id stringlengths 9 13 | submitter stringlengths 4 48 | authors stringlengths 4 9.62k | title stringlengths 4 343 | comments stringlengths 2 480 ⌀ | journal-ref stringlengths 9 309 ⌀ | doi stringlengths 12 138 ⌀ | report-no stringclasses 277 values | categories stringlengths 8 87 | license stringclasses 9 values | orig_abstract stringlengths 27 3.76k | versions listlengths 1 15 | update_date stringlengths 10 10 | authors_parsed listlengths 1 147 | abstract stringlengths 24 3.75k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2405.18329 | Davor Curic | Davor Curic, Surjeet Singh, Mojtaba Nazari, Majid H. Mohajerani, Joern
Davidsen | Spatial-temporal analysis of neural desynchronization in sleep-like
states reveals critical dynamics | null | Vol. 132, Iss. 21, 24 Phys. Rev. Lett. 132, 218403, Published 22
May 2024 | 10.1103/PhysRevLett.132.218403 | null | q-bio.NC cond-mat.stat-mech | http://creativecommons.org/licenses/by/4.0/ | Sleep is characterized by non-rapid eye movement (nREM) sleep, originating
from widespread neuronal synchrony, and REM sleep, with neuronal
desynchronization akin to waking behavior. While these were thought to be
global brain states, recent research suggests otherwise. Using time-frequency
analysis of mesoscopic voltage-sensitive dye recordings of mice in a
urethane-anesthetized model of sleep, we find transient neural
desynchronization occurring heterogeneously across the cortex within a
background of synchronized neural activity, in a manner reminiscent of a
critical spreading process and indicative of an "edge-of-synchronization phase"
transition.
| [
{
"created": "Tue, 28 May 2024 16:24:43 GMT",
"version": "v1"
}
] | 2024-05-29 | [
[
"Curic",
"Davor",
""
],
[
"Singh",
"Surjeet",
""
],
[
"Nazari",
"Mojtaba",
""
],
[
"Mohajerani",
"Majid H.",
""
],
[
"Davidsen",
"Joern",
""
]
] | Sleep is characterized by non-rapid eye movement (nREM) sleep, originating from widespread neuronal synchrony, and REM sleep, with neuronal desynchronization akin to waking behavior. While these were thought to be global brain states, recent research suggests otherwise. Using time-frequency analysis of mesoscopic voltage-sensitive dye recordings of mice in a urethane-anesthetized model of sleep, we find transient neural desynchronization occurring heterogeneously across the cortex within a background of synchronized neural activity, in a manner reminiscent of a critical spreading process and indicative of an "edge-of-synchronization phase" transition. |
1906.03078 | Jurgis Pods | Jurgis Pods | Electrodiffusion Models of Axon and Extracellular Space Using the
Poisson-Nernst-Planck Equations | PhD thesis, 2014, University of Heidelberg, permalink to university
library open access publication: http://www.ub.uni-heidelberg.de/archiv/17128 | null | 10.11588/heidok.00017128 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In studies of the brain and the nervous system, extracellular signals - as
measured by local field potentials (LFPs) or electroencephalography (EEG) - are
of capital importance, as they allow to simultaneously obtain data from
multiple neurons. The exact biophysical basis of these signals is, however,
still not fully understood. Most models for the extracellular potential today
are based on volume conductor theory, which assumes that the extracellular
fluid is electroneutral and that the only contributions to the electric field
are given by membrane currents, which can be imposed as boundary conditions in
the mathematical model. This neglects a second, possibly important contributor
to the extracellular field: the time- and position-dependent concentrations of
ions in the intra- and extracellular fluids. In this thesis, a 3D model of a
single axon in extracellular fluid is presented based on the
Poisson-Nernst-Planck (PNP) equations of electrodiffusion. This fundamental
model includes not only the potential, but also the concentrations of all
participating ion concentrations in a self-consistent way. This enables us to
study the propagation of an action potential (AP) along the axonal membrane
based on first principles by means of numerical simulations. By exploiting the
cylinder symmetry of this geometry, the problem can be reduced to two
dimensions. The numerical solution is implemented in a flexible and efficient
way, using the DUNE framework. A suitable mesh generation strategy and a
parallelization of the algorithm allow to solve the problem in reasonable time,
with a high spatial and temporal resolution. The methods and programming
techniques used to deal with the numerical challenges of this multi-scale
problem are presented in detail.
| [
{
"created": "Fri, 7 Jun 2019 13:16:24 GMT",
"version": "v1"
}
] | 2019-06-10 | [
[
"Pods",
"Jurgis",
""
]
] | In studies of the brain and the nervous system, extracellular signals - as measured by local field potentials (LFPs) or electroencephalography (EEG) - are of capital importance, as they allow to simultaneously obtain data from multiple neurons. The exact biophysical basis of these signals is, however, still not fully understood. Most models for the extracellular potential today are based on volume conductor theory, which assumes that the extracellular fluid is electroneutral and that the only contributions to the electric field are given by membrane currents, which can be imposed as boundary conditions in the mathematical model. This neglects a second, possibly important contributor to the extracellular field: the time- and position-dependent concentrations of ions in the intra- and extracellular fluids. In this thesis, a 3D model of a single axon in extracellular fluid is presented based on the Poisson-Nernst-Planck (PNP) equations of electrodiffusion. This fundamental model includes not only the potential, but also the concentrations of all participating ion concentrations in a self-consistent way. This enables us to study the propagation of an action potential (AP) along the axonal membrane based on first principles by means of numerical simulations. By exploiting the cylinder symmetry of this geometry, the problem can be reduced to two dimensions. The numerical solution is implemented in a flexible and efficient way, using the DUNE framework. A suitable mesh generation strategy and a parallelization of the algorithm allow to solve the problem in reasonable time, with a high spatial and temporal resolution. The methods and programming techniques used to deal with the numerical challenges of this multi-scale problem are presented in detail. |
2405.08523 | Janusz Uchmanski | Janusz Uchma\'nski | How forest insect outbreaks depend on forest size and tree distribution:
an individual-based model results | null | null | null | null | q-bio.PE math.PR | http://creativecommons.org/licenses/by/4.0/ | In this work, an individual-based model of forest insect outbreaks is
presented. The results obtained show that the outbreak is an emerging feature
of the system. It is a common product of the characteristics of insects, the
environment in which the insects live, and the way insects behave in it. The
outbreak dynamics is an effect of scale. In a sufficiently large forest
regardless of the density of trees and their spatial distribution, provided
that the range of insect dispersion is large enough, it develops in the form of
an outbreak. In very small forests, the dynamics becomes more chaotic. It loses
the outbreak character and, especially in the forest with random tree
distribution, there is a possibility that the insect population goes extinct.
The local dynamics of the number of insects on one tree in a forest, where the
dynamics of all insects has the character of outbreak, is characterized by a
rapid increase in number and then a rapid decrease until the extinction of the
local population. It is the result of the influx of immigrants from neighboring
trees. The type of tree distribution in the forest becomes visible when the
density of trees becomes low and/or the range of insect dispersion is small.
When trees are uniformly distributed and the range of insect dispersion is
small, the system persists as a set of more or less isolated local populations.
In the forest with randomly distributed trees, the insect population becomes
more susceptible to extinction when the tree density and/or range of insect
dispersion are small.
| [
{
"created": "Tue, 14 May 2024 11:56:32 GMT",
"version": "v1"
}
] | 2024-05-15 | [
[
"Uchmański",
"Janusz",
""
]
] | In this work, an individual-based model of forest insect outbreaks is presented. The results obtained show that the outbreak is an emerging feature of the system. It is a common product of the characteristics of insects, the environment in which the insects live, and the way insects behave in it. The outbreak dynamics is an effect of scale. In a sufficiently large forest regardless of the density of trees and their spatial distribution, provided that the range of insect dispersion is large enough, it develops in the form of an outbreak. In very small forests, the dynamics becomes more chaotic. It loses the outbreak character and, especially in the forest with random tree distribution, there is a possibility that the insect population goes extinct. The local dynamics of the number of insects on one tree in a forest, where the dynamics of all insects has the character of outbreak, is characterized by a rapid increase in number and then a rapid decrease until the extinction of the local population. It is the result of the influx of immigrants from neighboring trees. The type of tree distribution in the forest becomes visible when the density of trees becomes low and/or the range of insect dispersion is small. When trees are uniformly distributed and the range of insect dispersion is small, the system persists as a set of more or less isolated local populations. In the forest with randomly distributed trees, the insect population becomes more susceptible to extinction when the tree density and/or range of insect dispersion are small. |
1307.3389 | Binay Panda | Swetansu Pattnaik, Saurabh Gupta, Arjun A Rao and Binay Panda | SInC: An accurate and fast error-model based simulator for SNPs, Indels
and CNVs coupled with a read generator for short-read sequence data | null | null | null | null | q-bio.QM q-bio.GN | http://creativecommons.org/licenses/by-nc-sa/3.0/ | We report SInC (SNV, Indel and CNV) simulator and read generator, an
open-source tool capable of simulating biological variants taking into account
a platform-specific error model. SInC is capable of simulating and generating
single- and paired-end reads with user-defined insert size with high efficiency
compared to the other existing tools. SInC, due to its multi-threaded
capability during read generation, has a low time footprint. SInC is currently
optimised to work in limited infrastructure setup and can efficiently exploit
the commonly used quad-core desktop architecture to simulate short sequence
reads with deep coverage for large genomes. Sinc can be downloaded from
https://sourceforge.net/projects/sincsimulator/.
| [
{
"created": "Fri, 12 Jul 2013 09:28:19 GMT",
"version": "v1"
},
{
"created": "Fri, 16 Aug 2013 09:29:03 GMT",
"version": "v2"
}
] | 2013-08-19 | [
[
"Pattnaik",
"Swetansu",
""
],
[
"Gupta",
"Saurabh",
""
],
[
"Rao",
"Arjun A",
""
],
[
"Panda",
"Binay",
""
]
] | We report SInC (SNV, Indel and CNV) simulator and read generator, an open-source tool capable of simulating biological variants taking into account a platform-specific error model. SInC is capable of simulating and generating single- and paired-end reads with user-defined insert size with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes. Sinc can be downloaded from https://sourceforge.net/projects/sincsimulator/. |
2007.10228 | Misha Katsnelson | Yuri Bakhtin, Mikhail I. Katsnelson, Yuri I. Wolf, Eugene V. Koonin | Punctuated equilibrium as the default mode of evolution of large
populations on fitness landscapes dominated by saddle points in the
weak-mutation limit | 25 pages, 2 figures | null | null | null | q-bio.PE cond-mat.stat-mech nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Punctuated equilibrium is a mode of evolution in which phenetic change occurs
in rapid bursts that are separated by much longer intervals of stasis during
which mutations accumulate but no major phenotypic change occurs. Punctuated
equilibrium has been originally proposed within the framework of paleobiology,
to explain the lack of transitional forms that is typical of the fossil record.
Theoretically, punctuated equilibrium has been linked to self-organized
criticality (SOC), a model in which the size of avalanches in an evolving
system is power-law distributed, resulting in increasing rarity of major
events. We show here that, under the weak-mutation limit, a large population
would spend most of the time in stasis in the vicinity of saddle points in the
fitness landscape. The periods of stasis are punctuated by fast transitions, in
lnNe time (Ne, effective population size), when a new beneficial mutation is
fixed in the evolving population, which moves to a different saddle, or on much
rarer occasions, from a saddle to a local peak. Thus, punctuated equilibrium is
the default mode of evolution under a simple model that does not involve SOC or
other special conditions.
| [
{
"created": "Mon, 20 Jul 2020 16:19:19 GMT",
"version": "v1"
}
] | 2020-07-21 | [
[
"Bakhtin",
"Yuri",
""
],
[
"Katsnelson",
"Mikhail I.",
""
],
[
"Wolf",
"Yuri I.",
""
],
[
"Koonin",
"Eugene V.",
""
]
] | Punctuated equilibrium is a mode of evolution in which phenetic change occurs in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but no major phenotypic change occurs. Punctuated equilibrium has been originally proposed within the framework of paleobiology, to explain the lack of transitional forms that is typical of the fossil record. Theoretically, punctuated equilibrium has been linked to self-organized criticality (SOC), a model in which the size of avalanches in an evolving system is power-law distributed, resulting in increasing rarity of major events. We show here that, under the weak-mutation limit, a large population would spend most of the time in stasis in the vicinity of saddle points in the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNe time (Ne, effective population size), when a new beneficial mutation is fixed in the evolving population, which moves to a different saddle, or on much rarer occasions, from a saddle to a local peak. Thus, punctuated equilibrium is the default mode of evolution under a simple model that does not involve SOC or other special conditions. |
1410.1419 | J. C. Phillips | J. C. Phillips | Fractal Scaling of Cortical Matter, Amyloid Fragmentation and Plaque
Formation across Rodents and Primates | null | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Thermodynamic tools are well suited to connecting evolution of protein
functionalities to mutations of amino acid sequences, especially for neuronal
network structures. These tools enable one to quantify changes in modular
structure and correlate them with corresponding changes in observable
properties. Here we quantify modular rodent-primate changes in amyloid
precursor protein A4 and \b{eta} amyloid fragments. These are related to
changes in cortical connectivity and to the presence (absence) of plaque
formation in primates (rodents). Two thermodynamic scales are used, descriptive
of water/air protein unfolding (old), or fractal conformational restructuring
(new). These describe complementary aspects of protein activity, at
respectively higher and lower effective temperatures.
| [
{
"created": "Fri, 26 Sep 2014 21:30:35 GMT",
"version": "v1"
}
] | 2014-10-07 | [
[
"Phillips",
"J. C.",
""
]
] | Thermodynamic tools are well suited to connecting evolution of protein functionalities to mutations of amino acid sequences, especially for neuronal network structures. These tools enable one to quantify changes in modular structure and correlate them with corresponding changes in observable properties. Here we quantify modular rodent-primate changes in amyloid precursor protein A4 and \b{eta} amyloid fragments. These are related to changes in cortical connectivity and to the presence (absence) of plaque formation in primates (rodents). Two thermodynamic scales are used, descriptive of water/air protein unfolding (old), or fractal conformational restructuring (new). These describe complementary aspects of protein activity, at respectively higher and lower effective temperatures. |
1207.5684 | Richard A Neher | Vitaly V. Ganusov, Richard A. Neher, Alan S. Perelson | Mathematical modeling of escape of HIV from cytotoxic T lymphocyte
responses | null | null | 10.1088/1742-5468/2013/01/P01010 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Human immunodeficiency virus (HIV-1 or simply HIV) induces a persistent
infection, which in the absence of treatment leads to AIDS and death in almost
all infected individuals. HIV infection elicits a vigorous immune response
starting about 2-3 weeks post infection that can lower the amount of virus in
the body, but which cannot eradicate the virus. How HIV establishes a chronic
infection in the face of a strong immune response remains poorly understood. It
has been shown that HIV is able to rapidly change its proteins via mutation to
evade recognition by virus-specific cytotoxic T lymphocytes (CTLs). Typically,
an HIV-infected patient will generate 4-12 CTL responses specific for parts of
viral proteins called epitopes. Such CTL responses lead to strong selective
pressure to change the viral sequences encoding these epitopes so as to avoid
CTL recognition. Here we review experimental data on HIV evolution in response
to CTL pressure, mathematical models developed to explain this evolution, and
highlight problems associated with the data and previous modeling efforts. We
show that estimates of the strength of the epitope-specific CTL response depend
on the method used to fit models to experimental data and on the assumptions
made regarding how mutants are generated during infection. We illustrate that
allowing CTL responses to decay over time may improve the fit to experimental
data and provides higher estimates of the killing efficacy of HIV-specific
CTLs. We also propose a novel method for simultaneously estimating the killing
efficacy of multiple CTL populations specific for different epitopes of HIV
using stochastic simulations. Lastly, we show that current estimates of the
efficacy at which HIV-specific CTLs clear virus-infected cells can be improved
by more frequent sampling of viral sequences and by combining data on sequence
evolution with experimentally measured CTL dynamics.
| [
{
"created": "Tue, 24 Jul 2012 13:11:20 GMT",
"version": "v1"
}
] | 2015-06-05 | [
[
"Ganusov",
"Vitaly V.",
""
],
[
"Neher",
"Richard A.",
""
],
[
"Perelson",
"Alan S.",
""
]
] | Human immunodeficiency virus (HIV-1 or simply HIV) induces a persistent infection, which in the absence of treatment leads to AIDS and death in almost all infected individuals. HIV infection elicits a vigorous immune response starting about 2-3 weeks post infection that can lower the amount of virus in the body, but which cannot eradicate the virus. How HIV establishes a chronic infection in the face of a strong immune response remains poorly understood. It has been shown that HIV is able to rapidly change its proteins via mutation to evade recognition by virus-specific cytotoxic T lymphocytes (CTLs). Typically, an HIV-infected patient will generate 4-12 CTL responses specific for parts of viral proteins called epitopes. Such CTL responses lead to strong selective pressure to change the viral sequences encoding these epitopes so as to avoid CTL recognition. Here we review experimental data on HIV evolution in response to CTL pressure, mathematical models developed to explain this evolution, and highlight problems associated with the data and previous modeling efforts. We show that estimates of the strength of the epitope-specific CTL response depend on the method used to fit models to experimental data and on the assumptions made regarding how mutants are generated during infection. We illustrate that allowing CTL responses to decay over time may improve the fit to experimental data and provides higher estimates of the killing efficacy of HIV-specific CTLs. We also propose a novel method for simultaneously estimating the killing efficacy of multiple CTL populations specific for different epitopes of HIV using stochastic simulations. Lastly, we show that current estimates of the efficacy at which HIV-specific CTLs clear virus-infected cells can be improved by more frequent sampling of viral sequences and by combining data on sequence evolution with experimentally measured CTL dynamics. |
0901.3910 | Charles Lales | Charles Lales (LaBRI), N. Parisey, Jean-Pierre Mazat, Marie
Beurton-Aimar (LaBRI) | Simulation of mitochondrial metabolism using multi-agents system | null | AAMAS'05 (MAS*BIOMED'05), Utrecht : Pays-Bas (2005) | null | null | q-bio.SC cs.MA q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Metabolic pathways describe chains of enzymatic reactions. Their modelling is
a key point to understand living systems. An enzymatic reaction is an
interaction between one or several metabolites (substrates) and an enzyme
(simple protein or enzymatic complex build of several subunits). In our
Mitochondria in Silico Project, MitoScop, we study the metabolism of the
mitochondria, an intra-cellular organelle. Many ordinary differential equation
models are available in the literature. They well fit experimental results on
flux values inside the metabolic pathways, but many parameters are di$\pm$cult
to transcribe with such models: localization of enzymes, rules about the
reactions scheduler, etc Moreover, a model of a significant part of
mitochondrial metabolism could become very complex and contain more than 50
equations. In this context, the multi-agents systems appear as an alternative
to model the metabolic pathways. Firstly, we have looked after membrane design.
The mitochondria is a particular case because the inner mitochondrial space, ie
matricial space, is delimited by two membranes: the inner and the outer one. In
addition to matricial enzymes, other enzymes are located inside the membranes
or in the inter-membrane space. Analysis of mitochondrial metabolism must take
into account this kind of architecture.
| [
{
"created": "Sun, 25 Jan 2009 16:40:58 GMT",
"version": "v1"
}
] | 2009-01-27 | [
[
"Lales",
"Charles",
"",
"LaBRI"
],
[
"Parisey",
"N.",
"",
"LaBRI"
],
[
"Mazat",
"Jean-Pierre",
"",
"LaBRI"
],
[
"Beurton-Aimar",
"Marie",
"",
"LaBRI"
]
] | Metabolic pathways describe chains of enzymatic reactions. Their modelling is a key point to understand living systems. An enzymatic reaction is an interaction between one or several metabolites (substrates) and an enzyme (simple protein or enzymatic complex build of several subunits). In our Mitochondria in Silico Project, MitoScop, we study the metabolism of the mitochondria, an intra-cellular organelle. Many ordinary differential equation models are available in the literature. They well fit experimental results on flux values inside the metabolic pathways, but many parameters are di$\pm$cult to transcribe with such models: localization of enzymes, rules about the reactions scheduler, etc Moreover, a model of a significant part of mitochondrial metabolism could become very complex and contain more than 50 equations. In this context, the multi-agents systems appear as an alternative to model the metabolic pathways. Firstly, we have looked after membrane design. The mitochondria is a particular case because the inner mitochondrial space, ie matricial space, is delimited by two membranes: the inner and the outer one. In addition to matricial enzymes, other enzymes are located inside the membranes or in the inter-membrane space. Analysis of mitochondrial metabolism must take into account this kind of architecture. |
2402.01744 | Salvatore Contino | Paolo Sortino, Salvatore Contino, Ugo Perricone and Roberto Pirrone | Unveiling Molecular Moieties through Hierarchical Graph Explainability | null | null | null | null | q-bio.QM cs.AI cs.LG q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background: Graph Neural Networks (GNN) have emerged in very recent years as
a powerful tool for supporting in silico Virtual Screening. In this work we
present a GNN which uses Graph Convolutional architectures to achieve very
accurate multi-target screening. We also devised a hierarchical Explainable
Artificial Intelligence (XAI) technique to catch information directly at atom,
ring, and whole molecule level by leveraging the message passing mechanism. In
this way, we find the most relevant moieties involved in bioactivity
prediction. Results: We report a state-of-the-art GNN classifier on twenty
Cyclin-dependent Kinase targets in support of VS. Our classifier outperforms
previous SOTA approaches proposed by the authors. Moreover, a CDK1-only
high-sensitivity version of the GNN has been designed to use our explainer in
order to avoid the inherent bias of multi-class models. The hierarchical
explainer has been validated by an expert chemist on 19 approved drugs on CDK1.
