (in later part of dry season) and endemic
incidence (during rainy season). Results from total proportion ever infected
suggest that the model, in which {\phi}=0 obtained, can adequately represent,
in essence, the generalized model for this study.
| [
{
"created": "Fri, 31 Mar 2023 21:54:48 GMT",
"version": "v1"
}
] | 2023-04-04 | [
[
"Yaga",
"S. J",
""
],
[
"Saporu",
"F. W. O",
""
]
] | A compartmental deterministic model that allows (1) immunity from two stages of infection and carriage, and (2) disease induced death, is used in studying the dynamics of meningitis epidemic process in a closed population. It allows for difference in the transmission rate of infection to a susceptible by a carrier and an infective. It is generalized to allow a proportion ({\phi}) of those susceptibles infected to progress directly to infectives in stage I. Both models are used in this study. The threshold conditions for the spread of carrier and infectives in stage I are derived for the two models. Sensitivity analysis is performed on the reproductive number derived from the next generation matrix. The case-carrier ratio profile for various parameters and threshold values are shown. So also are the graphs of the total number ever infected as influenced by {\epsilon} and {\phi}. The infection transmission rate (\b{eta}), the odds in favor of a carrier, over an infective, in transmitting an infection to a susceptible ({\epsilon}) and the carrier conversion rate ({\phi}) to an infective in stage I, are identified as key parameters that should be subject of attention for any control intervention strategy. The case-carrier ratio profiles provide evidence of a critical case-carrier ratio attained before the number of reported cases grows to an epidemic level. They also provide visual evidence of epidemiological context, in this case, epidemic incidence (in later part of dry season) and endemic incidence (during rainy season). Results from total proportion ever infected suggest that the model, in which {\phi}=0 obtained, can adequately represent, in essence, the generalized model for this study. |
2107.01670 | Emil Iftekhar | Emil Nafis Iftekhar, Viola Priesemann, Rudi Balling, Simon Bauer,
Philippe Beutels, Andr\'e Calero Valdez, Sarah Cuschieri, Thomas Czypionka,
Uga Dumpis, Enrico Glaab, Eva Grill, Claudia Hanson, Pirta Hotulainen, Peter
Klimek, Mirjam Kretzschmar, Tyll Kr\"uger, Jenny Krutzinna, Nicola Low,
Helena Machado, Carlos Martins, Martin McKee, Sebastian Bernd Mohr, Armin
Nassehi, Matja\v{z} Perc, Elena Petelos, Martyn Pickersgill, Barbara
Prainsack, Joacim Rockl\"ov, Eva Schernhammer, Anthony Staines, Ewa Szczurek,
Sotirios Tsiodras, Steven Van Gucht, Peter Willeit | A look into the future of the COVID-19 pandemic in Europe: an expert
consultation | Manuscript is accepted by The Lancet Regional Health - Europe as a
Viewpoint article. Supplementary material can be accessed here:
https://owncloud.gwdg.de/index.php/f/1439962756 | Lancet Reg. Health Eur. 8, 100185 (2021) | 10.1016/j.lanepe.2021.100185 | null | q-bio.OT | http://creativecommons.org/licenses/by/4.0/ | How will the coronavirus disease 2019 (COVID-19) pandemic develop in the
coming months and years? Based on an expert survey, we examine key aspects that
are likely to influence COVID-19 in Europe. The future challenges and
developments will strongly depend on the progress of national and global
vaccination programs, the emergence and spread of variants of concern, and
public responses to nonpharmaceutical interventions (NPIs). In the short term,
many people are still unvaccinated, VOCs continue to emerge and spread, and
mobility and population mixing is expected to increase over the summer.
