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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1212.1909
|
Luay Nakhleh
|
Yun Yu and Luay Nakhleh
|
Fast Algorithms for Reconciliation under Hybridization and Incomplete
Lineage Sorting
| null | null | null | null |
q-bio.PE cs.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Reconciling a gene tree with a species tree is an important task that reveals
much about the evolution of genes, genomes, and species, as well as about the
molecular function of genes. A wide array of computational tools have been
devised for this task under certain evolutionary events such as hybridization,
gene duplication/loss, or incomplete lineage sorting. Work on reconciling gene
tree with species phylogenies under two or more of these events have also begun
to emerge. Our group recently devised both parsimony and probabilistic
frameworks for reconciling a gene tree with a phylogenetic network, thus
allowing for the detection of hybridization in the presence of incomplete
lineage sorting. While the frameworks were general and could handle any
topology, they are computationally intensive, rendering their application to
large datasets infeasible. In this paper, we present two novel approaches to
address the computational challenges of the two frameworks that are based on
the concept of ancestral configurations. Our approaches still compute exact
solutions while improving the computational time by up to five orders of
magnitude. These substantial gains in speed scale the applicability of these
unified reconciliation frameworks to much larger data sets. We discuss how the
topological features of the gene tree and phylogenetic network may affect the
performance of the new algorithms. We have implemented the algorithms in our
PhyloNet software package, which is publicly available in open source.
|
[
{
"created": "Sun, 9 Dec 2012 18:12:55 GMT",
"version": "v1"
}
] |
2012-12-11
|
[
[
"Yu",
"Yun",
""
],
[
"Nakhleh",
"Luay",
""
]
] |
Reconciling a gene tree with a species tree is an important task that reveals much about the evolution of genes, genomes, and species, as well as about the molecular function of genes. A wide array of computational tools have been devised for this task under certain evolutionary events such as hybridization, gene duplication/loss, or incomplete lineage sorting. Work on reconciling gene tree with species phylogenies under two or more of these events have also begun to emerge. Our group recently devised both parsimony and probabilistic frameworks for reconciling a gene tree with a phylogenetic network, thus allowing for the detection of hybridization in the presence of incomplete lineage sorting. While the frameworks were general and could handle any topology, they are computationally intensive, rendering their application to large datasets infeasible. In this paper, we present two novel approaches to address the computational challenges of the two frameworks that are based on the concept of ancestral configurations. Our approaches still compute exact solutions while improving the computational time by up to five orders of magnitude. These substantial gains in speed scale the applicability of these unified reconciliation frameworks to much larger data sets. We discuss how the topological features of the gene tree and phylogenetic network may affect the performance of the new algorithms. We have implemented the algorithms in our PhyloNet software package, which is publicly available in open source.
|
2405.04550
|
Cole Gawin
|
Cole Gawin
|
Exploring a Cognitive Architecture for Learning Arithmetic Equations
|
16 pages, 6 figures, 2 tables
| null | null | null |
q-bio.NC cs.AI
|
http://creativecommons.org/licenses/by/4.0/
|
The acquisition and performance of arithmetic skills and basic operations
such as addition, subtraction, multiplication, and division are essential for
daily functioning, and reflect complex cognitive processes. This paper explores
the cognitive mechanisms powering arithmetic learning, presenting a
neurobiologically plausible cognitive architecture that simulates the
acquisition of these skills. I implement a number vectorization embedding
network and an associative memory model to investigate how an intelligent
system can learn and recall arithmetic equations in a manner analogous to the
human brain. I perform experiments that provide insights into the
generalization capabilities of connectionist models, neurological causes of
dyscalculia, and the influence of network architecture on cognitive
performance. Through this interdisciplinary investigation, I aim to contribute
to ongoing research into the neural correlates of mathematical cognition in
intelligent systems.
|
[
{
"created": "Sun, 5 May 2024 18:42:00 GMT",
"version": "v1"
}
] |
2024-05-09
|
[
[
"Gawin",
"Cole",
""
]
] |
The acquisition and performance of arithmetic skills and basic operations such as addition, subtraction, multiplication, and division are essential for daily functioning, and reflect complex cognitive processes. This paper explores the cognitive mechanisms powering arithmetic learning, presenting a neurobiologically plausible cognitive architecture that simulates the acquisition of these skills. I implement a number vectorization embedding network and an associative memory model to investigate how an intelligent system can learn and recall arithmetic equations in a manner analogous to the human brain. I perform experiments that provide insights into the generalization capabilities of connectionist models, neurological causes of dyscalculia, and the influence of network architecture on cognitive performance. Through this interdisciplinary investigation, I aim to contribute to ongoing research into the neural correlates of mathematical cognition in intelligent systems.
|
q-bio/0609033
|
Deok-Sun Lee
|
Deok-Sun Lee, Heiko Rieger
|
Comparative study of the transcriptional regulatory networks of E. coli
and yeast: Structural characteristics leading to marginal dynamic stability
|
7 pages, 5 figures
| null | null | null |
q-bio.MN
| null |
Dynamical properties of the transcriptional regulatory network of {\it
Escherichia coli} and {\it Saccharomyces cerevisiae} are studied within the
framework of random Boolean functions. The dynamical response of these networks
to a single point mutation is characterized by the number of mutated elements
as a function of time and the distribution of the relaxation time to a new
stationary state, which turn out to be different in both networks. Comparison
with the behavior of randomized networks reveals relevant structural
characteristics other than the mean connectivity, namely the organization of
circuits and the functional form of the in-degree distribution. The abundance
of single-element circuits in {\it E. coli} and the power-law in-degree
distribution of {\it S. cerevisiae} shift their dynamics towards marginal
stability overcoming the restrictions imposed by their mean connectivities,
which is argued to be related to the simultaneous presence of robustness and
adaptivity in living organisms.
|
[
{
"created": "Fri, 22 Sep 2006 20:09:44 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Lee",
"Deok-Sun",
""
],
[
"Rieger",
"Heiko",
""
]
] |
Dynamical properties of the transcriptional regulatory network of {\it Escherichia coli} and {\it Saccharomyces cerevisiae} are studied within the framework of random Boolean functions. The dynamical response of these networks to a single point mutation is characterized by the number of mutated elements as a function of time and the distribution of the relaxation time to a new stationary state, which turn out to be different in both networks. Comparison with the behavior of randomized networks reveals relevant structural characteristics other than the mean connectivity, namely the organization of circuits and the functional form of the in-degree distribution. The abundance of single-element circuits in {\it E. coli} and the power-law in-degree distribution of {\it S. cerevisiae} shift their dynamics towards marginal stability overcoming the restrictions imposed by their mean connectivities, which is argued to be related to the simultaneous presence of robustness and adaptivity in living organisms.
|
q-bio/0602002
|
Thilo Gross
|
Ralf Steuer, Thilo Gross, Joachim Selbig and Bernd Blasius
|
Structural Kinetic Modeling of Metabolic Networks
|
14 pages, 8 figures (color)
|
PNAS 103(32), 11868-11873, 2006.
|
10.1073/pnas.0600013103
| null |
q-bio.MN q-bio.CB
| null |
To develop and investigate detailed mathematical models of cellular metabolic
processes is one of the primary challenges in systems biology. However, despite
considerable advance in the topological analysis of metabolic networks,
explicit kinetic modeling based on differential equations is still often
severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and
their associated parameter values. Here we propose a method that aims to give a
detailed and quantitative account of the dynamical capabilities of metabolic
systems, without requiring any explicit information about the particular
functional form of the rate equations. Our approach is based on constructing a
local linear model at each point in parameter space, such that each element of
the model is either directly experimentally accessible, or amenable to a
straightforward biochemical interpretation. This ensemble of local linear
models, encompassing all possible explicit kinetic models, then allows for a
systematic statistical exploration of the comprehensive parameter space. The
method is applied to two paradigmatic examples: The glycolytic pathway of yeast
and a realistic-scale representation of the photosynthetic Calvin cycle.
|
[
{
"created": "Wed, 1 Feb 2006 08:59:17 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Steuer",
"Ralf",
""
],
[
"Gross",
"Thilo",
""
],
[
"Selbig",
"Joachim",
""
],
[
"Blasius",
"Bernd",
""
]
] |
To develop and investigate detailed mathematical models of cellular metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, explicit kinetic modeling based on differential equations is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a detailed and quantitative account of the dynamical capabilities of metabolic systems, without requiring any explicit information about the particular functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible, or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a systematic statistical exploration of the comprehensive parameter space. The method is applied to two paradigmatic examples: The glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.
|
2302.09217
|
Yunyi Shen
|
Hongliang Bu and Yunyi Shen
|
Identify local limiting factors of species distribution using min-linear
logistic regression
| null | null | null | null |
q-bio.QM stat.AP
|
http://creativecommons.org/licenses/by-sa/4.0/
|
Logistic regression is a commonly used building block in ecological modeling,
but its additive structure among environmental predictors often assumes
compensatory relationships between predictors, which can lead to problematic
results. In reality, the distribution of species is often determined by the
least-favored factor, according to von Liebig's Law of the Minimum, which is
not addressed in modeling. To address this issue, we introduced the min-linear
logistic regression model, which has a built-in minimum structure of competing
factors. In our empirical analysis of the distribution of Asiatic black bears
($\textit{Ursus thibetanus}$), we found that the min-linear model performs well
compared to other methods and has several advantages. By using the model, we
were able to identify ecologically meaningful limiting factors on bear
distribution across the survey area. The model's inherent simplicity and
interpretability make it a promising tool for extending into other widely used
ecological models.
|
[
{
"created": "Sat, 18 Feb 2023 02:55:28 GMT",
"version": "v1"
}
] |
2023-02-21
|
[
[
"Bu",
"Hongliang",
""
],
[
"Shen",
"Yunyi",
""
]
] |
Logistic regression is a commonly used building block in ecological modeling, but its additive structure among environmental predictors often assumes compensatory relationships between predictors, which can lead to problematic results. In reality, the distribution of species is often determined by the least-favored factor, according to von Liebig's Law of the Minimum, which is not addressed in modeling. To address this issue, we introduced the min-linear logistic regression model, which has a built-in minimum structure of competing factors. In our empirical analysis of the distribution of Asiatic black bears ($\textit{Ursus thibetanus}$), we found that the min-linear model performs well compared to other methods and has several advantages. By using the model, we were able to identify ecologically meaningful limiting factors on bear distribution across the survey area. The model's inherent simplicity and interpretability make it a promising tool for extending into other widely used ecological models.
|
2104.09188
|
Claudius Gros
|
Claudius Gros
|
A devil's advocate view on 'self-organized' brain criticality
| null |
Journal of Physics: Complexity 2, 031001 (2021)
|
10.1088/2632-072X/abfa0f
| null |
q-bio.NC nlin.AO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Stationarity of the constituents of the body and of its functionalities is a
basic requirement for life, being equivalent to survival in first place.
Assuming that the resting state activity of the brain serves essential
functionalities, stationarity entails that the dynamics of the brain needs to
be regulated on a time-averaged basis. The combination of recurrent and driving
external inputs must therefore lead to a non-trivial stationary neural
activity, a condition which is fulfilled for afferent signals of varying
strengths only close to criticality. In this view, the benefits of working
vicinity of a second-order phase transition, such as signal enhancements, are
not the underlying evolutionary drivers, but side effects of the requirement to
keep the brain functional in first place. It is hence more appropriate to use
the term 'self-regulated' in this context, instead of 'self-organized'.
|
[
{
"created": "Mon, 19 Apr 2021 10:21:53 GMT",
"version": "v1"
}
] |
2021-05-14
|
[
[
"Gros",
"Claudius",
""
]
] |
Stationarity of the constituents of the body and of its functionalities is a basic requirement for life, being equivalent to survival in first place. Assuming that the resting state activity of the brain serves essential functionalities, stationarity entails that the dynamics of the brain needs to be regulated on a time-averaged basis. The combination of recurrent and driving external inputs must therefore lead to a non-trivial stationary neural activity, a condition which is fulfilled for afferent signals of varying strengths only close to criticality. In this view, the benefits of working vicinity of a second-order phase transition, such as signal enhancements, are not the underlying evolutionary drivers, but side effects of the requirement to keep the brain functional in first place. It is hence more appropriate to use the term 'self-regulated' in this context, instead of 'self-organized'.
|
1905.08518
|
Christian Jelsch
|
L. Dettori, Christian Jelsch (CRM2), Y. Guiavarc'h, S. Delaunay
(LSGC), X. Framboisier (LSGC), I. Chevalot (LSGC), C. Humeau (LIBio)
|
Molecular rules for selectivity in lipase-catalysed acylation of lysine
| null |
Process Biochemistry, Elsevier, 2018, 74, pp.50-60
|
10.1016/j.procbio.2018.07.021
| null |
q-bio.QM physics.chem-ph q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The selectivity of L-lysine acylation by lauric acid catalysed by Candida
antarctica lipase B (CALB) was investigated combining experimental and
theoretical methodologies. Experiments showed the near-exclusive acylation of
lysine $\epsilon$-amino group; only traces of product resulting from the
acylation of lysine $\alpha$-amino group were observed fleetingly. Molecular
modelling simulations were performed aiming to understand the molecular rules
for selectivity. Flexible docking simulations combined with structural
investigations into lysine/CALB binding modes also suggested the preferential
acylation of lysine $\epsilon$-amino group without, however, excluding the
acylation of the lysine $\alpha$-amino group. Electrostatic interaction energy
between lysine and the residues covering the catalytic cavity was calculated in
order to understand the discrimination between the two lysine amino groups. The
results suggests that the proximity of the carboxylate group hinders the
binding of the substrate in configurations enabling the N$\alpha$-acylation.
Key interactions with the polar region covering the catalytic triad were
identified and a plausible explanation for selectivity was proposed.
|
[
{
"created": "Tue, 21 May 2019 09:43:58 GMT",
"version": "v1"
}
] |
2019-05-22
|
[
[
"Dettori",
"L.",
"",
"CRM2"
],
[
"Jelsch",
"Christian",
"",
"CRM2"
],
[
"Guiavarc'h",
"Y.",
"",
"LSGC"
],
[
"Delaunay",
"S.",
"",
"LSGC"
],
[
"Framboisier",
"X.",
"",
"LSGC"
],
[
"Chevalot",
"I.",
"",
"LSGC"
],
[
"Humeau",
"C.",
"",
"LIBio"
]
] |
The selectivity of L-lysine acylation by lauric acid catalysed by Candida antarctica lipase B (CALB) was investigated combining experimental and theoretical methodologies. Experiments showed the near-exclusive acylation of lysine $\epsilon$-amino group; only traces of product resulting from the acylation of lysine $\alpha$-amino group were observed fleetingly. Molecular modelling simulations were performed aiming to understand the molecular rules for selectivity. Flexible docking simulations combined with structural investigations into lysine/CALB binding modes also suggested the preferential acylation of lysine $\epsilon$-amino group without, however, excluding the acylation of the lysine $\alpha$-amino group. Electrostatic interaction energy between lysine and the residues covering the catalytic cavity was calculated in order to understand the discrimination between the two lysine amino groups. The results suggests that the proximity of the carboxylate group hinders the binding of the substrate in configurations enabling the N$\alpha$-acylation. Key interactions with the polar region covering the catalytic triad were identified and a plausible explanation for selectivity was proposed.
|
1601.02240
|
Chaitanya A. Athale
|
Chaitanya A. Athale
|
Effect of Replication Fork Dynamics on Escherichia coli Cell Size
| null | null | null | null |
q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The variability in cell size of an isogenic population of Escherichia coli
has been widely reported in experiment. The probability density function (PDF)
of cell lengths has been variously described by exponential and lognormal
functions. While temperature, population density and growth rate have all been
shown to affect E. coli cell size distributions, and recent models have
validated a link between growth rate and cell size through DNA replication,
cell size variability is thought to emerge from growth rate variability. A
mechanistic link that could distinguish the source of stochasticity, could
improve our understanding of cell size regulation. Here, we have developed a
population dynamics model of individual cell division based on the BCD, birth,
chromosome replication and division model, with DNA replication based on the
Cooper and Helmstetter (CH) multi-fork replication. In our model, stochasticity
in the model arises solely from the dynamics of DNA replication forks. We model
the forks as two-state systems: stalled and recovered. Our model predicts an
increase in cell size variability with growth rate, consistent with previous
experimental reports. We perturb the model to test the effect of increased
replication fork (RF) stalling frequency, or uncoupling RF stalling from the
cell-division machinery. Indeed, despite ignoring DNA and protein segregation
asymmetry, the model can faithfully reproduce quantitative changes in cell size
distributions. In our model, multi-fork replication produces multiplicative
'noise' and provides a mechanism linking growth rate and cell size variability.
|
[
{
"created": "Sun, 10 Jan 2016 17:56:36 GMT",
"version": "v1"
},
{
"created": "Thu, 14 Jan 2016 13:05:11 GMT",
"version": "v2"
},
{
"created": "Thu, 13 Apr 2017 09:44:13 GMT",
"version": "v3"
},
{
"created": "Mon, 20 May 2019 07:32:35 GMT",
"version": "v4"
}
] |
2019-05-21
|
[
[
"Athale",
"Chaitanya A.",
""
]
] |
The variability in cell size of an isogenic population of Escherichia coli has been widely reported in experiment. The probability density function (PDF) of cell lengths has been variously described by exponential and lognormal functions. While temperature, population density and growth rate have all been shown to affect E. coli cell size distributions, and recent models have validated a link between growth rate and cell size through DNA replication, cell size variability is thought to emerge from growth rate variability. A mechanistic link that could distinguish the source of stochasticity, could improve our understanding of cell size regulation. Here, we have developed a population dynamics model of individual cell division based on the BCD, birth, chromosome replication and division model, with DNA replication based on the Cooper and Helmstetter (CH) multi-fork replication. In our model, stochasticity in the model arises solely from the dynamics of DNA replication forks. We model the forks as two-state systems: stalled and recovered. Our model predicts an increase in cell size variability with growth rate, consistent with previous experimental reports. We perturb the model to test the effect of increased replication fork (RF) stalling frequency, or uncoupling RF stalling from the cell-division machinery. Indeed, despite ignoring DNA and protein segregation asymmetry, the model can faithfully reproduce quantitative changes in cell size distributions. In our model, multi-fork replication produces multiplicative 'noise' and provides a mechanism linking growth rate and cell size variability.
|
q-bio/0406051
|
Ha Youn Lee
|
Ha Youn Lee and Mehran Kardar
|
Statistics of lines of natural images and implications for visual
detection
| null | null | null | null |
q-bio.NC cond-mat.soft
| null |
As borders between different regions, lines are an important element of
natural images. Already at the level of the mammalian primary visual cortex
(V1), neurons respond best to lines of a given orientation. We reduce a set of
images to linear segments and analyze their statistical properties. In
particular, appropriately defined Fourier spectra show more power in their
transverse component than in the longitudinal one. We then characterize filters
that are best suited for extracting information from such images, and find some
qualitative consistency with neural connections in V1. We also demonstrate that
such filters are efficient in reconstructing missing lines in an image.
|
[
{
"created": "Tue, 29 Jun 2004 15:42:28 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Lee",
"Ha Youn",
""
],
[
"Kardar",
"Mehran",
""
]
] |
As borders between different regions, lines are an important element of natural images. Already at the level of the mammalian primary visual cortex (V1), neurons respond best to lines of a given orientation. We reduce a set of images to linear segments and analyze their statistical properties. In particular, appropriately defined Fourier spectra show more power in their transverse component than in the longitudinal one. We then characterize filters that are best suited for extracting information from such images, and find some qualitative consistency with neural connections in V1. We also demonstrate that such filters are efficient in reconstructing missing lines in an image.
|
1005.3204
|
Sergei Nechaev
|
V.A. Avetisov, S.K. Nechaev, A.B. Shkarin
|
On the motifs distribution in random hierarchical networks
|
7 pages, 5 figures
| null |
10.1016/j.physa.2010.09.016
| null |
q-bio.QM cond-mat.dis-nn
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The distribution of motifs in random hierarchical networks defined by
nonsymmetric random block--hierarchical adjacency matrices, is constructed for
the first time. According to the classification of U. Alon et al of network
superfamilies by their motifs distributions, our artificial directed random
hierarchical networks falls into the superfamily of natural networks to which
the class of neuron networks belongs. This is the first example of ``handmade''
networks with the motifs distribution as in a special class of natural networks
of essential biological importance.
|
[
{
"created": "Tue, 18 May 2010 13:57:26 GMT",
"version": "v1"
}
] |
2015-05-19
|
[
[
"Avetisov",
"V. A.",
""
],
[
"Nechaev",
"S. K.",
""
],
[
"Shkarin",
"A. B.",
""
]
] |
The distribution of motifs in random hierarchical networks defined by nonsymmetric random block--hierarchical adjacency matrices, is constructed for the first time. According to the classification of U. Alon et al of network superfamilies by their motifs distributions, our artificial directed random hierarchical networks falls into the superfamily of natural networks to which the class of neuron networks belongs. This is the first example of ``handmade'' networks with the motifs distribution as in a special class of natural networks of essential biological importance.
|
1412.6225
|
Angelo Rosa Dr
|
Manon Valet, Angelo Rosa
|
Viscoelasticity of model interphase chromosomes
|
10 pages, 6 figures, accepted for publication in Journal of Chemical
Physics
|
J. Chem. Phys. 141, 245101 (2014)
|
10.1063/1.4903996
| null |
q-bio.BM cond-mat.soft physics.bio-ph q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We investigated the viscoelastic response of model interphase chromosomes by
tracking the three-dimensional motion of hundreds of dispersed Brownian
particles of sizes ranging from the thickness of the chromatin fiber up to
slightly above the mesh size of the chromatin solution. In agreement with
previous computational studies on polymer solutions and melts, we found that
the large-time behaviour of diffusion coefficient and the experienced viscosity
of moving particles as functions of particle size deviate from the traditional
Stokes-Einstein relation, and agree with a recent scaling theory of diffusion
of non-sticky particles in polymer solutions. Interestingly, we found that at
short times large particles are temporary "caged" by chromatin spatial
constraints, which thus form effective domains whose size match remarkably well
recent experimental results for micro-tracers inside interphase nuclei.
Finally, by employing a known mathematical relation between the time
mean-square displacement of tracked particles and the complex shear modulus of
the surrounding solution, we calculated the elastic and viscous moduli of
interphase chromosomes.
|
[
{
"created": "Fri, 19 Dec 2014 06:01:42 GMT",
"version": "v1"
}
] |
2015-01-06
|
[
[
"Valet",
"Manon",
""
],
[
"Rosa",
"Angelo",
""
]
] |
We investigated the viscoelastic response of model interphase chromosomes by tracking the three-dimensional motion of hundreds of dispersed Brownian particles of sizes ranging from the thickness of the chromatin fiber up to slightly above the mesh size of the chromatin solution. In agreement with previous computational studies on polymer solutions and melts, we found that the large-time behaviour of diffusion coefficient and the experienced viscosity of moving particles as functions of particle size deviate from the traditional Stokes-Einstein relation, and agree with a recent scaling theory of diffusion of non-sticky particles in polymer solutions. Interestingly, we found that at short times large particles are temporary "caged" by chromatin spatial constraints, which thus form effective domains whose size match remarkably well recent experimental results for micro-tracers inside interphase nuclei. Finally, by employing a known mathematical relation between the time mean-square displacement of tracked particles and the complex shear modulus of the surrounding solution, we calculated the elastic and viscous moduli of interphase chromosomes.
|
2206.06583
|
Fajie Yuan
|
Mingyang Hu, Fajie Yuan, Kevin K. Yang, Fusong Ju, Jin Su, Hui Wang,
Fei Yang, Qiuyang Ding
|
Exploring evolution-aware & -free protein language models as protein
function predictors
| null | null | null | null |
q-bio.QM cs.AI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Large-scale Protein Language Models (PLMs) have improved performance in
protein prediction tasks, ranging from 3D structure prediction to various
function predictions. In particular, AlphaFold, a ground-breaking AI system,
could potentially reshape structural biology. However, the utility of the PLM
module in AlphaFold, Evoformer, has not been explored beyond structure
prediction. In this paper, we investigate the representation ability of three
popular PLMs: ESM-1b (single sequence), MSA-Transformer (multiple sequence
alignment) and Evoformer (structural), with a special focus on Evoformer.
Specifically, we aim to answer the following key questions: (i) Does the
Evoformer trained as part of AlphaFold produce representations amenable to
predicting protein function? (ii) If yes, can Evoformer replace ESM-1b and
MSA-Transformer? (ii) How much do these PLMs rely on evolution-related protein
data? In this regard, are they complementary to each other? We compare these
models by empirical study along with new insights and conclusions. All code and
datasets for reproducibility are available at
https://github.com/elttaes/Revisiting-PLMs.
|
[
{
"created": "Tue, 14 Jun 2022 03:56:10 GMT",
"version": "v1"
},
{
"created": "Sun, 16 Oct 2022 10:00:24 GMT",
"version": "v2"
}
] |
2022-10-18
|
[
[
"Hu",
"Mingyang",
""
],
[
"Yuan",
"Fajie",
""
],
[
"Yang",
"Kevin K.",
""
],
[
"Ju",
"Fusong",
""
],
[
"Su",
"Jin",
""
],
[
"Wang",
"Hui",
""
],
[
"Yang",
"Fei",
""
],
[
"Ding",
"Qiuyang",
""
]
] |
Large-scale Protein Language Models (PLMs) have improved performance in protein prediction tasks, ranging from 3D structure prediction to various function predictions. In particular, AlphaFold, a ground-breaking AI system, could potentially reshape structural biology. However, the utility of the PLM module in AlphaFold, Evoformer, has not been explored beyond structure prediction. In this paper, we investigate the representation ability of three popular PLMs: ESM-1b (single sequence), MSA-Transformer (multiple sequence alignment) and Evoformer (structural), with a special focus on Evoformer. Specifically, we aim to answer the following key questions: (i) Does the Evoformer trained as part of AlphaFold produce representations amenable to predicting protein function? (ii) If yes, can Evoformer replace ESM-1b and MSA-Transformer? (ii) How much do these PLMs rely on evolution-related protein data? In this regard, are they complementary to each other? We compare these models by empirical study along with new insights and conclusions. All code and datasets for reproducibility are available at https://github.com/elttaes/Revisiting-PLMs.
|
1911.02601
|
Joaquin Goni
|
Enrico Amico, Kausar Abbas, Duy Anh Duong-Tran, Uttara Tipnis,
Meenusree Rajapandian, Evgeny Chumin, Mario Ventresca, Jaroslaw Harezlak,
Joaqu\'in Go\~ni
|
Towards an information theoretical description of communication in brain
networks
|
28 pages; 4 figures; 1 table; 2 supplementary figures; 2
supplementary tables
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Modeling communication dynamics in the brain is a key challenge in network
neuroscience. We present here a framework that combines two measurements for
any system where different communication processes are taking place on top of a
fixed structural topology: Path Processing Score (PPS) estimates how much the
brain signal has changed or has been transformed between any two brain regions
(source and target); Path Broadcasting Strength (PBS) estimates the propagation
of the signal through edges adjacent to the path being assessed. We use PPS and
PBS to explore communication dynamics in large-scale brain networks. We show
that brain communication dynamics can be divided into three main 'communication
regimes' of information transfer: absent communication (no communication
happening); relay communication (information is being transferred almost
intact); transducted communication (the information is being transformed). We
use PBS to categorize brain regions based on the way they broadcast
information. Subcortical regions are mainly direct broadcasters to multiple
receivers; Temporal and frontal nodes mainly operate as broadcast relay brain
stations; Visual and somato-motor cortices act as multi-channel transducted
broadcasters. This work paves the way towards the field of brain network
information theory by providing a principled methodology to explore
communication dynamics in large-scale brain networks.
|
[
{
"created": "Wed, 6 Nov 2019 19:18:17 GMT",
"version": "v1"
},
{
"created": "Fri, 2 Oct 2020 19:21:35 GMT",
"version": "v2"
}
] |
2020-10-06
|
[
[
"Amico",
"Enrico",
""
],
[
"Abbas",
"Kausar",
""
],
[
"Duong-Tran",
"Duy Anh",
""
],
[
"Tipnis",
"Uttara",
""
],
[
"Rajapandian",
"Meenusree",
""
],
[
"Chumin",
"Evgeny",
""
],
[
"Ventresca",
"Mario",
""
],
[
"Harezlak",
"Jaroslaw",
""
],
[
"Goñi",
"Joaquín",
""
]
] |
Modeling communication dynamics in the brain is a key challenge in network neuroscience. We present here a framework that combines two measurements for any system where different communication processes are taking place on top of a fixed structural topology: Path Processing Score (PPS) estimates how much the brain signal has changed or has been transformed between any two brain regions (source and target); Path Broadcasting Strength (PBS) estimates the propagation of the signal through edges adjacent to the path being assessed. We use PPS and PBS to explore communication dynamics in large-scale brain networks. We show that brain communication dynamics can be divided into three main 'communication regimes' of information transfer: absent communication (no communication happening); relay communication (information is being transferred almost intact); transducted communication (the information is being transformed). We use PBS to categorize brain regions based on the way they broadcast information. Subcortical regions are mainly direct broadcasters to multiple receivers; Temporal and frontal nodes mainly operate as broadcast relay brain stations; Visual and somato-motor cortices act as multi-channel transducted broadcasters. This work paves the way towards the field of brain network information theory by providing a principled methodology to explore communication dynamics in large-scale brain networks.
|
2112.07775
|
Tobiloba Adejumo
|
Tobiloba Adejumo, Tae-Hoon Kim, David Le, Taeyoon Son, Guangying Ma,
Xincheng Yao
|
Depth-resolved vascular profile features for artery-vein classification
in OCT and OCT angiography of human retina
|
11 pages, 4 figures
| null |
10.1364/BOE.450913
| null |
q-bio.TO eess.IV
|
http://creativecommons.org/licenses/by/4.0/
|
This study is to characterize reflectance profiles of retinal blood vessels
in optical coherence tomography (OCT), and to validate these vascular features
to guide artery-vein classification in OCT angiography (OCTA) of human retina.
Depth-resolved OCT reveals unique features of retinal arteries and veins.
Retinal arteries show hyper-reflective boundaries at both upper (inner side
towards the vitreous) and lower (outer side towards the choroid) walls. In
contrary, retinal veins reveal hyper-reflectivity at the upper boundary only.