Our explainer provided information in accordance to the docking analysis for 17
out of the 19 test drugs. Conclusion: Our approach is a valid support for
shortening both the screening and the hit-to-lead phase. Detailed knowledge
about the molecular substructures that play a role in the inhibitory action,
can help the computational chemist to gain insights into the pharmacophoric
function of the molecule also for repurposing purposes. Scientific Contribution
Statement: The core scientific innovation of our work is the use of a
hierarchical XAI approach on a GNN trained for a ligand-based VS task. The
application of the hierarchical explainer allows for eliciting also structural
information...
| [
{
"created": "Mon, 29 Jan 2024 17:23:25 GMT",
"version": "v1"
},
{
"created": "Thu, 29 Feb 2024 16:05:32 GMT",
"version": "v2"
},
{
"created": "Wed, 8 May 2024 15:04:37 GMT",
"version": "v3"
}
] | 2024-05-09 | [
[
"Sortino",
"Paolo",
""
],
[
"Contino",
"Salvatore",
""
],
[
"Perricone",
"Ugo",
""
],
[
"Pirrone",
"Roberto",
""
]
] | Background: Graph Neural Networks (GNN) have emerged in very recent years as a powerful tool for supporting in silico Virtual Screening. In this work we present a GNN which uses Graph Convolutional architectures to achieve very accurate multi-target screening. We also devised a hierarchical Explainable Artificial Intelligence (XAI) technique to catch information directly at atom, ring, and whole molecule level by leveraging the message passing mechanism. In this way, we find the most relevant moieties involved in bioactivity prediction. Results: We report a state-of-the-art GNN classifier on twenty Cyclin-dependent Kinase targets in support of VS. Our classifier outperforms previous SOTA approaches proposed by the authors. Moreover, a CDK1-only high-sensitivity version of the GNN has been designed to use our explainer in order to avoid the inherent bias of multi-class models. The hierarchical explainer has been validated by an expert chemist on 19 approved drugs on CDK1. Our explainer provided information in accordance to the docking analysis for 17 out of the 19 test drugs. Conclusion: Our approach is a valid support for shortening both the screening and the hit-to-lead phase. Detailed knowledge about the molecular substructures that play a role in the inhibitory action, can help the computational chemist to gain insights into the pharmacophoric function of the molecule also for repurposing purposes. Scientific Contribution Statement: The core scientific innovation of our work is the use of a hierarchical XAI approach on a GNN trained for a ligand-based VS task. The application of the hierarchical explainer allows for eliciting also structural information... |
1904.06639 | Takehiro Tottori | Takehiro Tottori, Masashi Fujii, Shinya Kuroda | Robustness against additional noise in cellular information transmission | null | Phys. Rev. E 100, 042403 (2019) | 10.1103/PhysRevE.100.042403 | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Fluctuations in intracellular reactions (intrinsic noise) reduce the
information transmitted from an extracellular input to a cellular response.
However, recent studies have demonstrated that the decrease in the transmitted
information with respect to extracellular input fluctuations (extrinsic noise)
is smaller when the intrinsic noise is larger. Therefore, it has been suggested
that robustness against extrinsic noise increases with the level of the
intrinsic noise. We call this phenomenon intrinsic noise-induced robustness
(INIR). As previous studies on this phenomenon have focused on complex
biochemical reactions, the relation between INIR and the input--output of a
system is unclear. Moreover, the mechanism of INIR remains elusive. In this
paper, we address these questions by analyzing simple models. We first analyze
a model in which the input--output relation is linear. We show that the
robustness against extrinsic noise increases with the intrinsic noise,
confirming the INIR phenomenon. Moreover, the robustness against the extrinsic
noise is more strongly dependent on the intrinsic noise when the variance of
the intrinsic noise is larger than that of the input distribution. Next, we
analyze a threshold model in which the output depends on whether the input
exceeds the threshold. When the threshold is equal to the mean of the input,
INIR is realized, but when the threshold is much larger than the mean, the
threshold model exhibits stochastic resonance, and INIR is not always apparent.
The robustness against extrinsic noise and the transmitted information can be
traded off against one another in the linear model and the threshold model
without stochastic resonance, whereas they can be simultaneously increased in
the threshold model with stochastic resonance.
| [
{
"created": "Sun, 14 Apr 2019 06:48:26 GMT",
"version": "v1"
},
{
"created": "Thu, 2 May 2019 03:25:06 GMT",
"version": "v2"
},
{
"created": "Thu, 3 Oct 2019 01:14:18 GMT",
"version": "v3"
}
] | 2019-10-09 | [
[
"Tottori",
"Takehiro",
""
],
[
"Fujii",
"Masashi",
""
],
[
"Kuroda",
"Shinya",
""
]
] | Fluctuations in intracellular reactions (intrinsic noise) reduce the information transmitted from an extracellular input to a cellular response. However, recent studies have demonstrated that the decrease in the transmitted information with respect to extracellular input fluctuations (extrinsic noise) is smaller when the intrinsic noise is larger. Therefore, it has been suggested that robustness against extrinsic noise increases with the level of the intrinsic noise. We call this phenomenon intrinsic noise-induced robustness (INIR). As previous studies on this phenomenon have focused on complex biochemical reactions, the relation between INIR and the input--output of a system is unclear. Moreover, the mechanism of INIR remains elusive. In this paper, we address these questions by analyzing simple models. We first analyze a model in which the input--output relation is linear. We show that the robustness against extrinsic noise increases with the intrinsic noise, confirming the INIR phenomenon. Moreover, the robustness against the extrinsic noise is more strongly dependent on the intrinsic noise when the variance of the intrinsic noise is larger than that of the input distribution. Next, we analyze a threshold model in which the output depends on whether the input exceeds the threshold. When the threshold is equal to the mean of the input, INIR is realized, but when the threshold is much larger than the mean, the threshold model exhibits stochastic resonance, and INIR is not always apparent. The robustness against extrinsic noise and the transmitted information can be traded off against one another in the linear model and the threshold model without stochastic resonance, whereas they can be simultaneously increased in the threshold model with stochastic resonance. |
1711.04078 | Baihan Lin | Avinash Bukkittu, Baihan Lin, Trung Vu, Itsik Pe'er | Parkinson's Disease Digital Biomarker Discovery with Optimized
Transitions and Inferred Markov Emissions | 10th RECOMB/ISCB Conference on Regulatory & Systems Genomics with
DREAM Challenges | null | null | null | q-bio.QM cs.AI stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We search for digital biomarkers from Parkinson's Disease by observing
approximate repetitive patterns matching hypothesized step and stride periodic
cycles. These observations were modeled as a cycle of hidden states with
randomness allowing deviation from a canonical pattern of transitions and
emissions, under the hypothesis that the averaged features of hidden states
would serve to informatively characterize classes of patients/controls. We
propose a Hidden Semi-Markov Model (HSMM), a latent-state model, emitting
3D-acceleration vectors. Transitions and emissions are inferred from data. We
fit separate models per unique device and training label. Hidden Markov Models
(HMM) force geometric distributions of the duration spent at each state before
transition to a new state. Instead, our HSMM allows us to specify the
distribution of state duration. This modified version is more effective because
we are interested more in each state's duration than the sequence of distinct
states, allowing inclusion of these durations the feature vector.
| [
{
"created": "Sat, 11 Nov 2017 05:06:20 GMT",
"version": "v1"
}
] | 2017-11-15 | [
[
"Bukkittu",
"Avinash",
""
],
[
"Lin",
"Baihan",
""
],
[
"Vu",
"Trung",
""
],
[
"Pe'er",
"Itsik",
""
]
] | We search for digital biomarkers from Parkinson's Disease by observing approximate repetitive patterns matching hypothesized step and stride periodic cycles. These observations were modeled as a cycle of hidden states with randomness allowing deviation from a canonical pattern of transitions and emissions, under the hypothesis that the averaged features of hidden states would serve to informatively characterize classes of patients/controls. We propose a Hidden Semi-Markov Model (HSMM), a latent-state model, emitting 3D-acceleration vectors. Transitions and emissions are inferred from data. We fit separate models per unique device and training label. Hidden Markov Models (HMM) force geometric distributions of the duration spent at each state before transition to a new state. Instead, our HSMM allows us to specify the distribution of state duration. This modified version is more effective because we are interested more in each state's duration than the sequence of distinct states, allowing inclusion of these durations the feature vector. |
0710.3278 | Daniel Silvestre | Daniel A. M. M. Silvestre, Jos\'e F. Fontanari | Package models and the information crisis of prebiotic evolution | 11 pages, two columns, 11 figures, submitted to J. Theor. Biol | null | null | null | q-bio.PE | null | The coexistence between different types of templates has been the choice
solution to the information crisis of prebiotic evolution, triggered by the
finding that a single RNA-like template cannot carry enough information to code
for any useful replicase. In principle, confining $d$ distinct templates of
length $L$ in a package or protocell, whose survival depends on the coexistence
of the templates it holds in, could resolve this crisis provided that $d$ is
made sufficiently large. Here we review the prototypical package model of
Niesert et al. 1981 which guarantees the greatest possible region of viability
of the protocell population, and show that this model, and hence the entire
package approach, does not resolve the information crisis. This is so because
to secure survival the total information content of the protocell, $Ld$, must
tend to a constant value that depends only on the spontaneous error rate per
nucleotide of the template replication mechanism. As a result, an increase of
$d$ must be followed by a decrease of $L$ to ensure the protocell viability, so
that the net information gain is null.
| [
{
"created": "Wed, 17 Oct 2007 18:14:07 GMT",
"version": "v1"
}
] | 2007-10-18 | [
[
"Silvestre",
"Daniel A. M. M.",
""
],
[
"Fontanari",
"José F.",
""
]
] | The coexistence between different types of templates has been the choice solution to the information crisis of prebiotic evolution, triggered by the finding that a single RNA-like template cannot carry enough information to code for any useful replicase. In principle, confining $d$ distinct templates of length $L$ in a package or protocell, whose survival depends on the coexistence of the templates it holds in, could resolve this crisis provided that $d$ is made sufficiently large. Here we review the prototypical package model of Niesert et al. 1981 which guarantees the greatest possible region of viability of the protocell population, and show that this model, and hence the entire package approach, does not resolve the information crisis. This is so because to secure survival the total information content of the protocell, $Ld$, must tend to a constant value that depends only on the spontaneous error rate per nucleotide of the template replication mechanism. As a result, an increase of $d$ must be followed by a decrease of $L$ to ensure the protocell viability, so that the net information gain is null. |
1307.2150 | Yaroslav Halchenko | Yaroslav O. Halchenko, Michael Hanke, James V. Haxby, Stephen Jose
Hanson, Christoph S. Herrmann | Transmodal Analysis of Neural Signals | null | null | null | null | q-bio.NC cs.LG q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Localizing neuronal activity in the brain, both in time and in space, is a
central challenge to advance the understanding of brain function. Because of
the inability of any single neuroimaging techniques to cover all aspects at
once, there is a growing interest to combine signals from multiple modalities
in order to benefit from the advantages of each acquisition method. Due to the
complexity and unknown parameterization of any suggested complete model of BOLD
response in functional magnetic resonance imaging (fMRI), the development of a
reliable ultimate fusion approach remains difficult. But besides the primary
goal of superior temporal and spatial resolution, conjoint analysis of data
from multiple imaging modalities can alternatively be used to segregate neural
information from physiological and acquisition noise. In this paper we suggest
a novel methodology which relies on constructing a quantifiable mapping of data
from one modality (electroencephalography; EEG) into another (fMRI), called
transmodal analysis of neural signals (TRANSfusion). TRANSfusion attempts to
map neural data embedded within the EEG signal into its reflection in fMRI
data. Assessing the mapping performance on unseen data allows to localize brain
areas where a significant portion of the signal could be reliably
reconstructed, hence the areas neural activity of which is reflected in both
EEG and fMRI data. Consecutive analysis of the learnt model allows to localize
areas associated with specific frequency bands of EEG, or areas functionally
related (connected or coherent) to any given EEG sensor. We demonstrate the
performance of TRANSfusion on artificial and real data from an auditory
experiment. We further speculate on possible alternative uses: cross-modal data
filtering and EEG-driven interpolation of fMRI signals to obtain arbitrarily
high temporal sampling of BOLD.
| [
{
"created": "Mon, 8 Jul 2013 16:30:29 GMT",
"version": "v1"
}
] | 2013-07-09 | [
[
"Halchenko",
"Yaroslav O.",
""
],
[
"Hanke",
"Michael",
""
],
[
"Haxby",
"James V.",
""
],
[
"Hanson",
"Stephen Jose",
""
],
[
"Herrmann",
"Christoph S.",
""
]
] | Localizing neuronal activity in the brain, both in time and in space, is a central challenge to advance the understanding of brain function. Because of the inability of any single neuroimaging techniques to cover all aspects at once, there is a growing interest to combine signals from multiple modalities in order to benefit from the advantages of each acquisition method. Due to the complexity and unknown parameterization of any suggested complete model of BOLD response in functional magnetic resonance imaging (fMRI), the development of a reliable ultimate fusion approach remains difficult. But besides the primary goal of superior temporal and spatial resolution, conjoint analysis of data from multiple imaging modalities can alternatively be used to segregate neural information from physiological and acquisition noise. In this paper we suggest a novel methodology which relies on constructing a quantifiable mapping of data from one modality (electroencephalography; EEG) into another (fMRI), called transmodal analysis of neural signals (TRANSfusion). TRANSfusion attempts to map neural data embedded within the EEG signal into its reflection in fMRI data. Assessing the mapping performance on unseen data allows to localize brain areas where a significant portion of the signal could be reliably reconstructed, hence the areas neural activity of which is reflected in both EEG and fMRI data. Consecutive analysis of the learnt model allows to localize areas associated with specific frequency bands of EEG, or areas functionally related (connected or coherent) to any given EEG sensor. We demonstrate the performance of TRANSfusion on artificial and real data from an auditory experiment. We further speculate on possible alternative uses: cross-modal data filtering and EEG-driven interpolation of fMRI signals to obtain arbitrarily high temporal sampling of BOLD. |
2103.03327 | Gabriel Arellano | Gabriel Arellano | Null expectations and null hypothesis testing for the species abundance
distribution | 14 pages, 1 figure | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The number of elements (N) and types (S) sampled from an ecological system
are among the most powerful constraints on observations of abundance,
distribution, and diversity. Together, N and S determine sets of possible forms
(i.e., feasible sets) for the species abundance distribution (SAD). There are
three approaches to the description of the null SAD (= the average feasible
SAD). The first approach is based on the random uniform sampling of
surjections. I calculate the probability of a given SAD, given N and S, under
this approach (Eq. 4). The second approach is based on the random sampling of
compositions. I calculate the probability of a given SAD, given N and S, under
this approach (Eq. 8). The third approach is based on the random uniform
sampling of partitions. I review the approach, which was developed by Locey &
White (2013), and provide some asymptotic results useful for ecologists. The
center of a feasible set is a null expectation, which should deviate enough
from the alternative models before invoking for biological or ecological
mechanisms underlying the SAD. Here, I integrate the feasible set approach with
the typical framework of inference in ecology (goodness-of-fit, null hypothesis
testing, model comparison, null modelling). I describe how to perform numerical
simulations to describe expectations under different approaches to the feasible
set. I develop objective or fitness functions to allow the estimation of the
most likely SAD using numerical optimization. I provide tools to compare null
expectations based on the feasible set approach with the observations, in the
context of model comparison and null hypothesis testing.
| [
{
"created": "Thu, 4 Mar 2021 20:55:39 GMT",
"version": "v1"
}
] | 2021-03-08 | [
[
"Arellano",
"Gabriel",
""
]
] | The number of elements (N) and types (S) sampled from an ecological system are among the most powerful constraints on observations of abundance, distribution, and diversity. Together, N and S determine sets of possible forms (i.e., feasible sets) for the species abundance distribution (SAD). There are three approaches to the description of the null SAD (= the average feasible SAD). The first approach is based on the random uniform sampling of surjections. I calculate the probability of a given SAD, given N and S, under this approach (Eq. 4). The second approach is based on the random sampling of compositions. I calculate the probability of a given SAD, given N and S, under this approach (Eq. 8). The third approach is based on the random uniform sampling of partitions. I review the approach, which was developed by Locey & White (2013), and provide some asymptotic results useful for ecologists. The center of a feasible set is a null expectation, which should deviate enough from the alternative models before invoking for biological or ecological mechanisms underlying the SAD. Here, I integrate the feasible set approach with the typical framework of inference in ecology (goodness-of-fit, null hypothesis testing, model comparison, null modelling). I describe how to perform numerical simulations to describe expectations under different approaches to the feasible set. I develop objective or fitness functions to allow the estimation of the most likely SAD using numerical optimization. I provide tools to compare null expectations based on the feasible set approach with the observations, in the context of model comparison and null hypothesis testing. |
1404.3470 | Bruno. Cessac | Hassan Nasser and Bruno Cessac | Parameters estimation for spatio-temporal maximum entropy distributions:
application to neural spike trains | 34 pages, 33 figures | null | 10.3390/e16042244 | null | q-bio.NC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We propose a numerical method to learn Maximum Entropy (MaxEnt) distributions
with spatio-temporal constraints from experimental spike trains. This is an
extension of two papers [10] and [4] who proposed the estimation of parameters
where only spatial constraints were taken into account. The extension we
propose allows to properly handle memory effects in spike statistics, for large
sized neural networks.
| [
{
"created": "Mon, 14 Apr 2014 06:44:02 GMT",
"version": "v1"
}
] | 2015-06-19 | [
[
"Nasser",
"Hassan",
""
],
[
"Cessac",
"Bruno",
""
]
] | We propose a numerical method to learn Maximum Entropy (MaxEnt) distributions with spatio-temporal constraints from experimental spike trains. This is an extension of two papers [10] and [4] who proposed the estimation of parameters where only spatial constraints were taken into account. The extension we propose allows to properly handle memory effects in spike statistics, for large sized neural networks. |
1512.06999 | Gael Varoquaux | Ga\"el Varoquaux (PARIETAL), Michael Eickenberg (PARIETAL), Elvis
Dohmatob (PARIETAL), Bertand Thirion (PARIETAL) | FAASTA: A fast solver for total-variation regularization of
ill-conditioned problems with application to brain imaging | null | Colloque GRETSI, Sep 2015, Lyon, France. Gretsi, 2015,
http://www.gretsi.fr/colloque2015/myGretsi/programme.php | null | null | q-bio.NC cs.LG stat.CO stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The total variation (TV) penalty, as many other analysis-sparsity problems,
does not lead to separable factors or a proximal operatorwith a closed-form
expression, such as soft thresholding for the $\ell\_1$ penalty. As a result,
in a variational formulation of an inverse problem or statisticallearning
estimation, it leads to challenging non-smooth optimization problemsthat are
often solved with elaborate single-step first-order methods. When thedata-fit
term arises from empirical measurements, as in brain imaging, it isoften very
ill-conditioned and without simple structure. In this situation, in proximal
splitting methods, the computation cost of thegradient step can easily dominate
each iteration. Thus it is beneficialto minimize the number of gradient
steps.We present fAASTA, a variant of FISTA, that relies on an internal solver
forthe TV proximal operator, and refines its tolerance to balance
computationalcost of the gradient and the proximal steps. We give benchmarks
andillustrations on "brain decoding": recovering brain maps from
noisymeasurements to predict observed behavior. The algorithm as well as
theempirical study of convergence speed are valuable for any non-exact
proximaloperator, in particular analysis-sparsity problems.
| [
{
"created": "Tue, 22 Dec 2015 09:35:55 GMT",
"version": "v1"
}
] | 2015-12-23 | [
[
"Varoquaux",
"Gaël",
"",
"PARIETAL"
],
[
"Eickenberg",
"Michael",
"",
"PARIETAL"
],
[
"Dohmatob",
"Elvis",
"",
"PARIETAL"
],
[
"Thirion",
"Bertand",
"",
"PARIETAL"
]
] | The total variation (TV) penalty, as many other analysis-sparsity problems, does not lead to separable factors or a proximal operatorwith a closed-form expression, such as soft thresholding for the $\ell\_1$ penalty. As a result, in a variational formulation of an inverse problem or statisticallearning estimation, it leads to challenging non-smooth optimization problemsthat are often solved with elaborate single-step first-order methods. When thedata-fit term arises from empirical measurements, as in brain imaging, it isoften very ill-conditioned and without simple structure. In this situation, in proximal splitting methods, the computation cost of thegradient step can easily dominate each iteration. Thus it is beneficialto minimize the number of gradient steps.We present fAASTA, a variant of FISTA, that relies on an internal solver forthe TV proximal operator, and refines its tolerance to balance computationalcost of the gradient and the proximal steps. We give benchmarks andillustrations on "brain decoding": recovering brain maps from noisymeasurements to predict observed behavior. The algorithm as well as theempirical study of convergence speed are valuable for any non-exact proximaloperator, in particular analysis-sparsity problems. |
2004.10291 | Martin F\'elix Medina | Mart\'in H. F\'elix-Medina | Estimaci\'on del n\'umero de reproducci\'on de la epidemia COVID-19 en
Culiac\'an Sinaloa, M\'exico | 12 pages, 7 figures, in Spanish | null | null | null | q-bio.PE stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Currently the COVID-19 epidemic is developing in the City of Culiac\'n
Sinaloa, Mexico, where up to April 20 of this year there have been 35 deaths
associated with this epidemic. The reproduction number $(R_0)$ of an epidemic
represents the average number of people infected by an infected person during
their period of infection. In this work we use the data published by the
Secretary of Health of the State of Sinaloa on the number of new infected cases
confirmed per day and we estimate that the value of $R_0$ is 1.562 with a 95%
confidence interval given by (1.401,1.742). We also estimate the mortality rate
among the confirmed cases, which turned out to be 16.8%.