Therefore, policies that lift restrictions too much and too early risk another
damaging wave. This challenge remains despite the reduced opportunities for
transmission due to vaccination progress and reduced indoor mixing in the
summer. In autumn 2021, increased indoor activity might accelerate the spread
again, but a necessary reintroduction of NPIs might be too slow. The incidence
may strongly rise again, possibly filling intensive care units, if vaccination
levels are not high enough. A moderate, adaptive level of NPIs will thus remain
necessary. These epidemiological aspects are put into perspective with the
economic, social, and health-related consequences and thereby provide a
holistic perspective on the future of COVID-19.
| [
{
"created": "Sun, 4 Jul 2021 15:55:34 GMT",
"version": "v1"
},
{
"created": "Fri, 23 Jul 2021 09:57:38 GMT",
"version": "v2"
}
] | 2021-10-04 | [
[
"Iftekhar",
"Emil Nafis",
""
],
[
"Priesemann",
"Viola",
""
],
[
"Balling",
"Rudi",
""
],
[
"Bauer",
"Simon",
""
],
[
"Beutels",
"Philippe",
""
],
[
"Valdez",
"André Calero",
""
],
[
"Cuschieri",
"Sarah",
""
],
[
"Czypionka",
"Thomas",
""
],
[
"Dumpis",
"Uga",
""
],
[
"Glaab",
"Enrico",
""
],
[
"Grill",
"Eva",
""
],
[
"Hanson",
"Claudia",
""
],
[
"Hotulainen",
"Pirta",
""
],
[
"Klimek",
"Peter",
""
],
[
"Kretzschmar",
"Mirjam",
""
],
[
"Krüger",
"Tyll",
""
],
[
"Krutzinna",
"Jenny",
""
],
[
"Low",
"Nicola",
""
],
[
"Machado",
"Helena",
""
],
[
"Martins",
"Carlos",
""
],
[
"McKee",
"Martin",
""
],
[
"Mohr",
"Sebastian Bernd",
""
],
[
"Nassehi",
"Armin",
""
],
[
"Perc",
"Matjaž",
""
],
[
"Petelos",
"Elena",
""
],
[
"Pickersgill",
"Martyn",
""
],
[
"Prainsack",
"Barbara",
""
],
[
"Rocklöv",
"Joacim",
""
],
[
"Schernhammer",
"Eva",
""
],
[
"Staines",
"Anthony",
""
],
[
"Szczurek",
"Ewa",
""
],
[
"Tsiodras",
"Sotirios",
""
],
[
"Van Gucht",
"Steven",
""
],
[
"Willeit",
"Peter",
""
]
] | How will the coronavirus disease 2019 (COVID-19) pandemic develop in the coming months and years? Based on an expert survey, we examine key aspects that are likely to influence COVID-19 in Europe. The future challenges and developments will strongly depend on the progress of national and global vaccination programs, the emergence and spread of variants of concern, and public responses to nonpharmaceutical interventions (NPIs). In the short term, many people are still unvaccinated, VOCs continue to emerge and spread, and mobility and population mixing is expected to increase over the summer. Therefore, policies that lift restrictions too much and too early risk another damaging wave. This challenge remains despite the reduced opportunities for transmission due to vaccination progress and reduced indoor mixing in the summer. In autumn 2021, increased indoor activity might accelerate the spread again, but a necessary reintroduction of NPIs might be too slow. The incidence may strongly rise again, possibly filling intensive care units, if vaccination levels are not high enough. A moderate, adaptive level of NPIs will thus remain necessary. These epidemiological aspects are put into perspective with the economic, social, and health-related consequences and thereby provide a holistic perspective on the future of COVID-19. |
1302.0395 | Vitaly Vodyanoy | T. Moore, I. Sorokulova, O. Pustovyy, L. Globa, D. Pascoe, M. Rudisill
and Vitaly Vodyanoy | Microscopic and thermodynamic evaluation of vesicles shed by
erythrocytes at elevated temperatures | 18 pages, 7 figures, Submitted to the Journal of Thermal Biology on
January 25, 2013 | null | null | null | q-bio.TO physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Erythrocytes and vesicles shed by erythrocytes from human and rat blood were
collected and analyzed after temperature was elevated by physical exercise or
by exposure to external heat. The images of erythrocytes and vesicles were
analyzed by the light microscopy system with spatial resolution of better than
90 nm. The samples were observed in an aqueous environment and required no
freezing, dehydration, staining, shadowing, marking or any other manipulation.