Uniform lumen intensity was observed in both small and large arteries. However,
the vein lumen intensity was dependent on the vessel size. Small veins exhibit
a hyper-reflective zone at the bottom half of the lumen, while large veins show
a hypo-reflective zone at the bottom half of the lumen
|
[
{
"created": "Tue, 14 Dec 2021 22:49:46 GMT",
"version": "v1"
},
{
"created": "Sun, 6 Feb 2022 18:39:06 GMT",
"version": "v2"
}
] |
2022-02-08
|
[
[
"Adejumo",
"Tobiloba",
""
],
[
"Kim",
"Tae-Hoon",
""
],
[
"Le",
"David",
""
],
[
"Son",
"Taeyoon",
""
],
[
"Ma",
"Guangying",
""
],
[
"Yao",
"Xincheng",
""
]
] |
This study is to characterize reflectance profiles of retinal blood vessels in optical coherence tomography (OCT), and to validate these vascular features to guide artery-vein classification in OCT angiography (OCTA) of human retina. Depth-resolved OCT reveals unique features of retinal arteries and veins. Retinal arteries show hyper-reflective boundaries at both upper (inner side towards the vitreous) and lower (outer side towards the choroid) walls. In contrary, retinal veins reveal hyper-reflectivity at the upper boundary only. Uniform lumen intensity was observed in both small and large arteries. However, the vein lumen intensity was dependent on the vessel size. Small veins exhibit a hyper-reflective zone at the bottom half of the lumen, while large veins show a hypo-reflective zone at the bottom half of the lumen
|
2206.15459
|
Axel Brandenburg
|
Axel Brandenburg
|
Quadratic growth during the COVID-19 pandemic: merging hotspots and
reinfections
|
11 pages, 10 figures, 1 table
|
J. Phys. A: Math. Theor. 56, 044002 (2023)
|
10.1088/1751-8121/acb743
|
NORDITA-2022-043
|
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The existence of an exponential growth phase during early stages of a
pandemic is often taken for granted. However, for the 2019 novel coronavirus
epidemic, the early exponential phase lasted only for about six days, while the
quadratic growth prevailed for forty days until it spread to other countries
and continued, again quadratically, but with a larger coefficient. Here we show
that this rapid phase is followed by a subsequent slow-down where the
coefficient is reduced to almost the original value at the outbreak. This can
be explained by the merging of previously disconnected sites that occurred
after the disease jumped (nonlocally) to a relatively small number of separated
sites. Subsequent variations in the slope with continued growth can
qualitatively be explained as a result of reinfections and changes in their
rate. We demonstrate that the observed behavior can be described by a standard
epidemiological model with spatial extent and reinfections included.
Time-dependent changes in the spatial diffusion coefficient can also model
corresponding variations in the slope.
|
[
{
"created": "Thu, 30 Jun 2022 17:53:08 GMT",
"version": "v1"
},
{
"created": "Fri, 30 Dec 2022 11:17:16 GMT",
"version": "v2"
}
] |
2023-02-14
|
[
[
"Brandenburg",
"Axel",
""
]
] |
The existence of an exponential growth phase during early stages of a pandemic is often taken for granted. However, for the 2019 novel coronavirus epidemic, the early exponential phase lasted only for about six days, while the quadratic growth prevailed for forty days until it spread to other countries and continued, again quadratically, but with a larger coefficient. Here we show that this rapid phase is followed by a subsequent slow-down where the coefficient is reduced to almost the original value at the outbreak. This can be explained by the merging of previously disconnected sites that occurred after the disease jumped (nonlocally) to a relatively small number of separated sites. Subsequent variations in the slope with continued growth can qualitatively be explained as a result of reinfections and changes in their rate. We demonstrate that the observed behavior can be described by a standard epidemiological model with spatial extent and reinfections included. Time-dependent changes in the spatial diffusion coefficient can also model corresponding variations in the slope.
|
2007.10458
|
Chowdhury Rahman
|
Ruhul Amin, Chowdhury Rafeed Rahman, Md. Sadrul Islam Toaha and
Swakkhar Shatabda
|
i6mA-CNN: a convolution based computational approach towards
identification of DNA N6-methyladenine sites in rice genome
| null | null |
10.1101/2020.07.08.194308
| null |
q-bio.GN cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
DNA N6-methylation (6mA) in Adenine nucleotide is a post replication
modification and is responsible for many biological functions. Experimental
methods for genome wide 6mA site detection is an expensive and manual labour
intensive process. Automated and accurate computational methods can help to
identify 6mA sites in long genomes saving significant time and money. Our study
develops a convolutional neural network based tool i6mA-CNN capable of
identifying 6mA sites in the rice genome. Our model coordinates among multiple
types of features such as PseAAC inspired customized feature vector, multiple
one hot representations and dinucleotide physicochemical properties. It
achieves area under the receiver operating characteristic curve of 0.98 with an
overall accuracy of 0.94 using 5 fold cross validation on benchmark dataset.
Finally, we evaluate our model on two other plant genome 6mA site
identification datasets besides rice. Results suggest that our proposed tool is
able to generalize its ability of 6mA site identification on plant genomes
irrespective of plant species. Web tool for this research can be found at:
https://cutt.ly/Co6KuWG. Supplementary data (benchmark dataset, independent
test dataset, comparison purpose dataset, trained model, physicochemical
property values, attention mechanism details for motif finding) are available
at https://cutt.ly/PpDdeDH.
|
[
{
"created": "Mon, 20 Jul 2020 20:37:01 GMT",
"version": "v1"
},
{
"created": "Tue, 11 Aug 2020 11:05:22 GMT",
"version": "v2"
}
] |
2020-08-12
|
[
[
"Amin",
"Ruhul",
""
],
[
"Rahman",
"Chowdhury Rafeed",
""
],
[
"Toaha",
"Md. Sadrul Islam",
""
],
[
"Shatabda",
"Swakkhar",
""
]
] |
DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification and is responsible for many biological functions. Experimental methods for genome wide 6mA site detection is an expensive and manual labour intensive process. Automated and accurate computational methods can help to identify 6mA sites in long genomes saving significant time and money. Our study develops a convolutional neural network based tool i6mA-CNN capable of identifying 6mA sites in the rice genome. Our model coordinates among multiple types of features such as PseAAC inspired customized feature vector, multiple one hot representations and dinucleotide physicochemical properties. It achieves area under the receiver operating characteristic curve of 0.98 with an overall accuracy of 0.94 using 5 fold cross validation on benchmark dataset. Finally, we evaluate our model on two other plant genome 6mA site identification datasets besides rice. Results suggest that our proposed tool is able to generalize its ability of 6mA site identification on plant genomes irrespective of plant species. Web tool for this research can be found at: https://cutt.ly/Co6KuWG. Supplementary data (benchmark dataset, independent test dataset, comparison purpose dataset, trained model, physicochemical property values, attention mechanism details for motif finding) are available at https://cutt.ly/PpDdeDH.
|
1103.5488
|
Jorge Ramirez
|
Jorge M Ramirez
|
Population persistence under advection-diffusion in river networks
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
An integro-differential equation on a tree graph is used to model the
evolution and spatial distribution of a population of organisms in a river
network. Individual organisms become mobile at a constant rate, and disperse
according to an advection-diffusion process with coefficients that are constant
on the edges of the graph. Appropriate boundary conditions are imposed at the
outlet and upstream nodes of the river network. The local rates of population
growth/decay and that by which the organisms become mobile, are assumed
constant in time and space. Imminent extinction of the population is understood
as the situation whereby the zero solution to the integro-differential equation
is stable. Lower and upper bounds for the eigenvalues of the dispersion
operator, and related Sturm-Liouville problems are found, and therefore
sufficient conditions for imminent extinction are given in terms of the
physical variables of the problem.
|
[
{
"created": "Mon, 28 Mar 2011 21:07:47 GMT",
"version": "v1"
},
{
"created": "Wed, 30 Mar 2011 21:35:21 GMT",
"version": "v2"
}
] |
2011-04-01
|
[
[
"Ramirez",
"Jorge M",
""
]
] |
An integro-differential equation on a tree graph is used to model the evolution and spatial distribution of a population of organisms in a river network. Individual organisms become mobile at a constant rate, and disperse according to an advection-diffusion process with coefficients that are constant on the edges of the graph. Appropriate boundary conditions are imposed at the outlet and upstream nodes of the river network. The local rates of population growth/decay and that by which the organisms become mobile, are assumed constant in time and space. Imminent extinction of the population is understood as the situation whereby the zero solution to the integro-differential equation is stable. Lower and upper bounds for the eigenvalues of the dispersion operator, and related Sturm-Liouville problems are found, and therefore sufficient conditions for imminent extinction are given in terms of the physical variables of the problem.
|
1105.4425
|
Andrea Markelz
|
J.Y. Chen, D.K. George, Yunfen He, J.R.Knab and A. G. Markelz
|
Functional State Dependence of Picosecond Protein Dynamics
|
4 main pages, 3 figures, 1 table, 2 supplemental tables
| null | null | null |
q-bio.BM cond-mat.soft
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We examine temperature dependent picosecond dynamics as a function of
structure and function for lysozyme and cytochrome c using temperature
dependent terahertz permittivity measurements. A double Arrhenius temperature
dependence with activation energies E1 ~ 0.1 kJ/mol and E2 ~10 kJ/mol fits the
native state response. The higher activation energy is consistent with the
so-called protein dynamical transition associated with beta relaxations at the
solvent-protein interface. The lower activation energy is consistent with
correlated structural motions. When the structure is removed by denaturing the
lower activation energy process is no longer present. Additionally the lower
activation energy process is diminished with ligand binding, but not for
changes in internal oxidation state. We suggest that the lower energy
activation process is associated with collective structural motions that are no
longer accessible with denaturing or binding.
|
[
{
"created": "Mon, 23 May 2011 08:01:45 GMT",
"version": "v1"
}
] |
2011-05-24
|
[
[
"Chen",
"J. Y.",
""
],
[
"George",
"D. K.",
""
],
[
"He",
"Yunfen",
""
],
[
"Knab",
"J. R.",
""
],
[
"Markelz",
"A. G.",
""
]
] |
We examine temperature dependent picosecond dynamics as a function of structure and function for lysozyme and cytochrome c using temperature dependent terahertz permittivity measurements. A double Arrhenius temperature dependence with activation energies E1 ~ 0.1 kJ/mol and E2 ~10 kJ/mol fits the native state response. The higher activation energy is consistent with the so-called protein dynamical transition associated with beta relaxations at the solvent-protein interface. The lower activation energy is consistent with correlated structural motions. When the structure is removed by denaturing the lower activation energy process is no longer present. Additionally the lower activation energy process is diminished with ligand binding, but not for changes in internal oxidation state. We suggest that the lower energy activation process is associated with collective structural motions that are no longer accessible with denaturing or binding.
|
0709.1195
|
Emmanuel Tannenbaum
|
Emmanuel Tannenbaum
|
Selective advantage for sexual reproduction with random haploid fusion
|
11 pages, 1 figure, submitted to Physical Review E (additional 4
figures included in Phys. Rev. E submission)
| null | null | null |
q-bio.PE q-bio.CB
| null |
This paper develops a simplified set of models describing asexual and sexual
replication in unicel- lular diploid organisms. The models assume organisms
whose genomes consist of two chromosomes, where each chromosome is assumed to
be functional if it is equal to some master sequence $ \sigma_0 $, and
non-functional otherwise. The first-order growth rate constant, or fitness, of
an organism, is determined by whether it has zero, one, or two functional
chromosomes in its genome. For a population replicating asexually, a given cell
replicates both of its chromosomes, and splits its genetic material evenly
between the two cells. For a population replicating sexually, a given cell
first divides into two haploids, which enter a haploid pool, fuse into
diploids, and then divide via the normal mitotic process. Haploid fusion is
modeled as a second-order rate process. When the cost for sex is small, as
measured by the ratio of the characteristic haploid fusion time to the
characteristic growth time, we find that sexual replication with random haploid
fusion leads to a greater mean fitness for the population than a purely asexual
strategy. However, independently of the cost for sex, we find that sexual
replication with a selective mating strategy leads to a higher mean fitness
than the random mating strategy. This result is based on the assumption that a
selective mating strategy does not have any additional time or energy costs
over the random mating strategy, an assumption that is discussed in the paper.
The results of this paper are consistent with previous studies suggesting that
sex is favored at intermediate mutation rates, for slowly replicating
organisms, and at high population densities.
|
[
{
"created": "Sat, 8 Sep 2007 09:52:35 GMT",
"version": "v1"
}
] |
2007-09-11
|
[
[
"Tannenbaum",
"Emmanuel",
""
]
] |
This paper develops a simplified set of models describing asexual and sexual replication in unicel- lular diploid organisms. The models assume organisms whose genomes consist of two chromosomes, where each chromosome is assumed to be functional if it is equal to some master sequence $ \sigma_0 $, and non-functional otherwise. The first-order growth rate constant, or fitness, of an organism, is determined by whether it has zero, one, or two functional chromosomes in its genome. For a population replicating asexually, a given cell replicates both of its chromosomes, and splits its genetic material evenly between the two cells. For a population replicating sexually, a given cell first divides into two haploids, which enter a haploid pool, fuse into diploids, and then divide via the normal mitotic process. Haploid fusion is modeled as a second-order rate process. When the cost for sex is small, as measured by the ratio of the characteristic haploid fusion time to the characteristic growth time, we find that sexual replication with random haploid fusion leads to a greater mean fitness for the population than a purely asexual strategy. However, independently of the cost for sex, we find that sexual replication with a selective mating strategy leads to a higher mean fitness than the random mating strategy. This result is based on the assumption that a selective mating strategy does not have any additional time or energy costs over the random mating strategy, an assumption that is discussed in the paper. The results of this paper are consistent with previous studies suggesting that sex is favored at intermediate mutation rates, for slowly replicating organisms, and at high population densities.
|
2401.10972
|
Paula Mercurio
|
Paula Mercurio and Di Liu
|
Clustering Molecular Energy Landscapes by Adaptive Network Embedding
|
19 pages, 10 figures
| null | null | null |
q-bio.BM cond-mat.stat-mech cs.LG
|
http://creativecommons.org/licenses/by/4.0/
|
In order to efficiently explore the chemical space of all possible small
molecules, a common approach is to compress the dimension of the system to
facilitate downstream machine learning tasks. Towards this end, we present a
data driven approach for clustering potential energy landscapes of molecular
structures by applying recently developed Network Embedding techniques, to
obtain latent variables defined through the embedding function. To scale up the
method, we also incorporate an entropy sensitive adaptive scheme for
hierarchical sampling of the energy landscape, based on Metadynamics and
Transition Path Theory. By taking into account the kinetic information implied
by a system's energy landscape, we are able to interpret dynamical node-node
relationships in reduced dimensions. We demonstrate the framework through
Lennard-Jones (LJ) clusters and a human DNA sequence.
|
[
{
"created": "Fri, 19 Jan 2024 17:12:07 GMT",
"version": "v1"
}
] |
2024-01-23
|
[
[
"Mercurio",
"Paula",
""
],
[
"Liu",
"Di",
""
]
] |
In order to efficiently explore the chemical space of all possible small molecules, a common approach is to compress the dimension of the system to facilitate downstream machine learning tasks. Towards this end, we present a data driven approach for clustering potential energy landscapes of molecular structures by applying recently developed Network Embedding techniques, to obtain latent variables defined through the embedding function. To scale up the method, we also incorporate an entropy sensitive adaptive scheme for hierarchical sampling of the energy landscape, based on Metadynamics and Transition Path Theory. By taking into account the kinetic information implied by a system's energy landscape, we are able to interpret dynamical node-node relationships in reduced dimensions. We demonstrate the framework through Lennard-Jones (LJ) clusters and a human DNA sequence.
|
1710.05914
|
Davide Nardone
|
Davide Nardone, Angelo Ciaramella, Mariangela Cerreta, Salvatore
Pulcrano, Gian Carlo Bellenchi, Giuseppe Manco, Ferdinando Febbraio
|
SELYMATRA: Web Application for the analysis of mass spectra
| null | null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Surface Enhanced Laser Desorption/Ionization-Time Of Flight Mass Spectrometry
(SELDI-TOF MS) is a variant of the MALDI. It is uses in many cases especially
for the analysis of protein profiling and for preliminary screening tasks of
complex sample aimed for the searching of biomarker. Unfortunately, these
analysis are time consuming and strictly limited about the protein
identification. Seldi analysis of mass spectra (SELYMATRA) is a Web Application
(WA) developed with the aim of reduce these lacks automating the identification
processes and introducing the possibility to predict the proteins present in
complex mixtures from cells and tissues analysed by Mass Spectrometry.
SELYMATRA has the following characteristics. The architectural pattern used to
develop the WA is the Model-View-Controller (MVC), extremely used in the
development of software system. The WA expects an user to upload data in a
Microsoft Excel spreadsheet file format, usually generated by means of the
proprietary Mass Spectrometry softwares. Several parameters can be set such as
experiment conditions, range of isoelectric point, range of pH, relative errors
and so on. The WA compare the mass value among two mass spectra (sample vs
control) to extract differences, and according to the parameters set, it
queries a local database for the prediction of the most likely proteins related
to the masses differently expressed. The WA was validated in a cellular model
overexpressing a tagged NURR1 receptor. SELYMATRA is available at
http://140.164.61.23:8080/SELYMATRA.
|
[
{
"created": "Sun, 15 Oct 2017 16:05:43 GMT",
"version": "v1"
}
] |
2017-10-18
|
[
[
"Nardone",
"Davide",
""
],
[
"Ciaramella",
"Angelo",
""
],
[
"Cerreta",
"Mariangela",
""
],
[
"Pulcrano",
"Salvatore",
""
],
[
"Bellenchi",
"Gian Carlo",
""
],
[
"Manco",
"Giuseppe",
""
],
[
"Febbraio",
"Ferdinando",
""
]
] |
Surface Enhanced Laser Desorption/Ionization-Time Of Flight Mass Spectrometry (SELDI-TOF MS) is a variant of the MALDI. It is uses in many cases especially for the analysis of protein profiling and for preliminary screening tasks of complex sample aimed for the searching of biomarker. Unfortunately, these analysis are time consuming and strictly limited about the protein identification. Seldi analysis of mass spectra (SELYMATRA) is a Web Application (WA) developed with the aim of reduce these lacks automating the identification processes and introducing the possibility to predict the proteins present in complex mixtures from cells and tissues analysed by Mass Spectrometry. SELYMATRA has the following characteristics. The architectural pattern used to develop the WA is the Model-View-Controller (MVC), extremely used in the development of software system. The WA expects an user to upload data in a Microsoft Excel spreadsheet file format, usually generated by means of the proprietary Mass Spectrometry softwares. Several parameters can be set such as experiment conditions, range of isoelectric point, range of pH, relative errors and so on. The WA compare the mass value among two mass spectra (sample vs control) to extract differences, and according to the parameters set, it queries a local database for the prediction of the most likely proteins related to the masses differently expressed. The WA was validated in a cellular model overexpressing a tagged NURR1 receptor. SELYMATRA is available at http://140.164.61.23:8080/SELYMATRA.
|
2102.04260
|
Delfim F. M. Torres
|
Marouane Mahrouf, Adnane Boukhouima, Houssine Zine, El Mehdi Lotfi,
Delfim F. M. Torres, Noura Yousfi
|
Modeling and Forecasting of COVID-19 Spreading by Delayed Stochastic
Differential Equations
|
This is a preprint of a paper whose final and definite form is
published, open access, by 'Axioms' (ISSN: 2075-1680). Submitted Axioms: 2
Dec 2020; Revised: 20 and 31 Jan 2021; correction to proofs: 4 Feb 2021
|
Axioms 10 (2021), no. 1, Art. 18, 16 pp
|
10.3390/axioms10010018
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The novel coronavirus disease (COVID-19) pneumonia has posed a great threat
to the world recent months by causing many deaths and enormous economic damage
worldwide. The first case of COVID-19 in Morocco was reported on 2 March 2020,
and the number of reported cases has increased day by day. In this work, we
extend the well-known SIR compartmental model to deterministic and stochastic
time-delayed models in order to predict the epidemiological trend of COVID-19
in Morocco and to assess the potential role of multiple preventive measures and
strategies imposed by Moroccan authorities. The main features of the work
include the well-posedness of the models and conditions under which the
COVID-19 may become extinct or persist in the population. Parameter values have
been estimated from real data and numerical simulations are presented for
forecasting the COVID-19 spreading as well as verification of theoretical
results.
|
[
{
"created": "Thu, 4 Feb 2021 19:15:32 GMT",
"version": "v1"
}
] |
2021-02-10
|
[
[
"Mahrouf",
"Marouane",
""
],
[
"Boukhouima",
"Adnane",
""
],
[
"Zine",
"Houssine",
""
],
[
"Lotfi",
"El Mehdi",
""
],
[
"Torres",
"Delfim F. M.",
""
],
[
"Yousfi",
"Noura",
""
]
] |
The novel coronavirus disease (COVID-19) pneumonia has posed a great threat to the world recent months by causing many deaths and enormous economic damage worldwide. The first case of COVID-19 in Morocco was reported on 2 March 2020, and the number of reported cases has increased day by day. In this work, we extend the well-known SIR compartmental model to deterministic and stochastic time-delayed models in order to predict the epidemiological trend of COVID-19 in Morocco and to assess the potential role of multiple preventive measures and strategies imposed by Moroccan authorities. The main features of the work include the well-posedness of the models and conditions under which the COVID-19 may become extinct or persist in the population. Parameter values have been estimated from real data and numerical simulations are presented for forecasting the COVID-19 spreading as well as verification of theoretical results.
|
1006.2923
|
Christian Guill
|
Christian Guill, Barbara Drossel, Wolfram Just, and Eddy Carmack
|
A three-species model explaining cyclic dominance of pacific salmon
|
7 pages, 5 figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The four-year oscillations of the number of spawning sockeye salmon
(Oncorhynchus nerka) that return to their native stream within the Fraser River
basin in Canada are a striking example of population oscillations. The period
of the oscillation corresponds to the dominant generation time of these fish.
Various - not fully convincing - explanations for these oscillations have been
proposed, including stochastic influences, depensatory fishing, or genetic
effects. Here, we show that the oscillations can be explained as a stable
dynamical attractor of the population dynamics, resulting from a strong
resonance near a Neimark Sacker bifurcation. This explains not only the
long-term persistence of these oscillations, but also reproduces correctly the
empirical sequence of salmon abundance within one period of the oscillations.
Furthermore, it explains the observation that these oscillations occur only in
sockeye stocks originating from large oligotrophic lakes, and that they are
usually not observed in salmon species that have a longer generation time.
|
[
{
"created": "Tue, 15 Jun 2010 08:40:28 GMT",
"version": "v1"
}
] |
2010-06-16
|
[
[
"Guill",
"Christian",
""
],
[
"Drossel",
"Barbara",
""
],
[
"Just",
"Wolfram",
""
],
[
"Carmack",
"Eddy",
""
]
] |
The four-year oscillations of the number of spawning sockeye salmon (Oncorhynchus nerka) that return to their native stream within the Fraser River basin in Canada are a striking example of population oscillations. The period of the oscillation corresponds to the dominant generation time of these fish. Various - not fully convincing - explanations for these oscillations have been proposed, including stochastic influences, depensatory fishing, or genetic effects. Here, we show that the oscillations can be explained as a stable dynamical attractor of the population dynamics, resulting from a strong resonance near a Neimark Sacker bifurcation. This explains not only the long-term persistence of these oscillations, but also reproduces correctly the empirical sequence of salmon abundance within one period of the oscillations. Furthermore, it explains the observation that these oscillations occur only in sockeye stocks originating from large oligotrophic lakes, and that they are usually not observed in salmon species that have a longer generation time.
|
1411.5624
|
Jian-Zhou Zhu
|
Kun Gao, HongGuang Sun, Jian-Zhou Zhu
|
Disorder and Power-law Tails of DNA Sequence Self-Alignment
Concentrations in Molecular Evolution
|
a figure for the introductory discussion removed; less lengthy
| null | null | null |
q-bio.PE physics.bio-ph q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The self-alignment concentrations, $c(x)$, as functions of the length, $x$,
of the identically matching maximal segments in the genomes of a variety of
species, typically present power-law tails extending to the largest scales,
i.e., $c(x) \propto x^{\alpha}$, with similar or apparently different negative
$\alpha$s ($<-2$). The relevant fundamental processes of molecular evolution
are segmental duplication and point mutation, and that recently the stick
fragmentation phenomenology has been used to account the neutral evolution.
However, disorder is intrinsic to the evolution system and, by freezing it in
time (quenching) for the setup of a simple fragmentation model, we obtain
decaying, steady-state and the general full time-dependent solutions, all
$\propto x^{\alpha}$ for $x\to \infty$, which is in contrast to the only
power-law solution, $x^{-3}$ for $x\to 0$ of the pure model (without disorder).
%Other algebraic terms may dominate at intermediate scales, which seems to be
confirmed by some species, such as rice. We also present self-alignment results
showing more than one scaling regimes, consistent with the theoretical results
of the existence of more than one algebraic terms which dominate at different
regimes.
|
[
{
"created": "Thu, 20 Nov 2014 17:49:54 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Nov 2014 11:44:07 GMT",
"version": "v2"
},
{
"created": "Sat, 20 Dec 2014 02:50:39 GMT",
"version": "v3"
}
] |
2014-12-23
|
[
[
"Gao",
"Kun",
""
],
[
"Sun",
"HongGuang",
""
],
[
"Zhu",
"Jian-Zhou",
""
]
] |
The self-alignment concentrations, $c(x)$, as functions of the length, $x$, of the identically matching maximal segments in the genomes of a variety of species, typically present power-law tails extending to the largest scales, i.e., $c(x) \propto x^{\alpha}$, with similar or apparently different negative $\alpha$s ($<-2$). The relevant fundamental processes of molecular evolution are segmental duplication and point mutation, and that recently the stick fragmentation phenomenology has been used to account the neutral evolution. However, disorder is intrinsic to the evolution system and, by freezing it in time (quenching) for the setup of a simple fragmentation model, we obtain decaying, steady-state and the general full time-dependent solutions, all $\propto x^{\alpha}$ for $x\to \infty$, which is in contrast to the only power-law solution, $x^{-3}$ for $x\to 0$ of the pure model (without disorder). %Other algebraic terms may dominate at intermediate scales, which seems to be confirmed by some species, such as rice. We also present self-alignment results showing more than one scaling regimes, consistent with the theoretical results of the existence of more than one algebraic terms which dominate at different regimes.
|
q-bio/0312006
|
Thomas Down
|
Thomas A. Down and Tim J. P. Hubbard
|
Relevance Vector Machines for classifying points and regions in
biological sequences
|
16 pages, 3 figures
| null | null | null |
q-bio.GN
| null |
The Relevance Vector Machine (RVM) is a recently developed machine learning
framework capable of building simple models from large sets of candidate
features. Here, we describe a protocol for using the RVM to explore very large
numbers of candidate features, and a family of models which apply the power of
the RVM to classifying and detecting interesting points and regions in
biological sequence data. The models described here have been used successfully
for predicting transcription start sites and other features in genome
sequences.
|
[
{
"created": "Thu, 4 Dec 2003 11:55:20 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Down",
"Thomas A.",
""
],
[
"Hubbard",
"Tim J. P.",
""
]
] |
The Relevance Vector Machine (RVM) is a recently developed machine learning framework capable of building simple models from large sets of candidate features. Here, we describe a protocol for using the RVM to explore very large numbers of candidate features, and a family of models which apply the power of the RVM to classifying and detecting interesting points and regions in biological sequence data. The models described here have been used successfully for predicting transcription start sites and other features in genome sequences.
|
1807.03784
|
Dirson Jian Li
|
Dirson Jian Li
|
Observations and perspectives on the diversification of genomes
|
43 pages, 10 figures
| null | null | null |
q-bio.OT
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Rich information on the prebiotic evolution is still stored in contemporary
genomic data. The statistical mechanism at the sequence level may play a
significant role in the prebiotic evolution. Based on statistical analysis of
genome sequences, it has been observed that there is a close relationship
between the evolution of the genetic code and the organisation of genomes. A
biodiversity space for species is constructed based on comparing the
distributions of codons in genomes for different species according to
recruitment order of codons in the prebiotic evolution, by which a closely
relationship between the evolution of the genetic code and the tree of life has
been confirmed. On one hand, the three domain tree of life can be reconstructed
according to the distance matrix of species in this biodiversity space, which
supports the three-domain tree rather than the eocyte tree. On the other hand,
an evolutionary tree of codons can be obtained by comparing the distributions
of the 64 codons in genomes, which agrees with the recruitment order of codons
on the roadmap. This is a simple phylogenomic method to study the origins of
metazoan, the evolution of primates, etc. This study should be regarded as an
exploratory attempt to explain the diversification of the three domains of life
by statistical mechanism in prebiotic sequence evolution. It is indicated that
the number of bases in the triplet codons might be explained statistically by
the number of strands in the triplex DNAs. The adaptation of life to the
changing environment might be due to assembly of redundant genomes at the
sequence level.
|
[
{
"created": "Tue, 10 Jul 2018 17:20:33 GMT",
"version": "v1"
}
] |
2018-07-12
|
[
[
"Li",
"Dirson Jian",
""
]
] |
Rich information on the prebiotic evolution is still stored in contemporary genomic data. The statistical mechanism at the sequence level may play a significant role in the prebiotic evolution. Based on statistical analysis of genome sequences, it has been observed that there is a close relationship between the evolution of the genetic code and the organisation of genomes. A biodiversity space for species is constructed based on comparing the distributions of codons in genomes for different species according to recruitment order of codons in the prebiotic evolution, by which a closely relationship between the evolution of the genetic code and the tree of life has been confirmed. On one hand, the three domain tree of life can be reconstructed according to the distance matrix of species in this biodiversity space, which supports the three-domain tree rather than the eocyte tree. On the other hand, an evolutionary tree of codons can be obtained by comparing the distributions of the 64 codons in genomes, which agrees with the recruitment order of codons on the roadmap. This is a simple phylogenomic method to study the origins of metazoan, the evolution of primates, etc. This study should be regarded as an exploratory attempt to explain the diversification of the three domains of life by statistical mechanism in prebiotic sequence evolution. It is indicated that the number of bases in the triplet codons might be explained statistically by the number of strands in the triplex DNAs. The adaptation of life to the changing environment might be due to assembly of redundant genomes at the sequence level.
|
q-bio/0612014
|
Vladislav Volman
|
Vladislav Volman, Eshel Ben-Jacob, Herbert Levine
|
The astrocyte as a gatekeeper of synaptic information transfer
|
31 pages, 8 figures
| null | null | null |
q-bio.NC
| null |
We present a simple biophysical model for the coupling between synaptic
transmission and the local calcium concentration on an enveloping astrocytic
domain. This interaction enables the astrocyte to modulate the information flow
from presynaptic to postsynaptic cells in a manner dependent on previous
activity at this and other nearby synapses. Our model suggests a novel,
testable hypothesis for the spike timing statistics measured for rapidly-firing
cells in culture experiments.
|
[
{
"created": "Thu, 7 Dec 2006 22:39:33 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Volman",
"Vladislav",
""
],
[
"Ben-Jacob",
"Eshel",
""
],
[
"Levine",
"Herbert",
""
]
] |
We present a simple biophysical model for the coupling between synaptic transmission and the local calcium concentration on an enveloping astrocytic domain. This interaction enables the astrocyte to modulate the information flow from presynaptic to postsynaptic cells in a manner dependent on previous activity at this and other nearby synapses. Our model suggests a novel, testable hypothesis for the spike timing statistics measured for rapidly-firing cells in culture experiments.
|
2402.16615
|
Gregory Reeves
|
Sharva V. Hiremath, Etika Goyal, Gregory T. Reeves, Cranos M. Williams
|
FRAP analysis Measuring biophysical kinetic parameters using image
analysis
|
10 pages, 10 figures
| null | null | null |
q-bio.QM
|
http://creativecommons.org/licenses/by/4.0/
|
Understanding transcription factor dynamics is crucial for unraveling the
regulatory mechanisms of gene expression that underpin cellular function and
development. Measurements of transcription factor subcellular movements are
essential for developing predictive models of gene expression. However,
obtaining these quantitative measurements poses significant challenges due to
the inherent variability of biological data and the need for high precision in
tracking the movement and interaction of molecules. Our computational pipeline
provides a solution to these challenges, offering a comprehensive approach to
the quantitative analysis of transcription factor dynamics. Our pipeline
integrates advanced image segmentation to accurately delineate individual
nuclei, precise nucleus tracking to monitor changes over time, and detailed
intensity extraction to measure fluorescence as a proxy for transcription
factor activity. Combining our pipeline with techniques such as fluorescence
recovery after photobleaching enables the estimation of vital biophysical
parameters, such as transcription factor import and export rates.
|
[
{
"created": "Fri, 23 Feb 2024 17:57:32 GMT",
"version": "v1"
},
{
"created": "Tue, 16 Jul 2024 20:38:38 GMT",
"version": "v2"
}
] |
2024-07-18
|
[
[
"Hiremath",
"Sharva V.",
""
],
[
"Goyal",
"Etika",
""
],
[
"Reeves",
"Gregory T.",
""
],
[
"Williams",
"Cranos M.",
""
]
] |
Understanding transcription factor dynamics is crucial for unraveling the regulatory mechanisms of gene expression that underpin cellular function and development. Measurements of transcription factor subcellular movements are essential for developing predictive models of gene expression. However, obtaining these quantitative measurements poses significant challenges due to the inherent variability of biological data and the need for high precision in tracking the movement and interaction of molecules. Our computational pipeline provides a solution to these challenges, offering a comprehensive approach to the quantitative analysis of transcription factor dynamics. Our pipeline integrates advanced image segmentation to accurately delineate individual nuclei, precise nucleus tracking to monitor changes over time, and detailed intensity extraction to measure fluorescence as a proxy for transcription factor activity. Combining our pipeline with techniques such as fluorescence recovery after photobleaching enables the estimation of vital biophysical parameters, such as transcription factor import and export rates.
|
1911.12253
|
Paul Samuel Ignacio
|
Paul Samuel Ignacio, David Uminsky, Christopher Dunstan, Esteban
Escobar, Luke Trujillo
|
Classification of Single-lead Electrocardiograms: TDA Informed Machine
Learning
|
\c{opyright} 2019 IEEE. Personal use of this material is permitted.