- - - - -
Actualmente la epidemia COVID-19 se est\'a desarrollando en la Ciudad de
Culiac\'an Sinaloa, M\'exico, donde hasta el 20 de abril del presente a\~no han
ocurrido 35 decesos asociados con esta epidemia. El n\'umero de reproducci\'on
$(R_0)$ de una epidemia representa el n\'umero promedio de personas contagiadas
por una persona infectada durante su periodo de infecci\'on. En este trabajo
usamos los datos publicados por la Secretaria de Salud del Estado de Sinaloa
sobre el n\'umero de nuevos casos infectados confirmados por dia y estimamos
que el valor de $R_0$ es de 1.562 con un intervalo del 95% de confianza dado
por (1.401,1.742). Estimamos tambi\'en la tasa de mortalidad entre los casos
confirmados, la cual result\'o ser de 16.8%.
| [
{
"created": "Tue, 21 Apr 2020 20:45:18 GMT",
"version": "v1"
}
] | 2020-04-23 | [
[
"Félix-Medina",
"Martín H.",
""
]
] | Currently the COVID-19 epidemic is developing in the City of Culiac\'n Sinaloa, Mexico, where up to April 20 of this year there have been 35 deaths associated with this epidemic. The reproduction number $(R_0)$ of an epidemic represents the average number of people infected by an infected person during their period of infection. In this work we use the data published by the Secretary of Health of the State of Sinaloa on the number of new infected cases confirmed per day and we estimate that the value of $R_0$ is 1.562 with a 95% confidence interval given by (1.401,1.742). We also estimate the mortality rate among the confirmed cases, which turned out to be 16.8%. - - - - - Actualmente la epidemia COVID-19 se est\'a desarrollando en la Ciudad de Culiac\'an Sinaloa, M\'exico, donde hasta el 20 de abril del presente a\~no han ocurrido 35 decesos asociados con esta epidemia. El n\'umero de reproducci\'on $(R_0)$ de una epidemia representa el n\'umero promedio de personas contagiadas por una persona infectada durante su periodo de infecci\'on. En este trabajo usamos los datos publicados por la Secretaria de Salud del Estado de Sinaloa sobre el n\'umero de nuevos casos infectados confirmados por dia y estimamos que el valor de $R_0$ es de 1.562 con un intervalo del 95% de confianza dado por (1.401,1.742). Estimamos tambi\'en la tasa de mortalidad entre los casos confirmados, la cual result\'o ser de 16.8%. |
1704.05344 | Rodrigo Cofre | Bruno Cessac, Ignacio Ampuero and Rodrigo Cofre | Linear response for spiking neuronal networks with unbounded memory | 60 pages, 8 figures | null | null | null | q-bio.NC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We establish a general linear response relation for spiking neuronal
networks, based on chains with unbounded memory. This relation allows us to
predict the influence of a weak amplitude time-dependent external stimuli on
spatio-temporal spike correlations, from the spontaneous statistics (without
stimulus) in a general context where the memory in spike dynamics can extend
arbitrarily far in the past. Using this approach, we show how linear response
is explicitly related to neuronal dynamics with an example, the gIF model,
introduced by M. Rudolph and A. Destexhe. This example illustrates the
collective effect of the stimuli, intrinsic neuronal dynamics, and network
connectivity on spike statistics. We illustrate our results with numerical
simulations.
| [
{
"created": "Tue, 18 Apr 2017 14:02:15 GMT",
"version": "v1"
},
{
"created": "Thu, 26 Oct 2017 14:18:59 GMT",
"version": "v2"
},
{
"created": "Sun, 14 Oct 2018 02:10:24 GMT",
"version": "v3"
},
{
"created": "Wed, 17 Oct 2018 01:08:36 GMT",
"version": "v4"
},
{
"created": "Thu, 2 Apr 2020 01:48:38 GMT",
"version": "v5"
}
] | 2020-04-03 | [
[
"Cessac",
"Bruno",
""
],
[
"Ampuero",
"Ignacio",
""
],
[
"Cofre",
"Rodrigo",
""
]
] | We establish a general linear response relation for spiking neuronal networks, based on chains with unbounded memory. This relation allows us to predict the influence of a weak amplitude time-dependent external stimuli on spatio-temporal spike correlations, from the spontaneous statistics (without stimulus) in a general context where the memory in spike dynamics can extend arbitrarily far in the past. Using this approach, we show how linear response is explicitly related to neuronal dynamics with an example, the gIF model, introduced by M. Rudolph and A. Destexhe. This example illustrates the collective effect of the stimuli, intrinsic neuronal dynamics, and network connectivity on spike statistics. We illustrate our results with numerical simulations. |
1312.4235 | Vladimir Privman | Vladimir Privman, Oleksandr Zavalov, Lenka Halamkova, Fiona Moseley,
Jan Halamek, Evgeny Katz | Networked Enzymatic Logic Gates with Filtering: New Theoretical Modeling
Expressions and Their Experimental Application | Keywords: binary AND; biocatalytic cascade; biochemical signals;
multi-input biosensor | J. Phys. Chem. B 117 (48), 14928-14939 (2013) | 10.1021/jp408973g | VP-259 | q-bio.MN physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We report the first study of a network of connected enzyme-catalyzed
reactions, with added chemical and enzymatic processes that incorporate the
recently developed biochemical filtering steps into the functioning of this
biocatalytic cascade. New theoretical expressions are derived to allow simple,
few-parameter modeling of network components concatenated in such cascades,
both with and without filtering. The derived expressions are tested against
experimental data obtained for the realized network's responses, measured
optically, to variations of its input chemicals' concentrations with and
without filtering processes. We also describe how the present modeling approach
captures and explains several observations and features identified in earlier
studies of enzymatic processes when they were considered as potential network
components for multi-step information/signal processing systems.
| [
{
"created": "Mon, 16 Dec 2013 02:47:46 GMT",
"version": "v1"
}
] | 2013-12-17 | [
[
"Privman",
"Vladimir",
""
],
[
"Zavalov",
"Oleksandr",
""
],
[
"Halamkova",
"Lenka",
""
],
[
"Moseley",
"Fiona",
""
],
[
"Halamek",
"Jan",
""
],
[
"Katz",
"Evgeny",
""
]
] | We report the first study of a network of connected enzyme-catalyzed reactions, with added chemical and enzymatic processes that incorporate the recently developed biochemical filtering steps into the functioning of this biocatalytic cascade. New theoretical expressions are derived to allow simple, few-parameter modeling of network components concatenated in such cascades, both with and without filtering. The derived expressions are tested against experimental data obtained for the realized network's responses, measured optically, to variations of its input chemicals' concentrations with and without filtering processes. We also describe how the present modeling approach captures and explains several observations and features identified in earlier studies of enzymatic processes when they were considered as potential network components for multi-step information/signal processing systems. |
1005.3341 | Iaroslav Ispolatov | Iaroslav Ispolatov, Michael Doebeli | On the evolution of decoys in plant immune systems | 15 pages, 6 figures | Biol Theory (2010) 5: 256 | 10.1162/BIOT_a_00055 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Guard-Guardee model for plant immunity describes how resistance proteins
(guards) in host cells monitor host target proteins (guardees) that are
manipulated by pathogen effector proteins. A recently suggested extension of
this model includes decoys, which are duplicated copies of guardee proteins,
and which have the sole function to attract the effector and, when modified by
the effector, trigger the plant immune response. Here we present a
proof-of-principle model for the functioning of decoys in plant immunity,
quantitatively developing this experimentally-derived concept. Our model links
the basic cellular chemistry to the outcomes of pathogen infection and
resulting fitness costs for the host. In particular, the model allows
identification of conditions under which it is optimal for decoys to act as
triggers for the plant immune response, and of conditions under which it is
optimal for decoys to act as sinks that bind the pathogen effectors but do not
trigger an immune response.
| [
{
"created": "Tue, 18 May 2010 23:55:35 GMT",
"version": "v1"
}
] | 2017-02-07 | [
[
"Ispolatov",
"Iaroslav",
""
],
[
"Doebeli",
"Michael",
""
]
] | The Guard-Guardee model for plant immunity describes how resistance proteins (guards) in host cells monitor host target proteins (guardees) that are manipulated by pathogen effector proteins. A recently suggested extension of this model includes decoys, which are duplicated copies of guardee proteins, and which have the sole function to attract the effector and, when modified by the effector, trigger the plant immune response. Here we present a proof-of-principle model for the functioning of decoys in plant immunity, quantitatively developing this experimentally-derived concept. Our model links the basic cellular chemistry to the outcomes of pathogen infection and resulting fitness costs for the host. In particular, the model allows identification of conditions under which it is optimal for decoys to act as triggers for the plant immune response, and of conditions under which it is optimal for decoys to act as sinks that bind the pathogen effectors but do not trigger an immune response. |
1505.05670 | Haralambos Hatzikirou | H. Hatzikirou, J. C. L. Alfonso, S. Muhle, C. Stern, S. Weiss and M.
Meyer-Hermann | Cancer therapeutic potential of combinatorial immuno- and
vaso-modulatory interventions | null | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Currently, most of the basic mechanisms governing tumor-immune system
interactions, in combination with modulations of tumor-associated vasculature,
are far from being completely understood. Here, we propose a mathematical model
of vascularized tumor growth, where the main novelty is the modeling of the
interplay between functional tumor vasculature and effector cell recruitment
dynamics. Parameters are calibrated on the basis of different in vivo
immunocompromised Rag1-/- and wild-type (WT) BALB/c murine tumor growth
experiments. The model analysis supports that tumor vasculature normalization
can be a plausible and effective strategy to treat cancer when combined with
appropriate immuno-stimulations. We find that improved levels of functional
tumor vasculature, potentially mediated by normalization or stress alleviation
strategies, can provide beneficial outcomes in terms of tumor burden reduction
and growth control. Normalization of tumor blood vessels opens a therapeutic
window of opportunity to augment the antitumor immune responses, as well as to
reduce the intratumoral immunosuppression and induced-hypoxia due to vascular
abnormalities. The potential success of normalizing tumor-associated
vasculature closely depends on the effector cell recruitment dynamics and tumor
sizes. Furthermore, an arbitrary increase of initial effector cell
concentration does not necessarily imply a better tumor control. We evidence
the existence of an optimal concentration range of effector cells for tumor
shrinkage. Based on these findings, we suggest a theory-driven therapeutic
proposal that optimally combines immuno- and vaso-modulatory interventions.
| [
{
"created": "Thu, 21 May 2015 10:38:39 GMT",
"version": "v1"
},
{
"created": "Wed, 22 Jul 2015 11:12:37 GMT",
"version": "v2"
},
{
"created": "Tue, 6 Oct 2015 12:03:00 GMT",
"version": "v3"
}
] | 2015-10-07 | [
[
"Hatzikirou",
"H.",
""
],
[
"Alfonso",
"J. C. L.",
""
],
[
"Muhle",
"S.",
""
],
[
"Stern",
"C.",
""
],
[
"Weiss",
"S.",
""
],
[
"Meyer-Hermann",
"M.",
""
]
] | Currently, most of the basic mechanisms governing tumor-immune system interactions, in combination with modulations of tumor-associated vasculature, are far from being completely understood. Here, we propose a mathematical model of vascularized tumor growth, where the main novelty is the modeling of the interplay between functional tumor vasculature and effector cell recruitment dynamics. Parameters are calibrated on the basis of different in vivo immunocompromised Rag1-/- and wild-type (WT) BALB/c murine tumor growth experiments. The model analysis supports that tumor vasculature normalization can be a plausible and effective strategy to treat cancer when combined with appropriate immuno-stimulations. We find that improved levels of functional tumor vasculature, potentially mediated by normalization or stress alleviation strategies, can provide beneficial outcomes in terms of tumor burden reduction and growth control. Normalization of tumor blood vessels opens a therapeutic window of opportunity to augment the antitumor immune responses, as well as to reduce the intratumoral immunosuppression and induced-hypoxia due to vascular abnormalities. The potential success of normalizing tumor-associated vasculature closely depends on the effector cell recruitment dynamics and tumor sizes. Furthermore, an arbitrary increase of initial effector cell concentration does not necessarily imply a better tumor control. We evidence the existence of an optimal concentration range of effector cells for tumor shrinkage. Based on these findings, we suggest a theory-driven therapeutic proposal that optimally combines immuno- and vaso-modulatory interventions. |
2012.13363 | Bruno Leandro Louren\c{c}o | Bruno Louren\c{c}o | A framework for large scale phylogenetic analysis | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | With growing exchanges of people and merchandise between countries, epidemics
have become an issue of increasing importance and huge amounts of data are
being collected every day. Hence, analyses that were usually run in personal
computers and desktops are no longer feasible. It is now common to run such
tasks in High-performance computing (HPC) environments and/or dedicated
systems. On the other hand we are often dealing in these analyses with graphs
and trees, and running algorithms to find patterns in such structures. Hence,
although graph oriented databases and processing systems can be of much help in
this setting, as far as we know there is no solution relying on these
technologies to address large scale phylogenetic analysis challenges. This
project aims to develop a modular framework for large scale phylogenetic
analysis that exploits such technologies, namely Neo4j. We address this
challenge by proposing and developing a framework which allows representing
large phylogenetic networks and trees, as well as ancillary data, that supports
queries on such data, and allows the deployment of algorithms for
inferring/detecting patterns and pre-computing visualizations, as a Neo4j
plugin. This framework is innovative and brings several advantages to the
phylogenetic analysis, such as by storing the phylogenetic trees will avoid
having to compute them again, and by using multilayer networks will make the
comparison between them more efficient and scalable. Experimental results
showcase that it can be very efficient in the mostly used operations and that
the supported algorithms comply with their time complexity.
| [
{
"created": "Wed, 23 Dec 2020 14:44:44 GMT",
"version": "v1"
},
{
"created": "Wed, 30 Dec 2020 23:38:22 GMT",
"version": "v2"
},
{
"created": "Sun, 3 Jan 2021 13:58:07 GMT",
"version": "v3"
},
{
"created": "Sat, 16 Jan 2021 22:38:34 GMT",
"version": "v4"
}
] | 2021-01-19 | [
[
"Lourenço",
"Bruno",
""
]
] | With growing exchanges of people and merchandise between countries, epidemics have become an issue of increasing importance and huge amounts of data are being collected every day. Hence, analyses that were usually run in personal computers and desktops are no longer feasible. It is now common to run such tasks in High-performance computing (HPC) environments and/or dedicated systems. On the other hand we are often dealing in these analyses with graphs and trees, and running algorithms to find patterns in such structures. Hence, although graph oriented databases and processing systems can be of much help in this setting, as far as we know there is no solution relying on these technologies to address large scale phylogenetic analysis challenges. This project aims to develop a modular framework for large scale phylogenetic analysis that exploits such technologies, namely Neo4j. We address this challenge by proposing and developing a framework which allows representing large phylogenetic networks and trees, as well as ancillary data, that supports queries on such data, and allows the deployment of algorithms for inferring/detecting patterns and pre-computing visualizations, as a Neo4j plugin. This framework is innovative and brings several advantages to the phylogenetic analysis, such as by storing the phylogenetic trees will avoid having to compute them again, and by using multilayer networks will make the comparison between them more efficient and scalable. Experimental results showcase that it can be very efficient in the mostly used operations and that the supported algorithms comply with their time complexity. |
2107.12352 | Robert Nerem | Peter Crawford-Kahrl, Robert R. Nerem, Bree Cummins, and Tomas Gedeon | Genetic Networks Encode Secrets of Their Past | 19 pages, 4 figures, 1 table | null | null | null | q-bio.MN | http://creativecommons.org/licenses/by/4.0/ | Research shows that gene duplication followed by either repurposing or
removal of duplicated genes is an important contributor to evolution of gene
and protein interaction networks. We aim to identify which characteristics of a
network can arise through this process, and which must have been produced in a
different way. To model the network evolution, we postulate vertex duplication
and edge deletion as evolutionary operations on graphs. Using the novel concept
of an ancestrally distinguished subgraph, we show how features of present-day
networks require certain features of their ancestors. In particular,
ancestrally distinguished subgraphs cannot be introduced by vertex duplication.
Additionally, if vertex duplication and edge deletion are the only evolutionary
mechanisms, then a graph's ancestrally distinguished subgraphs must be
contained in all of the graph's ancestors. We analyze two experimentally
derived genetic networks and show that our results accurately predict lack of
large ancestrally distinguished subgraphs, despite this feature being
statistically improbable in associated random networks. This observation is
consistent with the hypothesis that these networks evolved primarily via vertex
duplication. The tools we provide open the door for analysing ancestral
networks using current networks. Our results apply to edge-labeled (e.g.
signed) graphs which are either undirected or directed.
| [
{
"created": "Mon, 26 Jul 2021 17:46:37 GMT",
"version": "v1"
}
] | 2021-07-27 | [
[
"Crawford-Kahrl",
"Peter",
""
],
[
"Nerem",
"Robert R.",
""
],
[
"Cummins",
"Bree",
""
],
[
"Gedeon",
"Tomas",
""
]
] | Research shows that gene duplication followed by either repurposing or removal of duplicated genes is an important contributor to evolution of gene and protein interaction networks. We aim to identify which characteristics of a network can arise through this process, and which must have been produced in a different way. To model the network evolution, we postulate vertex duplication and edge deletion as evolutionary operations on graphs. Using the novel concept of an ancestrally distinguished subgraph, we show how features of present-day networks require certain features of their ancestors. In particular, ancestrally distinguished subgraphs cannot be introduced by vertex duplication. Additionally, if vertex duplication and edge deletion are the only evolutionary mechanisms, then a graph's ancestrally distinguished subgraphs must be contained in all of the graph's ancestors. We analyze two experimentally derived genetic networks and show that our results accurately predict lack of large ancestrally distinguished subgraphs, despite this feature being statistically improbable in associated random networks. This observation is consistent with the hypothesis that these networks evolved primarily via vertex duplication. The tools we provide open the door for analysing ancestral networks using current networks. Our results apply to edge-labeled (e.g. signed) graphs which are either undirected or directed. |
1411.3480 | Olga Chernomor | Olga Chernomor, Arndt von Haeseler and Bui Quang Minh | Terrace Aware Phylogenomic Inference from Supermatrices | 16 pages, 3 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One approach in phylogenomics to infer the tree of life is based on
concatenated multiple sequence alignments from many genes. Unfortunately, the
resulting so-called supermatrix is usually sparse, that is, not every gene
sequence is available for all species in the supermatrix. Due to the missing
sequence information a phylogenetic inference, assuming that each gene evolves
with its own substitution model, suffers from phylogenetic terraces on which
many phylogenetic trees show the same likelihood. Here, we propose a
phylogenetic terrace aware (PTA) data structure for efficient supermatrix based
tree inference under partition models. PTA avoids likelihood computations for
trees belonging to the same terrace. PTA is implemented in the IQ-TREE
software, and leads to an 1.7 to 6-fold speedup for real data sets compared
with a na\"ive implementation. Speedups are independent on terrace sizes but
correlate with the amount of missing data. Thus, the PTA data structure is well
suited for phylogenomic analyses. IQ-TREE source codes, binaries and
documentation are freely available at http://www.cibiv.at/software/iqtree .
| [
{
"created": "Thu, 13 Nov 2014 09:56:47 GMT",
"version": "v1"
}
] | 2014-11-14 | [
[
"Chernomor",
"Olga",
""
],
[
"von Haeseler",
"Arndt",
""
],
[
"Minh",
"Bui Quang",
""
]
] | One approach in phylogenomics to infer the tree of life is based on concatenated multiple sequence alignments from many genes. Unfortunately, the resulting so-called supermatrix is usually sparse, that is, not every gene sequence is available for all species in the supermatrix. Due to the missing sequence information a phylogenetic inference, assuming that each gene evolves with its own substitution model, suffers from phylogenetic terraces on which many phylogenetic trees show the same likelihood. Here, we propose a phylogenetic terrace aware (PTA) data structure for efficient supermatrix based tree inference under partition models. PTA avoids likelihood computations for trees belonging to the same terrace. PTA is implemented in the IQ-TREE software, and leads to an 1.7 to 6-fold speedup for real data sets compared with a na\"ive implementation. Speedups are independent on terrace sizes but correlate with the amount of missing data. Thus, the PTA data structure is well suited for phylogenomic analyses. IQ-TREE source codes, binaries and documentation are freely available at http://www.cibiv.at/software/iqtree . |
1410.7642 | Carsten Wiuf | Elisenda Feliu and Carsten Wiuf | Finding the positive feedback loops underlying multi-stationarity | 16 pages, 4 figures | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Bistability is ubiquitous in biological systems. For example, bistability is
found in many reaction networks that involve the control and execution of
important biological functions, such as signalling processes. Positive feedback
loops, composed of species and reactions, are necessary for bistability, and
generally for multi-stationarity, to occur. These loops are therefore often
used to illustrate and pinpoint the parts of a multi-stationary network that
are relevant (`responsible') for the observed multi-stationarity. However
positive feedback loops are generally abundant in reaction networks but not all
of them are important for subsequent interpretation of the network's dynamics.
We present an automated procedure to determine the relevant positive feedback
loops of a multi-stationary reaction network. The procedure only reports the
loops that are relevant for multi-stationarity (that is, when broken
multi-stationarity disappears) and not all positive feedback loops of the
network. We show that the relevant positive feedback loops must be understood
in the context of the network (one loop might be relevant for one network, but
cannot create multi-stationarity in another). Finally, we demonstrate the
procedure by applying it to several examples of signaling processes, including
a ubiquitination and an apoptosis network, and to models extracted from the
Biomodels database.