Temperature elevation, whether passive or through exercise, resulted in
significant concentration increase of structurally transformed erythrocytes
(echinocytes) and vesicles in blood. At temperature of 37 oC, mean vesicle
concentrations and diameters in human and rat blood were (1.50+-0.35)x10^6 and
(1.4+-0.2)x10^6 vesicles/{\mu}L, and 0.365+-0.065 and 0.436+-0.03 {\mu}m,
respectively. It was estimated that 80% of all vesicles found in human blood
are smaller than 0.4 {\mu}m. Thermodynamic analysis of experimental and
literature data showed that erythrocyte transformation, vesicle release and
other associated processes are driven by entropy with enthalpy-entropy
compensation. It is suggested that physical state of hydrated cell membrane is
responsible for the compensation. The increase of vesicle number related to
elevated temperatures may be indicative of the heat stress level and serve as
diagnostic of erythrocyte stability and human performance.
| [
{
"created": "Sat, 2 Feb 2013 15:58:44 GMT",
"version": "v1"
},
{
"created": "Tue, 5 Feb 2013 16:13:31 GMT",
"version": "v2"
}
] | 2013-02-06 | [
[
"Moore",
"T.",
""
],
[
"Sorokulova",
"I.",
""
],
[
"Pustovyy",
"O.",
""
],
[
"Globa",
"L.",
""
],
[
"Pascoe",
"D.",
""
],
[
"Rudisill",
"M.",
""
],
[
"Vodyanoy",
"Vitaly",
""
]
] | Erythrocytes and vesicles shed by erythrocytes from human and rat blood were collected and analyzed after temperature was elevated by physical exercise or by exposure to external heat. The images of erythrocytes and vesicles were analyzed by the light microscopy system with spatial resolution of better than 90 nm. The samples were observed in an aqueous environment and required no freezing, dehydration, staining, shadowing, marking or any other manipulation. Temperature elevation, whether passive or through exercise, resulted in significant concentration increase of structurally transformed erythrocytes (echinocytes) and vesicles in blood. At temperature of 37 oC, mean vesicle concentrations and diameters in human and rat blood were (1.50+-0.35)x10^6 and (1.4+-0.2)x10^6 vesicles/{\mu}L, and 0.365+-0.065 and 0.436+-0.03 {\mu}m, respectively. It was estimated that 80% of all vesicles found in human blood are smaller than 0.4 {\mu}m. Thermodynamic analysis of experimental and literature data showed that erythrocyte transformation, vesicle release and other associated processes are driven by entropy with enthalpy-entropy compensation. It is suggested that physical state of hydrated cell membrane is responsible for the compensation. The increase of vesicle number related to elevated temperatures may be indicative of the heat stress level and serve as diagnostic of erythrocyte stability and human performance. |
2403.05762 | Xinyu Yu | Hongguang Pan and Xinyu Yu and Yong Yang | Lateral Control of Brain-Controlled Vehicle Based on SVM Probability
Output Model | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The non-stationary characteristics of EEG signal and the individual
differences of brain-computer interfaces (BCIs) lead to poor performance in the
control process of the brain-controlled vehicles (BCVs). In this paper, by
combining steady-state visual evoked potential (SSVEP) interactive interface,
brain instructions generation module and vehicle lateral control module, a
probabilistic output model based on support vector machine (SVM) is proposed
for BCV lateral control to improve the driving performance. Firstly, a filter
bank common spatial pattern (FBCSP) algorithm is introduced into the brain
instructions generation module, which can improve the off-line decoding
performance. Secondly, a sigmod-fitting SVM (SF-SVM) is trained based on the
sigmod-fitting method and the lateral control module is developed, which can
produce all commands in the form of probability instead of specific single
command. Finally, a pre-experiment and two road-keeping experiments are
conducted. In the pre-experiment, the experiment results show that, the average
highest off-line accuracy among subjects is 95.64\%, while for those in the
online stage, the average accuracy is only 84.44\%. In the road-keeping
experiments, the task completion rate in the two designed scenes increased by
25.6\% and 20\%, respectively.