Permission from IEEE must be obtained for all other uses, in any current or
future media, including reprinting/republishing this material for advertising
or promotional purposes, creating new collective works, for resale or
redistribution to servers or lists, or reuse of any copyrighted component of
this work in other works
| null | null | null |
q-bio.QM cs.LG eess.SP math.AT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Atrial Fibrillation is a heart condition characterized by erratic heart
rhythms caused by chaotic propagation of electrical impulses in the atria,
leading to numerous health complications. State-of-the-art models employ
complex algorithms that extract expert-informed features to improve diagnosis.
In this note, we demonstrate how topological features can be used to help
accurately classify single lead electrocardiograms. Via delay embeddings, we
map electrocardiograms onto high-dimensional point-clouds that convert periodic
signals to algebraically computable topological signatures. We derive features
from persistent signatures, input them to a simple machine learning algorithm,
and benchmark its performance against winning entries in the 2017 Physionet
Computing in Cardiology Challenge.
|
[
{
"created": "Mon, 25 Nov 2019 05:20:48 GMT",
"version": "v1"
},
{
"created": "Thu, 28 Nov 2019 02:12:48 GMT",
"version": "v2"
}
] |
2019-12-02
|
[
[
"Ignacio",
"Paul Samuel",
""
],
[
"Uminsky",
"David",
""
],
[
"Dunstan",
"Christopher",
""
],
[
"Escobar",
"Esteban",
""
],
[
"Trujillo",
"Luke",
""
]
] |
Atrial Fibrillation is a heart condition characterized by erratic heart rhythms caused by chaotic propagation of electrical impulses in the atria, leading to numerous health complications. State-of-the-art models employ complex algorithms that extract expert-informed features to improve diagnosis. In this note, we demonstrate how topological features can be used to help accurately classify single lead electrocardiograms. Via delay embeddings, we map electrocardiograms onto high-dimensional point-clouds that convert periodic signals to algebraically computable topological signatures. We derive features from persistent signatures, input them to a simple machine learning algorithm, and benchmark its performance against winning entries in the 2017 Physionet Computing in Cardiology Challenge.
|
0902.2708
|
Maria Barbi
|
Vincent Dahirel, Fabien Paillusson, Marie Jardat, Maria Barbi,
Jean-Marc Victor
|
Non-specific DNA-protein interaction: Why proteins can diffuse along DNA
|
4 pages, 4 figures, submitted to PRL
| null |
10.1103/PhysRevLett.102.228101
| null |
q-bio.BM cond-mat.soft physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The structure of DNA Binding Proteins enables a strong interaction with their
specific target site on DNA. However, recent single molecule experiment
reported that proteins can diffuse on DNA. This suggests that the interactions
between proteins and DNA play a role during the target search even far from the
specific site. It is unclear how these non-specific interactions optimize the
search process, and how the protein structure comes into play. Each nucleotide
being negatively charged, one may think that the positive surface of DNA-BPs
should electrostatically collapse onto DNA. Here we show by means of Monte
Carlo simulations and analytical calculations that a counter-intuitive
repulsion between the two oppositely charged macromolecules exists at a
nanometer range. We also show that this repulsion is due to a local increase of
the osmotic pressure exerted by the ions which are trapped at the interface.
For the concave shape of DNA-BPs, and for realistic protein charge densities,
we find that the repulsion pushes the protein in a free energy minimum at a
distance from DNA. As a consequence, a favourable path exists along which
proteins can slide without interacting with the DNA bases. When a protein
encounters its target, the osmotic barrier is completely counter-balanced by
the H-bond interaction, thus enabling the sequence recognition.
|
[
{
"created": "Mon, 16 Feb 2009 15:31:56 GMT",
"version": "v1"
}
] |
2015-05-13
|
[
[
"Dahirel",
"Vincent",
""
],
[
"Paillusson",
"Fabien",
""
],
[
"Jardat",
"Marie",
""
],
[
"Barbi",
"Maria",
""
],
[
"Victor",
"Jean-Marc",
""
]
] |
The structure of DNA Binding Proteins enables a strong interaction with their specific target site on DNA. However, recent single molecule experiment reported that proteins can diffuse on DNA. This suggests that the interactions between proteins and DNA play a role during the target search even far from the specific site. It is unclear how these non-specific interactions optimize the search process, and how the protein structure comes into play. Each nucleotide being negatively charged, one may think that the positive surface of DNA-BPs should electrostatically collapse onto DNA. Here we show by means of Monte Carlo simulations and analytical calculations that a counter-intuitive repulsion between the two oppositely charged macromolecules exists at a nanometer range. We also show that this repulsion is due to a local increase of the osmotic pressure exerted by the ions which are trapped at the interface. For the concave shape of DNA-BPs, and for realistic protein charge densities, we find that the repulsion pushes the protein in a free energy minimum at a distance from DNA. As a consequence, a favourable path exists along which proteins can slide without interacting with the DNA bases. When a protein encounters its target, the osmotic barrier is completely counter-balanced by the H-bond interaction, thus enabling the sequence recognition.
|
1602.01743
|
Jing Yang
|
Jing Yang, Christopher A. Penfold, Murray R. Grant, Magnus Rattray
|
Inferring the perturbation time from biological time course data
|
63 pages, 20 figures, paper submitted to Bioinformatics
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Time course data are often used to study the changes to a biological process
after perturbation. Statistical methods have been developed to determine
whether such a perturbation induces changes over time, e.g. comparing a
perturbed and unperturbed time course dataset to uncover differences. However,
existing methods do not provide a principled statistical approach to identify
the specific time when the two time course datasets first begin to diverge
after a perturbation; we call this the perturbation time. Estimation of the
perturbation time for different variables in a biological process allows us to
identify the sequence of events following a perturbation and therefore provides
valuable insights into likely causal relationships.
In this paper, we propose a Bayesian method to infer the perturbation time
given time course data from a wild-type and perturbed system. We use a
non-parametric approach based on Gaussian Process regression. We derive a
probabilistic model of noise-corrupted and replicated time course data coming
from the same profile before the perturbation time and diverging after the
perturbation time. The likelihood function can be worked out exactly for this
model and the posterior distribution of the perturbation time is obtained by a
simple histogram approach, without recourse to complex approximate inference
algorithms. We validate the method on simulated data and apply it to study the
transcriptional change occurring in Arabidopsis following inoculation with P.
syringae pv. tomato DC3000 versus the disarmed strain DC3000hrpA.
An R package, DEtime, implementing the method is available at
https://github.com/ManchesterBioinference/DEtime along with the data and code
required to reproduce all the results.
|
[
{
"created": "Thu, 4 Feb 2016 16:55:36 GMT",
"version": "v1"
}
] |
2016-02-05
|
[
[
"Yang",
"Jing",
""
],
[
"Penfold",
"Christopher A.",
""
],
[
"Grant",
"Murray R.",
""
],
[
"Rattray",
"Magnus",
""
]
] |
Time course data are often used to study the changes to a biological process after perturbation. Statistical methods have been developed to determine whether such a perturbation induces changes over time, e.g. comparing a perturbed and unperturbed time course dataset to uncover differences. However, existing methods do not provide a principled statistical approach to identify the specific time when the two time course datasets first begin to diverge after a perturbation; we call this the perturbation time. Estimation of the perturbation time for different variables in a biological process allows us to identify the sequence of events following a perturbation and therefore provides valuable insights into likely causal relationships. In this paper, we propose a Bayesian method to infer the perturbation time given time course data from a wild-type and perturbed system. We use a non-parametric approach based on Gaussian Process regression. We derive a probabilistic model of noise-corrupted and replicated time course data coming from the same profile before the perturbation time and diverging after the perturbation time. The likelihood function can be worked out exactly for this model and the posterior distribution of the perturbation time is obtained by a simple histogram approach, without recourse to complex approximate inference algorithms. We validate the method on simulated data and apply it to study the transcriptional change occurring in Arabidopsis following inoculation with P. syringae pv. tomato DC3000 versus the disarmed strain DC3000hrpA. An R package, DEtime, implementing the method is available at https://github.com/ManchesterBioinference/DEtime along with the data and code required to reproduce all the results.
|
1812.03406
|
Breno de Oliveira Ferraz
|
D. Bazeia, B.F. de Oliveira, A. Szolnoki
|
Phase transitions in dependence of apex predator decaying ratio in a
cyclic dominant system
|
version to appear in EPL. 7 pages, 7 figures
|
EPL 124 (2018) 68001
|
10.1209/0295-5075/124/68001
| null |
q-bio.PE cond-mat.stat-mech physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Cyclic dominant systems, like rock-paper-scissors game, are frequently used
to explain biodiversity in nature, where mobility, reproduction and
intransitive competition are on stage to provide the coexistence of
competitors. A significantly new situation emerges if we introduce an apex
predator who can superior all members of the mentioned three-species system. In
the latter case the evolution may terminate into three qualitatively different
destinations depending on the apex predator decaying ratio $q$. In particular,
the whole population goes extinct or all four species survive or only the
original three-species system remains alive as we vary the control parameter.
These solutions are separated by a discontinuous and a continuous phase
transitions at critical $q$ values. Our results highlight that cyclic dominant
competition can offer a stable way to survive even in a predator-prey-like
system that can be maintained for large interval of critical parameter values.
|
[
{
"created": "Sat, 8 Dec 2018 23:50:39 GMT",
"version": "v1"
}
] |
2019-01-08
|
[
[
"Bazeia",
"D.",
""
],
[
"de Oliveira",
"B. F.",
""
],
[
"Szolnoki",
"A.",
""
]
] |
Cyclic dominant systems, like rock-paper-scissors game, are frequently used to explain biodiversity in nature, where mobility, reproduction and intransitive competition are on stage to provide the coexistence of competitors. A significantly new situation emerges if we introduce an apex predator who can superior all members of the mentioned three-species system. In the latter case the evolution may terminate into three qualitatively different destinations depending on the apex predator decaying ratio $q$. In particular, the whole population goes extinct or all four species survive or only the original three-species system remains alive as we vary the control parameter. These solutions are separated by a discontinuous and a continuous phase transitions at critical $q$ values. Our results highlight that cyclic dominant competition can offer a stable way to survive even in a predator-prey-like system that can be maintained for large interval of critical parameter values.
|
1911.04329
|
\'Alvaro Garc\'ia L\'opez
|
Irina Bashkirtseva, Lev Ryashko, \'Alvaro G. L\'opez, Jesus M. Seoane,
Miguel A. F. Sanju\'an
|
Tumor stabilization induced by T-cell recruitment fluctuations
| null | null |
10.1142/S0218127420501795
| null |
q-bio.OT nlin.CD
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The influence of random fluctuations on the recruitment of effector cells
towards a tumor is studied by means of a stochastic mathematical model.
Aggressively growing tumors are confronted against varying intensities of the
cell-mediated immune response for which chaotic and periodic oscillations
coexist together with stable tumor dynamics. A thorough parametric analysis of
the noise-induced transition from this oscillatory regime to complete tumor
dominance is carried out. A hysteresis phenomenon is uncovered, which
stabilizes the tumor at its carrying capacity and drives the healthy and the
immune cell populations to their extinction. Furthermore, it is shown that near
a crisis bifurcation such transitions occur under weak noise intensities.
Finally, the corresponding noise-induced chaos-order transformation is analyzed
and discussed in detail.
|
[
{
"created": "Thu, 7 Nov 2019 13:37:16 GMT",
"version": "v1"
},
{
"created": "Fri, 24 Jan 2020 11:02:39 GMT",
"version": "v2"
}
] |
2020-10-28
|
[
[
"Bashkirtseva",
"Irina",
""
],
[
"Ryashko",
"Lev",
""
],
[
"López",
"Álvaro G.",
""
],
[
"Seoane",
"Jesus M.",
""
],
[
"Sanjuán",
"Miguel A. F.",
""
]
] |
The influence of random fluctuations on the recruitment of effector cells towards a tumor is studied by means of a stochastic mathematical model. Aggressively growing tumors are confronted against varying intensities of the cell-mediated immune response for which chaotic and periodic oscillations coexist together with stable tumor dynamics. A thorough parametric analysis of the noise-induced transition from this oscillatory regime to complete tumor dominance is carried out. A hysteresis phenomenon is uncovered, which stabilizes the tumor at its carrying capacity and drives the healthy and the immune cell populations to their extinction. Furthermore, it is shown that near a crisis bifurcation such transitions occur under weak noise intensities. Finally, the corresponding noise-induced chaos-order transformation is analyzed and discussed in detail.
|
2005.12852
|
Monjoy Saha
|
Monjoy Saha, Amit Kumar Ray, Swapan Kumar Basu
|
3D CA model of tumor-induced angiogenesis
|
International Conference on Modeling and Simulation of Diffusive
Processes and Applications, 2012, Page 170-174
| null | null | null |
q-bio.OT cs.CE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Tumor-induced angiogenesis is the formation of new sprouts from preexisting
nearby parent blood vessels. Computationally, tumor-induced angiogenesis can be
modeled using cellular automata (CA), partial differential equations, etc. In
this present study, a realistic physiological approach has been made to model
the process of angiogenesis by using 3D CA model. CA technique uses various
neighborhoods like Von-Neumann neighborhood, Moore neighborhood, and Margolus
neighborhood. In our model Von-Neumann neighborhood has used for distribution
of some significant chemical and non-chemical tumor angiogenic factors like
vascular endothelial growth factor, endothelial cells, O2, extracellular
matrix, fibronectin, etc., and Moore neighborhood is used for distribution of
matrix metalloproteinase. In vivo tumor environment all the factors are not
distributed equally in the extracellular matrix. Distributions of those
chemical and nonchemical factors depend on their source, nature and function.
To keep similarity with the biological tumor environment, we have formulated
initial distributions of the chemical and non-chemical factors accordingly. We
have started the simulation in MATLAB with this initial distribution. Number of
sprouts randomly varies from one run to another. We observed that sprouts are
not originating from the same locations in each simulation. A sprout has high
sensitivity of VEGF and fibronectin concentrations. sVEGFR-1 always tries to
regress the sprout. When two or more sprouts come closer, they merge with each
other leading to anastomosis. Sufficient number of tip cells may cause sprout
towards tumor.
|
[
{
"created": "Mon, 25 May 2020 03:50:24 GMT",
"version": "v1"
}
] |
2020-05-27
|
[
[
"Saha",
"Monjoy",
""
],
[
"Ray",
"Amit Kumar",
""
],
[
"Basu",
"Swapan Kumar",
""
]
] |
Tumor-induced angiogenesis is the formation of new sprouts from preexisting nearby parent blood vessels. Computationally, tumor-induced angiogenesis can be modeled using cellular automata (CA), partial differential equations, etc. In this present study, a realistic physiological approach has been made to model the process of angiogenesis by using 3D CA model. CA technique uses various neighborhoods like Von-Neumann neighborhood, Moore neighborhood, and Margolus neighborhood. In our model Von-Neumann neighborhood has used for distribution of some significant chemical and non-chemical tumor angiogenic factors like vascular endothelial growth factor, endothelial cells, O2, extracellular matrix, fibronectin, etc., and Moore neighborhood is used for distribution of matrix metalloproteinase. In vivo tumor environment all the factors are not distributed equally in the extracellular matrix. Distributions of those chemical and nonchemical factors depend on their source, nature and function. To keep similarity with the biological tumor environment, we have formulated initial distributions of the chemical and non-chemical factors accordingly. We have started the simulation in MATLAB with this initial distribution. Number of sprouts randomly varies from one run to another. We observed that sprouts are not originating from the same locations in each simulation. A sprout has high sensitivity of VEGF and fibronectin concentrations. sVEGFR-1 always tries to regress the sprout. When two or more sprouts come closer, they merge with each other leading to anastomosis. Sufficient number of tip cells may cause sprout towards tumor.
|
2311.13901
|
Ute Rogner
|
Chantal B\'ecourt (IC UM3 (UMR 8104 / U1016)), Sandrine Luce (IC UM3
(UMR 8104 / U1016)), Ute C Rogner (IC UM3 (UMR 8104 / U1016)), Christian
Boitard (IC UM3 (UMR 8104 / U1016))
|
Differential action of TIGIT on islet and peripheral nerve autoimmunity
in the NOD mouse
|
Raw data and statistical analysis can be obtained from the
corresponding author
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We previously demonstrated that the abrogation of the ICOS pathway prevents
type 1 diabetes development in the Non Obese Diabetic (NOD) mouse, but results
in a CD4+ T-cell dependent autoimmune neuromyopathy in aged mice. Pancreatic
islet infiltrates in conventional NOD mice and neuromuscular infiltrates in
Icosl-/- NOD mice have in common that they exhibit a strong enrichment in
CD4+TIGIT+ T-cells, whilst TIGIT expression in the peripheral CD4+ T-cells is
limited to the CD4+FoxP3+ T-cell population.When deleting Tigit on the NOD
background, diabetes incidence was found increased. Peripheral CD4+CD226+
effector T-cells exhibited an increased frequency of IL-17 producing
CD4+CD226+RORgt+ T-cells versus a decreased frequency of IFN$\gamma$-producing
CD4+CD226+Tbet+ T-cells. ICOS is expressed in both CD4+FoxP3+ and CD4+CD226+
splenic T-cell subsets. Icosl deletion leads to a decrease of CD4+FoxP3+ cells,
with decrease of PD1 but increase of ICOS and CCRX3. Also in the Icosl-/-
model, CD4+CD226+ T-cells are decreased by Tigit deletion, and showed an
increase of CD4+CD226+RORgt+ T-cells and a decrease of CD4+CD226+Tbet+
T-cells.However, deletion of Tigit in aged Icosl-/- NOD mice population did not
increase the incidence of the autoimmune neuromyopathy observed in Icosl-/- NOD
mice. Interestingly, the upregulation of CD4+CD226+RORgt+ T-cells was partly
rescued.We conclude from our study that both Icosl and Tigit deletions on the
NOD background lead to a shift between the ratio of IFN$\gamma$ and
IL-17-producing CD4+CD226+ effector cells. The ICOS-dependent neuromyopathy
development remains dominant and is not further altered in the absence of
TIGIT.
|
[
{
"created": "Thu, 23 Nov 2023 10:33:22 GMT",
"version": "v1"
}
] |
2023-11-27
|
[
[
"Bécourt",
"Chantal",
"",
"IC UM3"
],
[
"Luce",
"Sandrine",
"",
"IC UM3"
],
[
"Rogner",
"Ute C",
"",
"IC UM3"
],
[
"Boitard",
"Christian",
"",
"IC UM3"
]
] |
We previously demonstrated that the abrogation of the ICOS pathway prevents type 1 diabetes development in the Non Obese Diabetic (NOD) mouse, but results in a CD4+ T-cell dependent autoimmune neuromyopathy in aged mice. Pancreatic islet infiltrates in conventional NOD mice and neuromuscular infiltrates in Icosl-/- NOD mice have in common that they exhibit a strong enrichment in CD4+TIGIT+ T-cells, whilst TIGIT expression in the peripheral CD4+ T-cells is limited to the CD4+FoxP3+ T-cell population.When deleting Tigit on the NOD background, diabetes incidence was found increased. Peripheral CD4+CD226+ effector T-cells exhibited an increased frequency of IL-17 producing CD4+CD226+RORgt+ T-cells versus a decreased frequency of IFN$\gamma$-producing CD4+CD226+Tbet+ T-cells. ICOS is expressed in both CD4+FoxP3+ and CD4+CD226+ splenic T-cell subsets. Icosl deletion leads to a decrease of CD4+FoxP3+ cells, with decrease of PD1 but increase of ICOS and CCRX3. Also in the Icosl-/- model, CD4+CD226+ T-cells are decreased by Tigit deletion, and showed an increase of CD4+CD226+RORgt+ T-cells and a decrease of CD4+CD226+Tbet+ T-cells.However, deletion of Tigit in aged Icosl-/- NOD mice population did not increase the incidence of the autoimmune neuromyopathy observed in Icosl-/- NOD mice. Interestingly, the upregulation of CD4+CD226+RORgt+ T-cells was partly rescued.We conclude from our study that both Icosl and Tigit deletions on the NOD background lead to a shift between the ratio of IFN$\gamma$ and IL-17-producing CD4+CD226+ effector cells. The ICOS-dependent neuromyopathy development remains dominant and is not further altered in the absence of TIGIT.
|
1306.3825
|
Jacek Tyburczyk
|
Zdzislaw Burda, Jennifer Kornelsen, Maciej A. Nowak, Bartosz Porebski,
Uta Sboto-Frankenstein, Boguslaw Tomanek, Jacek Tyburczyk
|
Collective Correlations of Brodmann Areas fMRI Study with RMT-Denoising
| null | null |
10.5506/APhysPolB.44.1243
| null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study collective behavior of Brodmann regions of human cerebral cortex
using functional Magnetic Resonance Imaging (fMRI) and Random Matrix Theory
(RMT). The raw fMRI data is mapped onto the cortex regions corresponding to the
Brodmann areas with the aid of the Talairach coordinates. Principal Component
Analysis (PCA) of the Pearson correlation matrix for 41 different Brodmann
regions is carried out to determine their collective activity in the idle state
and in the active state stimulated by tapping. The collective brain activity is
identified through the statistical analysis of the eigenvectors to the largest
eigenvalues of the Pearson correlation matrix. The leading eigenvectors have a
large participation ratio. This indicates that several Broadmann regions
collectively give rise to the brain activity associated with these
eigenvectors. We apply random matrix theory to interpret the underlying
multivariate data.
|
[
{
"created": "Mon, 17 Jun 2013 12:01:13 GMT",
"version": "v1"
}
] |
2015-06-16
|
[
[
"Burda",
"Zdzislaw",
""
],
[
"Kornelsen",
"Jennifer",
""
],
[
"Nowak",
"Maciej A.",
""
],
[
"Porebski",
"Bartosz",
""
],
[
"Sboto-Frankenstein",
"Uta",
""
],
[
"Tomanek",
"Boguslaw",
""
],
[
"Tyburczyk",
"Jacek",
""
]
] |
We study collective behavior of Brodmann regions of human cerebral cortex using functional Magnetic Resonance Imaging (fMRI) and Random Matrix Theory (RMT). The raw fMRI data is mapped onto the cortex regions corresponding to the Brodmann areas with the aid of the Talairach coordinates. Principal Component Analysis (PCA) of the Pearson correlation matrix for 41 different Brodmann regions is carried out to determine their collective activity in the idle state and in the active state stimulated by tapping. The collective brain activity is identified through the statistical analysis of the eigenvectors to the largest eigenvalues of the Pearson correlation matrix. The leading eigenvectors have a large participation ratio. This indicates that several Broadmann regions collectively give rise to the brain activity associated with these eigenvectors. We apply random matrix theory to interpret the underlying multivariate data.
|
1607.04435
|
Jose A. Cuesta
|
Jos\'e A. Cuesta and Susanna Manrubia
|
Enumerating secondary structures and structural moieties for circular
RNAs
|
18 pages, 2 figures, requires svjour3.cls
|
Journal of Theoretical Biology 419, 375-382 (2017)
|
10.1016/j.jtbi.2017.02.024
| null |
q-bio.PE physics.bio-ph q-bio.BM q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A quantitative characterization of the relationship between molecular
sequence and structure is essential to improve our understanding of how
function emerges. This particular genotype-phenotype map has been often studied
in the context of RNA sequences, with the folded configurations standing as a
proxy for the phenotype. Here, we count the secondary structures of circular
RNAs of length $n$ and calculate the asymptotic distributions of different
structural moieties, such as stems or hairpin loops, by means of symbolic
combinatorics. Circular RNAs differ in essential ways from their linear
counterparts. From the mathematical viewpoint, the enumeration of the
corresponding secondary structures demands the use of combinatorial techniques
additional to those used for linear RNAs. The asymptotic number of secondary
structures for circular RNAs grows as $a^nn^{-5/2}$, with a depending on
particular constraints applied to the secondary structure. The abundance of any
structural moiety is normally distributed in the limit $n\to\infty$, with a
mean and a variance that increase linearly with $n$.
|
[
{
"created": "Fri, 15 Jul 2016 09:50:02 GMT",
"version": "v1"
},
{
"created": "Mon, 20 Feb 2017 18:04:11 GMT",
"version": "v2"
}
] |
2017-04-20
|
[
[
"Cuesta",
"José A.",
""
],
[
"Manrubia",
"Susanna",
""
]
] |
A quantitative characterization of the relationship between molecular sequence and structure is essential to improve our understanding of how function emerges. This particular genotype-phenotype map has been often studied in the context of RNA sequences, with the folded configurations standing as a proxy for the phenotype. Here, we count the secondary structures of circular RNAs of length $n$ and calculate the asymptotic distributions of different structural moieties, such as stems or hairpin loops, by means of symbolic combinatorics. Circular RNAs differ in essential ways from their linear counterparts. From the mathematical viewpoint, the enumeration of the corresponding secondary structures demands the use of combinatorial techniques additional to those used for linear RNAs. The asymptotic number of secondary structures for circular RNAs grows as $a^nn^{-5/2}$, with a depending on particular constraints applied to the secondary structure. The abundance of any structural moiety is normally distributed in the limit $n\to\infty$, with a mean and a variance that increase linearly with $n$.
|
2105.01358
|
Apoorv Kishore
|
Apoorv Kishore, Vivek Saraswat, Udayan Ganguly
|
Simplified Klinokinesis using Spiking Neural Networks for
Resource-Constrained Navigation on the Neuromorphic Processor Loihi
| null | null | null | null |
q-bio.NC cs.NE cs.SY eess.SY
|
http://creativecommons.org/licenses/by/4.0/
|
C. elegans shows chemotaxis using klinokinesis where the worm senses the
concentration based on a single concentration sensor to compute the
concentration gradient to perform foraging through gradient ascent/descent
towards the target concentration followed by contour tracking. The biomimetic
implementation requires complex neurons with multiple ion channel dynamics as
well as interneurons for control. While this is a key capability of autonomous
robots, its implementation on energy-efficient neuromorphic hardware like
Intel's Loihi requires adaptation of the network to hardware-specific
constraints, which has not been achieved. In this paper, we demonstrate the
adaptation of chemotaxis based on klinokinesis to Loihi by implementing
necessary neuronal dynamics with only LIF neurons as well as a complete
spike-based implementation of all functions e.g. Heaviside function and
subtractions. Our results show that Loihi implementation is equivalent to the
software counterpart on Python in terms of performance - both during foraging
and contour tracking. The Loihi results are also resilient in noisy
environments. Thus, we demonstrate a successful adaptation of chemotaxis on
Loihi - which can now be combined with the rich array of SNN blocks for SNN
based complex robotic control.
|
[
{
"created": "Tue, 4 May 2021 08:26:46 GMT",
"version": "v1"
}
] |
2021-05-05
|
[
[
"Kishore",
"Apoorv",
""
],
[
"Saraswat",
"Vivek",
""
],
[
"Ganguly",
"Udayan",
""
]
] |
C. elegans shows chemotaxis using klinokinesis where the worm senses the concentration based on a single concentration sensor to compute the concentration gradient to perform foraging through gradient ascent/descent towards the target concentration followed by contour tracking. The biomimetic implementation requires complex neurons with multiple ion channel dynamics as well as interneurons for control. While this is a key capability of autonomous robots, its implementation on energy-efficient neuromorphic hardware like Intel's Loihi requires adaptation of the network to hardware-specific constraints, which has not been achieved. In this paper, we demonstrate the adaptation of chemotaxis based on klinokinesis to Loihi by implementing necessary neuronal dynamics with only LIF neurons as well as a complete spike-based implementation of all functions e.g. Heaviside function and subtractions. Our results show that Loihi implementation is equivalent to the software counterpart on Python in terms of performance - both during foraging and contour tracking. The Loihi results are also resilient in noisy environments. Thus, we demonstrate a successful adaptation of chemotaxis on Loihi - which can now be combined with the rich array of SNN blocks for SNN based complex robotic control.
|
1705.04942
|
Adam Mahdi
|
Adam Mahdi, Dragana Nikolic, Anthony A. Birch, Mette S. Olufsen,
Ronney B. Panerai, David M. Simpson, Stephen J. Payne
|
Increased blood pressure variability upon standing up improves
reproducibility of cerebral autoregulation indices
|
4 figures
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Dynamic cerebral autoregulation, that is the transient response of cerebral
blood flow to changes in arterial blood pressure, is currently assessed using a
variety of different time series methods and data collection protocols. In the
continuing absence of a gold standard for the study of cerebral autoregulation
it is unclear to what extent does the assessment depend on the choice of a
computational method and protocol. We use continuous measurements of blood
pressure and cerebral blood flow velocity in the middle cerebral artery from
the cohorts of 18 normotensive subjects performing sit-to-stand manoeuvre. We
estimate cerebral autoregulation using a wide variety of black-box approaches
(ARI, Mx, Sx, Dx, FIR and ARX) and compare them in the context of
reproducibility and variability. For all autoregulation indices, considered
here, the ICC was greater during the standing protocol, however, it was
significantly greater (Fisher's Z-test) for Mx (p < 0.03), Sx (p<0.003)$ and Dx
(p<0.03). In the specific case of the sit-to-stand manoeuvre, measurements
taken immediately after standing up greatly improve the reproducibility of the
autoregulation coefficients. This is generally coupled with an increase of the
within-group spread of the estimates.
|
[
{
"created": "Sun, 14 May 2017 09:57:04 GMT",
"version": "v1"
}
] |
2017-05-16
|
[
[
"Mahdi",
"Adam",
""
],
[
"Nikolic",
"Dragana",
""
],
[
"Birch",
"Anthony A.",
""
],
[
"Olufsen",
"Mette S.",
""
],
[
"Panerai",
"Ronney B.",
""
],
[
"Simpson",
"David M.",
""
],
[
"Payne",
"Stephen J.",
""
]
] |
Dynamic cerebral autoregulation, that is the transient response of cerebral blood flow to changes in arterial blood pressure, is currently assessed using a variety of different time series methods and data collection protocols. In the continuing absence of a gold standard for the study of cerebral autoregulation it is unclear to what extent does the assessment depend on the choice of a computational method and protocol. We use continuous measurements of blood pressure and cerebral blood flow velocity in the middle cerebral artery from the cohorts of 18 normotensive subjects performing sit-to-stand manoeuvre. We estimate cerebral autoregulation using a wide variety of black-box approaches (ARI, Mx, Sx, Dx, FIR and ARX) and compare them in the context of reproducibility and variability. For all autoregulation indices, considered here, the ICC was greater during the standing protocol, however, it was significantly greater (Fisher's Z-test) for Mx (p < 0.03), Sx (p<0.003)$ and Dx (p<0.03). In the specific case of the sit-to-stand manoeuvre, measurements taken immediately after standing up greatly improve the reproducibility of the autoregulation coefficients. This is generally coupled with an increase of the within-group spread of the estimates.
|
2302.06403
|
Xu Ji
|
Xu Ji, Eric Elmoznino, George Deane, Axel Constant, Guillaume Dumas,
Guillaume Lajoie, Jonathan Simon, Yoshua Bengio
|
Sources of Richness and Ineffability for Phenomenally Conscious States
| null | null | null | null |
q-bio.NC cs.AI
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Conscious states (states that there is something it is like to be in) seem
both rich or full of detail, and ineffable or hard to fully describe or recall.