We have developed and implemented an automated procedure to find relevant
positive feedback loops in reaction networks. The results of the procedure are
useful for interpretation and summary of the network's dynamics.
| [
{
"created": "Tue, 28 Oct 2014 14:47:23 GMT",
"version": "v1"
}
] | 2014-10-29 | [
[
"Feliu",
"Elisenda",
""
],
[
"Wiuf",
"Carsten",
""
]
] | Bistability is ubiquitous in biological systems. For example, bistability is found in many reaction networks that involve the control and execution of important biological functions, such as signalling processes. Positive feedback loops, composed of species and reactions, are necessary for bistability, and generally for multi-stationarity, to occur. These loops are therefore often used to illustrate and pinpoint the parts of a multi-stationary network that are relevant (`responsible') for the observed multi-stationarity. However positive feedback loops are generally abundant in reaction networks but not all of them are important for subsequent interpretation of the network's dynamics. We present an automated procedure to determine the relevant positive feedback loops of a multi-stationary reaction network. The procedure only reports the loops that are relevant for multi-stationarity (that is, when broken multi-stationarity disappears) and not all positive feedback loops of the network. We show that the relevant positive feedback loops must be understood in the context of the network (one loop might be relevant for one network, but cannot create multi-stationarity in another). Finally, we demonstrate the procedure by applying it to several examples of signaling processes, including a ubiquitination and an apoptosis network, and to models extracted from the Biomodels database. We have developed and implemented an automated procedure to find relevant positive feedback loops in reaction networks. The results of the procedure are useful for interpretation and summary of the network's dynamics. |
1611.06197 | Daniel Moyer | Daniel Moyer, Boris A. Gutman, Joshua Faskowitz, Neda Jahanshad, Paul
M. Thompson | An Empirical Study of Continuous Connectivity Degree Sequence
Equivalents | Presented at The MICCAI-BACON 16 Workshop
(https://arxiv.org/abs/1611.03363) | null | null | BACON/2016/04 | q-bio.NC cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In the present work we demonstrate the use of a parcellation free
connectivity model based on Poisson point processes. This model produces for
each subject a continuous bivariate intensity function that represents for
every possible pair of points the relative rate at which we observe tracts
terminating at those points. We fit this model to explore degree sequence
equivalents for spatial continuum graphs, and to investigate the local
differences between estimated intensity functions for two different
tractography methods. This is a companion paper to Moyer et al. (2016), where
the model was originally defined.
| [
{
"created": "Fri, 18 Nov 2016 18:53:45 GMT",
"version": "v1"
}
] | 2016-11-21 | [
[
"Moyer",
"Daniel",
""
],
[
"Gutman",
"Boris A.",
""
],
[
"Faskowitz",
"Joshua",
""
],
[
"Jahanshad",
"Neda",
""
],
[
"Thompson",
"Paul M.",
""
]
] | In the present work we demonstrate the use of a parcellation free connectivity model based on Poisson point processes. This model produces for each subject a continuous bivariate intensity function that represents for every possible pair of points the relative rate at which we observe tracts terminating at those points. We fit this model to explore degree sequence equivalents for spatial continuum graphs, and to investigate the local differences between estimated intensity functions for two different tractography methods. This is a companion paper to Moyer et al. (2016), where the model was originally defined. |
2004.08220 | Fernando Rosas | Fernando E. Rosas, Pedro A.M. Mediano, Henrik J. Jensen, Anil K. Seth,
Adam B. Barrett, Robin L. Carhart-Harris, Daniel Bor | Reconciling emergences: An information-theoretic approach to identify
causal emergence in multivariate data | 18 pages, 7 figures | null | 10.1371/journal.pcbi.1008289 | null | q-bio.NC nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The broad concept of emergence is instrumental in various of the most
challenging open scientific questions -- yet, few quantitative theories of what
constitutes emergent phenomena have been proposed. This article introduces a
formal theory of causal emergence in multivariate systems, which studies the
relationship between the dynamics of parts of a system and macroscopic features
of interest. Our theory provides a quantitative definition of downward
causation, and introduces a complementary modality of emergent behaviour --
which we refer to as causal decoupling. Moreover, the theory allows practical
criteria that can be efficiently calculated in large systems, making our
framework applicable in a range of scenarios of practical interest. We
illustrate our findings in a number of case studies, including Conway's Game of
Life, Reynolds' flocking model, and neural activity as measured by
electrocorticography.
| [
{
"created": "Fri, 17 Apr 2020 13:05:39 GMT",
"version": "v1"
}
] | 2021-01-27 | [
[
"Rosas",
"Fernando E.",
""
],
[
"Mediano",
"Pedro A. M.",
""
],
[
"Jensen",
"Henrik J.",
""
],
[
"Seth",
"Anil K.",
""
],
[
"Barrett",
"Adam B.",
""
],
[
"Carhart-Harris",
"Robin L.",
""
],
[
"Bor",
"Daniel",
""
]
] | The broad concept of emergence is instrumental in various of the most challenging open scientific questions -- yet, few quantitative theories of what constitutes emergent phenomena have been proposed. This article introduces a formal theory of causal emergence in multivariate systems, which studies the relationship between the dynamics of parts of a system and macroscopic features of interest. Our theory provides a quantitative definition of downward causation, and introduces a complementary modality of emergent behaviour -- which we refer to as causal decoupling. Moreover, the theory allows practical criteria that can be efficiently calculated in large systems, making our framework applicable in a range of scenarios of practical interest. We illustrate our findings in a number of case studies, including Conway's Game of Life, Reynolds' flocking model, and neural activity as measured by electrocorticography. |
1511.01010 | Sergio Gabriel Quesada Acuna | Erich Neurohr Bustamante, Juli\'an Monge-N\'ajera and Mar\'ia Isabel
Gonz\'alez Lutz | Air pollution in a tropical city: the relationship between wind
direction and lichen bio-indicators in San Jos\'e, Costa Rica | 8 pages, 2 figures | Rev. Biol. Trop. (Int. J. Trop. Biol. ISSN-0034-7744) Vol. 59 (2):
899-905, June 2011 | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Lichens are good bio-indicators of air pollution, but in most tropical
countries there are few studies on the subject; however, in the city of San
Jos\'e, Costa Rica, the relationship between air pollution and lichens has been
studied for decades. In this article we evaluate the hypothesis that air
pollution is lower where the wind enters the urban area (Northeast) and higher
where it exits San Jos\'e (Southwest). We identified the urban parks with a
minimum area of approximately 5 000m2 and randomly selected a sample of 40
parks located along the passage of wind through the city. To measure lichen
coverage, we applied a previously validated 10 x 20cm template with 50 random
points to five trees per park (1.5m above ground, to the side with most
lichens). Our results (years 2008 and 2009) fully agree with the generally
accepted view that lichens reflect air pollution carried by circulating air
masses. The practical implication is that the air enters the city relatively
clean by the semi-rural and economically middle class area of Coronado, and
leaves through the developed neighborhoods of Escaz\'u and Santa Ana with a
significant amount of pollutants. In the dry season, the live lichen coverage
of this tropical city was lower than in the May to December rainy season, a
pattern that contrasts with temperate habitats; but regardless of the season,
pollution follows the pattern of wind movement through the city.
| [
{
"created": "Tue, 3 Nov 2015 17:44:56 GMT",
"version": "v1"
}
] | 2015-11-04 | [
[
"Bustamante",
"Erich Neurohr",
""
],
[
"Monge-Nájera",
"Julián",
""
],
[
"Lutz",
"María Isabel González",
""
]
] | Lichens are good bio-indicators of air pollution, but in most tropical countries there are few studies on the subject; however, in the city of San Jos\'e, Costa Rica, the relationship between air pollution and lichens has been studied for decades. In this article we evaluate the hypothesis that air pollution is lower where the wind enters the urban area (Northeast) and higher where it exits San Jos\'e (Southwest). We identified the urban parks with a minimum area of approximately 5 000m2 and randomly selected a sample of 40 parks located along the passage of wind through the city. To measure lichen coverage, we applied a previously validated 10 x 20cm template with 50 random points to five trees per park (1.5m above ground, to the side with most lichens). Our results (years 2008 and 2009) fully agree with the generally accepted view that lichens reflect air pollution carried by circulating air masses. The practical implication is that the air enters the city relatively clean by the semi-rural and economically middle class area of Coronado, and leaves through the developed neighborhoods of Escaz\'u and Santa Ana with a significant amount of pollutants. In the dry season, the live lichen coverage of this tropical city was lower than in the May to December rainy season, a pattern that contrasts with temperate habitats; but regardless of the season, pollution follows the pattern of wind movement through the city. |
0704.0036 | Eduardo D. Sontag | Liming Wang and Eduardo D. Sontag | A remark on the number of steady states in a multiple futile cycle | Resubmit with new results on the upper bound of the number of steady
states. 20 pages, 2 figures, See
http://www.math.rutgers.edu/~sontag/PUBDIR/index.html for online preprints
and reprints of related work | null | null | null | q-bio.QM q-bio.MN | null | The multisite phosphorylation-dephosphorylation cycle is a motif repeatedly
used in cell signaling. This motif itself can generate a variety of dynamic
behaviors like bistability and ultrasensitivity without direct positive
feedbacks. In this paper, we study the number of positive steady states of a
general multisite phosphorylation-dephosphorylation cycle, and how the number
of positive steady states varies by changing the biological parameters. We show
analytically that (1) for some parameter ranges, there are at least n+1 (if n
is even) or n (if n is odd) steady states; (2) there never are more than 2n-1
steady states (in particular, this implies that for n=2, including single
levels of MAPK cascades, there are at most three steady states); (3) for
parameters near the standard Michaelis-Menten quasi-steady state conditions,
there are at most n+1 steady states; and (4) for parameters far from the
standard Michaelis-Menten quasi-steady state conditions, there is at most one
steady state.
| [
{
"created": "Sat, 31 Mar 2007 15:55:50 GMT",
"version": "v1"
},
{
"created": "Fri, 20 Jul 2007 01:25:10 GMT",
"version": "v2"
}
] | 2011-11-09 | [
[
"Wang",
"Liming",
""
],
[
"Sontag",
"Eduardo D.",
""
]
] | The multisite phosphorylation-dephosphorylation cycle is a motif repeatedly used in cell signaling. This motif itself can generate a variety of dynamic behaviors like bistability and ultrasensitivity without direct positive feedbacks. In this paper, we study the number of positive steady states of a general multisite phosphorylation-dephosphorylation cycle, and how the number of positive steady states varies by changing the biological parameters. We show analytically that (1) for some parameter ranges, there are at least n+1 (if n is even) or n (if n is odd) steady states; (2) there never are more than 2n-1 steady states (in particular, this implies that for n=2, including single levels of MAPK cascades, there are at most three steady states); (3) for parameters near the standard Michaelis-Menten quasi-steady state conditions, there are at most n+1 steady states; and (4) for parameters far from the standard Michaelis-Menten quasi-steady state conditions, there is at most one steady state. |
2101.02924 | Tim Prangemeier | Tim Prangemeier, Christian Wildner, Maleen Hanst, and Heinz Koeppl | Maximizing Information Gain for the Characterization of Biomolecular
Circuits | NanoCom 2018, accepted | null | 10.1145/3233188.3233217 | null | q-bio.MN cs.SY eess.SY physics.ins-det q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Quantitatively predictive models of biomolecular circuits are important tools
for the design of synthetic biology and molecular communication circuits. The
information content of typical time-lapse single-cell data for the inference of
kinetic parameters is not only limited by measurement uncertainty and intrinsic
stochasticity, but also by the employed perturbations. Novel microfluidic
devices enable the synthesis of temporal chemical concentration profiles. The
informativeness of a perturbation can be quantified based on mutual
information. We propose an approximate method to perform optimal experimental
design of such perturbation profiles. To estimate the mutual information we
perform a multivariate log-normal approximation of the joint distribution over
parameters and observations and scan the design space using Metropolis-Hastings
sampling. The method is demonstrated by finding optimal perturbation sequences
for synthetic case studies on a gene expression model with varying reporter
characteristics.
| [
{
"created": "Fri, 8 Jan 2021 09:13:46 GMT",
"version": "v1"
}
] | 2021-01-11 | [
[
"Prangemeier",
"Tim",
""
],
[
"Wildner",
"Christian",
""
],
[
"Hanst",
"Maleen",
""
],
[
"Koeppl",
"Heinz",
""
]
] | Quantitatively predictive models of biomolecular circuits are important tools for the design of synthetic biology and molecular communication circuits. The information content of typical time-lapse single-cell data for the inference of kinetic parameters is not only limited by measurement uncertainty and intrinsic stochasticity, but also by the employed perturbations. Novel microfluidic devices enable the synthesis of temporal chemical concentration profiles. The informativeness of a perturbation can be quantified based on mutual information. We propose an approximate method to perform optimal experimental design of such perturbation profiles. To estimate the mutual information we perform a multivariate log-normal approximation of the joint distribution over parameters and observations and scan the design space using Metropolis-Hastings sampling. The method is demonstrated by finding optimal perturbation sequences for synthetic case studies on a gene expression model with varying reporter characteristics. |
1211.0947 | Sebastian Bitzer | Sebastian Bitzer and Izzet B. Yildiz and Stefan J. Kiebel | Online Discrimination of Nonlinear Dynamics with Switching Differential
Equations | null | null | null | null | q-bio.NC stat.CO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | How to recognise whether an observed person walks or runs? We consider a
dynamic environment where observations (e.g. the posture of a person) are
caused by different dynamic processes (walking or running) which are active one
at a time and which may transition from one to another at any time. For this
setup, switching dynamic models have been suggested previously, mostly, for
linear and nonlinear dynamics in discrete time. Motivated by basic principles
of computations in the brain (dynamic, internal models) we suggest a model for
switching nonlinear differential equations. The switching process in the model
is implemented by a Hopfield network and we use parametric dynamic movement
primitives to represent arbitrary rhythmic motions. The model generates
observed dynamics by linearly interpolating the primitives weighted by the
switching variables and it is constructed such that standard filtering
algorithms can be applied. In two experiments with synthetic planar motion and
a human motion capture data set we show that inference with the unscented
Kalman filter can successfully discriminate several dynamic processes online.
| [
{
"created": "Mon, 5 Nov 2012 17:50:56 GMT",
"version": "v1"
}
] | 2012-11-06 | [
[
"Bitzer",
"Sebastian",
""
],
[
"Yildiz",
"Izzet B.",
""
],
[
"Kiebel",
"Stefan J.",
""
]
] | How to recognise whether an observed person walks or runs? We consider a dynamic environment where observations (e.g. the posture of a person) are caused by different dynamic processes (walking or running) which are active one at a time and which may transition from one to another at any time. For this setup, switching dynamic models have been suggested previously, mostly, for linear and nonlinear dynamics in discrete time. Motivated by basic principles of computations in the brain (dynamic, internal models) we suggest a model for switching nonlinear differential equations. The switching process in the model is implemented by a Hopfield network and we use parametric dynamic movement primitives to represent arbitrary rhythmic motions. The model generates observed dynamics by linearly interpolating the primitives weighted by the switching variables and it is constructed such that standard filtering algorithms can be applied. In two experiments with synthetic planar motion and a human motion capture data set we show that inference with the unscented Kalman filter can successfully discriminate several dynamic processes online. |
2303.02983 | Zhijie Feng | Zhijie Feng, Robert Marsland III, Jason W. Rocks, and Pankaj Mehta | Emergent competition shapes the ecological properties of multi-trophic
ecosystems | Main text: 10.5 pages, 7 figures (Total: 18 pages) | null | null | null | q-bio.PE cond-mat.stat-mech physics.bio-ph | http://creativecommons.org/licenses/by/4.0/ | Ecosystems are commonly organized into trophic levels -- organisms that
occupy the same level in a food chain (e.g., plants, herbivores, carnivores). A
fundamental question in theoretical ecology is how the interplay between
trophic structure, diversity, and competition shapes the properties of
ecosystems. To address this problem, we analyze a generalized Consumer Resource
Model with three trophic levels using the zero-temperature cavity method and
numerical simulations. We find that intra-trophic diversity gives rise to
``emergent competition'' between species within a trophic level due to
feedbacks mediated by other trophic levels. This emergent competition gives
rise to a crossover from a regime of top-down control (populations are limited
by predators) to a regime of bottom-up control (populations are limited by
primary producers) and is captured by a simple order parameter related to the
ratio of surviving species in different trophic levels. We show that our
theoretical results agree with empirical observations, suggesting that the
theoretical approach outlined here can be used to understand complex ecosystems
with multiple trophic levels.
| [
{
"created": "Mon, 6 Mar 2023 09:20:40 GMT",
"version": "v1"
}
] | 2023-03-07 | [
[
"Feng",
"Zhijie",
""
],
[
"Marsland",
"Robert",
"III"
],
[
"Rocks",
"Jason W.",
""
],
[
"Mehta",
"Pankaj",
""
]
] | Ecosystems are commonly organized into trophic levels -- organisms that occupy the same level in a food chain (e.g., plants, herbivores, carnivores). A fundamental question in theoretical ecology is how the interplay between trophic structure, diversity, and competition shapes the properties of ecosystems. To address this problem, we analyze a generalized Consumer Resource Model with three trophic levels using the zero-temperature cavity method and numerical simulations. We find that intra-trophic diversity gives rise to ``emergent competition'' between species within a trophic level due to feedbacks mediated by other trophic levels. This emergent competition gives rise to a crossover from a regime of top-down control (populations are limited by predators) to a regime of bottom-up control (populations are limited by primary producers) and is captured by a simple order parameter related to the ratio of surviving species in different trophic levels. We show that our theoretical results agree with empirical observations, suggesting that the theoretical approach outlined here can be used to understand complex ecosystems with multiple trophic levels. |
1312.7528 | Sergei Kozyrev | A.Yu. Khrennikov, S.V. Kozyrev, A. Mansson | Hierarchical model of the actomyosin molecular motor based on
ultrametric diffusion with drift | 15 pages | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We discuss the approach to investigation of molecular machines using systems
of integro--differential ultrametric (p-adic) reaction--diffusion equations
with drift. This approach combines the features of continuous and discrete
dynamic models. We apply this model to investigation of actomyosin molecular
motor.
The introduced system of equations is solved analytically using p-adic
wavelet theory. We find explicit stationary solutions and behavior in the
relaxation regime.
| [
{
"created": "Sun, 29 Dec 2013 12:24:26 GMT",
"version": "v1"
}
] | 2013-12-31 | [
[
"Khrennikov",
"A. Yu.",
""
],
[
"Kozyrev",
"S. V.",
""
],
[
"Mansson",
"A.",
""
]
] | We discuss the approach to investigation of molecular machines using systems of integro--differential ultrametric (p-adic) reaction--diffusion equations with drift. This approach combines the features of continuous and discrete dynamic models. We apply this model to investigation of actomyosin molecular motor. The introduced system of equations is solved analytically using p-adic wavelet theory. We find explicit stationary solutions and behavior in the relaxation regime. |
1302.4090 | Serge Sheremet'ev | Serge Sheremetiev and Yuri Gamalei | Towards angiosperms genome evolution in time | 24 pages, 11 figures, 4 tables | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this communication, direction of evolutionary variability of parameters of
genome size and structurally functional activity of plants in angiosperm taxa
among life forms, are analysed. It is shown that, in the Cretaceous-Cenozoic
era, the nuclear genome of the plants tended to increase. Functional genome
efficiency (intensity of functions per picogram of DNA) decreased as much as
possible from highest, at trees and lianas of rain and monsoonal forests of the
Paleogene, to minimum, at shrubs, perennial and annual grasses of meadow-steppe
vegetation appeared in the Neogene. Environmental changes in temperature,
humidity and carbon dioxide concentration in adverse direction, critical for
vegetation, are discussed as the cause of growth of evolutionary genome size
and loss in its functional efficiency. The growth of the genome in the Cenozoic
did not lead to the intensification of functions, but rather led to the
expansion of the adaptive capacity of species. Growth of nuclear
deoxyribonucleic acid content can be considered as one of the effective tools
of an adaptogenesis.
| [
{
"created": "Sun, 17 Feb 2013 17:10:15 GMT",
"version": "v1"
}
] | 2013-02-19 | [
[
"Sheremetiev",
"Serge",
""
],
[
"Gamalei",
"Yuri",
""
]
] | In this communication, direction of evolutionary variability of parameters of genome size and structurally functional activity of plants in angiosperm taxa among life forms, are analysed. It is shown that, in the Cretaceous-Cenozoic era, the nuclear genome of the plants tended to increase. Functional genome efficiency (intensity of functions per picogram of DNA) decreased as much as possible from highest, at trees and lianas of rain and monsoonal forests of the Paleogene, to minimum, at shrubs, perennial and annual grasses of meadow-steppe vegetation appeared in the Neogene. Environmental changes in temperature, humidity and carbon dioxide concentration in adverse direction, critical for vegetation, are discussed as the cause of growth of evolutionary genome size and loss in its functional efficiency. The growth of the genome in the Cenozoic did not lead to the intensification of functions, but rather led to the expansion of the adaptive capacity of species. Growth of nuclear deoxyribonucleic acid content can be considered as one of the effective tools of an adaptogenesis. |
2307.11133 | Jiaxing Xu | Jiaxing Xu, Qingtian Bian, Xinhang Li, Aihu Zhang, Yiping Ke, Miao
Qiao, Wei Zhang, Wei Khang Jeremy Sim, and Bal\'azs Guly\'as | Contrastive Graph Pooling for Explainable Classification of Brain
Networks | null | null | null | null | q-bio.NC cs.AI cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Functional magnetic resonance imaging (fMRI) is a commonly used technique to
measure neural activation. Its application has been particularly important in
identifying underlying neurodegenerative conditions such as Parkinson's,
Alzheimer's, and Autism. Recent analysis of fMRI data models the brain as a
graph and extracts features by graph neural networks (GNNs). However, the
unique characteristics of fMRI data require a special design of GNN. Tailoring
GNN to generate effective and domain-explainable features remains challenging.