| [
{
"created": "Sat, 9 Mar 2024 02:15:06 GMT",
"version": "v1"
}
] | 2024-03-12 | [
[
"Pan",
"Hongguang",
""
],
[
"Yu",
"Xinyu",
""
],
[
"Yang",
"Yong",
""
]
] | The non-stationary characteristics of EEG signal and the individual differences of brain-computer interfaces (BCIs) lead to poor performance in the control process of the brain-controlled vehicles (BCVs). In this paper, by combining steady-state visual evoked potential (SSVEP) interactive interface, brain instructions generation module and vehicle lateral control module, a probabilistic output model based on support vector machine (SVM) is proposed for BCV lateral control to improve the driving performance. Firstly, a filter bank common spatial pattern (FBCSP) algorithm is introduced into the brain instructions generation module, which can improve the off-line decoding performance. Secondly, a sigmod-fitting SVM (SF-SVM) is trained based on the sigmod-fitting method and the lateral control module is developed, which can produce all commands in the form of probability instead of specific single command. Finally, a pre-experiment and two road-keeping experiments are conducted. In the pre-experiment, the experiment results show that, the average highest off-line accuracy among subjects is 95.64\%, while for those in the online stage, the average accuracy is only 84.44\%. In the road-keeping experiments, the task completion rate in the two designed scenes increased by 25.6\% and 20\%, respectively. |
q-bio/0505053 | Christophe Pouzat | Matthieu Delescluse (LPC), Christophe Pouzat (LPC) | Efficient spike-sorting of multi-state neurons using inter-spike
intervals information | 25 pages, to be published in Journal of Neurocience Methods | null | null | null | q-bio.QM math.ST physics.bio-ph physics.data-an stat.TH | null | We demonstrate the efficacy of a new spike-sorting method based on a Markov
Chain Monte Carlo (MCMC) algorithm by applying it to real data recorded from
Purkinje cells (PCs) in young rat cerebellar slices. This algorithm is unique
in its capability to estimate and make use of the firing statistics as well as
the spike amplitude dynamics of the recorded neurons. PCs exhibit multiple
discharge states, giving rise to multimodal interspike interval (ISI)
histograms and to correlations between successive ISIs. The amplitude of the
spikes generated by a PC in an "active" state decreases, a feature typical of
many neurons from both vertebrates and invertebrates. These two features
constitute a major and recurrent problem for all the presently available
spike-sorting methods. We first show that a Hidden Markov Model with 3
log-Normal states provides a flexible and satisfying description of the complex
firing of single PCs. We then incorporate this model into our previous MCMC
based spike-sorting algorithm (Pouzat et al, 2004, J. Neurophys. 91, 2910-2928)
and test this new algorithm on multi-unit recordings of bursting PCs. We show
that our method successfully classifies the bursty spike trains fired by PCs by
using an independent single unit recording from a patch-clamp pipette.
| [
{
"created": "Fri, 27 May 2005 11:53:44 GMT",
"version": "v1"
}
] | 2011-11-10 | [
[
"Delescluse",
"Matthieu",
"",
"LPC"
],
[
"Pouzat",
"Christophe",
"",
"LPC"
]
] | We demonstrate the efficacy of a new spike-sorting method based on a Markov Chain Monte Carlo (MCMC) algorithm by applying it to real data recorded from Purkinje cells (PCs) in young rat cerebellar slices. This algorithm is unique in its capability to estimate and make use of the firing statistics as well as the spike amplitude dynamics of the recorded neurons. PCs exhibit multiple discharge states, giving rise to multimodal interspike interval (ISI) histograms and to correlations between successive ISIs. The amplitude of the spikes generated by a PC in an "active" state decreases, a feature typical of many neurons from both vertebrates and invertebrates. These two features constitute a major and recurrent problem for all the presently available spike-sorting methods. We first show that a Hidden Markov Model with 3 log-Normal states provides a flexible and satisfying description of the complex firing of single PCs. We then incorporate this model into our previous MCMC based spike-sorting algorithm (Pouzat et al, 2004, J. Neurophys. 91, 2910-2928) and test this new algorithm on multi-unit recordings of bursting PCs. We show that our method successfully classifies the bursty spike trains fired by PCs by using an independent single unit recording from a patch-clamp pipette. |
1711.09113 | Michael Deem | Melia E. Bonomo and Michael W. Deem | How the other half lives: CRISPR-Cas's influence on bacteriophages | 24 pages, 8 figures | Evolutionary Biology : Self, Non-Self Evolution, Species and
Complex Traits, Evolution, Methods and Concepts, ISBN 978-3-319-61569-1,
edited by Pierre Pontarotti, Springer Nature, September 2017, pp. 63-85 | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | CRISPR-Cas is a genetic adaptive immune system unique to prokaryotic cells
used to combat phage and plasmid threats. The host cell adapts by incorporating
DNA sequences from invading phages or plasmids into its CRISPR locus as
spacers. These spacers are expressed as mobile surveillance RNAs that direct
CRISPR-associated (Cas) proteins to protect against subsequent attack by the
same phages or plasmids. The threat from mobile genetic elements inevitably
shapes the CRISPR loci of archaea and bacteria, and simultaneously the
CRISPR-Cas immune system drives evolution of these invaders. Here we highlight
our recent work, as well as that of others, that seeks to understand phage
mechanisms of CRISPR-Cas evasion and conditions for population coexistence of
phages with CRISPR-protected prokaryotes.