The problem of ineffability, in particular, is a longstanding issue in
philosophy that partly motivates the explanatory gap: the belief that
consciousness cannot be reduced to underlying physical processes. Here, we
provide an information theoretic dynamical systems perspective on the richness
and ineffability of consciousness. In our framework, the richness of conscious
experience corresponds to the amount of information in a conscious state and
ineffability corresponds to the amount of information lost at different stages
of processing. We describe how attractor dynamics in working memory would
induce impoverished recollections of our original experiences, how the discrete
symbolic nature of language is insufficient for describing the rich and
high-dimensional structure of experiences, and how similarity in the cognitive
function of two individuals relates to improved communicability of their
experiences to each other. While our model may not settle all questions
relating to the explanatory gap, it makes progress toward a fully physicalist
explanation of the richness and ineffability of conscious experience: two
important aspects that seem to be part of what makes qualitative character so
puzzling.
|
[
{
"created": "Mon, 13 Feb 2023 14:41:04 GMT",
"version": "v1"
},
{
"created": "Wed, 1 Mar 2023 19:38:55 GMT",
"version": "v2"
},
{
"created": "Mon, 13 Mar 2023 01:06:34 GMT",
"version": "v3"
},
{
"created": "Fri, 17 Mar 2023 03:44:36 GMT",
"version": "v4"
},
{
"created": "Wed, 21 Jun 2023 01:41:09 GMT",
"version": "v5"
}
] |
2023-06-22
|
[
[
"Ji",
"Xu",
""
],
[
"Elmoznino",
"Eric",
""
],
[
"Deane",
"George",
""
],
[
"Constant",
"Axel",
""
],
[
"Dumas",
"Guillaume",
""
],
[
"Lajoie",
"Guillaume",
""
],
[
"Simon",
"Jonathan",
""
],
[
"Bengio",
"Yoshua",
""
]
] |
Conscious states (states that there is something it is like to be in) seem both rich or full of detail, and ineffable or hard to fully describe or recall. The problem of ineffability, in particular, is a longstanding issue in philosophy that partly motivates the explanatory gap: the belief that consciousness cannot be reduced to underlying physical processes. Here, we provide an information theoretic dynamical systems perspective on the richness and ineffability of consciousness. In our framework, the richness of conscious experience corresponds to the amount of information in a conscious state and ineffability corresponds to the amount of information lost at different stages of processing. We describe how attractor dynamics in working memory would induce impoverished recollections of our original experiences, how the discrete symbolic nature of language is insufficient for describing the rich and high-dimensional structure of experiences, and how similarity in the cognitive function of two individuals relates to improved communicability of their experiences to each other. While our model may not settle all questions relating to the explanatory gap, it makes progress toward a fully physicalist explanation of the richness and ineffability of conscious experience: two important aspects that seem to be part of what makes qualitative character so puzzling.
|
1404.5725
|
Ying Zhang
|
Ying Zhang
|
Application of signal processing techniques in the assessment of
clinical risks in preterm infants
| null | null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Preterm infants with very low birth weight suffer from a high risk of
intra-ventricular hemorrhage(IVH) and other serious diseases. To improve the
clinical risk assessment of preterm infants and develop potential clinically
makers for the adverse outcome, the first part of the paper develops the
frequency spectral analysis on the non-invasively measured heart rate
variability, blood pressure variability and cerebral near-infrared spectroscopy
measures. Moderate and high correlations with the clinical risk index for
babies were identified from various spectral measures of arterial baroreflex
and cerebral autoregulation functions. It was also observed that the
cross-spectral transfer function analysis of cerebral NIRS and arterial blood
pressure was able to provide a number of parameters that were potentially
useful for distinguishing between preterm infants with or without IVH.
Furthermore, the detrended fluctuation analysis that quantifies the fractal
correlation properties of physiological signals has been examined, to determine
whether it could derive markers for the identification of preterm infants with
IVH. Cardiac output(CO) and total peripheral resistance(TPR) are two important
parameters of the cardiovascular system. Measurement of these two parameters
can provide valuable information for the assessment and management of patients
needing intensive care, including preterm infants in the neonatal intensive
care unit. To further assess the changes in CO and TPR in the preterm infants,
the multivariate regression model based on the useful features from ABP method
was used to improve the accuracy and robustness of the estimation. The
combination of signal analysis and multivariate regression model in estimation
of CO has produced some outcomes, and in the future, more effort should be
involved in this kind of research to improve the prediction of serious diseases
in preterm infants.
|
[
{
"created": "Wed, 23 Apr 2014 07:18:51 GMT",
"version": "v1"
}
] |
2014-04-24
|
[
[
"Zhang",
"Ying",
""
]
] |
Preterm infants with very low birth weight suffer from a high risk of intra-ventricular hemorrhage(IVH) and other serious diseases. To improve the clinical risk assessment of preterm infants and develop potential clinically makers for the adverse outcome, the first part of the paper develops the frequency spectral analysis on the non-invasively measured heart rate variability, blood pressure variability and cerebral near-infrared spectroscopy measures. Moderate and high correlations with the clinical risk index for babies were identified from various spectral measures of arterial baroreflex and cerebral autoregulation functions. It was also observed that the cross-spectral transfer function analysis of cerebral NIRS and arterial blood pressure was able to provide a number of parameters that were potentially useful for distinguishing between preterm infants with or without IVH. Furthermore, the detrended fluctuation analysis that quantifies the fractal correlation properties of physiological signals has been examined, to determine whether it could derive markers for the identification of preterm infants with IVH. Cardiac output(CO) and total peripheral resistance(TPR) are two important parameters of the cardiovascular system. Measurement of these two parameters can provide valuable information for the assessment and management of patients needing intensive care, including preterm infants in the neonatal intensive care unit. To further assess the changes in CO and TPR in the preterm infants, the multivariate regression model based on the useful features from ABP method was used to improve the accuracy and robustness of the estimation. The combination of signal analysis and multivariate regression model in estimation of CO has produced some outcomes, and in the future, more effort should be involved in this kind of research to improve the prediction of serious diseases in preterm infants.
|
2402.01942
|
Michael Levet
|
Lora Bailey, Heather Smith Blake, Garner Cochran, Nathan Fox, Michael
Levet, Reem Mahmoud, Inne Singgih, Grace Stadnyk, Alexander Wiedemann
|
Pairwise Rearrangement is Fixed-Parameter Tractable in the Single
Cut-and-Join Model
|
Full version of paper to appear in SWAT 2024; arXiv admin note: text
overlap with arXiv:2305.01851
| null | null | null |
q-bio.GN cs.DS math.CO
|
http://creativecommons.org/licenses/by/4.0/
|
Genome rearrangement is a common model for molecular evolution. In this
paper, we consider the Pairwise Rearrangement problem, which takes as input two
genomes and asks for the number of minimum-length sequences of permissible
operations transforming the first genome into the second. In the Single
Cut-and-Join model (Bergeron, Medvedev, & Stoye, J. Comput. Biol. 2010),
Pairwise Rearrangement is $\#\textsf{P}$-complete (Bailey, et. al., COCOON
2023), which implies that exact sampling is intractable. In order to cope with
this intractability, we investigate the parameterized complexity of this
problem. We exhibit a fixed-parameter tractable algorithm with respect to the
number of components in the adjacency graph that are not cycles of length $2$
or paths of length $1$. As a consequence, we obtain that Pairwise Rearrangement
in the Single Cut-and-Join model is fixed-parameter tractable by distance. Our
results suggest that the number of nontrivial components in the adjacency graph
serves as the key obstacle for efficient sampling.
|
[
{
"created": "Fri, 2 Feb 2024 22:36:21 GMT",
"version": "v1"
},
{
"created": "Thu, 14 Mar 2024 20:44:21 GMT",
"version": "v2"
},
{
"created": "Tue, 23 Apr 2024 20:42:28 GMT",
"version": "v3"
}
] |
2024-04-25
|
[
[
"Bailey",
"Lora",
""
],
[
"Blake",
"Heather Smith",
""
],
[
"Cochran",
"Garner",
""
],
[
"Fox",
"Nathan",
""
],
[
"Levet",
"Michael",
""
],
[
"Mahmoud",
"Reem",
""
],
[
"Singgih",
"Inne",
""
],
[
"Stadnyk",
"Grace",
""
],
[
"Wiedemann",
"Alexander",
""
]
] |
Genome rearrangement is a common model for molecular evolution. In this paper, we consider the Pairwise Rearrangement problem, which takes as input two genomes and asks for the number of minimum-length sequences of permissible operations transforming the first genome into the second. In the Single Cut-and-Join model (Bergeron, Medvedev, & Stoye, J. Comput. Biol. 2010), Pairwise Rearrangement is $\#\textsf{P}$-complete (Bailey, et. al., COCOON 2023), which implies that exact sampling is intractable. In order to cope with this intractability, we investigate the parameterized complexity of this problem. We exhibit a fixed-parameter tractable algorithm with respect to the number of components in the adjacency graph that are not cycles of length $2$ or paths of length $1$. As a consequence, we obtain that Pairwise Rearrangement in the Single Cut-and-Join model is fixed-parameter tractable by distance. Our results suggest that the number of nontrivial components in the adjacency graph serves as the key obstacle for efficient sampling.
|
2303.00904
|
Hanbin Lee
|
Hanbin Lee, Moo Hyuk Lee
|
Disentangling Linkage and Population Structure in Association Mapping
|
11 pages, 1 figure
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Genome-wide association study (GWAS) tests single nucleotide polymorphism
(SNP) markers across the genome to localize the underlying causal variant of a
trait. Because causal variants are seldom observed directly, a surrogate model
based on genotyped markers are widely considered. Although many methods
estimating the parameters of the surrogate model have been proposed, the
connection between the surrogate model and the true causal model is yet
investigated. In this work, we establish the connection between the surrogate
model and the true causal model. The connection shows that population structure
is accounted in GWAS by modelling the variant of interest and not the trait.
Such observation explains how environmental confounding can be partially
corrected using genetic covariates and why the previously claimed connection
between PC correction and linear mixed models is incorrect.
|
[
{
"created": "Thu, 2 Mar 2023 01:54:02 GMT",
"version": "v1"
}
] |
2023-03-03
|
[
[
"Lee",
"Hanbin",
""
],
[
"Lee",
"Moo Hyuk",
""
]
] |
Genome-wide association study (GWAS) tests single nucleotide polymorphism (SNP) markers across the genome to localize the underlying causal variant of a trait. Because causal variants are seldom observed directly, a surrogate model based on genotyped markers are widely considered. Although many methods estimating the parameters of the surrogate model have been proposed, the connection between the surrogate model and the true causal model is yet investigated. In this work, we establish the connection between the surrogate model and the true causal model. The connection shows that population structure is accounted in GWAS by modelling the variant of interest and not the trait. Such observation explains how environmental confounding can be partially corrected using genetic covariates and why the previously claimed connection between PC correction and linear mixed models is incorrect.
|
1811.12490
|
Derek Curtis
|
Derek John Curtis, Pauline Holbrook, Sarah Bew, Lynne Ford, Penny
Butler
|
Functional change in children with cerebral palsy
|
14 pages, 5 tables
| null | null | null |
q-bio.QM q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Introduction There is increasing focus on the association between trunk
control and functional abilities in children with cerebral palsy (CP). The
purpose of this study was to determine the extent of functional change in
children with CP who participated in specific trunk and head postural control
training combined with physical therapy treatment as usual (TAU).
Methods This study included 140 consecutive referrals to a centre
specialising in head and trunk postural control (Targeted Training (TT))
between 2009 and 2016. Twenty-five children discontinued therapy due to
surgery, health, family issues or poor attendance. The remaining 115 children
(46 girls, 69 boys) had a mean age of 6 y 6 mo (SD 2 y 8 mo) with participants
from all GMFCS levels. The intervention was a program of TT and ongoing TAU
with a mean duration of 11 months. Gross Motor Function Measure (GMFM),
Pediatric Evaluation of Disability Inventory functional skills, Chailey Levels
of Ability and Segmental Assessment of Trunk Control were administered before
and after the intervention.
Results There were significant improvements in all outcomes. GMFM
improvements exceeded those predicted from the published reference curves,
especially for the children with more severe cerebral palsy.
Conclusions Functional improvement exceeded the expected norm, especially in
those children with more severe gross motor function disability. The other
outcomes also showed significant improvements. These findings support the case
for further studies and, if needed, tool development to facilitate
determination of the critical elements in a combined therapy approach of TT
with TAU.
|
[
{
"created": "Fri, 9 Nov 2018 13:56:23 GMT",
"version": "v1"
}
] |
2018-12-03
|
[
[
"Curtis",
"Derek John",
""
],
[
"Holbrook",
"Pauline",
""
],
[
"Bew",
"Sarah",
""
],
[
"Ford",
"Lynne",
""
],
[
"Butler",
"Penny",
""
]
] |
Introduction There is increasing focus on the association between trunk control and functional abilities in children with cerebral palsy (CP). The purpose of this study was to determine the extent of functional change in children with CP who participated in specific trunk and head postural control training combined with physical therapy treatment as usual (TAU). Methods This study included 140 consecutive referrals to a centre specialising in head and trunk postural control (Targeted Training (TT)) between 2009 and 2016. Twenty-five children discontinued therapy due to surgery, health, family issues or poor attendance. The remaining 115 children (46 girls, 69 boys) had a mean age of 6 y 6 mo (SD 2 y 8 mo) with participants from all GMFCS levels. The intervention was a program of TT and ongoing TAU with a mean duration of 11 months. Gross Motor Function Measure (GMFM), Pediatric Evaluation of Disability Inventory functional skills, Chailey Levels of Ability and Segmental Assessment of Trunk Control were administered before and after the intervention. Results There were significant improvements in all outcomes. GMFM improvements exceeded those predicted from the published reference curves, especially for the children with more severe cerebral palsy. Conclusions Functional improvement exceeded the expected norm, especially in those children with more severe gross motor function disability. The other outcomes also showed significant improvements. These findings support the case for further studies and, if needed, tool development to facilitate determination of the critical elements in a combined therapy approach of TT with TAU.
|
1611.01692
|
Raul Isea
|
Raul Isea, Rafael Mayo-Garcia and Silvia Restrepo
|
Reverse vaccinology in Plasmodium falciparum 3D7
|
7 pages, 2 tables
|
J Immunol Tech Infect Dis (2016) 5:3
| null | null |
q-bio.GN q-bio.PE
|
http://creativecommons.org/publicdomain/zero/1.0/
|
A timely immunization can be effective against certain diseases and can save
thousands of lives. However, for some diseases it has been difficult, so far,
to develop an efficient vaccine. Malaria, a tropical disease caused by a
parasite of the genus Plasmodium, is one example. Bioinformatics has opened the
way to new lines of experimental investigation One example is reverse
vaccinology that aims to identify antigens that are capable of generating an
immune response in a given organism using in silico studies. In this study we
applied a reverse vaccinology methodology using a bioinformatics pipeline. We
obtained 45 potential linear B cells consensus epitopes from the whole genome
of P. falciparum 3D7 that can be used as candidates for malaria vaccines. The
direct implication of the results obtained is to open the way to experimentally
validate more epitopes to increase the efficiency of the available treatments
against malaria and to explore the methodology in other diseases.
|
[
{
"created": "Sat, 5 Nov 2016 19:44:21 GMT",
"version": "v1"
}
] |
2016-11-08
|
[
[
"Isea",
"Raul",
""
],
[
"Mayo-Garcia",
"Rafael",
""
],
[
"Restrepo",
"Silvia",
""
]
] |
A timely immunization can be effective against certain diseases and can save thousands of lives. However, for some diseases it has been difficult, so far, to develop an efficient vaccine. Malaria, a tropical disease caused by a parasite of the genus Plasmodium, is one example. Bioinformatics has opened the way to new lines of experimental investigation One example is reverse vaccinology that aims to identify antigens that are capable of generating an immune response in a given organism using in silico studies. In this study we applied a reverse vaccinology methodology using a bioinformatics pipeline. We obtained 45 potential linear B cells consensus epitopes from the whole genome of P. falciparum 3D7 that can be used as candidates for malaria vaccines. The direct implication of the results obtained is to open the way to experimentally validate more epitopes to increase the efficiency of the available treatments against malaria and to explore the methodology in other diseases.
|
1509.08322
|
Simon Tanaka Mr.
|
Simon Tanaka
|
Technical Report: Modelling Multiple Cell Types with Partial
Differential Equations
|
technical report, 4 pages
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Partial differential equations are a convenient way to describe reaction-
advection-diffusion processes of signalling models. If only one cell type is
present, and tissue dynamics can be neglected, the equations can be solved
directly. However, in case of multiple cell types it is not always straight
forward to integrate a continuous description of the tissue dynamics. Here, we
discuss (delayed) differentiation of cells into different cell types and
hypertrophic cell volume change upon differentiation.
|
[
{
"created": "Mon, 28 Sep 2015 13:59:14 GMT",
"version": "v1"
}
] |
2015-09-29
|
[
[
"Tanaka",
"Simon",
""
]
] |
Partial differential equations are a convenient way to describe reaction- advection-diffusion processes of signalling models. If only one cell type is present, and tissue dynamics can be neglected, the equations can be solved directly. However, in case of multiple cell types it is not always straight forward to integrate a continuous description of the tissue dynamics. Here, we discuss (delayed) differentiation of cells into different cell types and hypertrophic cell volume change upon differentiation.
|
2405.06072
|
Miriam Furst
|
Asaf Zorea, Miriam Furst
|
Contribution of Coincidence Detection to Speech Segregation in Noisy
Environments
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
This study introduces a biologically-inspired model designed to examine the
role of coincidence detection cells in speech segregation tasks. The model
consists of three stages: a time-domain cochlear model that generates
instantaneous rates of auditory nerve fibers, coincidence detection cells that
amplify neural activity synchronously with speech presence, and an optimal
spectro-temporal speech presence estimator. A comparative analysis between
speech estimation based on the firing rates of auditory nerve fibers and those
of coincidence detection cells indicates that the neural representation of
coincidence cells significantly reduces noise components, resulting in a more
distinguishable representation of speech in noise. The proposed framework
demonstrates the potential of brainstem nuclei processing in enhancing auditory
skills. Moreover, this approach can be further tested in other sensory systems
in general and within the auditory system in particular.
|
[
{
"created": "Thu, 9 May 2024 19:43:19 GMT",
"version": "v1"
}
] |
2024-05-13
|
[
[
"Zorea",
"Asaf",
""
],
[
"Furst",
"Miriam",
""
]
] |
This study introduces a biologically-inspired model designed to examine the role of coincidence detection cells in speech segregation tasks. The model consists of three stages: a time-domain cochlear model that generates instantaneous rates of auditory nerve fibers, coincidence detection cells that amplify neural activity synchronously with speech presence, and an optimal spectro-temporal speech presence estimator. A comparative analysis between speech estimation based on the firing rates of auditory nerve fibers and those of coincidence detection cells indicates that the neural representation of coincidence cells significantly reduces noise components, resulting in a more distinguishable representation of speech in noise. The proposed framework demonstrates the potential of brainstem nuclei processing in enhancing auditory skills. Moreover, this approach can be further tested in other sensory systems in general and within the auditory system in particular.
|
2011.11717
|
Onofrio M. Marag\`o
|
Laura Natali, Saga Helgadottir, Onofrio M. Marago, and Giovanni Volpe
|
Improving epidemic testing and containment strategies using machine
learning
|
11 pages, 4 figures
| null | null | null |
q-bio.PE cs.LG physics.soc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Containment of epidemic outbreaks entails great societal and economic costs.
Cost-effective containment strategies rely on efficiently identifying infected
individuals, making the best possible use of the available testing resources.
Therefore, quickly identifying the optimal testing strategy is of critical
importance. Here, we demonstrate that machine learning can be used to identify
which individuals are most beneficial to test, automatically and dynamically
adapting the testing strategy to the characteristics of the disease outbreak.
Specifically, we simulate an outbreak using the archetypal
susceptible-infectious-recovered (SIR) model and we use data about the first
confirmed cases to train a neural network that learns to make predictions about
the rest of the population. Using these prediction, we manage to contain the
outbreak more effectively and more quickly than with standard approaches.
Furthermore, we demonstrate how this method can be used also when there is a
possibility of reinfection (SIRS model) to efficiently eradicate an endemic
disease.
|
[
{
"created": "Mon, 23 Nov 2020 20:46:01 GMT",
"version": "v1"
}
] |
2020-12-01
|
[
[
"Natali",
"Laura",
""
],
[
"Helgadottir",
"Saga",
""
],
[
"Marago",
"Onofrio M.",
""
],
[
"Volpe",
"Giovanni",
""
]
] |
Containment of epidemic outbreaks entails great societal and economic costs. Cost-effective containment strategies rely on efficiently identifying infected individuals, making the best possible use of the available testing resources. Therefore, quickly identifying the optimal testing strategy is of critical importance. Here, we demonstrate that machine learning can be used to identify which individuals are most beneficial to test, automatically and dynamically adapting the testing strategy to the characteristics of the disease outbreak. Specifically, we simulate an outbreak using the archetypal susceptible-infectious-recovered (SIR) model and we use data about the first confirmed cases to train a neural network that learns to make predictions about the rest of the population. Using these prediction, we manage to contain the outbreak more effectively and more quickly than with standard approaches. Furthermore, we demonstrate how this method can be used also when there is a possibility of reinfection (SIRS model) to efficiently eradicate an endemic disease.
|
2408.00367
|
Stephanie Hicks
|
Boyi Guo, Wodan Ling, Sang Ho Kwon, Pratibha Panwar, Shila Ghazanfar,
Keri Martinowich, Stephanie C. Hicks
|
Integrating spatially-resolved transcriptomics data across tissues and
individuals: challenges and opportunities
|
16 pages, 2 figures
| null | null | null |
q-bio.GN
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Advances in spatially-resolved transcriptomics (SRT) technologies have
propelled the development of new computational analysis methods to unlock
biological insights. As the cost of generating these data decreases, these
technologies provide an exciting opportunity to create large-scale atlases that
integrate SRT data across multiple tissues, individuals, species, or phenotypes
to perform population-level analyses. Here, we describe unique challenges of
varying spatial resolutions in SRT data, as well as highlight the opportunities
for standardized preprocessing methods along with computational algorithms
amenable to atlas-scale datasets leading to improved sensitivity and
reproducibility in the future.
|
[
{
"created": "Thu, 1 Aug 2024 08:16:22 GMT",
"version": "v1"
}
] |
2024-08-02
|
[
[
"Guo",
"Boyi",
""
],
[
"Ling",
"Wodan",
""
],
[
"Kwon",
"Sang Ho",
""
],
[
"Panwar",
"Pratibha",
""
],
[
"Ghazanfar",
"Shila",
""
],
[
"Martinowich",
"Keri",
""
],
[
"Hicks",
"Stephanie C.",
""
]
] |
Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. As the cost of generating these data decreases, these technologies provide an exciting opportunity to create large-scale atlases that integrate SRT data across multiple tissues, individuals, species, or phenotypes to perform population-level analyses. Here, we describe unique challenges of varying spatial resolutions in SRT data, as well as highlight the opportunities for standardized preprocessing methods along with computational algorithms amenable to atlas-scale datasets leading to improved sensitivity and reproducibility in the future.
|
1602.00723
|
Dario Riccardo Valenzano
|
Arian \v{S}ajina, Dario Riccardo Valenzano
|
An In Silico Model to Simulate the Evolution of Biological Aging
|
11 pages and 7 figures, written using the AIP distribution for REVTeX
4, Version 4.1 of REVTeX; corresponding author (D.R.V.) email:
dvalenzano@age.mpg.de
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Biological aging is characterized by an age-dependent increase in the
probability of death and by a decrease in the reproductive capacity. Individual
age-dependent rates of survival and reproduction have a strong impact on
population dynamics, and the genetic elements determining survival and
reproduction are under different selective forces throughout an organism
lifespan. Here we develop a highly versatile numerical model of genome
evolution --- both asexual and sexual --- for a population of virtual
individuals with overlapping generations, where the genetic elements affecting
survival and reproduction rate at different life stages are free to evolve due
to mutation and selection. Our model recapitulates several emerging properties
of natural populations, developing longer reproductive lifespan under stable
conditions and shorter survival and reproduction in unstable environments.