In this paper, we propose a contrastive dual-attention block and a
differentiable graph pooling method called ContrastPool to better utilize GNN
for brain networks, meeting fMRI-specific requirements. We apply our method to
5 resting-state fMRI brain network datasets of 3 diseases and demonstrate its
superiority over state-of-the-art baselines. Our case study confirms that the
patterns extracted by our method match the domain knowledge in neuroscience
literature, and disclose direct and interesting insights. Our contributions
underscore the potential of ContrastPool for advancing the understanding of
brain networks and neurodegenerative conditions. The source code is available
at https://github.com/AngusMonroe/ContrastPool.
| [
{
"created": "Fri, 7 Jul 2023 11:49:55 GMT",
"version": "v1"
},
{
"created": "Fri, 12 Apr 2024 12:05:57 GMT",
"version": "v2"
}
] | 2024-04-15 | [
[
"Xu",
"Jiaxing",
""
],
[
"Bian",
"Qingtian",
""
],
[
"Li",
"Xinhang",
""
],
[
"Zhang",
"Aihu",
""
],
[
"Ke",
"Yiping",
""
],
[
"Qiao",
"Miao",
""
],
[
"Zhang",
"Wei",
""
],
[
"Sim",
"Wei Khang Jeremy",
""
],
[
"Gulyás",
"Balázs",
""
]
] | Functional magnetic resonance imaging (fMRI) is a commonly used technique to measure neural activation. Its application has been particularly important in identifying underlying neurodegenerative conditions such as Parkinson's, Alzheimer's, and Autism. Recent analysis of fMRI data models the brain as a graph and extracts features by graph neural networks (GNNs). However, the unique characteristics of fMRI data require a special design of GNN. Tailoring GNN to generate effective and domain-explainable features remains challenging. In this paper, we propose a contrastive dual-attention block and a differentiable graph pooling method called ContrastPool to better utilize GNN for brain networks, meeting fMRI-specific requirements. We apply our method to 5 resting-state fMRI brain network datasets of 3 diseases and demonstrate its superiority over state-of-the-art baselines. Our case study confirms that the patterns extracted by our method match the domain knowledge in neuroscience literature, and disclose direct and interesting insights. Our contributions underscore the potential of ContrastPool for advancing the understanding of brain networks and neurodegenerative conditions. The source code is available at https://github.com/AngusMonroe/ContrastPool. |
1802.01627 | Nuno Nen\'e | Nuno R. Nen\'e, James Rivington and Alexey Zaikin | Sensitivity of asymmetric rate-dependent critical systems to initial
conditions: insights into cellular decision making | null | Phys. Rev. E 98, 022317 (2018) | 10.1103/PhysRevE.98.022317 | null | q-bio.QM q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The work reported here aims to address the effects of time-dependent
parameters and stochasticity on decision-making in biological systems. We
achieve this by extending previous studies that resorted to simple normal
forms. Yet, we focus primarily on the issue of the system's sensitivity to
initial conditions in the presence of different noise distributions. In
addition, we assess the impact of two-way sweeping through the critical region
of a canonical Pitchfork bifurcation with a constant external asymmetry. The
parallel with decision-making in bio-circuits is performed on this simple
system since it is equivalent in its available states and dynamics to more
complex genetic circuits. Overall, we verify that rate-dependent effects are
specific to particular initial conditions. Information processing for each
starting state is affected by the balance between sweeping speed through
critical regions, and the type of fluctuations added. For a heavy-tail noise,
forward-reverse dynamic bifurcations are more efficient in processing the
information contained in external signals, when compared to the system relying
on escape dynamics, if it starts at an attractor not favoured by the asymmetry
and, in conjunction, if the sweeping amplitude is large.
| [
{
"created": "Mon, 5 Feb 2018 20:00:37 GMT",
"version": "v1"
}
] | 2018-08-29 | [
[
"Nené",
"Nuno R.",
""
],
[
"Rivington",
"James",
""
],
[
"Zaikin",
"Alexey",
""
]
] | The work reported here aims to address the effects of time-dependent parameters and stochasticity on decision-making in biological systems. We achieve this by extending previous studies that resorted to simple normal forms. Yet, we focus primarily on the issue of the system's sensitivity to initial conditions in the presence of different noise distributions. In addition, we assess the impact of two-way sweeping through the critical region of a canonical Pitchfork bifurcation with a constant external asymmetry. The parallel with decision-making in bio-circuits is performed on this simple system since it is equivalent in its available states and dynamics to more complex genetic circuits. Overall, we verify that rate-dependent effects are specific to particular initial conditions. Information processing for each starting state is affected by the balance between sweeping speed through critical regions, and the type of fluctuations added. For a heavy-tail noise, forward-reverse dynamic bifurcations are more efficient in processing the information contained in external signals, when compared to the system relying on escape dynamics, if it starts at an attractor not favoured by the asymmetry and, in conjunction, if the sweeping amplitude is large. |
2408.08036 | Olivier Merlo | Olivier Merlo | Analysing pandemics in phase-space | 25 pages, 11 figures | null | null | null | q-bio.PE physics.soc-ph | http://creativecommons.org/publicdomain/zero/1.0/ | Based on the SIRD-model a new model including time-delay is proposed for a
description of the outbreak of the novel coronavirus Sars-CoV-2 pandemic. All
data were analysed by representing all quantities as a function of the
susceptible population, as opposed to the usual dependence on time. The total
number of deaths could be predicted for the first, second and third wave of the
pandemic in Germany with an accuracy of about 10\%, shortly after the maximum
of infectious people was reached. By using the presentation in phase space, it
could be shown that a classical SEIRD- and SIRD-model with constant parameters
will not be able to describe the first wave of the pandemic accurately.
| [
{
"created": "Thu, 15 Aug 2024 09:05:14 GMT",
"version": "v1"
}
] | 2024-08-16 | [
[
"Merlo",
"Olivier",
""
]
] | Based on the SIRD-model a new model including time-delay is proposed for a description of the outbreak of the novel coronavirus Sars-CoV-2 pandemic. All data were analysed by representing all quantities as a function of the susceptible population, as opposed to the usual dependence on time. The total number of deaths could be predicted for the first, second and third wave of the pandemic in Germany with an accuracy of about 10\%, shortly after the maximum of infectious people was reached. By using the presentation in phase space, it could be shown that a classical SEIRD- and SIRD-model with constant parameters will not be able to describe the first wave of the pandemic accurately. |
2307.10196 | Mehdi Delrobaei | Fateme Zare, Paniz Sedighi, and Mehdi Delrobaei | Evaluating Attentional Impulsivity: A Biomechatronic Approach | 10 pages, 5 figures, 5 tables | null | 10.1109/TIM.2023.3292964 | null | q-bio.NC cs.HC cs.SY eess.SY | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Executive function, also known as executive control, is a multifaceted
construct encompassing several cognitive abilities, including working memory,
attention, impulse control, and cognitive flexibility. To accurately measure
executive functioning skills, it is necessary to develop assessment tools and
strategies that can quantify the behaviors associated with cognitive control.
Impulsivity, a range of cognitive control deficits, is typically evaluated
using conventional neuropsychological tests. However, this study proposes a
biomechatronic approach to assess impulsivity as a behavioral construct, in
line with traditional neuropsychological assessments. The study involved
thirty-four healthy adults who completed the Barratt Impulsiveness Scale
(BIS-11) as an initial step. A low-cost biomechatronic system was developed,
and an approach based on standard neuropsychological tests, including the
trail-making test and serial subtraction-by-seven, was used to evaluate
impulsivity. Three tests were conducted: WTMT-A (numbers only), WTMT-B (numbers
and letters), and a dual-task of WTMT-A and serial subtraction-by-seven. The
preliminary findings suggest that the proposed instrument and experiments
successfully generated an attentional impulsivity score and differentiated
between participants with high and low attentional impulsivity.
| [
{
"created": "Tue, 11 Jul 2023 15:04:50 GMT",
"version": "v1"
},
{
"created": "Sat, 22 Jul 2023 09:11:01 GMT",
"version": "v2"
}
] | 2023-07-25 | [
[
"Zare",
"Fateme",
""
],
[
"Sedighi",
"Paniz",
""
],
[
"Delrobaei",
"Mehdi",
""
]
] | Executive function, also known as executive control, is a multifaceted construct encompassing several cognitive abilities, including working memory, attention, impulse control, and cognitive flexibility. To accurately measure executive functioning skills, it is necessary to develop assessment tools and strategies that can quantify the behaviors associated with cognitive control. Impulsivity, a range of cognitive control deficits, is typically evaluated using conventional neuropsychological tests. However, this study proposes a biomechatronic approach to assess impulsivity as a behavioral construct, in line with traditional neuropsychological assessments. The study involved thirty-four healthy adults who completed the Barratt Impulsiveness Scale (BIS-11) as an initial step. A low-cost biomechatronic system was developed, and an approach based on standard neuropsychological tests, including the trail-making test and serial subtraction-by-seven, was used to evaluate impulsivity. Three tests were conducted: WTMT-A (numbers only), WTMT-B (numbers and letters), and a dual-task of WTMT-A and serial subtraction-by-seven. The preliminary findings suggest that the proposed instrument and experiments successfully generated an attentional impulsivity score and differentiated between participants with high and low attentional impulsivity. |
1907.10009 | Fabrizio De Vico Fallani | Catalina Obando, Charlotte Rosso, Joshua Siegel, Maurizio Corbetta and
Fabrizio De Vico Fallani | Temporal connection signatures of human brain networks after stroke | null | Journal of the Royal Society Interface, 2022 | 10.1098/rsif.2021.0850 | null | q-bio.NC q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Plasticity after stroke is a complex phenomenon initiated by the functional
reorganization of the brain, especially in the perilesional tissue. At
macroscales, the reestablishment of segregation within the affected hemisphere
and interhemispheric integration has been extensively documented in the
reconfiguration of brain networks. However, the local connection mechanisms
generating such global network changes are still largely unknown as well as
their potential to better predict the outcome of patients. To address this
question, time must be considered as a formal variable of the problem and not
just a simple repeated observation. Here, we hypothesize that the temporal
formation of basic connection blocks such as intermodule edges and intramodule
triangles would be sufficient to determine the large-scale brain reorganization
after stroke. To test our hypothesis, we adopted a statistical approach based
on temporal exponential random graph models (tERGMs). First, we validated the
overall performance on synthetic time-varying networks simulating the
reconfiguration process after stroke. Then, using longitudinal functional
connectivity measurements of resting-state brain activity, we showed that both
the formation of triangles within the affected hemisphere and interhemispheric
links are sufficient to reproduce the longitudinal brain network changes from 2
weeks to 1 year after the stroke. Finally, we showed that these temporal
connection mechanisms are over-expressed in the subacute phase as compared to
healthy controls and predicted the chronic language and visual outcome
respectively in patients with subcortical and cortical lesions, whereas static
approaches failed to do so. Our results indicate the importance of considering
time-varying connection properties when modeling dynamic complex systems and
provide fresh insights into the network mechanisms of stroke recovery.
| [
{
"created": "Tue, 23 Jul 2019 17:07:50 GMT",
"version": "v1"
}
] | 2022-04-26 | [
[
"Obando",
"Catalina",
""
],
[
"Rosso",
"Charlotte",
""
],
[
"Siegel",
"Joshua",
""
],
[
"Corbetta",
"Maurizio",
""
],
[
"Fallani",
"Fabrizio De Vico",
""
]
] | Plasticity after stroke is a complex phenomenon initiated by the functional reorganization of the brain, especially in the perilesional tissue. At macroscales, the reestablishment of segregation within the affected hemisphere and interhemispheric integration has been extensively documented in the reconfiguration of brain networks. However, the local connection mechanisms generating such global network changes are still largely unknown as well as their potential to better predict the outcome of patients. To address this question, time must be considered as a formal variable of the problem and not just a simple repeated observation. Here, we hypothesize that the temporal formation of basic connection blocks such as intermodule edges and intramodule triangles would be sufficient to determine the large-scale brain reorganization after stroke. To test our hypothesis, we adopted a statistical approach based on temporal exponential random graph models (tERGMs). First, we validated the overall performance on synthetic time-varying networks simulating the reconfiguration process after stroke. Then, using longitudinal functional connectivity measurements of resting-state brain activity, we showed that both the formation of triangles within the affected hemisphere and interhemispheric links are sufficient to reproduce the longitudinal brain network changes from 2 weeks to 1 year after the stroke. Finally, we showed that these temporal connection mechanisms are over-expressed in the subacute phase as compared to healthy controls and predicted the chronic language and visual outcome respectively in patients with subcortical and cortical lesions, whereas static approaches failed to do so. Our results indicate the importance of considering time-varying connection properties when modeling dynamic complex systems and provide fresh insights into the network mechanisms of stroke recovery. |
1312.4106 | Tomasz Rutkowski | Chisaki Nakaizumi, Koichi Mori, Toshie Matsui, Shoji Makino, and
Tomasz M. Rutkowski | Auditory Brain-Computer Interface Paradigm with Head Related Impulse
Response-based Spatial Cues | The final publication is available at IEEE Xplore
http://ieeexplore.ieee.org and the copyright of the final version has been
transferred to IEEE (c)2013 | Proceedings of the 9th International Conference on Signal Image
Technology and Internet Based Systems. Kyoto, Japan: IEEE Computer Society;
2013. p. 806-811 | 10.1109/SITIS.2013.131 | null | q-bio.NC cs.HC | http://creativecommons.org/licenses/by-nc-sa/3.0/ | The aim of this study is to provide a comprehensive test of head related
impulse response (HRIR) for an auditory spatial speller brain-computer
interface (BCI) paradigm. The study is conducted with six users in an
experimental set up based on five Japanese hiragana vowels. Auditory evoked
potentials resulted with encouragingly good and stable "aha-" or P300-responses
in real-world online BCI experiments. Our case study indicated that the
auditory HRIR spatial sound reproduction paradigm could be a viable alternative
to the established multi-loudspeaker surround sound BCI-speller applications,
as far as healthy pilot study users are concerned.
| [
{
"created": "Sun, 15 Dec 2013 04:54:22 GMT",
"version": "v1"
}
] | 2013-12-17 | [
[
"Nakaizumi",
"Chisaki",
""
],
[
"Mori",
"Koichi",
""
],
[
"Matsui",
"Toshie",
""
],
[
"Makino",
"Shoji",
""
],
[
"Rutkowski",
"Tomasz M.",
""
]
] | The aim of this study is to provide a comprehensive test of head related impulse response (HRIR) for an auditory spatial speller brain-computer interface (BCI) paradigm. The study is conducted with six users in an experimental set up based on five Japanese hiragana vowels. Auditory evoked potentials resulted with encouragingly good and stable "aha-" or P300-responses in real-world online BCI experiments. Our case study indicated that the auditory HRIR spatial sound reproduction paradigm could be a viable alternative to the established multi-loudspeaker surround sound BCI-speller applications, as far as healthy pilot study users are concerned. |
q-bio/0605018 | Dima Kozakov | D. Kozakov, R. Brenke, S. Comeau, S. Vajda | PIPER: An FFT-based Protein Docking Program with Pairwise Potentials | null | null | null | 600600 | q-bio.BM | null | The Fast Fourier Transform (FFT) correlation approach to protein-protein
docking can evaluate the energies of billions of docked conformations on a grid
if the energy is described in the form of a correlation function. Here, this
restriction is removed, and the approach is efficiently used with pairwise
interactions potentials that substantially improve the docking results. The
basic idea is approximating the interaction matrix by its eigenvectors
corresponding to the few dominant eigenvalues, resulting in an energy
expression written as the sum of a few correlation functions, and solving the
problem by repeated FFT calculations. In addition to describing how the method
is implemented, we present a novel class of structure based pairwise
intermolecular potentials. The DARS (Decoys As the Reference State) potentials
are extracted from structures of protein-protein complexes and use large sets
of docked conformations as decoys to derive atom pair distributions in the
reference state. The current version of the DARS potential works well for
enzyme-inhibitor complexes. With the new FFT-based program, DARS provides much
better docking results than the earlier approaches, in many cases generating
50\% more near-native docked conformations. Although the potential is far from
optimal for antibody-antigen pairs, the results are still slightly better than
those given by an earlier FFT method. The docking program PIPER is freely
available for non-commercial applications.
| [
{
"created": "Thu, 11 May 2006 19:59:18 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Kozakov",
"D.",
""
],
[
"Brenke",
"R.",
""
],
[
"Comeau",
"S.",
""
],
[
"Vajda",
"S.",
""
]
] | The Fast Fourier Transform (FFT) correlation approach to protein-protein docking can evaluate the energies of billions of docked conformations on a grid if the energy is described in the form of a correlation function. Here, this restriction is removed, and the approach is efficiently used with pairwise interactions potentials that substantially improve the docking results. The basic idea is approximating the interaction matrix by its eigenvectors corresponding to the few dominant eigenvalues, resulting in an energy expression written as the sum of a few correlation functions, and solving the problem by repeated FFT calculations. In addition to describing how the method is implemented, we present a novel class of structure based pairwise intermolecular potentials. The DARS (Decoys As the Reference State) potentials are extracted from structures of protein-protein complexes and use large sets of docked conformations as decoys to derive atom pair distributions in the reference state. The current version of the DARS potential works well for enzyme-inhibitor complexes. With the new FFT-based program, DARS provides much better docking results than the earlier approaches, in many cases generating 50\% more near-native docked conformations. Although the potential is far from optimal for antibody-antigen pairs, the results are still slightly better than those given by an earlier FFT method. The docking program PIPER is freely available for non-commercial applications. |
2301.03907 | Thierry Mora | Lauritz Hahn, Aleksandra M. Walczak, Thierry Mora | Dynamical information synergy in biochemical signaling networks | null | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Biological cells encode information about their environment through
biochemical signaling networks that control their internal state and response.
This information is often encoded in the dynamical patterns of the signaling
molecules, rather than just their instantaneous concentrations. Here, we
analytically calculate the information contained in these dynamics for a number
of paradigmatic cases in the linear regime, for both static and time-dependent
input signals. When considering oscillatory output dynamics, we report the
emergence of synergy between successive measurements, meaning that the joint
information in two measurements exceeds the sum of the individual information.
We extend our analysis numerically beyond the scope of linear input encoding to
reveal synergetic effects in the cases of frequency or damping modulation, both
of which are relevant to classical biochemical signaling systems.
| [
{
"created": "Tue, 10 Jan 2023 11:08:40 GMT",
"version": "v1"
},
{
"created": "Fri, 21 Apr 2023 10:47:52 GMT",
"version": "v2"
}
] | 2023-04-24 | [
[
"Hahn",
"Lauritz",
""
],
[
"Walczak",
"Aleksandra M.",
""
],
[
"Mora",
"Thierry",
""
]
] | Biological cells encode information about their environment through biochemical signaling networks that control their internal state and response. This information is often encoded in the dynamical patterns of the signaling molecules, rather than just their instantaneous concentrations. Here, we analytically calculate the information contained in these dynamics for a number of paradigmatic cases in the linear regime, for both static and time-dependent input signals. When considering oscillatory output dynamics, we report the emergence of synergy between successive measurements, meaning that the joint information in two measurements exceeds the sum of the individual information. We extend our analysis numerically beyond the scope of linear input encoding to reveal synergetic effects in the cases of frequency or damping modulation, both of which are relevant to classical biochemical signaling systems. |
q-bio/0702047 | Danuta Makowiec | Danuta Makowiec, Aleksandra Dudkowska, Rafal Galaska, Andrzej
Rynkiewicz | Multifractal analysis of normal RR heart-interbeat signals in power
spectra ranges | 10 pages | null | null | null | q-bio.QM | null | Power spectral density is an accepted measure of heart rate variability. Two
estimators of multifractal properties: Wavelet Transform Modulus Maxima and
Multifractal Detrended Fluctuation Analysis are used to investigate
multifractal properties for the three strongly physiologically grounded
components of power spectra: low frequency (LF), very low frequency (VLF) and
ultra low frequency (ULV). Circadian rhythm changes are examined by
discrimination of daily activity from nocturnal rest. Investigations consider
normal sinus rhythms of healthy 39 subjects which are grouped in two sets:
5-hour wake series and 5-hour sleep series. Qualitative arguments are provided
to conjecture the presence of stochastic persistence in LF range, loss of heart
rate variability during night in VLF range and its increase in ULF.
| [
{
"created": "Fri, 23 Feb 2007 14:55:13 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Makowiec",
"Danuta",
""
],
[
"Dudkowska",
"Aleksandra",
""
],
[
"Galaska",
"Rafal",
""
],
[
"Rynkiewicz",
"Andrzej",
""
]
] | Power spectral density is an accepted measure of heart rate variability. Two estimators of multifractal properties: Wavelet Transform Modulus Maxima and Multifractal Detrended Fluctuation Analysis are used to investigate multifractal properties for the three strongly physiologically grounded components of power spectra: low frequency (LF), very low frequency (VLF) and ultra low frequency (ULV). Circadian rhythm changes are examined by discrimination of daily activity from nocturnal rest. Investigations consider normal sinus rhythms of healthy 39 subjects which are grouped in two sets: 5-hour wake series and 5-hour sleep series. Qualitative arguments are provided to conjecture the presence of stochastic persistence in LF range, loss of heart rate variability during night in VLF range and its increase in ULF. |
2005.11545 | Behnam Najafi | Behnam Najafi, Katherine G. Young, Jonathan Bath, Ard A. Louis,
Jonathan P. K. Doye, Andrew J. Turberfield | Characterising DNA T-motifs by Simulation and Experiment | 8 pages; 8 figures | null | null | null | q-bio.BM physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The success of DNA nanotechnology has been driven by the discovery of novel
structural motifs with a wide range of shapes and uses. We present a
comprehensive study of the T-motif, a 3-armed, planar, right-angled junction
that has been used in the self-assembly of DNA polyhedra and periodic
structures. The motif is formed through the interaction of a bulge loop in one
duplex and a sticky end of another. The polarity of the sticky end has
significant consequences for the thermodynamic and geometrical properties of
the T-motif: different polarities create junctions spanning different grooves
of the duplex. We compare experimental binding strengths with predictions of
oxDNA, a coarse-grained model of DNA, for various loop sizes. We find that,
although both sticky-end polarities can create stable junctions, junctions
resulting from 5$'$ sticky ends are stable over a wider range of bulge loop
sizes. We highlight the importance of possible coaxial stacking interactions
within the motif and investigate how each coaxial stacking interaction
stabilises the structure and favours a particular geometry.
| [
{
"created": "Sat, 23 May 2020 14:44:25 GMT",
"version": "v1"
}
] | 2020-05-26 | [
[
"Najafi",
"Behnam",
""
],
[
"Young",
"Katherine G.",
""
],
[
"Bath",
"Jonathan",
""
],
[
"Louis",
"Ard A.",
""
],
[
"Doye",
"Jonathan P. K.",
""
],
[
"Turberfield",
"Andrew J.",
""
]
] | The success of DNA nanotechnology has been driven by the discovery of novel structural motifs with a wide range of shapes and uses. We present a comprehensive study of the T-motif, a 3-armed, planar, right-angled junction that has been used in the self-assembly of DNA polyhedra and periodic structures. The motif is formed through the interaction of a bulge loop in one duplex and a sticky end of another. The polarity of the sticky end has significant consequences for the thermodynamic and geometrical properties of the T-motif: different polarities create junctions spanning different grooves of the duplex. We compare experimental binding strengths with predictions of oxDNA, a coarse-grained model of DNA, for various loop sizes. We find that, although both sticky-end polarities can create stable junctions, junctions resulting from 5$'$ sticky ends are stable over a wider range of bulge loop sizes. We highlight the importance of possible coaxial stacking interactions within the motif and investigate how each coaxial stacking interaction stabilises the structure and favours a particular geometry. |
0809.3639 | Vladimir Ivancevic | Vladimir G. Ivancevic and Tijana T. Ivancevic | $\infty-$Dimensional Cerebellar Controller for Realistic Human
Biodynamics | 28 pages, 6 figures, Latex | null | null | null | q-bio.NC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper we propose an $\infty-$dimensional cerebellar model of neural
controller for realistic human biodynamics. The model is developed using
Feynman's action-amplitude (partition function) formalism. The cerebellum
controller is acting as a supervisor for an autogenetic servo control of human
musculo-skeletal dynamics, which is presented in (dissipative, driven)
Hamiltonian form. The $\infty-$dimensional cerebellar controller is closely
related to entropic motor control.