| [
{
"created": "Fri, 24 Nov 2017 19:29:35 GMT",
"version": "v1"
}
] | 2017-11-28 | [
[
"Bonomo",
"Melia E.",
""
],
[
"Deem",
"Michael W.",
""
]
] | CRISPR-Cas is a genetic adaptive immune system unique to prokaryotic cells used to combat phage and plasmid threats. The host cell adapts by incorporating DNA sequences from invading phages or plasmids into its CRISPR locus as spacers. These spacers are expressed as mobile surveillance RNAs that direct CRISPR-associated (Cas) proteins to protect against subsequent attack by the same phages or plasmids. The threat from mobile genetic elements inevitably shapes the CRISPR loci of archaea and bacteria, and simultaneously the CRISPR-Cas immune system drives evolution of these invaders. Here we highlight our recent work, as well as that of others, that seeks to understand phage mechanisms of CRISPR-Cas evasion and conditions for population coexistence of phages with CRISPR-protected prokaryotes. |
2211.09005 | Florian Nill | Florian Nill | Endemic Oscillations for SARS-CoV-2 Omicron -- A SIRS model analysis | 19 pages, 9 figures | Chaos, Solitons and Fractals 173 (2023) 113678 | 10.1016/j.chaos.2023.113678 | null | q-bio.PE math.DS physics.soc-ph | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The SIRS model with constant vaccination and immunity waning rates is well
known to show a transition from a disease-free to an endemic equilibrium as the
basic reproduction number $r_0$ is raised above threshold. It is shown that
this model maps to Hethcote's classic endemic model originally published in
1973. In this way one obtains unifying formulas for a whole class of models
showing endemic bifurcation. In particular, if the vaccination rate is smaller
than the recovery rate and $r_- < r_0 < r_+$ for certain upper and lower bounds
$r_\pm$, then trajectories spiral into the endemic equilibrium via damped
infection waves. Latest data of the SARS-CoV-2 Omicron variant suggest that
according to this simplified model continuous vaccination programs will not be
capable to escape the oscillating endemic phase. However, in view of the strong
damping factors predicted by the model, in reality these oscillations will
certainly be overruled by time-dependent contact behaviors.
| [
{
"created": "Wed, 16 Nov 2022 16:02:04 GMT",
"version": "v1"
},
{
"created": "Tue, 30 May 2023 08:58:07 GMT",
"version": "v2"
}
] | 2023-06-26 | [
[
"Nill",
"Florian",
""
]
] | The SIRS model with constant vaccination and immunity waning rates is well known to show a transition from a disease-free to an endemic equilibrium as the basic reproduction number $r_0$ is raised above threshold. It is shown that this model maps to Hethcote's classic endemic model originally published in 1973. In this way one obtains unifying formulas for a whole class of models showing endemic bifurcation. In particular, if the vaccination rate is smaller than the recovery rate and $r_- < r_0 < r_+$ for certain upper and lower bounds $r_\pm$, then trajectories spiral into the endemic equilibrium via damped infection waves. Latest data of the SARS-CoV-2 Omicron variant suggest that according to this simplified model continuous vaccination programs will not be capable to escape the oscillating endemic phase. However, in view of the strong damping factors predicted by the model, in reality these oscillations will certainly be overruled by time-dependent contact behaviors. |
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