Faster aging results as the consequence of the reduced strength of purifying
selection in more unstable populations, which have large portions of the genome
that accumulate detrimental mutations. Unlike sexually reproducing populations
under constant resources, asexually reproducing populations fail to develop an
age-dependent increase in death rates and decrease in reproduction rates,
therefore escaping senescence. Our model provides a powerful in silico
framework to simulate how populations and genomes change in the context of
biological aging and opens a novel analytical opportunity to characterize how
real populations evolve their specific aging dynamics.
|
[
{
"created": "Mon, 1 Feb 2016 21:54:43 GMT",
"version": "v1"
}
] |
2016-02-03
|
[
[
"Šajina",
"Arian",
""
],
[
"Valenzano",
"Dario Riccardo",
""
]
] |
Biological aging is characterized by an age-dependent increase in the probability of death and by a decrease in the reproductive capacity. Individual age-dependent rates of survival and reproduction have a strong impact on population dynamics, and the genetic elements determining survival and reproduction are under different selective forces throughout an organism lifespan. Here we develop a highly versatile numerical model of genome evolution --- both asexual and sexual --- for a population of virtual individuals with overlapping generations, where the genetic elements affecting survival and reproduction rate at different life stages are free to evolve due to mutation and selection. Our model recapitulates several emerging properties of natural populations, developing longer reproductive lifespan under stable conditions and shorter survival and reproduction in unstable environments. Faster aging results as the consequence of the reduced strength of purifying selection in more unstable populations, which have large portions of the genome that accumulate detrimental mutations. Unlike sexually reproducing populations under constant resources, asexually reproducing populations fail to develop an age-dependent increase in death rates and decrease in reproduction rates, therefore escaping senescence. Our model provides a powerful in silico framework to simulate how populations and genomes change in the context of biological aging and opens a novel analytical opportunity to characterize how real populations evolve their specific aging dynamics.
|
1605.06207
|
Bernal Morera MSc
|
Bernal Morera
|
Mitochondrial genealogy of Maria Mercedes Cairol Antunez, footprint of
recent immigration to Costa Rica / La genealogia mitocondrial de Maria
Mercedes Cairol Antunez, huella de la inmigracion reciente a Costa Rica
|
4 pages, 1 figure, 1 table, in Spanish
|
Boletin ASOGEHInforma 6(2): 11-14. 2012
| null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The technological advances in Genetics have given rise to the science of
Molecular Genealogy, by giving us the opportunity to approach the study of
pedigrees from a new perspective, examining alive people at the same time than
collating records from their ancestors. A four generations matrilineal
genealogy is presented from Da. Angela Antunez (b. a. 1881 in Barcelona, Spain)
to their descendants in Cuba and Costa Rica. The observed mitochondrial lineage
has a substitution in the region HVR1 respect to the reference sequence (CRS)
and belongs to H haplogroup. This is consistent -as expected, with the recent
documented European lineage. This is an example of differential female
migration, in which women move to the husband's place of origin. Because of
patrilocal marriages are practiced in most societies, such migration mechanism
has had a major impact since the arrival of immigrant women bring new and
different lineages of mtDNA, which together with the admixture process
contributed to enrich the diversity and regionalization of the gene pool of
human populations in the Americas.
|
[
{
"created": "Fri, 20 May 2016 03:55:18 GMT",
"version": "v1"
}
] |
2016-05-23
|
[
[
"Morera",
"Bernal",
""
]
] |
The technological advances in Genetics have given rise to the science of Molecular Genealogy, by giving us the opportunity to approach the study of pedigrees from a new perspective, examining alive people at the same time than collating records from their ancestors. A four generations matrilineal genealogy is presented from Da. Angela Antunez (b. a. 1881 in Barcelona, Spain) to their descendants in Cuba and Costa Rica. The observed mitochondrial lineage has a substitution in the region HVR1 respect to the reference sequence (CRS) and belongs to H haplogroup. This is consistent -as expected, with the recent documented European lineage. This is an example of differential female migration, in which women move to the husband's place of origin. Because of patrilocal marriages are practiced in most societies, such migration mechanism has had a major impact since the arrival of immigrant women bring new and different lineages of mtDNA, which together with the admixture process contributed to enrich the diversity and regionalization of the gene pool of human populations in the Americas.
|
1606.05802
|
Amy Gilson
|
Amy I. Gilson, Ahmee Marshall-Christensen, Jeong-Mo Choi, and Eugene
I. Shakhnovich
|
The role of evolutionary selection in the dynamics of protein structure
evolution
| null | null |
10.1016/j.bpj.2017.02.029
| null |
q-bio.PE q-bio.BM
|
http://creativecommons.org/licenses/by/4.0/
|
Emergence of new protein structures has proved difficult to trace in nature
and engineer in the laboratory. However, one aspect of structure evolution has
proved immensely helpful for determining the three-dimensional structure of
proteins from their sequences: in the vast majority of cases, proteins that
share more than 30% sequence identity have similar structures. Below this mark
is the "twilight zone" where proteins may have identical or very different
structures. These observations form the foundational intuition behind structure
homology modeling. Despite their importance, however, they have never received
a comprehensive biophysical justification. Here we show that the onset of the
twilight zone is more gradual for proteins with low contact density, a proxy
for low thermodynamic stability, than proteins with high contact density. Then
we present an analytical model that treats divergent fold evolution as an
activated process, in analogy to chemical kinetics, where sequence evolution
must overcome thermodynamically unstable evolutionary intermediates to discover
new folds. This model explains the existence of a twilight zone and explains
why its onset is more abrupt for some classes of proteins than for others. We
test the assumptions of the model and characterize the dynamics of fold
evolution using evolutionary simulations of model proteins and cell
populations. Overall these results show how fundamental biophysical constraints
directed evolutionary dynamics leading to the Universe of modern protein
structures and sequences.
|
[
{
"created": "Sat, 18 Jun 2016 20:34:08 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Oct 2016 17:26:45 GMT",
"version": "v2"
}
] |
2017-05-24
|
[
[
"Gilson",
"Amy I.",
""
],
[
"Marshall-Christensen",
"Ahmee",
""
],
[
"Choi",
"Jeong-Mo",
""
],
[
"Shakhnovich",
"Eugene I.",
""
]
] |
Emergence of new protein structures has proved difficult to trace in nature and engineer in the laboratory. However, one aspect of structure evolution has proved immensely helpful for determining the three-dimensional structure of proteins from their sequences: in the vast majority of cases, proteins that share more than 30% sequence identity have similar structures. Below this mark is the "twilight zone" where proteins may have identical or very different structures. These observations form the foundational intuition behind structure homology modeling. Despite their importance, however, they have never received a comprehensive biophysical justification. Here we show that the onset of the twilight zone is more gradual for proteins with low contact density, a proxy for low thermodynamic stability, than proteins with high contact density. Then we present an analytical model that treats divergent fold evolution as an activated process, in analogy to chemical kinetics, where sequence evolution must overcome thermodynamically unstable evolutionary intermediates to discover new folds. This model explains the existence of a twilight zone and explains why its onset is more abrupt for some classes of proteins than for others. We test the assumptions of the model and characterize the dynamics of fold evolution using evolutionary simulations of model proteins and cell populations. Overall these results show how fundamental biophysical constraints directed evolutionary dynamics leading to the Universe of modern protein structures and sequences.
|
q-bio/0607041
|
Blas Echebarria
|
Blas Echebarria, Alain Karma
|
Amplitude equation approach to spatiotemporal dynamics of cardiac
alternans
|
55 pages, 13 figures, to appear in Phys. Rev. E
| null |
10.1103/PhysRevE.76.051911
| null |
q-bio.TO nlin.PS
| null |
Amplitude equations are derived that describe the spatiotemporal dynamics of
cardiac alternans during periodic pacing of one- and two-dimensional
homogeneous tissue and one-dimensional anatomical reentry in a ring of
homogeneous tissue. These equations provide a simple physical understanding of
arrhythmogenic patterns of period-doubling oscillations of action potential
duration with a spatially varying phase and amplitude as well as explicit
quantitative predictions that can be compared to ionic model simulations or
experiments. The form of the equations is expected to be valid for a large
class of ionic models but the coefficients are only derived analytically for a
two-variable ionic model and calculated numerically for the original Noble
model of Purkinje fiber action potential.In paced tissue, the main result is
the existence of a linear instability that produces a periodic pattern of
discordant alternans. Moreover, the patterns of alternans can be either
stationary, with fixed nodes, or travelling, with moving nodes and hence
quasiperiodic oscillations of action potential duration, depending on the
relative strength of the destabilizing effect of CV-restitution and the
stabilizing effect of diffusive coupling. In both the paced geometries and the
ring, the onset of alternans is different in tissue than for a paced isolated
cell. The implications of these results for alternans dynamics during
two-dimensional reentry are briefly discussed.
|
[
{
"created": "Sun, 23 Jul 2006 15:27:19 GMT",
"version": "v1"
},
{
"created": "Mon, 15 Oct 2007 13:43:35 GMT",
"version": "v2"
}
] |
2009-11-13
|
[
[
"Echebarria",
"Blas",
""
],
[
"Karma",
"Alain",
""
]
] |
Amplitude equations are derived that describe the spatiotemporal dynamics of cardiac alternans during periodic pacing of one- and two-dimensional homogeneous tissue and one-dimensional anatomical reentry in a ring of homogeneous tissue. These equations provide a simple physical understanding of arrhythmogenic patterns of period-doubling oscillations of action potential duration with a spatially varying phase and amplitude as well as explicit quantitative predictions that can be compared to ionic model simulations or experiments. The form of the equations is expected to be valid for a large class of ionic models but the coefficients are only derived analytically for a two-variable ionic model and calculated numerically for the original Noble model of Purkinje fiber action potential.In paced tissue, the main result is the existence of a linear instability that produces a periodic pattern of discordant alternans. Moreover, the patterns of alternans can be either stationary, with fixed nodes, or travelling, with moving nodes and hence quasiperiodic oscillations of action potential duration, depending on the relative strength of the destabilizing effect of CV-restitution and the stabilizing effect of diffusive coupling. In both the paced geometries and the ring, the onset of alternans is different in tissue than for a paced isolated cell. The implications of these results for alternans dynamics during two-dimensional reentry are briefly discussed.
|
1707.08990
|
Yi-Hsuan Lin
|
Yi-Hsuan Lin, Jacob P. Brady, Julie D. Forman-Kay, Hue Sun Chan
|
Charge Pattern Matching as a "Fuzzy" Mode of Molecular Recognition for
the Functional Phase Separations of Intrinsically Disordered Proteins
|
Accepted for publication in New Journal of Physics (IOP) for the
"Focus On Phase Transitions in Cells" Special Issue; 37 pages, 11 figures
|
New J. Phys. 19, 115003 (2017)
|
10.1088/1367-2630/aa9369
| null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Biologically functional liquid-liquid phase separation of intrinsically
disordered proteins (IDPs) is driven by interactions encoded by their amino
acid sequences. Little is currently known about the molecular recognition
mechanisms for distributing different IDP sequences into various cellular
membraneless compartments. Pertinent physics was addressed recently by applying
random-phase-approximation (RPA) polymer theory to electrostatics, which is a
major energetic component governing IDP phase properties. RPA accounts for
charge patterns and thus has advantages over Flory-Huggins and Overbeek-Voorn
mean-field theories. To make progress toward deciphering the phase behaviors of
multiple IDP sequences, the RPA formulation for one IDP species plus solvent is
hereby extended to treat polyampholyte solutions containing two IDP species.
The new formulation generally allows for binary coexistence of two phases, each
containing a different set of volume fractions $(\phi_1,\phi_2)$ for the two
different IDP sequences. The asymmetry between the two predicted coexisting
phases with regard to their $\phi_1/\phi_2$ ratios for the two sequences
increases with increasing mismatch between their charge patterns. This finding
points to a multivalent, stochastic, "fuzzy" mode of molecular recognition that
helps populate various IDP sequences differentially into separate phase
compartments. An intuitive illustration of this trend is provided by
Flory-Huggins models, whereby a hypothetical case of ternary coexistence is
also explored. Augmentations of the present RPA theory with a relative
permittivity $\epsilon_{\rm r}(\phi)$ that depends on IDP volume fraction
$\phi=\phi_1+\phi_2$ lead to higher propensities to phase separate, in line
with the case with one IDP species we studied previously. ...
|
[
{
"created": "Thu, 27 Jul 2017 18:28:04 GMT",
"version": "v1"
},
{
"created": "Fri, 20 Oct 2017 00:53:26 GMT",
"version": "v2"
}
] |
2017-11-15
|
[
[
"Lin",
"Yi-Hsuan",
""
],
[
"Brady",
"Jacob P.",
""
],
[
"Forman-Kay",
"Julie D.",
""
],
[
"Chan",
"Hue Sun",
""
]
] |
Biologically functional liquid-liquid phase separation of intrinsically disordered proteins (IDPs) is driven by interactions encoded by their amino acid sequences. Little is currently known about the molecular recognition mechanisms for distributing different IDP sequences into various cellular membraneless compartments. Pertinent physics was addressed recently by applying random-phase-approximation (RPA) polymer theory to electrostatics, which is a major energetic component governing IDP phase properties. RPA accounts for charge patterns and thus has advantages over Flory-Huggins and Overbeek-Voorn mean-field theories. To make progress toward deciphering the phase behaviors of multiple IDP sequences, the RPA formulation for one IDP species plus solvent is hereby extended to treat polyampholyte solutions containing two IDP species. The new formulation generally allows for binary coexistence of two phases, each containing a different set of volume fractions $(\phi_1,\phi_2)$ for the two different IDP sequences. The asymmetry between the two predicted coexisting phases with regard to their $\phi_1/\phi_2$ ratios for the two sequences increases with increasing mismatch between their charge patterns. This finding points to a multivalent, stochastic, "fuzzy" mode of molecular recognition that helps populate various IDP sequences differentially into separate phase compartments. An intuitive illustration of this trend is provided by Flory-Huggins models, whereby a hypothetical case of ternary coexistence is also explored. Augmentations of the present RPA theory with a relative permittivity $\epsilon_{\rm r}(\phi)$ that depends on IDP volume fraction $\phi=\phi_1+\phi_2$ lead to higher propensities to phase separate, in line with the case with one IDP species we studied previously. ...
|
2307.03757
|
Adam Shephard
|
Adam J Shephard, Raja Muhammad Saad Bashir, Hanya Mahmood, Mostafa
Jahanifar, Fayyaz Minhas, Shan E Ahmed Raza, Kris D McCombe, Stephanie G
Craig, Jacqueline James, Jill Brooks, Paul Nankivell, Hisham Mehanna, Syed
Ali Khurram, Nasir M Rajpoot
|
A Fully Automated and Explainable Algorithm for the Prediction of
Malignant Transformation in Oral Epithelial Dysplasia
| null | null | null | null |
q-bio.QM cs.CV eess.IV
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis
given to lesions of the oral cavity. Its grading suffers from significant
inter-/intra- observer variability, and does not reliably predict malignancy
progression, potentially leading to suboptimal treatment decisions. To address
this, we developed a novel artificial intelligence algorithm that can assign an
Oral Malignant Transformation (OMT) risk score, based on histological patterns
in the in Haematoxylin and Eosin stained whole slide images, to quantify the
risk of OED progression. The algorithm is based on the detection and
segmentation of nuclei within (and around) the epithelium using an in-house
segmentation model. We then employed a shallow neural network fed with
interpretable morphological/spatial features, emulating histological markers.
We conducted internal cross-validation on our development cohort (Sheffield; n
= 193 cases) followed by independent validation on two external cohorts
(Birmingham and Belfast; n = 92 cases). The proposed OMTscore yields an AUROC =
0.74 in predicting whether an OED progresses to malignancy or not. Survival
analyses showed the prognostic value of our OMTscore for predicting malignancy
transformation, when compared to the manually-assigned WHO and binary grades.
Analysis of the correctly predicted cases elucidated the presence of
peri-epithelial and epithelium-infiltrating lymphocytes in the most predictive
patches of cases that transformed (p < 0.0001). This is the first study to
propose a completely automated algorithm for predicting OED transformation
based on interpretable nuclear features, whilst being validated on external
datasets. The algorithm shows better-than-human-level performance for
prediction of OED malignant transformation and offers a promising solution to
the challenges of grading OED in routine clinical practice.
|
[
{
"created": "Thu, 6 Jul 2023 19:11:00 GMT",
"version": "v1"
}
] |
2023-07-11
|
[
[
"Shephard",
"Adam J",
""
],
[
"Bashir",
"Raja Muhammad Saad",
""
],
[
"Mahmood",
"Hanya",
""
],
[
"Jahanifar",
"Mostafa",
""
],
[
"Minhas",
"Fayyaz",
""
],
[
"Raza",
"Shan E Ahmed",
""
],
[
"McCombe",
"Kris D",
""
],
[
"Craig",
"Stephanie G",
""
],
[
"James",
"Jacqueline",
""
],
[
"Brooks",
"Jill",
""
],
[
"Nankivell",
"Paul",
""
],
[
"Mehanna",
"Hisham",
""
],
[
"Khurram",
"Syed Ali",
""
],
[
"Rajpoot",
"Nasir M",
""
]
] |
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. Its grading suffers from significant inter-/intra- observer variability, and does not reliably predict malignancy progression, potentially leading to suboptimal treatment decisions. To address this, we developed a novel artificial intelligence algorithm that can assign an Oral Malignant Transformation (OMT) risk score, based on histological patterns in the in Haematoxylin and Eosin stained whole slide images, to quantify the risk of OED progression. The algorithm is based on the detection and segmentation of nuclei within (and around) the epithelium using an in-house segmentation model. We then employed a shallow neural network fed with interpretable morphological/spatial features, emulating histological markers. We conducted internal cross-validation on our development cohort (Sheffield; n = 193 cases) followed by independent validation on two external cohorts (Birmingham and Belfast; n = 92 cases). The proposed OMTscore yields an AUROC = 0.74 in predicting whether an OED progresses to malignancy or not. Survival analyses showed the prognostic value of our OMTscore for predicting malignancy transformation, when compared to the manually-assigned WHO and binary grades. Analysis of the correctly predicted cases elucidated the presence of peri-epithelial and epithelium-infiltrating lymphocytes in the most predictive patches of cases that transformed (p < 0.0001). This is the first study to propose a completely automated algorithm for predicting OED transformation based on interpretable nuclear features, whilst being validated on external datasets. The algorithm shows better-than-human-level performance for prediction of OED malignant transformation and offers a promising solution to the challenges of grading OED in routine clinical practice.
|
1903.10323
|
Kim Henriksen
|
Maja R. Radojcic, Christian S. Thudium, Kim Henriksen, Keith Tan, Rolf
Karlsten, Amanda Dudley, Iain Chessell, Morten A. Karsdal, Anne-Christine
Bay-Jensen, Michel D. Crema, Ali Guermazi
|
Biomarker of extracellular matrix remodelling C1M and proinflammatory
cytokine IL-6 are related to synovitis and pain in end-stage knee
osteoarthritis patients
|
19 pages, 2 figures, 5 tables and 2 supplementary figures
|
Pain. 2017 Jul;158(7):1254-1263
|
10.1097/j.pain.0000000000000908
| null |
q-bio.TO
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Little is known about local and systemic biomarkers in relation to synovitis
and pain in end-stage osteoarthritis (OA) patients. We investigated the
associations between the novel extracellular matrix biomarker, C1M, and local
and systemic interleukin 6 (IL-6) with synovitis and pain. Serum C1M, plasma
and synovial fluid IL-6 (p-IL-6, sf-IL-6) were measured in 104 end-stage knee
OA patients. Contrast-enhanced magnetic resonance imaging (MRI) was used to
semi-quantitatively assess an 11-point synovitis score; pain was assessed by
the Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) and
the Neuropathic Pain Questionnaire (NPQ). Linear regression was used to
investigate associations between biomarkers and synovitis, and biomarkers and
pain while controlling for age, sex and body mass index. We also tested whether
associations between biomarkers and pain were confounded by synovitis. We found
sf-IL-6 was associated with synovitis in the parapatellar subregion (B=0.006;
95% CI 0.003-0.010), and no association between p-IL-6 and synovitis. We also
observed an association between C1M and synovitis in the peri-ligamentous
subregion (B=0.013; 95% CI 0.003-0.023). Further, sf-IL-6, but not p-IL-6, was
significantly associated with pain, WOMAC (B=0.022; 95% CI 0.004-0.040) and NPQ
(B=0.043;95% CI 0.005-0.082). There was no association between C1M and WOMAC
pain but we did find an association between C1M and NPQ (B=0.229; 95% CI
0.036-0.422). Lastly, synovitis explained both biomarker-NPQ associations, but
not the biomarker-WOMAC association. These results suggest C1M and IL-6 are
associated with synovitis and pain, and synovitis is an important confounding
variable when studying biomarkers and neuropathic features in OA patients.
|
[
{
"created": "Wed, 20 Mar 2019 07:18:32 GMT",
"version": "v1"
}
] |
2019-03-26
|
[
[
"Radojcic",
"Maja R.",
""
],
[
"Thudium",
"Christian S.",
""
],
[
"Henriksen",
"Kim",
""
],
[
"Tan",
"Keith",
""
],
[
"Karlsten",
"Rolf",
""
],
[
"Dudley",
"Amanda",
""
],
[
"Chessell",
"Iain",
""
],
[
"Karsdal",
"Morten A.",
""
],
[
"Bay-Jensen",
"Anne-Christine",
""
],
[
"Crema",
"Michel D.",
""
],
[
"Guermazi",
"Ali",
""
]
] |
Little is known about local and systemic biomarkers in relation to synovitis and pain in end-stage osteoarthritis (OA) patients. We investigated the associations between the novel extracellular matrix biomarker, C1M, and local and systemic interleukin 6 (IL-6) with synovitis and pain. Serum C1M, plasma and synovial fluid IL-6 (p-IL-6, sf-IL-6) were measured in 104 end-stage knee OA patients. Contrast-enhanced magnetic resonance imaging (MRI) was used to semi-quantitatively assess an 11-point synovitis score; pain was assessed by the Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) and the Neuropathic Pain Questionnaire (NPQ). Linear regression was used to investigate associations between biomarkers and synovitis, and biomarkers and pain while controlling for age, sex and body mass index. We also tested whether associations between biomarkers and pain were confounded by synovitis. We found sf-IL-6 was associated with synovitis in the parapatellar subregion (B=0.006; 95% CI 0.003-0.010), and no association between p-IL-6 and synovitis. We also observed an association between C1M and synovitis in the peri-ligamentous subregion (B=0.013; 95% CI 0.003-0.023). Further, sf-IL-6, but not p-IL-6, was significantly associated with pain, WOMAC (B=0.022; 95% CI 0.004-0.040) and NPQ (B=0.043;95% CI 0.005-0.082). There was no association between C1M and WOMAC pain but we did find an association between C1M and NPQ (B=0.229; 95% CI 0.036-0.422). Lastly, synovitis explained both biomarker-NPQ associations, but not the biomarker-WOMAC association. These results suggest C1M and IL-6 are associated with synovitis and pain, and synovitis is an important confounding variable when studying biomarkers and neuropathic features in OA patients.
|
1305.4622
|
Jacob Scott
|
Jacob G. Scott, Philip Gerlee, David Basanta, Alexander G. Fletcher,
Philip K. Maini and Alexander RA Anderson
|
Mathematical modeling of the metastatic process
|
24 pages, 6 figures, Review
| null | null | null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Mathematical modeling in cancer has been growing in popularity and impact
since its inception in 1932. The first theoretical mathematical modeling in
cancer research was focused on understanding tumor growth laws and has grown to
include the competition between healthy and normal tissue, carcinogenesis,
therapy and metastasis. It is the latter topic, metastasis, on which we will
focus this short review, specifically discussing various computational and
mathematical models of different portions of the metastatic process, including:
the emergence of the metastatic phenotype, the timing and size distribution of
metastases, the factors that influence the dormancy of micrometastases and
patterns of spread from a given primary tumor.
|
[
{
"created": "Mon, 20 May 2013 19:54:03 GMT",
"version": "v1"
},
{
"created": "Tue, 21 May 2013 14:02:52 GMT",
"version": "v2"
}
] |
2013-05-22
|
[
[
"Scott",
"Jacob G.",
""
],
[
"Gerlee",
"Philip",
""
],
[
"Basanta",
"David",
""
],
[
"Fletcher",
"Alexander G.",
""
],
[
"Maini",
"Philip K.",
""
],
[
"Anderson",
"Alexander RA",
""
]
] |
Mathematical modeling in cancer has been growing in popularity and impact since its inception in 1932. The first theoretical mathematical modeling in cancer research was focused on understanding tumor growth laws and has grown to include the competition between healthy and normal tissue, carcinogenesis, therapy and metastasis. It is the latter topic, metastasis, on which we will focus this short review, specifically discussing various computational and mathematical models of different portions of the metastatic process, including: the emergence of the metastatic phenotype, the timing and size distribution of metastases, the factors that influence the dormancy of micrometastases and patterns of spread from a given primary tumor.
|
1509.01957
|
Jos\'e Halloy
|
A. Gribovskiy, F. Mondada, J.L. Deneubourg, L. Cazenille, N. Bredeche,
J. Halloy
|
Automated Analysis of Behavioural Variability and Filial Imprinting of
Chicks (G. gallus), using Autonomous Robots
|
17 pages, 17 figures, 2 tables
| null | null | null |
q-bio.QM cs.LG cs.RO physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Inter-individual variability has various impacts in animal social behaviour.
This implies that not only collective behaviours have to be studied but also
the behavioural variability of each member composing the groups. To understand
those effects on group behaviour, we develop a quantitative methodology based
on automated ethograms and autonomous robots to study the inter-individual
variability among social animals. We choose chicks of \textit{Gallus gallus
domesticus} as a classic social animal model system for their suitability in
laboratory and controlled experimentation. Moreover, even domesticated chicken
present social structures implying forms or leadership and filial imprinting.
We develop an imprinting methodology on autonomous robots to study individual
and social behaviour of free moving animals. This allows to quantify the
behaviours of large number of animals. We develop an automated experimental
methodology that allows to make relatively fast controlled experiments and
efficient data analysis. Our analysis are based on high-throughput data
allowing a fine quantification of individual behavioural traits. We quantify
the efficiency of various state-of-the-art algorithms to automate data analysis
and produce automated ethograms. We show that the use of robots allows to
provide controlled and quantified stimuli to the animals in absence of human
intervention. We quantify the individual behaviour of 205 chicks obtained from
hatching after synchronized fecundation. Our results show a high variability of
individual behaviours and of imprinting quality and success. Three classes of
chicks are observed with various level of imprinting. Our study shows that the
concomitant use of autonomous robots and automated ethograms allows detailed
and quantitative analysis of behavioural patterns of animals in controlled
laboratory experiments.
|
[
{
"created": "Mon, 7 Sep 2015 09:22:43 GMT",
"version": "v1"
}
] |
2016-01-28
|
[
[
"Gribovskiy",
"A.",
""
],
[
"Mondada",
"F.",
""
],
[
"Deneubourg",
"J. L.",
""
],
[
"Cazenille",
"L.",
""
],
[
"Bredeche",
"N.",
""
],
[
"Halloy",
"J.",
""
]
] |
Inter-individual variability has various impacts in animal social behaviour. This implies that not only collective behaviours have to be studied but also the behavioural variability of each member composing the groups. To understand those effects on group behaviour, we develop a quantitative methodology based on automated ethograms and autonomous robots to study the inter-individual variability among social animals. We choose chicks of \textit{Gallus gallus domesticus} as a classic social animal model system for their suitability in laboratory and controlled experimentation. Moreover, even domesticated chicken present social structures implying forms or leadership and filial imprinting. We develop an imprinting methodology on autonomous robots to study individual and social behaviour of free moving animals. This allows to quantify the behaviours of large number of animals. We develop an automated experimental methodology that allows to make relatively fast controlled experiments and efficient data analysis. Our analysis are based on high-throughput data allowing a fine quantification of individual behavioural traits. We quantify the efficiency of various state-of-the-art algorithms to automate data analysis and produce automated ethograms. We show that the use of robots allows to provide controlled and quantified stimuli to the animals in absence of human intervention. We quantify the individual behaviour of 205 chicks obtained from hatching after synchronized fecundation. Our results show a high variability of individual behaviours and of imprinting quality and success. Three classes of chicks are observed with various level of imprinting. Our study shows that the concomitant use of autonomous robots and automated ethograms allows detailed and quantitative analysis of behavioural patterns of animals in controlled laboratory experiments.
|
q-bio/0508023
|
Eli Ben-Naim
|
E. Ben-Naim, P.L. Krapivsky
|
Rank Statistics in Biological Evolution
|
4 pages, 3 figures
|
J. Stat. Mech. L10002 (2005)
|
10.1088/1742-5468/2005/10/L10002
| null |
q-bio.PE cond-mat.stat-mech math.PR q-bio.GN
| null |
We present a statistical analysis of biological evolution processes.
Specifically, we study the stochastic replication-mutation-death model where
the population of a species may grow or shrink by birth or death, respectively,
and additionally, mutations lead to the creation of new species. We rank the
various species by the chronological order by which they originate. The average
population N_k of the kth species decays algebraically with rank, N_k ~ M^{mu}
k^{-mu}, where M is the average total population. The characteristic exponent
mu=(alpha-gamma)/(alpha+beta-gamma)$ depends on alpha, beta, and gamma, the
replication, mutation, and death rates. Furthermore, the average population P_k
of all descendants of the kth species has a universal algebraic behavior, P_k ~
M/k.
|
[
{
"created": "Thu, 18 Aug 2005 04:52:50 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Ben-Naim",
"E.",
""
],
[
"Krapivsky",
"P. L.",
""
]
] |
We present a statistical analysis of biological evolution processes. Specifically, we study the stochastic replication-mutation-death model where the population of a species may grow or shrink by birth or death, respectively, and additionally, mutations lead to the creation of new species. We rank the various species by the chronological order by which they originate. The average population N_k of the kth species decays algebraically with rank, N_k ~ M^{mu} k^{-mu}, where M is the average total population. The characteristic exponent mu=(alpha-gamma)/(alpha+beta-gamma)$ depends on alpha, beta, and gamma, the replication, mutation, and death rates. Furthermore, the average population P_k of all descendants of the kth species has a universal algebraic behavior, P_k ~ M/k.
|
1012.3957
|
Leonid Perlovsky
|
Leonid Perlovsky
|
Free Will and Advances in Cognitive Science
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Free will is fundamental to morality, intuition of self, and normal
functioning of the society. However, science does not provide a clear logical
foundation for this idea. This paper considers the fundamental scientific
argument against free will, called reductionism, and explains the reasons for
choosing dualism against monism. Then, the paper summarizes unexpected
conclusions from recent discoveries in cognitive science. Classical logic turns
out not to be the fundamental mechanism of mind. It is replaced by dynamic
logic. Mathematical and experimental evidence are considered conceptually.
Dynamic logic counters logical arguments for reductionism. Contemporary science
of mind is not reducible; free will can be scientifically accepted along with
scientific monism.
|
[
{
"created": "Fri, 17 Dec 2010 18:37:54 GMT",
"version": "v1"
}
] |
2010-12-20
|
[
[
"Perlovsky",
"Leonid",
""
]
] |
Free will is fundamental to morality, intuition of self, and normal functioning of the society. However, science does not provide a clear logical foundation for this idea. This paper considers the fundamental scientific argument against free will, called reductionism, and explains the reasons for choosing dualism against monism. Then, the paper summarizes unexpected conclusions from recent discoveries in cognitive science. Classical logic turns out not to be the fundamental mechanism of mind. It is replaced by dynamic logic. Mathematical and experimental evidence are considered conceptually. Dynamic logic counters logical arguments for reductionism. Contemporary science of mind is not reducible; free will can be scientifically accepted along with scientific monism.
|
1705.05919
|
Maxat Kulmanov
|
Maxat Kulmanov, Mohammed Asif Khan and Robert Hoehndorf
|
DeepGO: Predicting protein functions from sequence and interactions
using a deep ontology-aware classifier
| null | null |
10.1093/bioinformatics/btx624
| null |
q-bio.GN cs.LG q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A large number of protein sequences are becoming available through the
application of novel high-throughput sequencing technologies. Experimental
functional characterization of these proteins is time-consuming and expensive,
and is often only done rigorously for few selected model organisms.
Computational function prediction approaches have been suggested to fill this
gap. The functions of proteins are classified using the Gene Ontology (GO),
which contains over 40,000 classes. Additionally, proteins have multiple
functions, making function prediction a large-scale, multi-class, multi-label
problem.
We have developed a novel method to predict protein function from sequence.