Keywords: realistic human biodynamics, cerebellum motion control,
$\infty-$dimensional neural network
| [
{
"created": "Mon, 22 Sep 2008 07:06:43 GMT",
"version": "v1"
},
{
"created": "Wed, 24 Sep 2008 03:58:34 GMT",
"version": "v2"
},
{
"created": "Mon, 29 Sep 2008 12:23:33 GMT",
"version": "v3"
}
] | 2008-09-29 | [
[
"Ivancevic",
"Vladimir G.",
""
],
[
"Ivancevic",
"Tijana T.",
""
]
] | In this paper we propose an $\infty-$dimensional cerebellar model of neural controller for realistic human biodynamics. The model is developed using Feynman's action-amplitude (partition function) formalism. The cerebellum controller is acting as a supervisor for an autogenetic servo control of human musculo-skeletal dynamics, which is presented in (dissipative, driven) Hamiltonian form. The $\infty-$dimensional cerebellar controller is closely related to entropic motor control. Keywords: realistic human biodynamics, cerebellum motion control, $\infty-$dimensional neural network |
2107.07760 | Korabel | Nickolay Korabel, Daniel Han, Alessandro Taloni, Gianni Pagnini,
Sergei Fedotov, Viki Allan and Thomas Andrew Waigh | Unravelling Heterogeneous Transport of Endosomes | 17 pages, 8 figures | null | null | null | q-bio.SC cond-mat.soft | http://creativecommons.org/licenses/by/4.0/ | A major open problem in biophysics is to understand the highly heterogeneous
transport of many structures inside living cells, such as endosomes. We find
that mathematically it is described by spatio-temporal heterogeneous fractional
Brownian motion (hFBM) which is defined as FBM with a randomly switching
anomalous exponent and random generalized diffusion coefficient. Using a
comprehensive local analysis of a large ensemble of experimental endosome
trajectories (> 10^5), we show that their motion is characterized by power-law
probability distributions of displacements and displacement increments,
exponential probability distributions of local anomalous exponents and
power-law probability distributions of local generalized diffusion coefficients
of endosomes which are crucial ingredients of spatio-temporal hFBM. The
increased sensitivity of deep learning neural networks for FBM characterisation
corroborates the development of this multi-fractal analysis. Our findings are
an important step in understanding endosome transport. We also provide a
powerful tool for studying other heterogeneous cellular processes.
| [
{
"created": "Fri, 16 Jul 2021 08:30:34 GMT",
"version": "v1"
}
] | 2021-07-20 | [
[
"Korabel",
"Nickolay",
""
],
[
"Han",
"Daniel",
""
],
[
"Taloni",
"Alessandro",
""
],
[
"Pagnini",
"Gianni",
""
],
[
"Fedotov",
"Sergei",
""
],
[
"Allan",
"Viki",
""
],
[
"Waigh",
"Thomas Andrew",
""
]
] | A major open problem in biophysics is to understand the highly heterogeneous transport of many structures inside living cells, such as endosomes. We find that mathematically it is described by spatio-temporal heterogeneous fractional Brownian motion (hFBM) which is defined as FBM with a randomly switching anomalous exponent and random generalized diffusion coefficient. Using a comprehensive local analysis of a large ensemble of experimental endosome trajectories (> 10^5), we show that their motion is characterized by power-law probability distributions of displacements and displacement increments, exponential probability distributions of local anomalous exponents and power-law probability distributions of local generalized diffusion coefficients of endosomes which are crucial ingredients of spatio-temporal hFBM. The increased sensitivity of deep learning neural networks for FBM characterisation corroborates the development of this multi-fractal analysis. Our findings are an important step in understanding endosome transport. We also provide a powerful tool for studying other heterogeneous cellular processes. |
1505.04846 | Atefeh Taherian Fard | Atefeh Taherian Fard, Sriganesh Srihari and Mark A. Ragan | An evaluation of DNA-damage response and cell-cycle pathways for breast
cancer classification | 28 pages, 7 figures, 6 tables | null | 10.1093/bib/bbu020 | null | q-bio.QM q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Accurate subtyping or classification of breast cancer is important for
ensuring proper treatment of patients and also for understanding the molecular
mechanisms driving this disease. While there have been several gene signatures
proposed in the literature to classify breast tumours, these signatures show
very low overlaps, different classification performance, and not much relevance
to the underlying biology of these tumours. Here we evaluate DNA-damage
response (DDR) and cell cycle pathways, which are critical pathways implicated
in a considerable proportion of breast tumours, for their usefulness and
ability in breast tumour subtyping. We think that subtyping breast tumours
based on these two pathways could lead to vital insights into molecular
mechanisms driving these tumours. Here, we performed a systematic evaluation of
DDR and cell-cycle pathways for subtyping of breast tumours into the five known
intrinsic subtypes. Homologous Recombination (HR) pathway showed the best
performance in subtyping breast tumours, indicating that HR genes are strongly
involved in all breast tumours. Comparisons of pathway based signatures and two
standard gene signatures supported the use of known pathways for breast tumour
subtyping. Further, the evaluation of these standard gene signatures showed
that breast tumour subtyping, prognosis and survival estimation are all closely
related. Finally, we constructed an all-inclusive super-signature by combining
(union of) all genes and performing a stringent feature selection, and found it
to be reasonably accurate and robust in classification as well as prognostic
value. Adopting DDR and cell cycle pathways for breast tumour subtyping
achieved robust and accurate breast tumour subtyping, and constructing a
super-signature which contains feature selected mix of genes from these
molecular pathways as well as clinical aspects is valuable in clinical
practice.
| [
{
"created": "Tue, 19 May 2015 01:17:31 GMT",
"version": "v1"
}
] | 2015-05-20 | [
[
"Fard",
"Atefeh Taherian",
""
],
[
"Srihari",
"Sriganesh",
""
],
[
"Ragan",
"Mark A.",
""
]
] | Accurate subtyping or classification of breast cancer is important for ensuring proper treatment of patients and also for understanding the molecular mechanisms driving this disease. While there have been several gene signatures proposed in the literature to classify breast tumours, these signatures show very low overlaps, different classification performance, and not much relevance to the underlying biology of these tumours. Here we evaluate DNA-damage response (DDR) and cell cycle pathways, which are critical pathways implicated in a considerable proportion of breast tumours, for their usefulness and ability in breast tumour subtyping. We think that subtyping breast tumours based on these two pathways could lead to vital insights into molecular mechanisms driving these tumours. Here, we performed a systematic evaluation of DDR and cell-cycle pathways for subtyping of breast tumours into the five known intrinsic subtypes. Homologous Recombination (HR) pathway showed the best performance in subtyping breast tumours, indicating that HR genes are strongly involved in all breast tumours. Comparisons of pathway based signatures and two standard gene signatures supported the use of known pathways for breast tumour subtyping. Further, the evaluation of these standard gene signatures showed that breast tumour subtyping, prognosis and survival estimation are all closely related. Finally, we constructed an all-inclusive super-signature by combining (union of) all genes and performing a stringent feature selection, and found it to be reasonably accurate and robust in classification as well as prognostic value. Adopting DDR and cell cycle pathways for breast tumour subtyping achieved robust and accurate breast tumour subtyping, and constructing a super-signature which contains feature selected mix of genes from these molecular pathways as well as clinical aspects is valuable in clinical practice. |
2211.02523 | Ximena Fern\'andez | Ximena Fern\'andez and Diego Mateos | Topological biomarkers for real-time detection of epileptic seizures | 27 pages, 12 figures. Global restructuring of the paper. New
experiments with further datasets across different seizures of the same
patients | null | null | null | q-bio.QM math.AT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Real time seizure detection is a fundamental problem in computational
neuroscience towards diagnosis and treatment's improvement of epileptic
disease. We propose a real-time computational method for tracking and detection
of epileptic seizures from raw neurophysiological recordings. Our mechanism is
based on the topological analysis of the sliding-window embedding of the time
series derived from simultaneously recorded channels. We extract topological
biomarkers from the signals via the computation of the persistent homology of
time-evolving topological spaces. Remarkably, the proposed biomarkers robustly
captures the change in the brain dynamics during the ictal state. We apply our
methods in different types of signals including scalp and intracranial
electroencephalograms and magnetoencephalograms, in patients during interictal
and ictal states, showing high accuracy in a range of clinical situations.
| [
{
"created": "Fri, 4 Nov 2022 15:30:47 GMT",
"version": "v1"
},
{
"created": "Fri, 14 Jun 2024 11:00:30 GMT",
"version": "v2"
}
] | 2024-06-17 | [
[
"Fernández",
"Ximena",
""
],
[
"Mateos",
"Diego",
""
]
] | Real time seizure detection is a fundamental problem in computational neuroscience towards diagnosis and treatment's improvement of epileptic disease. We propose a real-time computational method for tracking and detection of epileptic seizures from raw neurophysiological recordings. Our mechanism is based on the topological analysis of the sliding-window embedding of the time series derived from simultaneously recorded channels. We extract topological biomarkers from the signals via the computation of the persistent homology of time-evolving topological spaces. Remarkably, the proposed biomarkers robustly captures the change in the brain dynamics during the ictal state. We apply our methods in different types of signals including scalp and intracranial electroencephalograms and magnetoencephalograms, in patients during interictal and ictal states, showing high accuracy in a range of clinical situations. |
1211.7307 | Mike Steel Prof. | Mike Steel, Simone Linz, Daniel H. Huson and Michael J. Sanderson | Identifying a species tree subject to random lateral gene transfer | 19 pages, 9 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A major problem for inferring species trees from gene trees is that
evolutionary processes can sometimes favour gene tree topologies that conflict
with an underlying species tree. In the case of incomplete lineage sorting,
this phenomenon has recently been well-studied, and some elegant solutions for
species tree reconstruction have been proposed. One particularly simple and
statistically consistent estimator of the species tree under incomplete lineage
sorting is to combine three-taxon analyses, which are phylogenetically robust
to incomplete lineage sorting. In this paper, we consider whether such an
approach will also work under lateral gene transfer (LGT). By providing an
exact analysis of some cases of this model, we show that there is a zone of
inconsistency for triplet-based species tree reconstruction under LGT. However,
a triplet-based approach will consistently reconstruct a species tree under
models of LGT, provided that the expected number of LGT transfers is not too
high. Our analysis involves a novel connection between the LGT problem and
random walks on cyclic graphs. We have implemented a procedure for
reconstructing trees subject to LGT or lineage sorting in settings where taxon
coverage may be patchy and illustrate its use on two sample data sets.
| [
{
"created": "Fri, 30 Nov 2012 16:39:58 GMT",
"version": "v1"
}
] | 2012-12-03 | [
[
"Steel",
"Mike",
""
],
[
"Linz",
"Simone",
""
],
[
"Huson",
"Daniel H.",
""
],
[
"Sanderson",
"Michael J.",
""
]
] | A major problem for inferring species trees from gene trees is that evolutionary processes can sometimes favour gene tree topologies that conflict with an underlying species tree. In the case of incomplete lineage sorting, this phenomenon has recently been well-studied, and some elegant solutions for species tree reconstruction have been proposed. One particularly simple and statistically consistent estimator of the species tree under incomplete lineage sorting is to combine three-taxon analyses, which are phylogenetically robust to incomplete lineage sorting. In this paper, we consider whether such an approach will also work under lateral gene transfer (LGT). By providing an exact analysis of some cases of this model, we show that there is a zone of inconsistency for triplet-based species tree reconstruction under LGT. However, a triplet-based approach will consistently reconstruct a species tree under models of LGT, provided that the expected number of LGT transfers is not too high. Our analysis involves a novel connection between the LGT problem and random walks on cyclic graphs. We have implemented a procedure for reconstructing trees subject to LGT or lineage sorting in settings where taxon coverage may be patchy and illustrate its use on two sample data sets. |
2208.06355 | Swarnavo Sarkar | Swarnavo Sarkar | Communication network model of the immune system identifies the impact
of interactions with SARS-CoV-2 proteins | 14 pages, 4 figures; Code: https://github.com/sarkar-s/core | null | null | null | q-bio.MN cs.IT math.IT | http://creativecommons.org/licenses/by/4.0/ | Interactions between SARS-CoV-2 and human proteins (SARS-CoV-2 PPIs) cause
information transfer through biochemical pathways that contribute to the
immunopathology of COVID-19. Here, we present a communication network model of
the immune system to compute the information transferred by the viral proteins
using the available SARS-CoV-2 PPIs data. The amount of transferred information
depends on the reference state of the immune system, or the state without
SARS-CoV-2 PPIs, and can quantify how many variables of the immune system are
controlled by the viral proteins. The information received by the immune system
proteins from the viral proteins is useful to identify the biological processes
(BPs) susceptible to dysregulation, and also to estimate the duration of viral
PPIs necessary for the dysregulation to occur. We found that computing the drop
in information from viral PPIs due to drugs provides a direct measure for the
efficacy of therapies.
| [
{
"created": "Fri, 12 Aug 2022 16:19:44 GMT",
"version": "v1"
}
] | 2022-08-15 | [
[
"Sarkar",
"Swarnavo",
""
]
] | Interactions between SARS-CoV-2 and human proteins (SARS-CoV-2 PPIs) cause information transfer through biochemical pathways that contribute to the immunopathology of COVID-19. Here, we present a communication network model of the immune system to compute the information transferred by the viral proteins using the available SARS-CoV-2 PPIs data. The amount of transferred information depends on the reference state of the immune system, or the state without SARS-CoV-2 PPIs, and can quantify how many variables of the immune system are controlled by the viral proteins. The information received by the immune system proteins from the viral proteins is useful to identify the biological processes (BPs) susceptible to dysregulation, and also to estimate the duration of viral PPIs necessary for the dysregulation to occur. We found that computing the drop in information from viral PPIs due to drugs provides a direct measure for the efficacy of therapies. |
1504.00413 | Nilima Nigam | Hadi Rahemi, Nilima Nigam and James M. Wakeling | Structural Changes of Active Skeletal Muscles: Modelling, Validation and
Numerical Experiments | null | null | null | null | q-bio.QM q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The purpose of this study was to report numerical validation of a 3D finite
element model of contracting muscle. The model was based on continuum theory
for fibre-reinforced composite materials. Here we simulated contractions for an
idealized medial gastrocnemius muscle in man, using the model. Simulations were
performed to test the force-length relation of the whole muscle, to evaluate
the changes in internal fascicle geometry during contractions, and to assess
the importance of material formulations for the aponeurosis and tendon. The
simulation results were compared to previously published experimental values.
The force-length profile for the whole muscle showed a realistic profile. As
the muscle contracted the fascicles curved into S-shaped trajectories and
curled around 3D paths, both of which matched previous experimental findings.
As the fascicles shortened they increased in their cross-sectional area, but
this increase was asymmetric with the smaller increase occurring within the
fascicle-plane: the Poisson's ratio in this plane matched that previously shown
from ultrasound imaging. The distribution of strains in the aponeurosis and
tendon was shown to be a function of their material properties. This study
demonstrated that the model could replicate realistic patterns of whole
muscle-force, and changes to the internal muscle geometry, and so will be
useful for testing mechanisms that affect the structural changes within
contracting muscle.
| [
{
"created": "Wed, 1 Apr 2015 23:16:09 GMT",
"version": "v1"
}
] | 2015-04-03 | [
[
"Rahemi",
"Hadi",
""
],
[
"Nigam",
"Nilima",
""
],
[
"Wakeling",
"James M.",
""
]
] | The purpose of this study was to report numerical validation of a 3D finite element model of contracting muscle. The model was based on continuum theory for fibre-reinforced composite materials. Here we simulated contractions for an idealized medial gastrocnemius muscle in man, using the model. Simulations were performed to test the force-length relation of the whole muscle, to evaluate the changes in internal fascicle geometry during contractions, and to assess the importance of material formulations for the aponeurosis and tendon. The simulation results were compared to previously published experimental values. The force-length profile for the whole muscle showed a realistic profile. As the muscle contracted the fascicles curved into S-shaped trajectories and curled around 3D paths, both of which matched previous experimental findings. As the fascicles shortened they increased in their cross-sectional area, but this increase was asymmetric with the smaller increase occurring within the fascicle-plane: the Poisson's ratio in this plane matched that previously shown from ultrasound imaging. The distribution of strains in the aponeurosis and tendon was shown to be a function of their material properties. This study demonstrated that the model could replicate realistic patterns of whole muscle-force, and changes to the internal muscle geometry, and so will be useful for testing mechanisms that affect the structural changes within contracting muscle. |
1911.10316 | Peiran Jiang | Peiran Jiang, Shujun Huang, Zhenyuan Fu, Zexuan Sun, Ted M. Lakowski,
Pingzhao Hu | Deep graph embedding for prioritizing synergistic anticancer drug
combinations | null | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Drug combinations are frequently used for the treatment of cancer patients in
order to increase efficacy, decrease adverse side effects, or overcome drug
resistance. Given the enormous number of drug combinations, it is cost- and
time-consuming to screen all possible drug pairs experimentally. Currently, it
has not been fully explored to integrate multiple networks to predict
synergistic drug combinations using recently developed deep learning
technologies. In this study, we proposed a Graph Convolutional Network (GCN)
model to predict synergistic drug combinations in particular cancer cell lines.
Specifically, the GCN method used a convolutional neural network model to do
heterogeneous graph embedding, and thus solved a link prediction task. The
graph in this study was a multimodal graph, which was constructed by
integrating the drug-drug combination, drug-protein interaction, and
protein-protein interaction networks. We found that the GCN model was able to
correctly predict cell line-specific synergistic drug combinations from a large
heterogonous network. The majority (30) of the 39 cell line-specific models
show an area under the receiver operational characteristic curve (AUC) larger
than 0.80, resulting in a mean AUC of 0.84. Moreover, we conducted an in-depth
literature survey to investigate the top predicted drug combinations in
specific cancer cell lines and found that many of them have been found to show
synergistic antitumor activity against the same or other cancers in vitro or in
vivo. Taken together, the results indicate that our study provides a promising
way to better predict and optimize synergistic drug pairs in silico.
| [
{
"created": "Sat, 23 Nov 2019 06:21:47 GMT",
"version": "v1"
}
] | 2021-02-18 | [
[
"Jiang",
"Peiran",
""
],
[
"Huang",
"Shujun",
""
],
[
"Fu",
"Zhenyuan",
""
],
[
"Sun",
"Zexuan",
""
],
[
"Lakowski",
"Ted M.",
""
],
[
"Hu",
"Pingzhao",
""
]
] | Drug combinations are frequently used for the treatment of cancer patients in order to increase efficacy, decrease adverse side effects, or overcome drug resistance. Given the enormous number of drug combinations, it is cost- and time-consuming to screen all possible drug pairs experimentally. Currently, it has not been fully explored to integrate multiple networks to predict synergistic drug combinations using recently developed deep learning technologies. In this study, we proposed a Graph Convolutional Network (GCN) model to predict synergistic drug combinations in particular cancer cell lines. Specifically, the GCN method used a convolutional neural network model to do heterogeneous graph embedding, and thus solved a link prediction task. The graph in this study was a multimodal graph, which was constructed by integrating the drug-drug combination, drug-protein interaction, and protein-protein interaction networks. We found that the GCN model was able to correctly predict cell line-specific synergistic drug combinations from a large heterogonous network. The majority (30) of the 39 cell line-specific models show an area under the receiver operational characteristic curve (AUC) larger than 0.80, resulting in a mean AUC of 0.84. Moreover, we conducted an in-depth literature survey to investigate the top predicted drug combinations in specific cancer cell lines and found that many of them have been found to show synergistic antitumor activity against the same or other cancers in vitro or in vivo. Taken together, the results indicate that our study provides a promising way to better predict and optimize synergistic drug pairs in silico. |
1001.4177 | C T J Dodson | C.T.J. Dodson | An inhomogeneous stochastic rate process for evolution from states in an
information geometric neighbourhood of uniform fitness | 9 pages, 11 figures, 9 references | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This study elaborates some examples of a simple evolutionary stochastic rate
process where the population rate of change depends on the distribution of
properties--so different cohorts change at different rates. We investigate the
effect on the evolution arising from parametrized perturbations of uniformity
for the initial inhomogeneity. The information geometric neighbourhood system
yields also solutions for a wide range of other initial inhomogeneity
distributions, including approximations to truncated Gaussians of arbitrarily
small variance and distributions with pronounced extreme values. It is found
that, under quite considerable alterations in the shape and variance of the
initial distribution of inhomogeneity in unfitness, the decline of the mean
does change markedly with the variation in starting conditions, but the net
population evolution seems surprisingly stable.
| [
{
"created": "Sat, 23 Jan 2010 17:22:37 GMT",
"version": "v1"
}
] | 2010-01-26 | [
[
"Dodson",
"C. T. J.",
""
]
] | This study elaborates some examples of a simple evolutionary stochastic rate process where the population rate of change depends on the distribution of properties--so different cohorts change at different rates. We investigate the effect on the evolution arising from parametrized perturbations of uniformity for the initial inhomogeneity. The information geometric neighbourhood system yields also solutions for a wide range of other initial inhomogeneity distributions, including approximations to truncated Gaussians of arbitrarily small variance and distributions with pronounced extreme values. It is found that, under quite considerable alterations in the shape and variance of the initial distribution of inhomogeneity in unfitness, the decline of the mean does change markedly with the variation in starting conditions, but the net population evolution seems surprisingly stable. |
1107.5853 | Fabio Pichierri | Fabio Pichierri | Quantum Proteomics | 12 pages, 3 figures, 1 table | null | null | null | q-bio.BM q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We put forward the idea of establishing a novel interdisciplinary field of
research at the interface between quantum mechanics and proteomics. The new
field, called quantum proteomics, is defined as the large-scale study of the
electronic structure of the proteins that define an organism's proteome. The
electronic structure of proteins is unveiled with the aid of linear-scaling
quantum mechanical calculations. Such calculations provide information about
the energy levels of the proteins, the charges of their amino acid side chains,
their electrostatic potentials and permanent dipole moments ({\mu}). Since the
magnitude of the electric dipole moment of any protein is not null ({\mu}\neq0
Debye), the dipole moment can be employed to characterize the electronic
structure of each protein that belongs to an organism's proteome. As an
example, we investigate six proteins from the thermophilic bacterium
Methanobacterium thermoautotrophicum (Mth) whose atomic structures were
characterized by solution NMR spectroscopy.
| [
{
"created": "Fri, 29 Jul 2011 01:25:47 GMT",
"version": "v1"
}
] | 2011-08-01 | [
[
"Pichierri",
"Fabio",
""
]
] | We put forward the idea of establishing a novel interdisciplinary field of research at the interface between quantum mechanics and proteomics. The new field, called quantum proteomics, is defined as the large-scale study of the electronic structure of the proteins that define an organism's proteome. The electronic structure of proteins is unveiled with the aid of linear-scaling quantum mechanical calculations. Such calculations provide information about the energy levels of the proteins, the charges of their amino acid side chains, their electrostatic potentials and permanent dipole moments ({\mu}). Since the magnitude of the electric dipole moment of any protein is not null ({\mu}\neq0 Debye), the dipole moment can be employed to characterize the electronic structure of each protein that belongs to an organism's proteome. As an example, we investigate six proteins from the thermophilic bacterium Methanobacterium thermoautotrophicum (Mth) whose atomic structures were characterized by solution NMR spectroscopy. |
1510.07592 | Andrew Sornborger | Zhou Wang, Andrew T Sornborger, Louis Tao | Graded, Dynamically Routable Information Processing with Synfire-Gated
Synfire Chains | null | null | 10.1371/journal.pcbi.1004979 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Coherent neural spiking and local field potentials are believed to be
signatures of the binding and transfer of information in the brain. Coherent
activity has now been measured experimentally in many regions of mammalian
cortex. Synfire chains are one of the main theoretical constructs that have
been appealed to to describe coherent spiking phenomena. However, for some
time, it has been known that synchronous activity in feedforward networks
asymptotically either approaches an attractor with fixed waveform and
amplitude, or fails to propagate. This has limited their ability to explain
graded neuronal responses. Recently, we have shown that pulse-gated synfire
chains are capable of propagating graded information coded in mean population
current or firing rate amplitudes. In particular, we showed that it is possible
to use one synfire chain to provide gating pulses and a second, pulse-gated
synfire chain to propagate graded information. We called these circuits
synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded
information can rapidly cascade through a neural circuit, and show a
correspondence between this type of transfer and a mean-field model in which
gating pulses overlap in time. We show that SGSCs are robust in the presence of
variability in population size, pulse timing and synaptic strength. Finally, we
demonstrate the computational capabilities of SGSC-based information coding by
implementing a self-contained, spike-based, modular neural circuit that is
triggered by, then reads in streaming input, processes the input, then makes a
decision based on the processed information and shuts itself down.
| [
{
"created": "Mon, 26 Oct 2015 18:46:05 GMT",
"version": "v1"
}
] | 2016-09-28 | [
[
"Wang",
"Zhou",
""
],
[
"Sornborger",
"Andrew T",
""
],
[
"Tao",
"Louis",
""
]
] | Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Synfire chains are one of the main theoretical constructs that have been appealed to to describe coherent spiking phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited their ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by, then reads in streaming input, processes the input, then makes a decision based on the processed information and shuts itself down. |
2104.10962 | Mar\'ia Vallet-Regi | Preethi Balasubramanian, Antonio J. Salinas, Sandra Sanchez-Salcedo,
Rainer Detsch, Maria Vallet-Regi, Aldo R. Boccaccini | Induction of VEGF secretion from bone marrow stromal cell line (ST-2) by
the dissolution products of mesoporous silica glass particles containing CuO
and SrO | 21 pages, 7 figures | J. Non-cryst. Solids. 500, 217-224 (2018) | 10.1016/j.jnoncrysol.2018.07.073 | null | q-bio.TO | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Certain biomaterials are capable of inducing the secretion of Vascular
Endothelial Growth Factor (VEGF) from cells exposed to their biochemical
influence, which plays a vital role in stimulating angiogenesis. Looking for
this capacity, in this study three porous glasses were synthesized and
characterized. The objective of this study was to determine the concentration
of the glass particles that, being out of the cytotoxic range, could increase
VEGF secretion. The viability of cultivated bone marrow stromal cells (ST-2)
was assessed. The samples were examined with light microscopy (LM) after the
histochemical staining for haematoxylin and eosin (HE). The biological activity
of glasses was evaluated in terms of the influence of the Cu2+ and Sr2+ ions on
the cells. The dissolution products of CuSr-1 and CuSr-2.5 produced the highest
secretion of VEGF from ST-2 cells after 48 h of incubation. The combination of
Cu2+ and Sr2+ lays the foundation for engineering a bioactive glass than can
lead to vascularized, functional bone tissue when used in bone regeneration
applications.
| [
{
"created": "Thu, 22 Apr 2021 09:46:16 GMT",
"version": "v1"
}
] | 2021-04-23 | [
[
"Balasubramanian",
"Preethi",
""
],
[
"Salinas",
"Antonio J.",
""
],
[
"Sanchez-Salcedo",
"Sandra",
""
],
[
"Detsch",
"Rainer",
""
],
[
"Vallet-Regi",
"Maria",
""
],
[
"Boccaccini",
"Aldo R.",
""
]
] | Certain biomaterials are capable of inducing the secretion of Vascular Endothelial Growth Factor (VEGF) from cells exposed to their biochemical influence, which plays a vital role in stimulating angiogenesis. Looking for this capacity, in this study three porous glasses were synthesized and characterized. The objective of this study was to determine the concentration of the glass particles that, being out of the cytotoxic range, could increase VEGF secretion. The viability of cultivated bone marrow stromal cells (ST-2) was assessed. The samples were examined with light microscopy (LM) after the histochemical staining for haematoxylin and eosin (HE). The biological activity of glasses was evaluated in terms of the influence of the Cu2+ and Sr2+ ions on the cells. The dissolution products of CuSr-1 and CuSr-2.5 produced the highest secretion of VEGF from ST-2 cells after 48 h of incubation. The combination of Cu2+ and Sr2+ lays the foundation for engineering a bioactive glass than can lead to vascularized, functional bone tissue when used in bone regeneration applications. |
2006.11955 | Nitish Nag | Daniel B. Azzam, Nitish Nag, Julia Tran, Lauren Chen, Kaajal Visnagra,
Kailey Marshall, Matthew Wade | A Novel Epidemiological Approach to Geographically Mapping Population
Dry Eye Disease in the United States through Google Trends | American Society of Cataract and Refractive Surgery Meeting. Boston,
Massachusetts. May 18, 2020. Podium | null | null | null | q-bio.PE cs.IR | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dry eye disease (DED) affects approximately half of the United States
population. DED is characterized by dryness on the corena surface due to a
variety of causes. This study fills the spatiotemporal gaps in DED epidemiology
by using Google Trends as a novel epidemiological tool for geographically
mapping DED in relation to environmental risk factors. We utilized Google
Trends to extract DED-related queries estimating user intent from 2004-2019 in
the United States. We incorporated national climate data to generate heat maps
comparing geographic, temporal, and environmental relationships of DED.
Multi-variable regression models were constructed to generate quadratic
forecasts predicting DED and control searches. Our results illustrated the
upward trend, seasonal pattern, environmental influence, and spatial
relationship of DED search volume across US geography. Localized patches of DED
interest were visualized along the coastline. There was no significant
difference in DED queries across US census regions. Regression model 1
predicted DED searches over time (R^2=0.97) with significant predictors being
control queries (p=0.0024), time (p=0.001), and seasonality (Winter p=0.0028;
Spring p<0.001; Summer p=0.018). Regression model 2 predicted DED queries per
state (R^2=0.49) with significant predictors being temperature (p=0.0003) and
coastal zone (p=0.025). Importantly, temperature, coastal status, and
seasonality were stronger risk factors of DED searches than humidity, sunshine,
pollution, or region as clinical literature may suggest. Our work paves the way
for future exploration of geographic information systems for locating DED and
other diseases via online search query metrics.
| [
{
"created": "Mon, 22 Jun 2020 00:56:05 GMT",
"version": "v1"
}
] | 2020-06-23 | [
[
"Azzam",
"Daniel B.",
""
],
[
"Nag",
"Nitish",
""
],
[
"Tran",
"Julia",
""
],
[
"Chen",
"Lauren",
""
],
[
"Visnagra",
"Kaajal",
""
],
[
"Marshall",
"Kailey",
""
],
[
"Wade",
"Matthew",
""
]
] | Dry eye disease (DED) affects approximately half of the United States population. DED is characterized by dryness on the corena surface due to a variety of causes. This study fills the spatiotemporal gaps in DED epidemiology by using Google Trends as a novel epidemiological tool for geographically mapping DED in relation to environmental risk factors. We utilized Google Trends to extract DED-related queries estimating user intent from 2004-2019 in the United States. We incorporated national climate data to generate heat maps comparing geographic, temporal, and environmental relationships of DED. Multi-variable regression models were constructed to generate quadratic forecasts predicting DED and control searches. Our results illustrated the upward trend, seasonal pattern, environmental influence, and spatial relationship of DED search volume across US geography. Localized patches of DED interest were visualized along the coastline. There was no significant difference in DED queries across US census regions. Regression model 1 predicted DED searches over time (R^2=0.97) with significant predictors being control queries (p=0.0024), time (p=0.001), and seasonality (Winter p=0.0028; Spring p<0.001; Summer p=0.018). Regression model 2 predicted DED queries per state (R^2=0.49) with significant predictors being temperature (p=0.0003) and coastal zone (p=0.025). Importantly, temperature, coastal status, and seasonality were stronger risk factors of DED searches than humidity, sunshine, pollution, or region as clinical literature may suggest. Our work paves the way for future exploration of geographic information systems for locating DED and other diseases via online search query metrics. |
2407.20116 | Belinda Neo | Belinda Neo, Noel Nannup, Dale Tilbrook, Eleanor Dunlop, John Jacky,
Carol Michie, Cindy Prior, Brad Farrant, Carrington C.J. Shepherd and Lucinda
J. Black | Modelling vitamin D food fortification among Aboriginal and Torres
Strait Islander peoples in Australia | null | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background: Low vitamin D intake and high prevalence of vitamin D deficiency
(serum 25-hydroxyvitamin D concentration < 50 nmol/L) among Aboriginal and
Torres Strait Islander peoples highlight a need for public health strategies to
improve vitamin D status. As few foods contain naturally occurring vitamin D,
fortification strategies may be needed to improve vitamin D intake and status
among Aboriginal and Torres Strait Islander peoples. Objective: We aimed to
model vitamin D food fortification scenarios among Aboriginal and Torres Strait
Islander peoples. Methods: We used nationally representative food consumption
data (n=4,109) and vitamin D food composition data to model four food
fortification scenarios. The modelling for Scenario 1 included foods and
maximum vitamin D concentrations permitted for fortification in Australia: i)
dairy products and alternatives, ii) butter/margarine/oil spreads, iii)
formulated beverages, and iv) selected ready-to-eat breakfast cereals. The
modelling for Scenarios 2a-c included some vitamin D concentrations higher than
permitted in Australia; Scenario 2c included bread, which is not permitted for
vitamin D fortification in Australia. Scenario 2a: i) dairy products and
alternatives, ii) butter/margarine/oil spreads, iii) formulated beverages.
Scenario 2b: as per Scenario 2a plus selected ready-to-eat breakfast cereals.
Scenario 2c: as per Scenario 2b plus bread. Results: Vitamin D fortification of
a range of staple foods could potentially increase vitamin D intake among
Aboriginal and Torres Strait Islander peoples by ~ 3-6 {\mu}g/day. Scenario 2c
showed the highest potential median vitamin D intake increase to ~ 8
{\mu}g/day. Across all modelled scenarios, none of the participants had vitamin
D intake above the Australian upper level of intake of 80 {\mu}g/day.
| [
{
"created": "Mon, 29 Jul 2024 15:47:00 GMT",
"version": "v1"
},
{
"created": "Tue, 30 Jul 2024 02:07:41 GMT",
"version": "v2"
}
] | 2024-07-31 | [
[
"Neo",
"Belinda",
""
],
[
"Nannup",
"Noel",
""
],
[
"Tilbrook",
"Dale",
""
],
[
"Dunlop",
"Eleanor",
""
],
[
"Jacky",
"John",
""
],
[
"Michie",
"Carol",
""
],
[
"Prior",
"Cindy",
""
],
[
"Farrant",
"Brad",
""
],
[
"Shepherd",
"Carrington C. J.",
""
],
[
"Black",
"Lucinda J.",
""
]
] | Background: Low vitamin D intake and high prevalence of vitamin D deficiency (serum 25-hydroxyvitamin D concentration < 50 nmol/L) among Aboriginal and Torres Strait Islander peoples highlight a need for public health strategies to improve vitamin D status. As few foods contain naturally occurring vitamin D, fortification strategies may be needed to improve vitamin D intake and status among Aboriginal and Torres Strait Islander peoples. Objective: We aimed to model vitamin D food fortification scenarios among Aboriginal and Torres Strait Islander peoples. Methods: We used nationally representative food consumption data (n=4,109) and vitamin D food composition data to model four food fortification scenarios. The modelling for Scenario 1 included foods and maximum vitamin D concentrations permitted for fortification in Australia: i) dairy products and alternatives, ii) butter/margarine/oil spreads, iii) formulated beverages, and iv) selected ready-to-eat breakfast cereals. The modelling for Scenarios 2a-c included some vitamin D concentrations higher than permitted in Australia; Scenario 2c included bread, which is not permitted for vitamin D fortification in Australia. Scenario 2a: i) dairy products and alternatives, ii) butter/margarine/oil spreads, iii) formulated beverages. Scenario 2b: as per Scenario 2a plus selected ready-to-eat breakfast cereals. Scenario 2c: as per Scenario 2b plus bread. Results: Vitamin D fortification of a range of staple foods could potentially increase vitamin D intake among Aboriginal and Torres Strait Islander peoples by ~ 3-6 {\mu}g/day. Scenario 2c showed the highest potential median vitamin D intake increase to ~ 8 {\mu}g/day. Across all modelled scenarios, none of the participants had vitamin D intake above the Australian upper level of intake of 80 {\mu}g/day. |
1910.07451 | Jan Karbowski | Jan Karbowski | Deciphering neural circuits for Caenorhabditis elegans behavior by
computations and perturbations to genome and connectome | Systems Biology of C. elegans worms; Computational Neuroscience;
Models | Current Opinion in Systems Biology 13: 44-51 (2019) | 10.1016/j.coisb.2018.09.008 | null | q-bio.NC q-bio.GN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | {\it Caenorhabditis elegans} nematode worms are the only animals with the
known detailed neural connectivity diagram, well characterized genomics, and
relatively simple quantifiable behavioral output. With this in mind, many
researchers view this animal as the best candidate for a systems biology
approach, where one can integrate molecular and cellular knowledge to gain
global understanding of worm's behavior. This work reviews some research in
this direction, emphasizing computational perspective, and points out some
successes and challenges to meet this lofty goal.
| [
{
"created": "Wed, 16 Oct 2019 16:17:33 GMT",
"version": "v1"
}
] | 2019-10-17 | [
[
"Karbowski",
"Jan",
""
]
] | {\it Caenorhabditis elegans} nematode worms are the only animals with the known detailed neural connectivity diagram, well characterized genomics, and relatively simple quantifiable behavioral output. With this in mind, many researchers view this animal as the best candidate for a systems biology approach, where one can integrate molecular and cellular knowledge to gain global understanding of worm's behavior. This work reviews some research in this direction, emphasizing computational perspective, and points out some successes and challenges to meet this lofty goal. |
1905.00621 | Piero Fariselli | Piero Fariselli, Cristian Taccioli, Luca Pagani, Amos Maritan | DNA energy constraints shape biological evolutionary trajectories | 21 pages, 8 figures | null | null | null | q-bio.BM q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Most living systems rely on double-stranded DNA (dsDNA) to store their
genetic information and perpetuate themselves. This biological information has
been considered the main target of evolution. However, here we show that
symmetries and patterns in the dsDNA sequence can emerge from the physical
peculiarities of the dsDNA molecule itself and the maximum entropy principle
alone, rather than from biological or environmental evolutionary pressure. The
randomness justifies the human codon biases and context-dependent mutation
patterns in human populations. Thus, the DNA "exceptional symmetries", emerged
from the randomness, have to be taken into account when looking for the DNA
encoded information. Our results suggest that the double helix energy
constraints and, more generally, the physical properties of the dsDNA are the
hard drivers of the overall DNA sequence architecture, whereas the biological
selective processes act as soft drivers, which only under extraordinary
circumstances overtake the overall entropy content of the genome.
| [
{
"created": "Thu, 2 May 2019 08:54:14 GMT",
"version": "v1"
},
{
"created": "Wed, 27 Nov 2019 16:04:51 GMT",
"version": "v2"
}
] | 2019-11-28 | [
[
"Fariselli",
"Piero",
""
],
[
"Taccioli",
"Cristian",
""
],
[
"Pagani",
"Luca",
""
],
[
"Maritan",
"Amos",
""
]
] | Most living systems rely on double-stranded DNA (dsDNA) to store their genetic information and perpetuate themselves. This biological information has been considered the main target of evolution. However, here we show that symmetries and patterns in the dsDNA sequence can emerge from the physical peculiarities of the dsDNA molecule itself and the maximum entropy principle alone, rather than from biological or environmental evolutionary pressure. The randomness justifies the human codon biases and context-dependent mutation patterns in human populations. Thus, the DNA "exceptional symmetries", emerged from the randomness, have to be taken into account when looking for the DNA encoded information. Our results suggest that the double helix energy constraints and, more generally, the physical properties of the dsDNA are the hard drivers of the overall DNA sequence architecture, whereas the biological selective processes act as soft drivers, which only under extraordinary circumstances overtake the overall entropy content of the genome. |
2204.05132 | Shengjie Zheng | Shengjie Zheng, Wenyi Li, Lang Qian, Chenggang He, Xiaojian Li | A Spiking Neural Network based on Neural Manifold for Augmenting
Intracortical Brain-Computer Interface Data | 12pages , 9 figures | 31st International Conference on Artificial Neural Networks 2022 | null | null | q-bio.NC cs.AI | http://creativecommons.org/licenses/by/4.0/ | Brain-computer interfaces (BCIs), transform neural signals in the brain into
in-structions to control external devices. However, obtaining sufficient
training data is difficult as well as limited. With the advent of advanced
machine learning methods, the capability of brain-computer interfaces has been
enhanced like never before, however, these methods require a large amount of
data for training and thus require data augmentation of the limited data
available. Here, we use spiking neural networks (SNN) as data generators. It is
touted as the next-generation neu-ral network and is considered as one of the
algorithms oriented to general artifi-cial intelligence because it borrows the
neural information processing from bio-logical neurons. We use the SNN to
generate neural spike information that is bio-interpretable and conforms to the
intrinsic patterns in the original neural data. Ex-periments show that the
model can directly synthesize new spike trains, which in turn improves the
generalization ability of the BCI decoder. Both the input and output of the
spiking neural model are spike information, which is a brain-inspired
intelligence approach that can be better integrated with BCI in the future.
| [
{
"created": "Sat, 26 Mar 2022 15:32:31 GMT",
"version": "v1"
}
] | 2024-07-02 | [
[
"Zheng",
"Shengjie",
""
],
[
"Li",
"Wenyi",
""
],
[
"Qian",
"Lang",
""
],
[
"He",
"Chenggang",
""
],
[
"Li",
"Xiaojian",
""
]
] | Brain-computer interfaces (BCIs), transform neural signals in the brain into in-structions to control external devices. However, obtaining sufficient training data is difficult as well as limited. With the advent of advanced machine learning methods, the capability of brain-computer interfaces has been enhanced like never before, however, these methods require a large amount of data for training and thus require data augmentation of the limited data available. Here, we use spiking neural networks (SNN) as data generators. It is touted as the next-generation neu-ral network and is considered as one of the algorithms oriented to general artifi-cial intelligence because it borrows the neural information processing from bio-logical neurons. We use the SNN to generate neural spike information that is bio-interpretable and conforms to the intrinsic patterns in the original neural data. Ex-periments show that the model can directly synthesize new spike trains, which in turn improves the generalization ability of the BCI decoder. Both the input and output of the spiking neural model are spike information, which is a brain-inspired intelligence approach that can be better integrated with BCI in the future. |
2204.12270 | Andre Lamurias | Andre Lamurias, Alessandro Tibo, Katja Hose, Mads Albertsen and Thomas
Dyhre Nielsen | Graph Neural Networks for Microbial Genome Recovery | null | null | null | null | q-bio.GN cs.LG q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Microbes have a profound impact on our health and environment, but our
understanding of the diversity and function of microbial communities is
severely limited. Through DNA sequencing of microbial communities
(metagenomics), DNA fragments (reads) of the individual microbes can be
obtained, which through assembly graphs can be combined into long contiguous
DNA sequences (contigs). Given the complexity of microbial communities, single
contig microbial genomes are rarely obtained. Instead, contigs are eventually
clustered into bins, with each bin ideally making up a full genome. This
process is referred to as metagenomic binning.
Current state-of-the-art techniques for metagenomic binning rely only on the
local features for the individual contigs. These techniques therefore fail to
exploit the similarities between contigs as encoded by the assembly graph, in
which the contigs are organized. In this paper, we propose to use Graph Neural
Networks (GNNs) to leverage the assembly graph when learning contig
representations for metagenomic binning. Our method, VaeG-Bin, combines
variational autoencoders for learning latent representations of the individual
contigs, with GNNs for refining these representations by taking into account
the neighborhood structure of the contigs in the assembly graph. We explore
several types of GNNs and demonstrate that VaeG-Bin recovers more high-quality
genomes than other state-of-the-art binners on both simulated and real-world
datasets.
| [
{
"created": "Tue, 26 Apr 2022 12:49:51 GMT",
"version": "v1"
}
] | 2022-04-27 | [
[
"Lamurias",
"Andre",
""
],
[
"Tibo",
"Alessandro",
""
],
[
"Hose",
"Katja",
""
],
[
"Albertsen",
"Mads",
""
],
[
"Nielsen",
"Thomas Dyhre",
""
]
] | Microbes have a profound impact on our health and environment, but our understanding of the diversity and function of microbial communities is severely limited. Through DNA sequencing of microbial communities (metagenomics), DNA fragments (reads) of the individual microbes can be obtained, which through assembly graphs can be combined into long contiguous DNA sequences (contigs). Given the complexity of microbial communities, single contig microbial genomes are rarely obtained. Instead, contigs are eventually clustered into bins, with each bin ideally making up a full genome. This process is referred to as metagenomic binning. Current state-of-the-art techniques for metagenomic binning rely only on the local features for the individual contigs. These techniques therefore fail to exploit the similarities between contigs as encoded by the assembly graph, in which the contigs are organized. In this paper, we propose to use Graph Neural Networks (GNNs) to leverage the assembly graph when learning contig representations for metagenomic binning. Our method, VaeG-Bin, combines variational autoencoders for learning latent representations of the individual contigs, with GNNs for refining these representations by taking into account the neighborhood structure of the contigs in the assembly graph. We explore several types of GNNs and demonstrate that VaeG-Bin recovers more high-quality genomes than other state-of-the-art binners on both simulated and real-world datasets. |
2208.04689 | Nilay Mondal | Nilay Mondal, K. S. Yadav, D. C. Dalal | Enhanced drug uptake on application of electroporation in a single-cell
model | 18 pages | null | null | null | q-bio.TO math.AP q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Electroporation method is a useful tool for delivering drugs into various
diseased tissues in the human body. As a result of an applied electric field,
drug particles enter the intracellular compartment through the temporarily
permeabilized cell membrane. Consequently, electroporation method allows better
penetration of the drug into the diseased tissue and improves treatment
clinically. In this study, a more generalized model of drug transport in a
single-cell is proposed. The model is able to capture non-homogeneous drug
transport in the cell due to non-uniform cell membrane permeabilization.