We use deep learning to learn features from protein sequences as well as a
cross-species protein-protein interaction network. Our approach specifically
outputs information in the structure of the GO and utilizes the dependencies
between GO classes as background information to construct a deep learning
model. We evaluate our method using the standards established by the
Computational Assessment of Function Annotation (CAFA) and demonstrate a
significant improvement over baseline methods such as BLAST, with significant
improvement for predicting cellular locations.
|
[
{
"created": "Mon, 15 May 2017 06:04:08 GMT",
"version": "v1"
}
] |
2017-09-28
|
[
[
"Kulmanov",
"Maxat",
""
],
[
"Khan",
"Mohammed Asif",
""
],
[
"Hoehndorf",
"Robert",
""
]
] |
A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often only done rigorously for few selected model organisms. Computational function prediction approaches have been suggested to fill this gap. The functions of proteins are classified using the Gene Ontology (GO), which contains over 40,000 classes. Additionally, proteins have multiple functions, making function prediction a large-scale, multi-class, multi-label problem. We have developed a novel method to predict protein function from sequence. We use deep learning to learn features from protein sequences as well as a cross-species protein-protein interaction network. Our approach specifically outputs information in the structure of the GO and utilizes the dependencies between GO classes as background information to construct a deep learning model. We evaluate our method using the standards established by the Computational Assessment of Function Annotation (CAFA) and demonstrate a significant improvement over baseline methods such as BLAST, with significant improvement for predicting cellular locations.
|
2308.03563
|
Konstantin Sorokin
|
Konstantin Sorokin, Andrey Zaitsew, Aleksandr Levin, German Magai,
Maxim Beketov, Vladimir Sotskov
|
Global cognitive graph properties dynamics of hippocampal formation
|
12 pages, 6 figures, paper for DAMDID 2023 Conference
| null | null | null |
q-bio.NC cs.IR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In the present study we have used a set of methods and metrics to build a
graph of relative neural connections in a hippocampus of a rodent. A set of
graphs was built on top of time-sequenced data and analyzed in terms of
dynamics of a connection genesis. The analysis has shown that during the
process of a rodent exploring a novel environment, the relations between
neurons constantly change which indicates that globally memory is constantly
updated even for known areas of space. Even if some neurons gain cognitive
specialization, the global network though remains relatively stable.
Additionally we suggest a set of methods for building a graph of cognitive
neural network.
|
[
{
"created": "Mon, 7 Aug 2023 13:15:33 GMT",
"version": "v1"
}
] |
2023-08-08
|
[
[
"Sorokin",
"Konstantin",
""
],
[
"Zaitsew",
"Andrey",
""
],
[
"Levin",
"Aleksandr",
""
],
[
"Magai",
"German",
""
],
[
"Beketov",
"Maxim",
""
],
[
"Sotskov",
"Vladimir",
""
]
] |
In the present study we have used a set of methods and metrics to build a graph of relative neural connections in a hippocampus of a rodent. A set of graphs was built on top of time-sequenced data and analyzed in terms of dynamics of a connection genesis. The analysis has shown that during the process of a rodent exploring a novel environment, the relations between neurons constantly change which indicates that globally memory is constantly updated even for known areas of space. Even if some neurons gain cognitive specialization, the global network though remains relatively stable. Additionally we suggest a set of methods for building a graph of cognitive neural network.
|
0909.1370
|
Conrad Burden
|
Sylvain Foret, Susan R. Wilson, Conrad J. Burden
|
Characterising the D2 statistic: word matches in biological sequences
|
23 pages, 3 figures
| null | null | null |
q-bio.QM q-bio.GN stat.AP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Word matches are often used in sequence comparison methods, either as a
measure of sequence similarity or in the first search steps of algorithms such
as BLAST or BLAT. The D2 statistic is the number of matches of words of k
letters between two sequences. Recent advances have been made in the
characterisation of this statistic and in the approximation of its
distribution. Here, these results are extended to the case of approximate word
matches.
We compute the exact value of the variance of the D2 statistic for the case
of a uniform letter distribution, and introduce a method to provide accurate
approximations of the variance in the remaining cases. This enables the
distribution of D2 to be approximated for typical situations arising in
biological research. We apply these results to the identification of
cis-regulatory modules, and show that this method detects such sequences with a
high accuracy.
The ability to approximate the distribution of D2 for both exact and
approximate word matches will enable the use of this statistic in a more
precise manner for sequence comparison, database searches, and identification
of transcription factor binding sites.
|
[
{
"created": "Tue, 8 Sep 2009 01:46:58 GMT",
"version": "v1"
}
] |
2009-09-09
|
[
[
"Foret",
"Sylvain",
""
],
[
"Wilson",
"Susan R.",
""
],
[
"Burden",
"Conrad J.",
""
]
] |
Word matches are often used in sequence comparison methods, either as a measure of sequence similarity or in the first search steps of algorithms such as BLAST or BLAT. The D2 statistic is the number of matches of words of k letters between two sequences. Recent advances have been made in the characterisation of this statistic and in the approximation of its distribution. Here, these results are extended to the case of approximate word matches. We compute the exact value of the variance of the D2 statistic for the case of a uniform letter distribution, and introduce a method to provide accurate approximations of the variance in the remaining cases. This enables the distribution of D2 to be approximated for typical situations arising in biological research. We apply these results to the identification of cis-regulatory modules, and show that this method detects such sequences with a high accuracy. The ability to approximate the distribution of D2 for both exact and approximate word matches will enable the use of this statistic in a more precise manner for sequence comparison, database searches, and identification of transcription factor binding sites.
|
2303.04898
|
Daniel Friedman
|
Karl Friston, Daniel Ari Friedman, Axel Constant, V. Bleu Knight,
Thomas Parr, John O. Campbell
|
A variational synthesis of evolutionary and developmental dynamics
| null | null |
10.3390/e25070964
| null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
This paper introduces a variational formulation of natural selection, paying
special attention to the nature of "things" and the way that different "kinds"
of "things" are individuated from - and influence - each other. We use the
Bayesian mechanics of particular partitions to understand how slow phylogenetic
processes constrain - and are constrained by - fast, phenotypic processes. The
main result is a formulation of adaptive fitness as a path integral of
phenotypic fitness. Paths of least action, at the phenotypic and phylogenetic
scales, can then be read as inference and learning processes, respectively. In
this view, a phenotype actively infers the state of its econiche under a
generative model, whose parameters are learned via natural (bayesian model
selection). The ensuing variational synthesis features some unexpected aspects.
Perhaps the most notable is that it is not possible to describe or model a
population of conspecifics per se. Rather, it is necessary to consider
populations - and nested meta-populations - of different natural kinds that
influence each other. This paper is limited to a description of the
mathematical apparatus and accompanying ideas. Subsequent work will use these
methods for simulations and numerical analyses - and identify points of contact
with related mathematical formulations of evolution.
|
[
{
"created": "Wed, 8 Mar 2023 21:30:28 GMT",
"version": "v1"
}
] |
2023-07-05
|
[
[
"Friston",
"Karl",
""
],
[
"Friedman",
"Daniel Ari",
""
],
[
"Constant",
"Axel",
""
],
[
"Knight",
"V. Bleu",
""
],
[
"Parr",
"Thomas",
""
],
[
"Campbell",
"John O.",
""
]
] |
This paper introduces a variational formulation of natural selection, paying special attention to the nature of "things" and the way that different "kinds" of "things" are individuated from - and influence - each other. We use the Bayesian mechanics of particular partitions to understand how slow phylogenetic processes constrain - and are constrained by - fast, phenotypic processes. The main result is a formulation of adaptive fitness as a path integral of phenotypic fitness. Paths of least action, at the phenotypic and phylogenetic scales, can then be read as inference and learning processes, respectively. In this view, a phenotype actively infers the state of its econiche under a generative model, whose parameters are learned via natural (bayesian model selection). The ensuing variational synthesis features some unexpected aspects. Perhaps the most notable is that it is not possible to describe or model a population of conspecifics per se. Rather, it is necessary to consider populations - and nested meta-populations - of different natural kinds that influence each other. This paper is limited to a description of the mathematical apparatus and accompanying ideas. Subsequent work will use these methods for simulations and numerical analyses - and identify points of contact with related mathematical formulations of evolution.
|
2011.08088
|
Mark Humphries
|
Mark D Humphries
|
Strong and weak principles of neural dimension reduction
|
27 pages, 5 figures
| null |
10.51628/001c.24619
| null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
If spikes are the medium, what is the message? Answering that question is
driving the development of large-scale, single neuron resolution recordings
from behaving animals, on the scale of thousands of neurons. But these data are
inherently high-dimensional, with as many dimensions as neurons - so how do we
make sense of them? For many the answer is to reduce the number of dimensions.
Here I argue we can distinguish weak and strong principles of neural dimension
reduction. The weak principle is that dimension reduction is a convenient tool
for making sense of complex neural data. The strong principle is that dimension
reduction shows us how neural circuits actually operate and compute.
Elucidating these principles is crucial, for which we subscribe to provides
radically different interpretations of the same neural activity data. I show
how we could make either the weak or strong principles appear to be true based
on innocuous looking decisions about how we use dimension reduction on our
data. To counteract these confounds, I outline the experimental evidence for
the strong principle that do not come from dimension reduction; but also show
there are a number of neural phenomena that the strong principle fails to
address. To reconcile these conflicting data, I suggest that the brain has both
principles at play.
|
[
{
"created": "Mon, 16 Nov 2020 16:39:56 GMT",
"version": "v1"
},
{
"created": "Thu, 18 Mar 2021 17:22:03 GMT",
"version": "v2"
},
{
"created": "Mon, 24 May 2021 10:51:20 GMT",
"version": "v3"
},
{
"created": "Fri, 24 Feb 2023 15:06:18 GMT",
"version": "v4"
}
] |
2023-02-27
|
[
[
"Humphries",
"Mark D",
""
]
] |
If spikes are the medium, what is the message? Answering that question is driving the development of large-scale, single neuron resolution recordings from behaving animals, on the scale of thousands of neurons. But these data are inherently high-dimensional, with as many dimensions as neurons - so how do we make sense of them? For many the answer is to reduce the number of dimensions. Here I argue we can distinguish weak and strong principles of neural dimension reduction. The weak principle is that dimension reduction is a convenient tool for making sense of complex neural data. The strong principle is that dimension reduction shows us how neural circuits actually operate and compute. Elucidating these principles is crucial, for which we subscribe to provides radically different interpretations of the same neural activity data. I show how we could make either the weak or strong principles appear to be true based on innocuous looking decisions about how we use dimension reduction on our data. To counteract these confounds, I outline the experimental evidence for the strong principle that do not come from dimension reduction; but also show there are a number of neural phenomena that the strong principle fails to address. To reconcile these conflicting data, I suggest that the brain has both principles at play.
|
1411.0075
|
Fabio Dercole
|
Fabio Dercole
|
The ecology of asexual pairwise interactions: A generalized law of mass
action
|
Submitted to Journal of Mathematical Biology on Feb. 3, 2014
| null | null | null |
q-bio.PE math.DS nlin.AO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A general procedure to formulate asexual (unstructured, deterministic)
population dynamical models resulting from individual pairwise interactions is
proposed. Individuals are characterized by a continuous strategy that
represents all their behavioral, morphological, and functional traits.
Populations group conspecific individuals with identical strategy and are
measured by densities in space. Species can be monomorphic, if only one
strategy is present, or polymorphic otherwise. The procedure highlights the
structural properties fulfilled by the population per-capita growth rates. In
particular, the effect of perturbing a set of similar strategies is
proportional to the product of the corresponding densities, with a
proportionality coefficient that is density-dependent only through the total
density. This generalizes the law of mass action, which traditionally refers to
the case in which the per-capita growth rates are linearly density-dependent
and insensitive to joint strategy perturbations. Being underpinned with
individual strategies, the proposed procedure is most useful for evolutionary
considerations, in the case strategies are inheritable. The developed body of
theory is exemplified on a Holling-type-II many-prey-one-predator system and on
a model of a cannibalistic community.
|
[
{
"created": "Sat, 1 Nov 2014 06:36:10 GMT",
"version": "v1"
}
] |
2014-11-04
|
[
[
"Dercole",
"Fabio",
""
]
] |
A general procedure to formulate asexual (unstructured, deterministic) population dynamical models resulting from individual pairwise interactions is proposed. Individuals are characterized by a continuous strategy that represents all their behavioral, morphological, and functional traits. Populations group conspecific individuals with identical strategy and are measured by densities in space. Species can be monomorphic, if only one strategy is present, or polymorphic otherwise. The procedure highlights the structural properties fulfilled by the population per-capita growth rates. In particular, the effect of perturbing a set of similar strategies is proportional to the product of the corresponding densities, with a proportionality coefficient that is density-dependent only through the total density. This generalizes the law of mass action, which traditionally refers to the case in which the per-capita growth rates are linearly density-dependent and insensitive to joint strategy perturbations. Being underpinned with individual strategies, the proposed procedure is most useful for evolutionary considerations, in the case strategies are inheritable. The developed body of theory is exemplified on a Holling-type-II many-prey-one-predator system and on a model of a cannibalistic community.
|
2208.08127
|
Sakuntala Chatterjee
|
Shobhan Dev Mandal and Sakuntala Chatterjee
|
Effect of switching time scale of receptor activity on chemotactic
performance of Escherichia coli
| null |
Indian Journal of Physics, Special Issue: Physical Views of
Cellular processes, Volume 96, Issue 9, Pages 2619-2627 (2022)
|
10.1007/s12648-021-02259-y
| null |
q-bio.CB physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
In the chemotactic motion of Escherichia coli, the switching of transmembrane
chemoreceptors between active and inactive states is one of the most important
steps of the signaling pathway. We study the effect of this switching
time-scale on the chemotactic performance of the cell. We quantify performance
by the chemotactic drift velocity of the cell. Our extensive numerical
simulations on a detailed theoretical model show that as the activity switching
rate increases, the drift velocity increases and then saturates. Our data also
show the mean duration of a downhill run decreases strongly with the switching
rate, while that of an uphill run decreases relatively slowly. We explain this
effect from temporal variation of activity along uphill and downhill
trajectories. We show that for large and small switching rates the nature of
activity variation show qualitatively different behaviors along a downhill run
but similar behavior along an uphill run. This results in a stronger dependence
of downhill run duration on the switching rate and relatively milder dependence
for uphill run duration.
|
[
{
"created": "Wed, 17 Aug 2022 07:46:07 GMT",
"version": "v1"
}
] |
2022-08-18
|
[
[
"Mandal",
"Shobhan Dev",
""
],
[
"Chatterjee",
"Sakuntala",
""
]
] |
In the chemotactic motion of Escherichia coli, the switching of transmembrane chemoreceptors between active and inactive states is one of the most important steps of the signaling pathway. We study the effect of this switching time-scale on the chemotactic performance of the cell. We quantify performance by the chemotactic drift velocity of the cell. Our extensive numerical simulations on a detailed theoretical model show that as the activity switching rate increases, the drift velocity increases and then saturates. Our data also show the mean duration of a downhill run decreases strongly with the switching rate, while that of an uphill run decreases relatively slowly. We explain this effect from temporal variation of activity along uphill and downhill trajectories. We show that for large and small switching rates the nature of activity variation show qualitatively different behaviors along a downhill run but similar behavior along an uphill run. This results in a stronger dependence of downhill run duration on the switching rate and relatively milder dependence for uphill run duration.
|
1209.6513
|
Mina Zarei
|
Mina Zarei, Bianca Sclavi, Marco Cosentino Lagomarsino
|
Gene silencing and large-scale domain structure of the E. coli genome
| null | null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The H-NS chromosome-organizing protein in E. coli can stabilize genomic DNA
loops, and form oligomeric structures connected to repression of gene
expression. Motivated by the link between chromosome organization, protein
binding and gene expression, we analyzed publicly available genomic data sets
of various origins, from genome-wide protein binding profiles to evolutionary
information, exploring the connections between chromosomal organization,
genesilencing, pseudo-gene localization and horizontal gene transfer. We report
the existence of transcriptionally silent contiguous areas corresponding to
large regions of H-NS protein binding along the genome, their position
indicates a possible relationship with the known large-scale features of
chromosome organization.
|
[
{
"created": "Fri, 28 Sep 2012 13:27:20 GMT",
"version": "v1"
}
] |
2012-10-01
|
[
[
"Zarei",
"Mina",
""
],
[
"Sclavi",
"Bianca",
""
],
[
"Lagomarsino",
"Marco Cosentino",
""
]
] |
The H-NS chromosome-organizing protein in E. coli can stabilize genomic DNA loops, and form oligomeric structures connected to repression of gene expression. Motivated by the link between chromosome organization, protein binding and gene expression, we analyzed publicly available genomic data sets of various origins, from genome-wide protein binding profiles to evolutionary information, exploring the connections between chromosomal organization, genesilencing, pseudo-gene localization and horizontal gene transfer. We report the existence of transcriptionally silent contiguous areas corresponding to large regions of H-NS protein binding along the genome, their position indicates a possible relationship with the known large-scale features of chromosome organization.
|
2012.09562
|
Anastasia Ignatieva
|
Anastasia Ignatieva, Rune B. Lyngs\o, Paul A. Jenkins, Jotun Hein
|
KwARG: Parsimonious reconstruction of ancestral recombination graphs
with recurrent mutation
|
18 pages, 12 figures; accepted for publication in Bioinformatics
| null |
10.1093/bioinformatics/btab351
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The reconstruction of possible histories given a sample of genetic data in
the presence of recombination and recurrent mutation is a challenging problem,
but can provide key insights into the evolution of a population. We present
KwARG, which implements a parsimony-based greedy heuristic algorithm for
finding plausible genealogical histories (ancestral recombination graphs) that
are minimal or near-minimal in the number of posited recombination and mutation
events. Given an input dataset of aligned sequences, KwARG outputs a list of
possible candidate solutions, each comprising a list of mutation and
recombination events that could have generated the dataset; the relative
proportion of recombinations and recurrent mutations in a solution can be
controlled via specifying a set of 'cost' parameters. We demonstrate that the
algorithm performs well when compared against existing methods. The software is
made available on GitHub.
|
[
{
"created": "Thu, 17 Dec 2020 13:19:39 GMT",
"version": "v1"
},
{
"created": "Thu, 13 May 2021 15:47:15 GMT",
"version": "v2"
}
] |
2021-05-14
|
[
[
"Ignatieva",
"Anastasia",
""
],
[
"Lyngsø",
"Rune B.",
""
],
[
"Jenkins",
"Paul A.",
""
],
[
"Hein",
"Jotun",
""
]
] |
The reconstruction of possible histories given a sample of genetic data in the presence of recombination and recurrent mutation is a challenging problem, but can provide key insights into the evolution of a population. We present KwARG, which implements a parsimony-based greedy heuristic algorithm for finding plausible genealogical histories (ancestral recombination graphs) that are minimal or near-minimal in the number of posited recombination and mutation events. Given an input dataset of aligned sequences, KwARG outputs a list of possible candidate solutions, each comprising a list of mutation and recombination events that could have generated the dataset; the relative proportion of recombinations and recurrent mutations in a solution can be controlled via specifying a set of 'cost' parameters. We demonstrate that the algorithm performs well when compared against existing methods. The software is made available on GitHub.
|
2111.14961
|
David Bryant
|
Jandre Snyman and Colin Fox and David Bryant
|
Parsimony and the rank of a flattening matrix
| null | null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
The standard models of sequence evolution on a tree determine probabilities
for every character or site pattern. A flattening is an arrangement of these
probabilities into a matrix, with rows corresponding to all possible site
patterns for one set $A$ of taxa and columns corresponding to all site patterns
for another set $B$ of taxa. Flattenings have been used to prove difficult
results relating to phylogenetic invariants and consistency and also form the
basis of several methods of phylogenetic inference. We prove that the rank of
the flattening equals $r^{\ell_T(A|B)}$, where $r$ is the number of states and
$\ell_T(A|B)$ is the parsimony length of the binary character separating $A$
and $B$. This result corrects an earlier published formula and opens up new
applications for old parsimony theorems.
Since completing this work, we have learnt that an equivalent result has been
proved much earlier by Casanellas and Fern\'andez-S\'anchez, using a different
proof strategy.
|
[
{
"created": "Mon, 29 Nov 2021 21:13:21 GMT",
"version": "v1"
},
{
"created": "Fri, 3 Dec 2021 02:03:25 GMT",
"version": "v2"
},
{
"created": "Thu, 9 Dec 2021 01:37:47 GMT",
"version": "v3"
}
] |
2021-12-10
|
[
[
"Snyman",
"Jandre",
""
],
[
"Fox",
"Colin",
""
],
[
"Bryant",
"David",
""
]
] |
The standard models of sequence evolution on a tree determine probabilities for every character or site pattern. A flattening is an arrangement of these probabilities into a matrix, with rows corresponding to all possible site patterns for one set $A$ of taxa and columns corresponding to all site patterns for another set $B$ of taxa. Flattenings have been used to prove difficult results relating to phylogenetic invariants and consistency and also form the basis of several methods of phylogenetic inference. We prove that the rank of the flattening equals $r^{\ell_T(A|B)}$, where $r$ is the number of states and $\ell_T(A|B)$ is the parsimony length of the binary character separating $A$ and $B$. This result corrects an earlier published formula and opens up new applications for old parsimony theorems. Since completing this work, we have learnt that an equivalent result has been proved much earlier by Casanellas and Fern\'andez-S\'anchez, using a different proof strategy.
|
2007.02169
|
Joe Klobusicky
|
Joseph J. Klobusicky and John Fricks and Peter R. Kramer
|
Effective behavior of cooperative and nonidentical molecular motors
|
73 pages, 4 Figures
| null | null | null |
q-bio.SC math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Analytical formulas for effective drift, diffusivity, run times, and run
lengths are derived for an intracellular transport system consisting of a cargo
attached to two cooperative but not identical molecular motors (for example,
kinesin-1 and kinesin-2) which can each attach and detach from a microtubule.
The dynamics of the motor and cargo in each phase are governed by stochastic
differential equations, and the switching rates depend on the spatial
configuration of the motor and cargo. This system is analyzed in a limit where
the detached motors have faster dynamics than the cargo, which in turn has
faster dynamics than the attached motors. The attachment and detachment rates
are also taken to be slow relative to the spatial dynamics. Through an
application of iterated stochastic averaging to this system, and the use of
renewal-reward theory to stitch together the progress within each switching
phase, we obtain explicit analytical expressions for the effective drift,
diffusivity, and processivity of the motor-cargo system. Our approach accounts
in particular for jumps in motor-cargo position that occur during attachment
and detachment events, as the cargo tracking variable makes a rapid adjustment
due to the averaged fast scales. The asymptotic formulas are in generally good
agreement with direct stochastic simulations of the detailed model based on
experimental parameters for various pairings of kinesin-1 and kinesin-2 under
assisting, hindering, or no load.
|
[
{
"created": "Sat, 4 Jul 2020 19:24:24 GMT",
"version": "v1"
},
{
"created": "Mon, 31 Aug 2020 18:47:07 GMT",
"version": "v2"
},
{
"created": "Thu, 21 Jan 2021 16:15:52 GMT",
"version": "v3"
}
] |
2021-01-22
|
[
[
"Klobusicky",
"Joseph J.",
""
],
[
"Fricks",
"John",
""
],
[
"Kramer",
"Peter R.",
""
]
] |
Analytical formulas for effective drift, diffusivity, run times, and run lengths are derived for an intracellular transport system consisting of a cargo attached to two cooperative but not identical molecular motors (for example, kinesin-1 and kinesin-2) which can each attach and detach from a microtubule. The dynamics of the motor and cargo in each phase are governed by stochastic differential equations, and the switching rates depend on the spatial configuration of the motor and cargo. This system is analyzed in a limit where the detached motors have faster dynamics than the cargo, which in turn has faster dynamics than the attached motors. The attachment and detachment rates are also taken to be slow relative to the spatial dynamics. Through an application of iterated stochastic averaging to this system, and the use of renewal-reward theory to stitch together the progress within each switching phase, we obtain explicit analytical expressions for the effective drift, diffusivity, and processivity of the motor-cargo system. Our approach accounts in particular for jumps in motor-cargo position that occur during attachment and detachment events, as the cargo tracking variable makes a rapid adjustment due to the averaged fast scales. The asymptotic formulas are in generally good agreement with direct stochastic simulations of the detailed model based on experimental parameters for various pairings of kinesin-1 and kinesin-2 under assisting, hindering, or no load.
|
1212.1696
|
Priya Moorjani
|
Priya Moorjani, Nick Patterson, Po-Ru Loh, Mark Lipson, P\'eter
Kisfali, Bela I Melegh, Michael Bonin, \v{L}udev\'it K\'ada\v{s}i, Olaf
Rie{\ss}, Bonnie Berger, David Reich, B\'ela Melegh
|
Reconstructing Roma history from genome-wide data
| null | null |
10.1371/journal.pone.0058633
| null |
q-bio.PE q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The Roma people, living throughout Europe, are a diverse population linked by
the Romani language and culture. Previous linguistic and genetic studies have
suggested that the Roma migrated into Europe from South Asia about 1000-1500
years ago. Genetic inferences about Roma history have mostly focused on the Y
chromosome and mitochondrial DNA. To explore what additional information can be
learned from genome-wide data, we analyzed data from six Roma groups that we
genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs).
We estimate that the Roma harbor about 80% West Eurasian ancestry-deriving from
a combination of European and South Asian sources- and that the date of
admixture of South Asian and European ancestry was about 850 years ago. We
provide evidence for Eastern Europe being a major source of European ancestry,
and North-west India being a major source of the South Asian ancestry in the
Roma. By computing allele sharing as a measure of linkage disequilibrium, we
estimate that the migration of Roma out of the Indian subcontinent was
accompanied by a severe founder event, which we hypothesize was followed by a
major demographic expansion once the population arrived in Europe.
|
[
{
"created": "Fri, 7 Dec 2012 19:59:41 GMT",
"version": "v1"
}
] |
2015-06-12
|
[
[
"Moorjani",
"Priya",
""
],
[
"Patterson",
"Nick",
""
],
[
"Loh",
"Po-Ru",
""
],
[
"Lipson",
"Mark",
""
],
[
"Kisfali",
"Péter",
""
],
[
"Melegh",
"Bela I",
""
],
[
"Bonin",
"Michael",
""
],
[
"Kádaši",
"Ľudevít",
""
],
[
"Rieß",
"Olaf",
""
],
[
"Berger",
"Bonnie",
""
],
[
"Reich",
"David",
""
],
[
"Melegh",
"Béla",
""
]
] |
The Roma people, living throughout Europe, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1000-1500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs). We estimate that the Roma harbor about 80% West Eurasian ancestry-deriving from a combination of European and South Asian sources- and that the date of admixture of South Asian and European ancestry was about 850 years ago. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which we hypothesize was followed by a major demographic expansion once the population arrived in Europe.
|
1210.0050
|
Rohan Maddamsetti
|
Rohan Maddamsetti, Philip J. Hatcher, St\'ephane Cruveiller, Claudine
M\'edigue, Jeffrey E. Barrick, Richard E. Lenski
|
Horizontal gene transfer may explain variation in {\theta}s
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Martincorena et al. estimated synonymous diversity ({\theta}s = 2N{\mu})
across 2,930 orthologous gene alignments from 34 Escherichia coli genomes, and
found substantial variation among genes in the density of synonymous
polymorphisms. They argue that this pattern reflects variation in the mutation
rate per nucleotide ({\mu}) among genes. However, the effective population size
(N) is not necessarily constant across the genome. In particular, different
genes may have different histories of horizontal gene transfer (HGT), whereas
Martincorena et al. used a model with random recombination to calculate
{\theta}s. They did filter alignments in an effort to minimize the effects of
HGT, but we doubt that any procedure can completely eliminate HGT among closely
related genomes, such as E. coli living in the complex gut community.
Here we show that there is no significant variation among genes in rates of
synonymous substitutions in a long-term evolution experiment with E. coli and
that the per-gene rates are not correlated with {\theta}s estimates from genome
comparisons. However, there is a significant association between {\theta}s and
HGT events. Together, these findings imply that {\theta}s variation reflects
different histories of HGT, not local optimization of mutation rates to reduce
the risk of deleterious mutations as proposed by Martincorena et al.
|
[
{
"created": "Fri, 28 Sep 2012 22:14:55 GMT",
"version": "v1"
}
] |
2012-10-02
|
[
[
"Maddamsetti",
"Rohan",
""
],
[
"Hatcher",
"Philip J.",
""
],
[
"Cruveiller",
"Stéphane",
""
],
[
"Médigue",
"Claudine",
""
],
[
"Barrick",
"Jeffrey E.",
""
],
[
"Lenski",
"Richard E.",
""
]
] |
Martincorena et al. estimated synonymous diversity ({\theta}s = 2N{\mu}) across 2,930 orthologous gene alignments from 34 Escherichia coli genomes, and found substantial variation among genes in the density of synonymous polymorphisms. They argue that this pattern reflects variation in the mutation rate per nucleotide ({\mu}) among genes. However, the effective population size (N) is not necessarily constant across the genome. In particular, different genes may have different histories of horizontal gene transfer (HGT), whereas Martincorena et al. used a model with random recombination to calculate {\theta}s. They did filter alignments in an effort to minimize the effects of HGT, but we doubt that any procedure can completely eliminate HGT among closely related genomes, such as E. coli living in the complex gut community. Here we show that there is no significant variation among genes in rates of synonymous substitutions in a long-term evolution experiment with E. coli and that the per-gene rates are not correlated with {\theta}s estimates from genome comparisons. However, there is a significant association between {\theta}s and HGT events. Together, these findings imply that {\theta}s variation reflects different histories of HGT, not local optimization of mutation rates to reduce the risk of deleterious mutations as proposed by Martincorena et al.
|
1301.2440
|
Namiko Mitarai
|
Namiko Mitarai, Uri Alon, and Mogens H. Jensen
|
Entrainment of noise-induced and limit cycle oscillators under weak
noise
|
27 pages in preprint style, 12 figues, 2 table
|
Chaos 23, 023125 (2013)
|
10.1063/1.4808253
| null |
q-bio.QM nlin.CD
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Theoretical models that describe oscillations in biological systems are often
either a limit cycle oscillator, where the deterministic nonlinear dynamics
gives sustained periodic oscillations, or a noise-induced oscillator, where a
fixed point is linearly stable with complex eigenvalues and addition of noise
gives oscillations around the fixed point with fluctuating amplitude. We
investigate how each class of model behaves under the external periodic
forcing, taking the well-studied van der Pol equation as an example. We find
that, when the forcing is additive, the noise-induced oscillator can show only
one-to-one entrainment to the external frequency, in contrast to the limit
cycle oscillator which is known to entrain to any ratio. When the external
forcing is multiplicative, on the other hand, the noise-induced oscillator can
show entrainment to a few ratios other than one-to-one, while the limit cycle
oscillator shows entrain to any ratio. The noise blurs the entrainment in
general, but clear entrainment regions for limit cycles can be identified as
long as the noise is not too strong.
|
[
{
"created": "Fri, 11 Jan 2013 10:01:49 GMT",
"version": "v1"
},
{
"created": "Fri, 17 May 2013 01:52:31 GMT",
"version": "v2"
}
] |
2015-01-20
|
[
[
"Mitarai",
"Namiko",
""
],
[
"Alon",
"Uri",
""
],
[
"Jensen",
"Mogens H.",
""
]
] |
Theoretical models that describe oscillations in biological systems are often either a limit cycle oscillator, where the deterministic nonlinear dynamics gives sustained periodic oscillations, or a noise-induced oscillator, where a fixed point is linearly stable with complex eigenvalues and addition of noise gives oscillations around the fixed point with fluctuating amplitude. We investigate how each class of model behaves under the external periodic forcing, taking the well-studied van der Pol equation as an example. We find that, when the forcing is additive, the noise-induced oscillator can show only one-to-one entrainment to the external frequency, in contrast to the limit cycle oscillator which is known to entrain to any ratio. When the external forcing is multiplicative, on the other hand, the noise-induced oscillator can show entrainment to a few ratios other than one-to-one, while the limit cycle oscillator shows entrain to any ratio. The noise blurs the entrainment in general, but clear entrainment regions for limit cycles can be identified as long as the noise is not too strong.
|
1004.3138
|
Adri\'an L\'opez Garc\'ia de Lomana
|
Adri\'an L\'opez Garc\'ia de Lomana, Qasim K. Beg, G. de Fabritiis and
Jordi Vill\`a-Freixa
|
Statistical Analysis of Global Connectivity and Activity Distributions
in Cellular Networks
|
17 pages, 1 figure, accepted for publication in Journal of
Computational Biology
| null | null | null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Various molecular interaction networks have been claimed to follow power-law
decay for their global connectivity distribution. It has been proposed that
there may be underlying generative models that explain this heavy-tailed
behavior by self-reinforcement processes such as classical or hierarchical
scale-free network models. Here we analyze a comprehensive data set of
protein-protein and transcriptional regulatory interaction networks in yeast,
an E. coli metabolic network, and gene activity profiles for different
metabolic states in both organisms. We show that in all cases the networks have
a heavy-tailed distribution, but most of them present significant differences
from a power-law model according to a stringent statistical test. Those few
data sets that have a statistically significant fit with a power-law model
follow other distributions equally well. Thus, while our analysis supports that
both global connectivity interaction networks and activity distributions are
heavy-tailed, they are not generally described by any specific distribution
model, leaving space for further inferences on generative models.
|
[
{
"created": "Mon, 19 Apr 2010 09:34:02 GMT",
"version": "v1"
}
] |
2010-04-20
|
[
[
"de Lomana",
"Adrián López García",
""
],
[
"Beg",
"Qasim K.",
""
],
[
"de Fabritiis",
"G.",
""
],
[
"Villà-Freixa",
"Jordi",
""
]
] |
Various molecular interaction networks have been claimed to follow power-law decay for their global connectivity distribution. It has been proposed that there may be underlying generative models that explain this heavy-tailed behavior by self-reinforcement processes such as classical or hierarchical scale-free network models. Here we analyze a comprehensive data set of protein-protein and transcriptional regulatory interaction networks in yeast, an E. coli metabolic network, and gene activity profiles for different metabolic states in both organisms. We show that in all cases the networks have a heavy-tailed distribution, but most of them present significant differences from a power-law model according to a stringent statistical test. Those few data sets that have a statistically significant fit with a power-law model follow other distributions equally well. Thus, while our analysis supports that both global connectivity interaction networks and activity distributions are heavy-tailed, they are not generally described by any specific distribution model, leaving space for further inferences on generative models.
|
q-bio/0607010
|
Franco Bagnoli
|
Luca Sguanci, Pietro Lio', Franco Bagnoli
|
The influence of risk perception in epidemics: a cellular agent model
| null |
Lecture Notes in Computer Science. vol. 4173, pp. 321-329 (2006)
|
10.1007/11861201_38
| null |
q-bio.PE
| null |
Our work stems from the consideration that the spreading of a disease is
modulated by the individual's perception of the infected neighborhood and
his/her strategy to avoid being infected as well. We introduced a general
``cellular agent'' model that accounts for a hetereogeneous and variable
network of connections. The probability of infection is assumed to depend on
the perception that an individual has about the spreading of the disease in her
local neighborhood and on broadcasting media. In the one-dimensional
homogeneous case the model reduces to the DK one, while for long-range coupling
the dynamics exhibits large fluctuations that may lead to the complete
extinction of the disease.
|
[
{
"created": "Thu, 6 Jul 2006 13:50:21 GMT",
"version": "v1"
}
] |
2008-01-20
|
[
[
"Sguanci",
"Luca",
""
],
[
"Lio'",
"Pietro",
""
],
[
"Bagnoli",
"Franco",
""
]
] |
Our work stems from the consideration that the spreading of a disease is modulated by the individual's perception of the infected neighborhood and his/her strategy to avoid being infected as well. We introduced a general ``cellular agent'' model that accounts for a hetereogeneous and variable network of connections. The probability of infection is assumed to depend on the perception that an individual has about the spreading of the disease in her local neighborhood and on broadcasting media. In the one-dimensional homogeneous case the model reduces to the DK one, while for long-range coupling the dynamics exhibits large fluctuations that may lead to the complete extinction of the disease.
|
0802.0209
|
Corey S. O'Hern
|
Gregg Lois, Jerzy Blawzdziewicz, and Corey S. O'Hern
|
Reliable protein folding on non-funneled energy landscapes: the free
energy reaction path
|
13 pages, 9 figures
|
Biophys. J. 95, 2692 (2008)
|
10.1529/biophysj.108.133132
| null |
q-bio.BM
| null |
A theoretical framework is developed to study the dynamics of protein
folding. The key insight is that the search for the native protein conformation
is influenced by the rate r at which external parameters, such as temperature,
chemical denaturant or pH, are adjusted to induce folding. A theory based on
this insight predicts that (1) proteins with non-funneled energy landscapes can
fold reliably to their native state, (2) reliable folding can occur as an
equilibrium or out-of-equilibrium process, and (3) reliable folding only occurs
when the rate r is below a limiting value, which can be calculated from
measurements of the free energy. We test these predictions against numerical
simulations of model proteins with a single energy scale.
|
[
{
"created": "Fri, 1 Feb 2008 21:55:57 GMT",
"version": "v1"
}
] |
2009-11-13
|
[
[
"Lois",
"Gregg",
""
],
[
"Blawzdziewicz",
"Jerzy",
""
],
[
"O'Hern",
"Corey S.",
""
]
] |
A theoretical framework is developed to study the dynamics of protein folding. The key insight is that the search for the native protein conformation is influenced by the rate r at which external parameters, such as temperature, chemical denaturant or pH, are adjusted to induce folding. A theory based on this insight predicts that (1) proteins with non-funneled energy landscapes can fold reliably to their native state, (2) reliable folding can occur as an equilibrium or out-of-equilibrium process, and (3) reliable folding only occurs when the rate r is below a limiting value, which can be calculated from measurements of the free energy. We test these predictions against numerical simulations of model proteins with a single energy scale.
|
2206.14947
|
Alexandra Rekesh
|
Tekin Gunasar, Alexandra Rekesh, Atul Nair, Penelope King, Anastasiya
Markova, Jiaqi Zhang, and Isabel Tate
|
Decision Forest Based EMG Signal Classification with Low Volume Dataset
Augmented with Random Variance Gaussian Noise
| null | null | null | null |
q-bio.NC cs.LG eess.SP stat.ML
|
http://creativecommons.org/licenses/by/4.0/
|
Electromyography signals can be used as training data by machine learning
models to classify various gestures. We seek to produce a model that can
classify six different hand gestures with a limited number of samples that
generalizes well to a wider audience while comparing the effect of our feature
extraction results on model accuracy to other more conventional methods such as
the use of AR parameters on a sliding window across the channels of a signal.
We appeal to a set of more elementary methods such as the use of random bounds
on a signal, but desire to show the power these methods can carry in an online
setting where EMG classification is being conducted, as opposed to more
complicated methods such as the use of the Fourier Transform. To augment our
limited training data, we used a standard technique, known as jitter, where
random noise is added to each observation in a channel wise manner. Once all
datasets were produced using the above methods, we performed a grid search with
Random Forest and XGBoost to ultimately create a high accuracy model. For human
computer interface purposes, high accuracy classification of EMG signals is of
particular importance to their functioning and given the difficulty and cost of
amassing any sort of biomedical data in a high volume, it is valuable to have
techniques that can work with a low amount of high-quality samples with less
expensive feature extraction methods that can reliably be carried out in an
online application.
|
[
{
"created": "Wed, 29 Jun 2022 23:22:18 GMT",
"version": "v1"
}
] |
2022-07-01
|
[
[
"Gunasar",
"Tekin",
""
],
[
"Rekesh",
"Alexandra",
""
],
[
"Nair",
"Atul",
""
],
[
"King",
"Penelope",
""
],
[
"Markova",
"Anastasiya",
""
],
[
"Zhang",
"Jiaqi",
""
],
[
"Tate",
"Isabel",
""
]
] |
Electromyography signals can be used as training data by machine learning models to classify various gestures. We seek to produce a model that can classify six different hand gestures with a limited number of samples that generalizes well to a wider audience while comparing the effect of our feature extraction results on model accuracy to other more conventional methods such as the use of AR parameters on a sliding window across the channels of a signal. We appeal to a set of more elementary methods such as the use of random bounds on a signal, but desire to show the power these methods can carry in an online setting where EMG classification is being conducted, as opposed to more complicated methods such as the use of the Fourier Transform. To augment our limited training data, we used a standard technique, known as jitter, where random noise is added to each observation in a channel wise manner. Once all datasets were produced using the above methods, we performed a grid search with Random Forest and XGBoost to ultimately create a high accuracy model. For human computer interface purposes, high accuracy classification of EMG signals is of particular importance to their functioning and given the difficulty and cost of amassing any sort of biomedical data in a high volume, it is valuable to have techniques that can work with a low amount of high-quality samples with less expensive feature extraction methods that can reliably be carried out in an online application.
|
2104.08280
|
\'Elie Besserer-Offroy Ph.D.
|
M\'elanie Vivancos, Roberto Fanelli, \'Elie Besserer-Offroy, Sabrina
Beaulieu, Magali Chartier, Martin Resua-Rojas, Christine E. Mona, Santo
Previti, Emmanuelle R\'emond, Jean-Michel Longpr\'e, Florine Cavelier,
Philippe Sarret
|
Metabolically Stable Neurotensin Analogs Exert Potent and Long-Acting
Analgesia Without Hypothermia
|
This is the post-print (accepted) version of the following article:
Vivancos M, et al. (2021), Behav Brain Res. doi: 10.1016/j.bbr.2021.113189,
which has been accepted and published in final form at
https://www.sciencedirect.com/science/article/pii/S0166432821000772
|
Behavioural Brain Research, 405:113189 (2021)
|
10.1016/j.bbr.2021.113189
| null |
q-bio.BM
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
The endogenous tridecapeptide neurotensin (NT) has emerged as an important
inhibitory modulator of pain transmission, exerting its analgesic action
through the activation of the G protein-coupled receptors, NTS1 and NTS2.
Whereas both NT receptors mediate the analgesic effects of NT, NTS1 activation
also produces hypotension and hypothermia, which may represent obstacles for
the development of new pain medications. In the present study, we implemented
various chemical strategies to improve the metabolic stability of the
biologically active fragment NT(8-13) and assessed their NTS1/NTS2 relative
binding affinities. We then determined their ability to reduce the nociceptive
behaviors in acute, tonic, and chronic pain models and to modulate blood
pressure and body temperature. To this end, we synthesized a series of NT(8-13)
analogs carrying a reduced amide bond at Lys8-Lys9 and harboring site-selective
modifications with unnatural amino acids, such as silaproline (Sip) and
trimethylsilylalanine (TMSAla). Incorporation of Sip and TMSAla respectively in
positions 10 and 13 of NT(8-13) combined with the Lys8-Lys9 reduced amine bond
(JMV5296) greatly prolonged the plasma half-life time over 20 hours. These
modifications also led to a 25-fold peptide selectivity toward NTS2. More
importantly, central delivery of JMV5296 was able to induce a strong
antinociceptive effect in acute (tail-flick), tonic (formalin), and chronic
inflammatory (CFA) pain models without inducing hypothermia. Altogether, these
results demonstrate that the chemically-modified NT(8-13) analog JMV5296
exhibits a better therapeutic profile and may thus represent a promising avenue
to guide the development of new stable NT agonists and improve pain management.
|
[
{
"created": "Fri, 16 Apr 2021 23:18:14 GMT",
"version": "v1"
}
] |
2021-04-20
|
[
[
"Vivancos",
"Mélanie",
""
],
[
"Fanelli",
"Roberto",
""
],
[
"Besserer-Offroy",
"Élie",
""
],
[
"Beaulieu",
"Sabrina",
""
],
[
"Chartier",
"Magali",
""
],
[
"Resua-Rojas",
"Martin",
""
],
[
"Mona",
"Christine E.",
""
],
[
"Previti",
"Santo",
""
],
[
"Rémond",
"Emmanuelle",
""
],
[
"Longpré",
"Jean-Michel",
""
],
[
"Cavelier",
"Florine",
""
],
[
"Sarret",
"Philippe",
""
]
] |
The endogenous tridecapeptide neurotensin (NT) has emerged as an important inhibitory modulator of pain transmission, exerting its analgesic action through the activation of the G protein-coupled receptors, NTS1 and NTS2. Whereas both NT receptors mediate the analgesic effects of NT, NTS1 activation also produces hypotension and hypothermia, which may represent obstacles for the development of new pain medications. In the present study, we implemented various chemical strategies to improve the metabolic stability of the biologically active fragment NT(8-13) and assessed their NTS1/NTS2 relative binding affinities. We then determined their ability to reduce the nociceptive behaviors in acute, tonic, and chronic pain models and to modulate blood pressure and body temperature. To this end, we synthesized a series of NT(8-13) analogs carrying a reduced amide bond at Lys8-Lys9 and harboring site-selective modifications with unnatural amino acids, such as silaproline (Sip) and trimethylsilylalanine (TMSAla). Incorporation of Sip and TMSAla respectively in positions 10 and 13 of NT(8-13) combined with the Lys8-Lys9 reduced amine bond (JMV5296) greatly prolonged the plasma half-life time over 20 hours. These modifications also led to a 25-fold peptide selectivity toward NTS2. More importantly, central delivery of JMV5296 was able to induce a strong antinociceptive effect in acute (tail-flick), tonic (formalin), and chronic inflammatory (CFA) pain models without inducing hypothermia. Altogether, these results demonstrate that the chemically-modified NT(8-13) analog JMV5296 exhibits a better therapeutic profile and may thus represent a promising avenue to guide the development of new stable NT agonists and improve pain management.
|
1501.01860
|
Simon R. Schultz
|
Simon R. Schultz, Robin A. A. Ince and Stefano Panzeri
|
Applications of Information Theory to Analysis of Neural Data
|
8 pages, 2 figures
|
Encyclopedia of Computational Neuroscience 2014, pp 1-6
|
10.1007/978-1-4614-7320-6_280-1
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Information theory is a practical and theoretical framework developed for the
study of communication over noisy channels. Its probabilistic basis and
capacity to relate statistical structure to function make it ideally suited for
studying information flow in the nervous system. It has a number of useful
properties: it is a general measure sensitive to any relationship, not only
linear effects; it has meaningful units which in many cases allow direct
comparison between different experiments; and it can be used to study how much
information can be gained by observing neural responses in single trials,
rather than in averages over multiple trials. A variety of information
theoretic quantities are commonly used in neuroscience - (see entry
"Definitions of Information-Theoretic Quantities"). In this entry we review
some applications of information theory in neuroscience to study encoding of
information in both single neurons and neuronal populations.
|
[
{
"created": "Thu, 8 Jan 2015 14:16:02 GMT",
"version": "v1"
}
] |
2015-01-09
|
[
[
"Schultz",
"Simon R.",
""
],
[
"Ince",
"Robin A. A.",
""
],
[
"Panzeri",
"Stefano",
""
]
] |
Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying information flow in the nervous system. It has a number of useful properties: it is a general measure sensitive to any relationship, not only linear effects; it has meaningful units which in many cases allow direct comparison between different experiments; and it can be used to study how much information can be gained by observing neural responses in single trials, rather than in averages over multiple trials. A variety of information theoretic quantities are commonly used in neuroscience - (see entry "Definitions of Information-Theoretic Quantities"). In this entry we review some applications of information theory in neuroscience to study encoding of information in both single neurons and neuronal populations.
|
2210.06069
|
Yangtian Zhang
|
Yangtian Zhang, Huiyu Cai, Chence Shi, Bozitao Zhong, Jian Tang
|
E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
|
International Conference on Learning Representations (ICLR 2023)
| null | null | null |
q-bio.BM cs.LG
|
http://creativecommons.org/licenses/by/4.0/
|
In silico prediction of the ligand binding pose to a given protein target is
a crucial but challenging task in drug discovery. This work focuses on blind
flexible selfdocking, where we aim to predict the positions, orientations and
conformations of docked molecules. Traditional physics-based methods usually
suffer from inaccurate scoring functions and high inference cost. Recently,
data-driven methods based on deep learning techniques are attracting growing
interest thanks to their efficiency during inference and promising performance.
These methods usually either adopt a two-stage approach by first predicting the
distances between proteins and ligands and then generating the final
coordinates based on the predicted distances, or directly predicting the global
roto-translation of ligands. In this paper, we take a different route. Inspired
by the resounding success of AlphaFold2 for protein structure prediction, we
propose E3Bind, an end-to-end equivariant network that iteratively updates the
ligand pose. E3Bind models the protein-ligand interaction through careful
consideration of the geometric constraints in docking and the local context of
the binding site. Experiments on standard benchmark datasets demonstrate the
superior performance of our end-to-end trainable model compared to traditional
and recently-proposed deep learning methods.
|
[
{
"created": "Wed, 12 Oct 2022 10:25:54 GMT",
"version": "v1"
},
{
"created": "Thu, 1 Jun 2023 10:05:06 GMT",
"version": "v2"
}
] |
2023-06-02
|
[
[
"Zhang",
"Yangtian",
""
],
[
"Cai",
"Huiyu",
""
],
[
"Shi",
"Chence",
""
],
[
"Zhong",
"Bozitao",
""
],
[
"Tang",
"Jian",
""
]
] |
In silico prediction of the ligand binding pose to a given protein target is a crucial but challenging task in drug discovery. This work focuses on blind flexible selfdocking, where we aim to predict the positions, orientations and conformations of docked molecules. Traditional physics-based methods usually suffer from inaccurate scoring functions and high inference cost. Recently, data-driven methods based on deep learning techniques are attracting growing interest thanks to their efficiency during inference and promising performance. These methods usually either adopt a two-stage approach by first predicting the distances between proteins and ligands and then generating the final coordinates based on the predicted distances, or directly predicting the global roto-translation of ligands. In this paper, we take a different route. Inspired by the resounding success of AlphaFold2 for protein structure prediction, we propose E3Bind, an end-to-end equivariant network that iteratively updates the ligand pose. E3Bind models the protein-ligand interaction through careful consideration of the geometric constraints in docking and the local context of the binding site. Experiments on standard benchmark datasets demonstrate the superior performance of our end-to-end trainable model compared to traditional and recently-proposed deep learning methods.
|
2402.15181
|
Diwakar Shukla
|
Joseph D. Clark, Xuenan Mi, Douglas A. Mitchell, and Diwakar Shukla
|
Substrate Prediction for RiPP Biosynthetic Enzymes via Masked Language
Modeling and Transfer Learning
| null | null | null | null |
q-bio.QM q-bio.BM
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Ribosomally synthesized and post-translationally modified peptide (RiPP)
biosynthetic enzymes often exhibit promiscuous substrate preferences that
cannot be reduced to simple rules. Large language models are promising tools
for predicting such peptide fitness landscapes. However, state-of-the-art
protein language models are trained on relatively few peptide sequences. A
previous study comprehensively profiled the peptide substrate preferences of
LazBF (a two-component serine dehydratase) and LazDEF (a three-component azole
synthetase) from the lactazole biosynthetic pathway. We demonstrated that
masked language modeling of LazBF substrate preferences produced language model
embeddings that improved downstream classification models of both LazBF and
LazDEF substrates. Similarly, masked language modeling of LazDEF substrate
preferences produced embeddings that improved the performance of classification
models of both LazBF and LazDEF substrates. Our results suggest that the models
learned functional forms that are transferable between distinct enzymatic
transformations that act within the same biosynthetic pathway. Our transfer
learning method improved performance and data efficiency in data-scarce
scenarios. We then fine-tuned models on each data set and showed that the
fine-tuned models provided interpretable insight that we anticipate will
facilitate the design of substrate libraries that are compatible with desired
RiPP biosynthetic pathways.
|
[
{
"created": "Fri, 23 Feb 2024 08:23:26 GMT",
"version": "v1"
}
] |
2024-02-26
|
[
[
"Clark",
"Joseph D.",
""
],
[
"Mi",
"Xuenan",
""
],
[
"Mitchell",
"Douglas A.",
""
],
[
"Shukla",
"Diwakar",
""
]
] |
Ribosomally synthesized and post-translationally modified peptide (RiPP) biosynthetic enzymes often exhibit promiscuous substrate preferences that cannot be reduced to simple rules. Large language models are promising tools for predicting such peptide fitness landscapes. However, state-of-the-art protein language models are trained on relatively few peptide sequences. A previous study comprehensively profiled the peptide substrate preferences of LazBF (a two-component serine dehydratase) and LazDEF (a three-component azole synthetase) from the lactazole biosynthetic pathway. We demonstrated that masked language modeling of LazBF substrate preferences produced language model embeddings that improved downstream classification models of both LazBF and LazDEF substrates. Similarly, masked language modeling of LazDEF substrate preferences produced embeddings that improved the performance of classification models of both LazBF and LazDEF substrates. Our results suggest that the models learned functional forms that are transferable between distinct enzymatic transformations that act within the same biosynthetic pathway. Our transfer learning method improved performance and data efficiency in data-scarce scenarios. We then fine-tuned models on each data set and showed that the fine-tuned models provided interpretable insight that we anticipate will facilitate the design of substrate libraries that are compatible with desired RiPP biosynthetic pathways.
|
0705.2105
|
Erik Volz
|
Erik Volz and Lauren Ancel Meyers
|
SIR epidemics in dynamic contact networks
|
20 pages, 4 figures. Submitted to Proc. Roy. Soc. B
| null | null | null |
q-bio.PE q-bio.QM
| null |
Contact patterns in populations fundamentally influence the spread of
infectious diseases. Current mathematical methods for epidemiological
forecasting on networks largely assume that contacts between individuals are
fixed, at least for the duration of an outbreak. In reality, contact patterns
may be quite fluid, with individuals frequently making and breaking social or
sexual relationships. Here we develop a mathematical approach to predicting
disease transmission on dynamic networks in which each individual has a
characteristic behavior (typical contact number), but the identities of their
contacts change in time. We show that dynamic contact patterns shape
epidemiological dynamics in ways that cannot be adequately captured in static
network models or mass-action models. Our new model interpolates smoothly
between static network models and mass-action models using a mixing parameter,
thereby providing a bridge between disparate classes of epidemiological models.
Using epidemiological and sexual contact data from an Atlanta high school, we
then demonstrate the utility of this method for forecasting and controlling
sexually transmitted disease outbreaks.
|
[
{
"created": "Tue, 15 May 2007 09:40:40 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Volz",
"Erik",
""
],
[
"Meyers",
"Lauren Ancel",
""
]
] |
Contact patterns in populations fundamentally influence the spread of infectious diseases. Current mathematical methods for epidemiological forecasting on networks largely assume that contacts between individuals are fixed, at least for the duration of an outbreak. In reality, contact patterns may be quite fluid, with individuals frequently making and breaking social or sexual relationships. Here we develop a mathematical approach to predicting disease transmission on dynamic networks in which each individual has a characteristic behavior (typical contact number), but the identities of their contacts change in time. We show that dynamic contact patterns shape epidemiological dynamics in ways that cannot be adequately captured in static network models or mass-action models. Our new model interpolates smoothly between static network models and mass-action models using a mixing parameter, thereby providing a bridge between disparate classes of epidemiological models. Using epidemiological and sexual contact data from an Atlanta high school, we then demonstrate the utility of this method for forecasting and controlling sexually transmitted disease outbreaks.
|
1904.01208
|
Genki Ichinose
|
Azumi Mamiya and Genki Ichinose
|
Strategies that enforce linear payoff relationships under observation
errors in Repeated Prisoner's Dilemma game
|
19 pages, 3 figures
|
Journal of Theoretical Biology 477, 63-76 (2019)
| null | null |
q-bio.PE physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The theory of repeated games analyzes the long-term relationship of
interacting players and mathematically reveals the condition of how cooperation
is achieved, which is not achieved in a one-shot game. In the repeated
prisoner's dilemma (RPD) game with no errors, zero-determinant (ZD) strategies
allow a player to unilaterally set a linear relationship between the player's
own payoff and the opponent's payoff regardless of the strategy that the
opponent implements. In contrast, unconditional strategies such as ALLD and
ALLC also unilaterally set a linear payoff relationship. Errors often happen
between players in the real world. However, little is known about the existence
of such strategies in the RPD game with errors. Here, we analytically search
for all strategies that enforce a linear payoff relationship under observation
errors in the RPD game. As a result, we found that, even in the case with
observation errors, the only strategy sets that enforce a linear payoff
relationship are either ZD strategies or unconditional strategies and that no
other strategies can enforce it, which were numerically confirmed.
|
[
{
"created": "Tue, 2 Apr 2019 04:30:14 GMT",
"version": "v1"
},
{
"created": "Wed, 19 Jun 2019 01:15:36 GMT",
"version": "v2"
}
] |
2019-06-20
|
[
[
"Mamiya",
"Azumi",
""
],
[
"Ichinose",
"Genki",
""
]
] |
The theory of repeated games analyzes the long-term relationship of interacting players and mathematically reveals the condition of how cooperation is achieved, which is not achieved in a one-shot game. In the repeated prisoner's dilemma (RPD) game with no errors, zero-determinant (ZD) strategies allow a player to unilaterally set a linear relationship between the player's own payoff and the opponent's payoff regardless of the strategy that the opponent implements. In contrast, unconditional strategies such as ALLD and ALLC also unilaterally set a linear payoff relationship. Errors often happen between players in the real world. However, little is known about the existence of such strategies in the RPD game with errors. Here, we analytically search for all strategies that enforce a linear payoff relationship under observation errors in the RPD game. As a result, we found that, even in the case with observation errors, the only strategy sets that enforce a linear payoff relationship are either ZD strategies or unconditional strategies and that no other strategies can enforce it, which were numerically confirmed.
|
1610.07212
|
Alexander Pimenov
|
Alexander Pimenov
|
Positive steady state in multi-species models of real food webs
|
11 pages, 3 tables
| null | null | null |
q-bio.PE q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Real food web data available in the literature presents us with the relations
between various species, sizes of these species, metabolic types of the species
and other useful information, which allows us to define parameters for the
mathematical dynamical models of these food webs, and perform theoretical
studies of these models. Unfortunately, the researches often face the problem
of the extinction of the species in such situations, which could be an
important limiting factor. In this paper, we propose a simple algorithm of
parameterisation that leads to the existence of positive steady state and
improves persistence of the species in multi-species models of real food webs.
|
[
{
"created": "Sun, 23 Oct 2016 18:37:39 GMT",
"version": "v1"
}
] |
2016-10-25
|
[
[
"Pimenov",
"Alexander",
""
]
] |
Real food web data available in the literature presents us with the relations between various species, sizes of these species, metabolic types of the species and other useful information, which allows us to define parameters for the mathematical dynamical models of these food webs, and perform theoretical studies of these models. Unfortunately, the researches often face the problem of the extinction of the species in such situations, which could be an important limiting factor. In this paper, we propose a simple algorithm of parameterisation that leads to the existence of positive steady state and improves persistence of the species in multi-species models of real food webs.
|
1812.00625
|
Gestionnaire Hal-Upmc
|
Kevin Fidelin (ICM, INSERM, CNRS, UPMC), Lydia Djenoune (ICM, INSERM,
CNRS, UPMC, MNHN), Caleb Stokes (ICM, INSERM, CNRS, UPMC), Andrew Prendergast
(ICM, INSERM, CNRS, UPMC), Johanna G\'omez (ICM, INSERM, CNRS, UPMC), Audrey
Baradel (ICM, INSERM, CNRS, UPMC), Filippo Del\^A bene (UPMC), Claire Wyart
(ICM, INSERM, CNRS, UPMC)
|
State-Dependent Modulation of Locomotion by GABAergic Spinal Sensory
Neurons
| null |
Current Biology - CB, Elsevier, 2015, 25 (23), pp.3035-3047
| null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The cerebrospinal fluid (CSF) constitutes an interface through which chemical
cues can reach and modulate the activity of neurons located at the epithelial
boundary within the entire nervous system. Here, we investigate the role and
functional connectivity of a class of GABAergic sensory neurons contacting the
CSF in the vertebrate spinal cord and referred to as CSF-cNs. The remote
activation of CSF-cNs was shown to trigger delayed slow locomotion in the
zebrafish larva, suggesting that these cells modulate components of locomotor
central pattern generators (CPGs). Combining anatomy, electrophysiology, and
optogenetics in vivo, we show that CSF-cNs form active GABAergic synapses onto
V0-v glutamatergic interneurons, an essential component of locomotor CPGs. We
confirmed that activating CSF-cNs at rest induced delayed slow locomotion in
the fictive preparation. In contrast, the activation of CSF-cNs promptly
inhibited ongoing slow locomotion. Moreover, selective activation of rostral
CSF-cNs during ongoing activity disrupted rostrocaudal propagation of
descending excitation along the spinal cord, indicating that CSF-cNs primarily
act at the premotor level. Altogether, our results demonstrate how a spinal
GABAergic sensory neuron can tune the excitability of locomotor CPGs in a
state-dependent manner by projecting onto essential components of the
excitatory premotor pool.
|
[
{
"created": "Mon, 3 Dec 2018 09:35:14 GMT",
"version": "v1"
}
] |
2018-12-04
|
[
[
"Fidelin",
"Kevin",
"",
"ICM, INSERM, CNRS, UPMC"
],
[
"Djenoune",
"Lydia",
"",
"ICM, INSERM,\n CNRS, UPMC, MNHN"
],
[
"Stokes",
"Caleb",
"",
"ICM, INSERM, CNRS, UPMC"
],
[
"Prendergast",
"Andrew",
"",
"ICM, INSERM, CNRS, UPMC"
],
[
"Gómez",
"Johanna",
"",
"ICM, INSERM, CNRS, UPMC"
],
[
"Baradel",
"Audrey",
"",
"ICM, INSERM, CNRS, UPMC"
],
[
"bene",
"Filippo DelÂ",
"",
"UPMC"
],
[
"Wyart",
"Claire",
"",
"ICM, INSERM, CNRS, UPMC"
]
] |
The cerebrospinal fluid (CSF) constitutes an interface through which chemical cues can reach and modulate the activity of neurons located at the epithelial boundary within the entire nervous system. Here, we investigate the role and functional connectivity of a class of GABAergic sensory neurons contacting the CSF in the vertebrate spinal cord and referred to as CSF-cNs. The remote activation of CSF-cNs was shown to trigger delayed slow locomotion in the zebrafish larva, suggesting that these cells modulate components of locomotor central pattern generators (CPGs). Combining anatomy, electrophysiology, and optogenetics in vivo, we show that CSF-cNs form active GABAergic synapses onto V0-v glutamatergic interneurons, an essential component of locomotor CPGs. We confirmed that activating CSF-cNs at rest induced delayed slow locomotion in the fictive preparation. In contrast, the activation of CSF-cNs promptly inhibited ongoing slow locomotion. Moreover, selective activation of rostral CSF-cNs during ongoing activity disrupted rostrocaudal propagation of descending excitation along the spinal cord, indicating that CSF-cNs primarily act at the premotor level. Altogether, our results demonstrate how a spinal GABAergic sensory neuron can tune the excitability of locomotor CPGs in a state-dependent manner by projecting onto essential components of the excitatory premotor pool.
|
1005.5536
|
Peter Pfaffelhuber
|
Greg Ewing, Joachim Hermisson, Peter Pfaffelhuber, Johannes Rudolf
|
Selective sweeps for recessive alleles and for other modes of dominance
|
Published in the Journal of Mathematical Biology. The final
publication is available at http://www.springerlink.com
| null | null | null |
q-bio.PE math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A selective sweep describes the reduction of linked genetic variation due to
strong positive selection. If s is the fitness advantage of a homozygote for
the beneficial allele and h its dominance coefficient, it is usually assumed
that h=1/2, i.e. the beneficial allele is co-dominant. We complement existing
theory for selective sweeps by assuming that h is any value in [0,1]. We show
that genetic diversity patters under selective sweeps with strength s and
dominance 0<h<1 are similar to co-dominant sweeps with selection strength 2hs.
Moreover, we focus on the case h=0 of a completely recessive beneficial allele.
We find that the length of the sweep, i.e. the time from occurrence until
fixation of the beneficial allele, is of the order of sqrt(N/s) generations, if
N is the population size. Simulations as well as our results show that genetic
diversity patterns in the recessive case h=0 greatly differ from all other
cases.
|
[
{
"created": "Sun, 30 May 2010 14:39:26 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Nov 2010 10:55:48 GMT",
"version": "v2"
}
] |
2010-11-03
|
[
[
"Ewing",
"Greg",
""
],
[
"Hermisson",
"Joachim",
""
],
[
"Pfaffelhuber",
"Peter",
""
],
[
"Rudolf",
"Johannes",
""
]
] |
A selective sweep describes the reduction of linked genetic variation due to strong positive selection. If s is the fitness advantage of a homozygote for the beneficial allele and h its dominance coefficient, it is usually assumed that h=1/2, i.e. the beneficial allele is co-dominant. We complement existing theory for selective sweeps by assuming that h is any value in [0,1]. We show that genetic diversity patters under selective sweeps with strength s and dominance 0<h<1 are similar to co-dominant sweeps with selection strength 2hs. Moreover, we focus on the case h=0 of a completely recessive beneficial allele. We find that the length of the sweep, i.e. the time from occurrence until fixation of the beneficial allele, is of the order of sqrt(N/s) generations, if N is the population size. Simulations as well as our results show that genetic diversity patterns in the recessive case h=0 greatly differ from all other cases.
|
1302.7102
|
Zuo-Bing Wu
|
Zuo-Bing Wu
|
Periodic correlation structures in bacterial and archaeal complete
genomes
|
23 pages, 6 figures, 2 tables
|
Current Bioinformatics, Vol. 8(2), 267-274 (2013)
| null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The periodic transference of nucleotide strings in bacterial and archaeal
complete genomes is investigated by using the metric representation and the
recurrence plot method. The generated periodic correlation structures exhibit
four kinds of fundamental transferring characteristics: a single increasing
period, several increasing periods, an increasing quasi-period and almost
noincreasing period. The mechanism of the periodic transference is further
analyzed by determining all long periodic nucleotide strings in the bacterial
and archaeal complete genomes and is explained as follows: both the repetition
of basic periodic nucleotide strings and the transference of non-periodic
nucleotide strings would form the periodic correlation structures with
approximately the same increasing periods.
|
[
{
"created": "Thu, 28 Feb 2013 07:20:52 GMT",
"version": "v1"
}
] |
2013-03-01
|
[
[
"Wu",
"Zuo-Bing",
""
]
] |
The periodic transference of nucleotide strings in bacterial and archaeal complete genomes is investigated by using the metric representation and the recurrence plot method. The generated periodic correlation structures exhibit four kinds of fundamental transferring characteristics: a single increasing period, several increasing periods, an increasing quasi-period and almost noincreasing period. The mechanism of the periodic transference is further analyzed by determining all long periodic nucleotide strings in the bacterial and archaeal complete genomes and is explained as follows: both the repetition of basic periodic nucleotide strings and the transference of non-periodic nucleotide strings would form the periodic correlation structures with approximately the same increasing periods.
|
2208.04852
|
Artur M Schweidtmann
|
Jan G. Rittig, Qinghe Gao, Manuel Dahmen, Alexander Mitsos, Artur M.
Schweidtmann
|
Graph neural networks for the prediction of molecular structure-property
relationships
| null |
Machine Learning and Hybrid Modelling for Reaction Engineering,
Royal Society of Chemistry, ISBN 978-1-83916-563-4, 159-181, 2023
|
10.1039/BK9781837670178-00159
| null |
q-bio.BM cs.LG math.OC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Molecular property prediction is of crucial importance in many disciplines
such as drug discovery, molecular biology, or material and process design. The
frequently employed quantitative structure-property/activity relationships
(QSPRs/QSARs) characterize molecules by descriptors which are then mapped to
the properties of interest via a linear or nonlinear model. In contrast, graph
neural networks, a novel machine learning method, directly work on the
molecular graph, i.e., a graph representation where atoms correspond to nodes
and bonds correspond to edges. GNNs allow to learn properties in an end-to-end
fashion, thereby avoiding the need for informative descriptors as in
QSPRs/QSARs. GNNs have been shown to achieve state-of-the-art prediction
performance on various property predictions tasks and represent an active field
of research. We describe the fundamentals of GNNs and demonstrate the
application of GNNs via two examples for molecular property prediction.
|
[
{
"created": "Mon, 25 Jul 2022 11:30:44 GMT",
"version": "v1"
}
] |
2024-01-17
|
[
[
"Rittig",
"Jan G.",
""
],
[
"Gao",
"Qinghe",
""
],
[
"Dahmen",
"Manuel",
""
],
[
"Mitsos",
"Alexander",
""
],
[
"Schweidtmann",
"Artur M.",
""
]
] |
Molecular property prediction is of crucial importance in many disciplines such as drug discovery, molecular biology, or material and process design. The frequently employed quantitative structure-property/activity relationships (QSPRs/QSARs) characterize molecules by descriptors which are then mapped to the properties of interest via a linear or nonlinear model. In contrast, graph neural networks, a novel machine learning method, directly work on the molecular graph, i.e., a graph representation where atoms correspond to nodes and bonds correspond to edges. GNNs allow to learn properties in an end-to-end fashion, thereby avoiding the need for informative descriptors as in QSPRs/QSARs. GNNs have been shown to achieve state-of-the-art prediction performance on various property predictions tasks and represent an active field of research. We describe the fundamentals of GNNs and demonstrate the application of GNNs via two examples for molecular property prediction.
|
q-bio/0408016
|
Michael Deem
|
Enrique T. Munoz and Michael W. Deem
|
Epitope analysis for influenza vaccine design
|
20 pages, 3 figures, to appear in Vaccine
| null | null | null |
q-bio.BM q-bio.QM
| null |
Until now, design of the annual influenza vaccine has relied on phylogenetic
or whole-sequence comparisons of the viral coat proteins hemagglutinin and
neuraminidase, with vaccine effectiveness assumed to correlate monotonically to
the vaccine-influenza sequence difference. We use a theory from statistical
mechanics to quantify the non-monotonic immune response that results from
antigenic drift in the epitopes of the hemagglutinin and neuraminidase
proteins. The results explain the ineffectiveness of the 2003--2004 influenza
vaccine in the United States and provide an accurate measure by which to
optimize the effectiveness of future annual influenza vaccines.
|
[
{
"created": "Mon, 23 Aug 2004 22:11:05 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Munoz",
"Enrique T.",
""
],
[
"Deem",
"Michael W.",
""
]
] |
Until now, design of the annual influenza vaccine has relied on phylogenetic or whole-sequence comparisons of the viral coat proteins hemagglutinin and neuraminidase, with vaccine effectiveness assumed to correlate monotonically to the vaccine-influenza sequence difference. We use a theory from statistical mechanics to quantify the non-monotonic immune response that results from antigenic drift in the epitopes of the hemagglutinin and neuraminidase proteins. The results explain the ineffectiveness of the 2003--2004 influenza vaccine in the United States and provide an accurate measure by which to optimize the effectiveness of future annual influenza vaccines.
|
2104.08237
|
Johanna Vielhaben
|
Johanna Vielhaben, Markus Wenzel, Eva Weicken, Nils Strodthoff
|
Predicting the Binding of SARS-CoV-2 Peptides to the Major
Histocompatibility Complex with Recurrent Neural Networks
|
Accepted at ICLR 2021 Workshop: Machine Learning for Preventing and
Combating Pandemics; code available at https://github.com/nstrodt/USMPep
| null | null | null |
q-bio.QM cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Predicting the binding of viral peptides to the major histocompatibility
complex with machine learning can potentially extend the computational
immunology toolkit for vaccine development, and serve as a key component in the
fight against a pandemic. In this work, we adapt and extend USMPep, a recently
proposed, conceptually simple prediction algorithm based on recurrent neural
networks. Most notably, we combine regressors (binding affinity data) and
classifiers (mass spectrometry data) from qualitatively different data sources
to obtain a more comprehensive prediction tool. We evaluate the performance on
a recently released SARS-CoV-2 dataset with binding stability measurements.
USMPep not only sets new benchmarks on selected single alleles, but
consistently turns out to be among the best-performing methods or, for some
metrics, to be even the overall best-performing method for this task.
|
[
{
"created": "Fri, 16 Apr 2021 17:16:35 GMT",
"version": "v1"
}
] |
2021-04-19
|
[
[
"Vielhaben",
"Johanna",
""
],
[
"Wenzel",
"Markus",
""
],
[
"Weicken",
"Eva",
""
],
[
"Strodthoff",
"Nils",
""
]
] |
Predicting the binding of viral peptides to the major histocompatibility complex with machine learning can potentially extend the computational immunology toolkit for vaccine development, and serve as a key component in the fight against a pandemic. In this work, we adapt and extend USMPep, a recently proposed, conceptually simple prediction algorithm based on recurrent neural networks. Most notably, we combine regressors (binding affinity data) and classifiers (mass spectrometry data) from qualitatively different data sources to obtain a more comprehensive prediction tool. We evaluate the performance on a recently released SARS-CoV-2 dataset with binding stability measurements. USMPep not only sets new benchmarks on selected single alleles, but consistently turns out to be among the best-performing methods or, for some metrics, to be even the overall best-performing method for this task.
|
1504.03343
|
Apoorvagiri Lnu
|
Apoorvagiri, M.S. Nagananda
|
Quantization of mental stress using various physiological markers
|
16 pages,11 Figures, 2 Tables; can also be found at PeerJ PrePrints
3:e1250 2015, page 1-16
| null |
10.7287/peerj.preprints.777v3
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The aim of this study is to quantize mental stress by integrating different
physiological markers like reaction time, photoplethysmograph (PPG), heart rate
variability (HRV) and subjective markers like questionnaire. The study included
10 subjects of age between 22 and 26 years. Study materials included the
results of PSS questionnaire, simple reaction time, PPG data, and HRV data
during a stress inducing stroop test. The study suggests that mental stress can
be quantized when stress is induced acquisitively and more accurate
quantification of stress can be achieved by integrating many physiological
parameters.
|
[
{
"created": "Thu, 5 Feb 2015 19:19:30 GMT",
"version": "v1"
},
{
"created": "Fri, 1 May 2015 03:30:45 GMT",
"version": "v2"
}
] |
2015-05-04
|
[
[
"Apoorvagiri",
"",
""
],
[
"Nagananda",
"M. S.",
""
]
] |
The aim of this study is to quantize mental stress by integrating different physiological markers like reaction time, photoplethysmograph (PPG), heart rate variability (HRV) and subjective markers like questionnaire. The study included 10 subjects of age between 22 and 26 years. Study materials included the results of PSS questionnaire, simple reaction time, PPG data, and HRV data during a stress inducing stroop test. The study suggests that mental stress can be quantized when stress is induced acquisitively and more accurate quantification of stress can be achieved by integrating many physiological parameters.
|
2110.13830
|
Farshad Rafiei
|
Farshad Rafiei and Dobromir Rahnev
|
Does TMS increase BOLD activity at the site of stimulation?
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Transcranial magnetic stimulation (TMS) is widely used for understanding
brain function in neurologically intact subjects and for the treatment of
various disorders. However, the precise neurophysiological effects of TMS at
the site of stimulation remain poorly understood. The local effects of TMS can
be studied using concurrent TMS-fMRI, a technique where TMS is delivered during
fMRI scanning. However, although concurrent TMS-fMRI was developed over 20
years ago and dozens of studies have used this technique, there is still no
consensus on whether TMS increases blood-oxygen-level-dependent (BOLD) activity
at the site of stimulation. To address this question, here we review all
previous concurrent TMS-fMRI studies that reported analyses of BOLD activity at
the target location. We find evidence that TMS increases local BOLD activity
when stimulating the primary motor and visual cortices but that these effects
are likely driven by the downstream consequences of TMS (finger twitches and
phosphenes). However, TMS does not appear to increase BOLD activity at the site
of stimulation for areas outside of the primary motor and visual cortices when
conducted at rest. We examine the possible reasons for such lack of BOLD signal
increase based on recent work in non-human animals. We argue that the current
evidence points to TMS inducing periods of increased and decreased neuronal
firing that mostly cancel each other out and therefore lead to no change in the
overall BOLD signal.
|
[
{
"created": "Tue, 26 Oct 2021 16:24:23 GMT",
"version": "v1"
}
] |
2021-10-27
|
[
[
"Rafiei",
"Farshad",
""
],
[
"Rahnev",
"Dobromir",
""
]
] |
Transcranial magnetic stimulation (TMS) is widely used for understanding brain function in neurologically intact subjects and for the treatment of various disorders. However, the precise neurophysiological effects of TMS at the site of stimulation remain poorly understood. The local effects of TMS can be studied using concurrent TMS-fMRI, a technique where TMS is delivered during fMRI scanning. However, although concurrent TMS-fMRI was developed over 20 years ago and dozens of studies have used this technique, there is still no consensus on whether TMS increases blood-oxygen-level-dependent (BOLD) activity at the site of stimulation. To address this question, here we review all previous concurrent TMS-fMRI studies that reported analyses of BOLD activity at the target location. We find evidence that TMS increases local BOLD activity when stimulating the primary motor and visual cortices but that these effects are likely driven by the downstream consequences of TMS (finger twitches and phosphenes). However, TMS does not appear to increase BOLD activity at the site of stimulation for areas outside of the primary motor and visual cortices when conducted at rest. We examine the possible reasons for such lack of BOLD signal increase based on recent work in non-human animals. We argue that the current evidence points to TMS inducing periods of increased and decreased neuronal firing that mostly cancel each other out and therefore lead to no change in the overall BOLD signal.
|
1408.6583
|
Chiu Man Ho
|
Chiu Man Ho, Stephen D.H. Hsu
|
Determination of Nonlinear Genetic Architecture using Compressed Sensing
|
20 pages, 8 figures. arXiv admin note: text overlap with
arXiv:1408.3421
|
GigaScience 4: 44 (2015)
| null | null |
q-bio.GN stat.AP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We introduce a statistical method that can reconstruct nonlinear genetic
models (i.e., including epistasis, or gene-gene interactions) from
phenotype-genotype (GWAS) data. The computational and data resource
requirements are similar to those necessary for reconstruction of linear
genetic models (or identification of gene-trait associations), assuming a
condition of generalized sparsity, which limits the total number of gene-gene
interactions. An example of a sparse nonlinear model is one in which a typical
locus interacts with several or even many others, but only a small subset of
all possible interactions exist. It seems plausible that most genetic
architectures fall in this category. Our method uses a generalization of
compressed sensing (L1-penalized regression) applied to nonlinear functions of
the sensing matrix. We give theoretical arguments suggesting that the method is
nearly optimal in performance, and demonstrate its effectiveness on broad
classes of nonlinear genetic models using both real and simulated human
genomes.
|
[
{
"created": "Wed, 27 Aug 2014 22:32:50 GMT",
"version": "v1"
},
{
"created": "Sun, 19 Jul 2015 21:33:35 GMT",
"version": "v2"
}
] |
2015-09-29
|
[
[
"Ho",
"Chiu Man",
""
],
[
"Hsu",
"Stephen D. H.",
""
]
] |
We introduce a statistical method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. The computational and data resource requirements are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. Our method uses a generalization of compressed sensing (L1-penalized regression) applied to nonlinear functions of the sensing matrix. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using both real and simulated human genomes.
|
0809.0773
|
Mukhtar Ullah Mr.
|
Mukhtar Ullah, Olaf Wolkenhauer
|
Investigating the two-moment characterisation of subcellular biochemical
networks
|
32 pages, 10 figures
| null | null | null |
q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
While ordinary differential equations (ODEs) form the conceptual framework
for modelling many cellular processes, specific situations demand stochastic
models to capture the influence of noise. The most common formulation of
stochastic models for biochemical networks is the chemical master equation
(CME). While stochastic simulations are a practical way to realise the CME,
analytical approximations offer more insight into the influence of noise.
Towards that end, the two-moment approximation (2MA) is a promising addition to
the established analytical approaches including the chemical Langevin equation
(CLE) and the related linear noise approximation (LNA). The 2MA approach
directly tracks the mean and (co)variance which are coupled in general. This
coupling is not obvious in CME and CLE and ignored by LNA and conventional ODE
models. We extend previous derivations of 2MA by allowing a) non-elementary
reactions and b) relative concentrations. Often, several elementary reactions
are approximated by a single step. Furthermore, practical situations often
require the use relative concentrations. We investigate the applicability of
the 2MA approach to the well established fission yeast cell cycle model. Our
analytical model reproduces the clustering of cycle times observed in
experiments. This is explained through multiple resettings of MPF, caused by
the coupling between mean and (co)variance, near the G2/M transition.
|
[
{
"created": "Thu, 4 Sep 2008 08:54:09 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Feb 2009 12:03:38 GMT",
"version": "v2"
},
{
"created": "Thu, 2 Apr 2009 10:56:46 GMT",
"version": "v3"
}
] |
2009-04-02
|
[
[
"Ullah",
"Mukhtar",
""
],
[
"Wolkenhauer",
"Olaf",
""
]
] |
While ordinary differential equations (ODEs) form the conceptual framework for modelling many cellular processes, specific situations demand stochastic models to capture the influence of noise. The most common formulation of stochastic models for biochemical networks is the chemical master equation (CME). While stochastic simulations are a practical way to realise the CME, analytical approximations offer more insight into the influence of noise. Towards that end, the two-moment approximation (2MA) is a promising addition to the established analytical approaches including the chemical Langevin equation (CLE) and the related linear noise approximation (LNA). The 2MA approach directly tracks the mean and (co)variance which are coupled in general. This coupling is not obvious in CME and CLE and ignored by LNA and conventional ODE models. We extend previous derivations of 2MA by allowing a) non-elementary reactions and b) relative concentrations. Often, several elementary reactions are approximated by a single step. Furthermore, practical situations often require the use relative concentrations. We investigate the applicability of the 2MA approach to the well established fission yeast cell cycle model. Our analytical model reproduces the clustering of cycle times observed in experiments. This is explained through multiple resettings of MPF, caused by the coupling between mean and (co)variance, near the G2/M transition.
|
1010.2508
|
Wilfred Kepseu
|
Wilfred D. Kepseu, Paul Woafo and H. Sakaguchi
|
Intercellular spiral waves of calcium in a two dimensional network of
cells
|
12 pages, 9 figures
| null | null | null |
q-bio.MN physics.bio-ph q-bio.BM q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
It is shown, by means of numerical simulations, that intercellular spiral
waves of calcium can be initiated in a network of coupled cells as a result of
a de-synchronization between Ca2+ oscillations in two domains. No artificial
heterogeneities need to be imposed to the system for spontaneous formation of
spiral waves. The de-synchronization occurs near the interface of the
stimulated region (which acts as a pacemaker) and propagates over the entire
network. We also find the outcome of the collision of two spiral waves.
|
[
{
"created": "Tue, 12 Oct 2010 20:29:04 GMT",
"version": "v1"
}
] |
2010-10-14
|
[
[
"Kepseu",
"Wilfred D.",
""
],
[
"Woafo",
"Paul",
""
],
[
"Sakaguchi",
"H.",
""
]
] |
It is shown, by means of numerical simulations, that intercellular spiral waves of calcium can be initiated in a network of coupled cells as a result of a de-synchronization between Ca2+ oscillations in two domains. No artificial heterogeneities need to be imposed to the system for spontaneous formation of spiral waves. The de-synchronization occurs near the interface of the stimulated region (which acts as a pacemaker) and propagates over the entire network. We also find the outcome of the collision of two spiral waves.
|
2404.02789
|
Giovanni Bussi
|
Giovanni Bussi, Massimiliano Bonomi, Paraskevi Gkeka, Michael Sattler,
Hashim M. Al-Hashimi, Pascal Auffinger, Maria Duca, Yann Foricher, Danny
Incarnato, Alisha N. Jones, Serdal Kirmizialtin, Miroslav Krepl, Modesto
Orozco, Giulia Palermo, Samuela Pasquali, Lo\"ic Salmon, Harald Schwalbe,
Eric Westhof, Martin Zacharias
|
RNA Dynamics from Experimental and Computational Approaches
| null | null | null | null |
q-bio.BM physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Ribonucleic acids (RNA) are unique in that they can store genetic
information, replicate and perform catalysis. Importantly, RNA molecules are
highly dynamic, and thus determining the ensemble of conformations that they
populate is crucial not only to elucidate their biological functions, but also
for their potential use as therapeutic targets. Computational and experimental
techniques provide complementary views on RNA dynamics, and their integration
is fundamental to improve the accuracy of computations and the resolution of
experiments. Recent exciting developments in this field, were discussed at the
CECAM workshop ``RNA dynamics from experimental and computational approaches'',
in Paris, June 26-28, 2023. This report outlines key `take-home' messages that
emerged during this workshop from the presentations and discussions.
|
[
{
"created": "Wed, 3 Apr 2024 14:56:41 GMT",
"version": "v1"
}
] |
2024-04-04
|
[
[
"Bussi",
"Giovanni",
""
],
[
"Bonomi",
"Massimiliano",
""
],
[
"Gkeka",
"Paraskevi",
""
],
[
"Sattler",
"Michael",
""
],
[
"Al-Hashimi",
"Hashim M.",
""
],
[
"Auffinger",
"Pascal",
""
],
[
"Duca",
"Maria",
""
],
[
"Foricher",
"Yann",
""
],
[
"Incarnato",
"Danny",
""
],
[
"Jones",
"Alisha N.",
""
],
[
"Kirmizialtin",
"Serdal",
""
],
[
"Krepl",
"Miroslav",
""
],
[
"Orozco",
"Modesto",
""
],
[
"Palermo",
"Giulia",
""
],
[
"Pasquali",
"Samuela",
""
],
[
"Salmon",
"Loïc",
""
],
[
"Schwalbe",
"Harald",
""
],
[
"Westhof",
"Eric",
""
],
[
"Zacharias",
"Martin",
""
]
] |
Ribonucleic acids (RNA) are unique in that they can store genetic information, replicate and perform catalysis. Importantly, RNA molecules are highly dynamic, and thus determining the ensemble of conformations that they populate is crucial not only to elucidate their biological functions, but also for their potential use as therapeutic targets. Computational and experimental techniques provide complementary views on RNA dynamics, and their integration is fundamental to improve the accuracy of computations and the resolution of experiments. Recent exciting developments in this field, were discussed at the CECAM workshop ``RNA dynamics from experimental and computational approaches'', in Paris, June 26-28, 2023. This report outlines key `take-home' messages that emerged during this workshop from the presentations and discussions.
|
2110.06228
|
Reinhard Schumacher
|
Robert A. Mason, Reinhard A. Schumacher, and Marcel A. Just
|
The Neuroscience of Advanced Scientific Concepts
|
12 pages, 6 figures, open access publication
|
npj Science of Learning, 6, 29 (2021)
|
10.1038/s41539-021-00107-6
| null |
q-bio.NC physics.ed-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Cognitive neuroscience methods can identify the fMRI-measured neural
representation of familiar individual concepts, such as apple, and decompose
them into meaningful neural and semantic components. This approach was applied
here to determine the neural representations and underlying dimensions of
representation of far more abstract physics concepts related to matter and
energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon
physics faculty members who thought about the main properties of each of the
concepts. One novel dimension coded the measurability vs. immeasurability of a
concept. Another novel dimension of representation evoked particularly by
post-classical concepts was associated with four types of cognitive processes,
each linked to particular brain regions: (1) Reasoning about intangibles,
taking into account their separation from direct experience and observability;
(2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning
about relations that are not apparent or observable; and (4) Knowledge
management of a large knowledge organization consisting of a multi-level
structure of other concepts. Two other underlying dimensions, previously found
in physics students, periodicity, and mathematical formulation, were also
present in this faculty sample. The data were analyzed using factor analysis of
stably responding voxels, a Gaussian-na\"ive Bayes machine-learning
classification of the activation patterns associated with each concept, and a
regression model that predicted activation patterns associated with each
concept based on independent ratings of the dimensions of the concepts. The
findings indicate that the human brain systematically organizes novel
scientific concepts in terms of new dimensions of neural representation.
|
[
{
"created": "Tue, 12 Oct 2021 18:00:03 GMT",
"version": "v1"
}
] |
2021-10-15
|
[
[
"Mason",
"Robert A.",
""
],
[
"Schumacher",
"Reinhard A.",
""
],
[
"Just",
"Marcel A.",
""
]
] |
Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-na\"ive Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation.
|
1208.2247
|
Alessandro Daducci
|
Alessandro Daducci, Dimitri Van De Ville, Jean-Philippe Thiran, Yves
Wiaux
|
Sparse regularization for fiber ODF reconstruction: from the
suboptimality of $\ell_2$ and $\ell_1$ priors to $\ell_0$
|
26 pages, 9 figures
| null | null | null |
q-bio.QM physics.med-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Diffusion MRI is a well established imaging modality providing a powerful way
to probe the structure of the white matter non-invasively. Despite its
potential, the intrinsic long scan times of these sequences have hampered their
use in clinical practice. For this reason, a large variety of methods have been
recently proposed to shorten the acquisition times. Among them, spherical
deconvolution approaches have gained a lot of interest for their ability to
reliably recover the intra-voxel fiber configuration with a relatively small
number of data samples. To overcome the intrinsic instabilities of
deconvolution, these methods use regularization schemes generally based on the
assumption that the fiber orientation distribution (FOD) to be recovered in
each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD)
approach resorts to Tikhonov regularization, based on an l2-norm prior, which
promotes a weak version of sparsity. Also, in the last few years compressed
sensing has been advocated to further accelerate the acquisitions and l1-norm
minimization is generally employed as a means to promote sparsity in the
recovered FODs. In this paper, we provide evidence that the use of an l1-norm
prior to regularize this class of problems is somewhat inconsistent with the
fact that the fiber compartments all sum up to unity. To overcome this l1
inconsistency while simultaneously exploiting sparsity more optimally than
through an l2 prior, we reformulate the reconstruction problem as a constrained
formulation between a data term and and a sparsity prior consisting in an
explicit bound on the l0 norm of the FOD, i.e. on the number of fibers. The
method has been tested both on synthetic and real data. Experimental results
show that the proposed l0 formulation significantly reduces modeling errors
compared to the state-of-the-art l2 and l1 regularization approaches.
|
[
{
"created": "Fri, 10 Aug 2012 18:44:28 GMT",
"version": "v1"
},
{
"created": "Thu, 11 Jul 2013 10:50:12 GMT",
"version": "v2"
},
{
"created": "Sat, 28 Dec 2013 12:38:21 GMT",
"version": "v3"
}
] |
2013-12-31
|
[
[
"Daducci",
"Alessandro",
""
],
[
"Van De Ville",
"Dimitri",
""
],
[
"Thiran",
"Jean-Philippe",
""
],
[
"Wiaux",
"Yves",
""
]
] |
Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an l2-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and l1-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an l1-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this l1 inconsistency while simultaneously exploiting sparsity more optimally than through an l2 prior, we reformulate the reconstruction problem as a constrained formulation between a data term and and a sparsity prior consisting in an explicit bound on the l0 norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed l0 formulation significantly reduces modeling errors compared to the state-of-the-art l2 and l1 regularization approaches.
|
1008.5072
|
Cornelis Storm
|
Elisabeth M. Huisman, Claus Heussinger, Cornelis Storm, Gerard T.
Barkema
|
Semiflexible Filamentous Composites
|
Phys. Rev. Lett, to appear (4 pages, 2 figures)
| null |
10.1103/PhysRevLett.105.118101
| null |
q-bio.BM cond-mat.soft
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Inspired by the ubiquity of composite filamentous networks in nature we
investigate models of biopolymer networks that consist of interconnected floppy
and stiff filaments. Numerical simulations carried out in three dimensions
allow us to explore the microscopic partitioning of stresses and strains
between the stiff and floppy fractions c_s and c_f, and reveal a non-trivial
relationship between the mechanical behavior and the relative fraction of stiff
polymer: when there are few stiff polymers, non-percolated stiff ``inclusions``
are protected from large deformations by an encompassing floppy matrix, while
at higher fractions of stiff material the stiff network is independently
percolated and dominates the mechanical response.
|
[
{
"created": "Mon, 30 Aug 2010 12:54:58 GMT",
"version": "v1"
}
] |
2015-05-19
|
[
[
"Huisman",
"Elisabeth M.",
""
],
[
"Heussinger",
"Claus",
""
],
[
"Storm",
"Cornelis",
""
],
[
"Barkema",
"Gerard T.",
""
]
] |
Inspired by the ubiquity of composite filamentous networks in nature we investigate models of biopolymer networks that consist of interconnected floppy and stiff filaments. Numerical simulations carried out in three dimensions allow us to explore the microscopic partitioning of stresses and strains between the stiff and floppy fractions c_s and c_f, and reveal a non-trivial relationship between the mechanical behavior and the relative fraction of stiff polymer: when there are few stiff polymers, non-percolated stiff ``inclusions`` are protected from large deformations by an encompassing floppy matrix, while at higher fractions of stiff material the stiff network is independently percolated and dominates the mechanical response.
|
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