Several numerical experiments are conducted to understand the effects of
electric field and drug permeability on drug uptake into the cell. Through
investigation, the appropriate electric field and drug permeability are
identified that lead to sufficient drug uptake into the cell. This model can be
used by experimentalists to get information prior to conduct any experiment,
and it may help reduce the number of actual experiments that might be conducted
otherwise.
| [
{
"created": "Mon, 1 Aug 2022 14:57:35 GMT",
"version": "v1"
}
] | 2022-08-10 | [
[
"Mondal",
"Nilay",
""
],
[
"Yadav",
"K. S.",
""
],
[
"Dalal",
"D. C.",
""
]
] | Electroporation method is a useful tool for delivering drugs into various diseased tissues in the human body. As a result of an applied electric field, drug particles enter the intracellular compartment through the temporarily permeabilized cell membrane. Consequently, electroporation method allows better penetration of the drug into the diseased tissue and improves treatment clinically. In this study, a more generalized model of drug transport in a single-cell is proposed. The model is able to capture non-homogeneous drug transport in the cell due to non-uniform cell membrane permeabilization. Several numerical experiments are conducted to understand the effects of electric field and drug permeability on drug uptake into the cell. Through investigation, the appropriate electric field and drug permeability are identified that lead to sufficient drug uptake into the cell. This model can be used by experimentalists to get information prior to conduct any experiment, and it may help reduce the number of actual experiments that might be conducted otherwise. |
1611.03327 | Osamu Narikiyo | Miki Fukunoue, Osamu Narikiyo | Early Evolution of Bird-Type Language without Grammar: Duplication and
Mutation | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Using a series of computer simulations we have demonstrated a scenario of the
early evolution of the bird-type primitive language. We do not assume wise
agents who can use a grammar and manage an evolution without a grammar.
Duplication and mutation of phrases is our strategy. Such a strategy is seen in
wide classes of living phenomena.
| [
{
"created": "Sat, 22 Oct 2016 08:06:56 GMT",
"version": "v1"
},
{
"created": "Sat, 4 Mar 2017 08:14:11 GMT",
"version": "v2"
}
] | 2017-03-07 | [
[
"Fukunoue",
"Miki",
""
],
[
"Narikiyo",
"Osamu",
""
]
] | Using a series of computer simulations we have demonstrated a scenario of the early evolution of the bird-type primitive language. We do not assume wise agents who can use a grammar and manage an evolution without a grammar. Duplication and mutation of phrases is our strategy. Such a strategy is seen in wide classes of living phenomena. |
1005.4146 | Sebastian Schreiber | Josef Hofbauer and Sebastian J. Schreiber | Robust permanence for interacting structured populations | null | Journal of Differential Equations, 248, 1955-1971 (2010) | null | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The dynamics of interacting structured populations can be modeled by
$\frac{dx_i}{dt}= A_i (x)x_i$ where $x_i\in \R^{n_i}$, $x=(x_1,\dots,x_k)$, and
$A_i(x)$ are matrices with non-negative off-diagonal entries. These models are
permanent if there exists a positive global attractor and are robustly
permanent if they remain permanent following perturbations of $A_i(x)$.
Necessary and sufficient conditions for robust permanence are derived using
dominant Lyapunov exponents $\lambda_i(\mu)$ of the $A_i(x)$ with respect to
invariant measures $\mu$. The necessary condition requires $\max_i
\lambda_i(\mu)>0$ for all ergodic measures with support in the boundary of the
non-negative cone. The sufficient condition requires that the boundary admits a
Morse decomposition such that $\max_i \lambda_i(\mu)>0$ for all invariant
measures $\mu$ supported by a component of the Morse decomposition. When the
Morse components are Axiom A, uniquely ergodic, or support all but one
population, the necessary and sufficient conditions are equivalent.
Applications to spatial ecology, epidemiology, and gene networks are given.
| [
{
"created": "Sat, 22 May 2010 20:22:23 GMT",
"version": "v1"
}
] | 2010-05-25 | [
[
"Hofbauer",
"Josef",
""
],
[
"Schreiber",
"Sebastian J.",
""
]
] | The dynamics of interacting structured populations can be modeled by $\frac{dx_i}{dt}= A_i (x)x_i$ where $x_i\in \R^{n_i}$, $x=(x_1,\dots,x_k)$, and $A_i(x)$ are matrices with non-negative off-diagonal entries. These models are permanent if there exists a positive global attractor and are robustly permanent if they remain permanent following perturbations of $A_i(x)$. Necessary and sufficient conditions for robust permanence are derived using dominant Lyapunov exponents $\lambda_i(\mu)$ of the $A_i(x)$ with respect to invariant measures $\mu$. The necessary condition requires $\max_i \lambda_i(\mu)>0$ for all ergodic measures with support in the boundary of the non-negative cone. The sufficient condition requires that the boundary admits a Morse decomposition such that $\max_i \lambda_i(\mu)>0$ for all invariant measures $\mu$ supported by a component of the Morse decomposition. When the Morse components are Axiom A, uniquely ergodic, or support all but one population, the necessary and sufficient conditions are equivalent. Applications to spatial ecology, epidemiology, and gene networks are given. |
1703.07987 | Sarwan Kumar | Chhaya Atri, Bharti Kumar, Hitesh Kumar, Sanjula Sharma and Surinder
S. Banga | Development and characterization of Brassica juncea fruticulosa
introgression lines exhibiting resistance to mustard aphid | Phenotyped introgression lines for resistance to mustard aphid,
Lipaphis erysimi - a key pest of rapeseed mustard in India and other
countries | null | 10.1186/1471-2156-13-104 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background: Mustard aphid is a major pest of Brassica oilseeds. No source for
aphid resistance is presently available in Brassica juncea . A wild crucifer,
Brassica fruticulosa is known to be resistant to mustard aphid. An artificially
synthesized amphiploid, AD-4 (B. fruticulosa x B. rapa var. brown sarson) was
developed for use as a bridge species to transfer fruticulosa resistance to B.
juncea. Using the selfed backcross we could select a large number of lines with
resistance to mustard aphid. This paper reports cytogenetic stability of
introgression lines, molecular evidence for alien introgression and their
reaction to mustard aphid infestation. Results: Majority of introgression lines
had expected euploid chromosome number(2n= 36), showed normal meiosis and high
pollen grain fertility. Well-distributed and transferable simple-sequence
repeats (SSR) markers for all the 18 B. juncea chromosomes helped to
characterize introgression events. Average proportions of recipient and donor
genome in the substitution lines were 49.72 and 35.06%, respectively. Minimum
alien parent genome presence (27.29%) was observed in the introgression line,
Ad3K-280 . Introgressed genotypes also varied for their resistance responses to
mustard aphid infestations under artificial release conditions for two
continuous seasons. Some of the test genotypes showed consistent resistant
reaction. Conclusions: B.juncea-fruticulosa introgression set may prove to be a
very powerful breeding tool for aphid resistance related QTL/gene discovery and
fine mapping of the desired genes/QTLs to facilitate marker assisted transfer
of identified gene(s) for mustard aphid resistance in the background of
commercial mustard genotypes.
| [
{
"created": "Thu, 23 Mar 2017 10:17:04 GMT",
"version": "v1"
}
] | 2017-03-24 | [
[
"Atri",
"Chhaya",
""
],
[
"Kumar",
"Bharti",
""
],
[
"Kumar",
"Hitesh",
""
],
[
"Sharma",
"Sanjula",
""
],
[
"Banga",
"Surinder S.",
""
]
] | Background: Mustard aphid is a major pest of Brassica oilseeds. No source for aphid resistance is presently available in Brassica juncea . A wild crucifer, Brassica fruticulosa is known to be resistant to mustard aphid. An artificially synthesized amphiploid, AD-4 (B. fruticulosa x B. rapa var. brown sarson) was developed for use as a bridge species to transfer fruticulosa resistance to B. juncea. Using the selfed backcross we could select a large number of lines with resistance to mustard aphid. This paper reports cytogenetic stability of introgression lines, molecular evidence for alien introgression and their reaction to mustard aphid infestation. Results: Majority of introgression lines had expected euploid chromosome number(2n= 36), showed normal meiosis and high pollen grain fertility. Well-distributed and transferable simple-sequence repeats (SSR) markers for all the 18 B. juncea chromosomes helped to characterize introgression events. Average proportions of recipient and donor genome in the substitution lines were 49.72 and 35.06%, respectively. Minimum alien parent genome presence (27.29%) was observed in the introgression line, Ad3K-280 . Introgressed genotypes also varied for their resistance responses to mustard aphid infestations under artificial release conditions for two continuous seasons. Some of the test genotypes showed consistent resistant reaction. Conclusions: B.juncea-fruticulosa introgression set may prove to be a very powerful breeding tool for aphid resistance related QTL/gene discovery and fine mapping of the desired genes/QTLs to facilitate marker assisted transfer of identified gene(s) for mustard aphid resistance in the background of commercial mustard genotypes. |
2312.05484 | Nizar Islah | Nizar Islah, Guillaume Etter, Mashbayar Tugsbayar, Tugce Gurbuz, Blake
Richards, Eilif Muller | Learning to combine top-down context and feed-forward representations
under ambiguity with apical and basal dendrites | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One of the most striking features of neocortical anatomy is the presence of
extensive top-down projections into primary sensory areas. Notably, many of
these top-down projections impinge on the distal apical dendrites of pyramidal
neurons, where they exert a modulatory effect, altering the gain of responses.
It is thought that these top-down projections carry contextual information that
can help animals to resolve ambiguities in sensory data. However, it has yet to
be demonstrated how such modulatory connections to the distal apical dendrites
can serve this computational function. Here, we develop a computational model
of pyramidal cells that integrates contextual information from top-down
projections to apical compartments with sensory representations driven by
bottom-up projections to basal compartments. When input stimuli are ambiguous
and relevant contextual information is available, the apical feedback modulates
the basal signals to recover unambiguous sensory representations. Importantly,
when stimuli are unambiguous, contextual information which is irrelevant or
opposes sensory evidence is appropriately ignored by the model. By generalizing
the task to temporal sequences, we further show that our model can learn to
integrate contextual information across time. Using layer-wise relevance
propagation, we extract the importance of individual neurons to the prediction
of each category, revealing that neurons that are most relevant for the overlap
of categories receive the largest magnitude of top-down signals, and are
necessary for solving the task. This work thus provides a proof-of-concept
demonstrating how the top-down modulatory inputs to apical dendrites in sensory
regions could be used by the cortex to handle the ambiguities that animals
encounter in the real world.
| [
{
"created": "Sat, 9 Dec 2023 07:18:43 GMT",
"version": "v1"
}
] | 2023-12-12 | [
[
"Islah",
"Nizar",
""
],
[
"Etter",
"Guillaume",
""
],
[
"Tugsbayar",
"Mashbayar",
""
],
[
"Gurbuz",
"Tugce",
""
],
[
"Richards",
"Blake",
""
],
[
"Muller",
"Eilif",
""
]
] | One of the most striking features of neocortical anatomy is the presence of extensive top-down projections into primary sensory areas. Notably, many of these top-down projections impinge on the distal apical dendrites of pyramidal neurons, where they exert a modulatory effect, altering the gain of responses. It is thought that these top-down projections carry contextual information that can help animals to resolve ambiguities in sensory data. However, it has yet to be demonstrated how such modulatory connections to the distal apical dendrites can serve this computational function. Here, we develop a computational model of pyramidal cells that integrates contextual information from top-down projections to apical compartments with sensory representations driven by bottom-up projections to basal compartments. When input stimuli are ambiguous and relevant contextual information is available, the apical feedback modulates the basal signals to recover unambiguous sensory representations. Importantly, when stimuli are unambiguous, contextual information which is irrelevant or opposes sensory evidence is appropriately ignored by the model. By generalizing the task to temporal sequences, we further show that our model can learn to integrate contextual information across time. Using layer-wise relevance propagation, we extract the importance of individual neurons to the prediction of each category, revealing that neurons that are most relevant for the overlap of categories receive the largest magnitude of top-down signals, and are necessary for solving the task. This work thus provides a proof-of-concept demonstrating how the top-down modulatory inputs to apical dendrites in sensory regions could be used by the cortex to handle the ambiguities that animals encounter in the real world. |
q-bio/0407030 | Jie Liang | Jinfeng Zhang, Rong Chen, Jie Liang | Potential function of simplified protein models for discriminating
native proteins from decoys: Combining contact interaction and local
sequence-dependent geometry | 4 pages, 2 figures, Accepted by 26th IEEE-EMBS Conference, San
Francisco | null | 10.1109/IEMBS.2004.1403844 | null | q-bio.BM | null | An effective potential function is critical for protein structure prediction
and folding simulation. For simplified models of proteins where coordinates of
only $C_\alpha$ atoms need to be specified, an accurate potential function is
important. Such a simplified model is essential for efficient search of
conformational space. In this work, we present a formulation of potential
function for simplified representations of protein structures. It is based on
the combination of descriptors derived from residue-residue contact and
sequence-dependent local geometry. The optimal weight coefficients for contact
and local geometry is obtained through optimization by maximizing margins among
native and decoy structures. The latter are generated by chain growth and by
gapless threading. The performance of the potential function in blind test of
discriminating native protein structures from decoys is evaluated using several
benchmark decoy sets. This potential function have comparable or better
performance than several residue-based potential functions that require in
addition coordinates of side chain centers or coordinates of all side chain
atoms.
| [
{
"created": "Thu, 22 Jul 2004 21:37:33 GMT",
"version": "v1"
}
] | 2016-11-17 | [
[
"Zhang",
"Jinfeng",
""
],
[
"Chen",
"Rong",
""
],
[
"Liang",
"Jie",
""
]
] | An effective potential function is critical for protein structure prediction and folding simulation. For simplified models of proteins where coordinates of only $C_\alpha$ atoms need to be specified, an accurate potential function is important. Such a simplified model is essential for efficient search of conformational space. In this work, we present a formulation of potential function for simplified representations of protein structures. It is based on the combination of descriptors derived from residue-residue contact and sequence-dependent local geometry. The optimal weight coefficients for contact and local geometry is obtained through optimization by maximizing margins among native and decoy structures. The latter are generated by chain growth and by gapless threading. The performance of the potential function in blind test of discriminating native protein structures from decoys is evaluated using several benchmark decoy sets. This potential function have comparable or better performance than several residue-based potential functions that require in addition coordinates of side chain centers or coordinates of all side chain atoms. |
1901.03864 | Jean-Leon Thomas | Laurent Jacob, Ligia Boisserand, Juliette Pestel, Salli Antila,
Jean-Mickael Thomas, Marie-Stephane Aigrot, Thomas Mathivet, Seyoung Lee,
Kari Alitalo, Nicolas Renier, Anne Eichmann, Jean-Leon Thomas | Anatomy of the vertebral column lymphatic network in mice | 8 figures + 2 supplemental figures | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cranial lymphatic vessels (LVs) are involved in transport of fluids,
macromolecules and CNS immune responses. Little information about spinal LVs is
available, because these delicate structures are embedded within vertebral
tissues and difficult to visualize using traditional histology. Here we reveal
an extended vertebral column LV network using three-dimensional imaging of
decalcified iDISCO-clarified spine segments. Spinal LVs are metameric circuits
exiting along spinal nerve roots and connecting to lymph nodes and the thoracic
duct. They navigate in the epidural space and the dura mater around the spinal
cord, and associate with leukocytes, peripheral dorsal root and sympathetic
ganglia. Spinal LVs are VEGF-C-dependent and remodel extensively after spinal
cord injury. They constitute an extension to cranial circuits for meningeal
fluids, but also a route for perineural fluids and a link with peripheral
immune and nervous circuits. Vertebral column LVs may be potential targets to
improve the maintenance and repair of 32 spinal tissues as well as gatekeepers
of CNS immunity.
| [
{
"created": "Sat, 12 Jan 2019 14:14:55 GMT",
"version": "v1"
}
] | 2019-01-15 | [
[
"Jacob",
"Laurent",
""
],
[
"Boisserand",
"Ligia",
""
],
[
"Pestel",
"Juliette",
""
],
[
"Antila",
"Salli",
""
],
[
"Thomas",
"Jean-Mickael",
""
],
[
"Aigrot",
"Marie-Stephane",
""
],
[
"Mathivet",
"Thomas",
""
],
[
"Lee",
"Seyoung",
""
],
[
"Alitalo",
"Kari",
""
],
[
"Renier",
"Nicolas",
""
],
[
"Eichmann",
"Anne",
""
],
[
"Thomas",
"Jean-Leon",
""
]
] | Cranial lymphatic vessels (LVs) are involved in transport of fluids, macromolecules and CNS immune responses. Little information about spinal LVs is available, because these delicate structures are embedded within vertebral tissues and difficult to visualize using traditional histology. Here we reveal an extended vertebral column LV network using three-dimensional imaging of decalcified iDISCO-clarified spine segments. Spinal LVs are metameric circuits exiting along spinal nerve roots and connecting to lymph nodes and the thoracic duct. They navigate in the epidural space and the dura mater around the spinal cord, and associate with leukocytes, peripheral dorsal root and sympathetic ganglia. Spinal LVs are VEGF-C-dependent and remodel extensively after spinal cord injury. They constitute an extension to cranial circuits for meningeal fluids, but also a route for perineural fluids and a link with peripheral immune and nervous circuits. Vertebral column LVs may be potential targets to improve the maintenance and repair of 32 spinal tissues as well as gatekeepers of CNS immunity. |
1210.2338 | Andrea De Martino | Matteo Figliuzzi, Enzo Marinari, Andrea De Martino | MicroRNAs as a selective channel of communication between competing
RNAs: a steady-state theory | 15 pages, 10 figures, to appear in Biophys J | null | 10.1016/j.bpj.2013.01.012 | null | q-bio.MN cond-mat.dis-nn cond-mat.stat-mech physics.bio-ph q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It has recently been suggested that the competition for a finite pool of
microRNAs (miRNA) gives rise to effective interactions among their common
targets (competing endogenous RNAs or ceRNAs) that could prove to be crucial
for post-transcriptional regulation (PTR). We have studied a minimal model of
PTR where the emergence and the nature of such interactions can be
characterized in detail at steady state. Sensitivity analysis shows that
binding free energies and repression mechanisms are the key ingredients for the
cross-talk between ceRNAs to arise. Interactions emerge in specific ranges of
repression values, can be symmetrical (one ceRNA influences another and
vice-versa) or asymmetrical (one ceRNA influences another but not the reverse)
and may be highly selective, while possibly limited by noise. In addition, we
show that non-trivial correlations among ceRNAs can emerge in experimental
readouts due to transcriptional fluctuations even in absence of miRNA-mediated
cross-talk.
| [
{
"created": "Mon, 8 Oct 2012 16:54:19 GMT",
"version": "v1"
},
{
"created": "Wed, 30 Jan 2013 11:25:56 GMT",
"version": "v2"
}
] | 2015-06-11 | [
[
"Figliuzzi",
"Matteo",
""
],
[
"Marinari",
"Enzo",
""
],
[
"De Martino",
"Andrea",
""
]
] | It has recently been suggested that the competition for a finite pool of microRNAs (miRNA) gives rise to effective interactions among their common targets (competing endogenous RNAs or ceRNAs) that could prove to be crucial for post-transcriptional regulation (PTR). We have studied a minimal model of PTR where the emergence and the nature of such interactions can be characterized in detail at steady state. Sensitivity analysis shows that binding free energies and repression mechanisms are the key ingredients for the cross-talk between ceRNAs to arise. Interactions emerge in specific ranges of repression values, can be symmetrical (one ceRNA influences another and vice-versa) or asymmetrical (one ceRNA influences another but not the reverse) and may be highly selective, while possibly limited by noise. In addition, we show that non-trivial correlations among ceRNAs can emerge in experimental readouts due to transcriptional fluctuations even in absence of miRNA-mediated cross-talk. |
2212.01384 | Chunyu Ma | Chunyu Ma, Zhihan Zhou, Han Liu, David Koslicki | KGML-xDTD: A Knowledge Graph-based Machine Learning Framework for Drug
Treatment Prediction and Mechanism Description | null | null | null | null | q-bio.QM cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Background: Computational drug repurposing is a cost- and time-efficient
approach that aims to identify new therapeutic targets or diseases
(indications) of existing drugs/compounds. It is especially critical for
emerging and/or orphan diseases due to its cheaper investment and shorter
research cycle compared with traditional wet-lab drug discovery approaches.
However, the underlying mechanisms of action (MOAs) between repurposed drugs
and their target diseases remain largely unknown, which is still a main
obstacle for computational drug repurposing methods to be widely adopted in
clinical settings.
Results: In this work, we propose KGML-xDTD: a Knowledge Graph-based Machine
Learning framework for explainably predicting Drugs Treating Diseases. It is a
two-module framework that not only predicts the treatment probabilities between
drugs/compounds and diseases but also biologically explains them via knowledge
graph (KG) path-based, testable mechanisms of action (MOAs). We leverage
knowledge-and-publication based information to extract biologically meaningful
"demonstration paths" as the intermediate guidance in the Graph-based
Reinforcement Learning (GRL) path-finding process. Comprehensive experiments
and case study analyses show that the proposed framework can achieve
state-of-the-art performance in both predictions of drug repurposing and
recapitulation of human-curated drug MOA paths.
Conclusions: KGML-xDTD is the first model framework that can offer KG-path
explanations for drug repurposing predictions by leveraging the combination of
prediction outcomes and existing biological knowledge and publications. We
believe it can effectively reduce "black-box" concerns and increase prediction
confidence for drug repurposing based on predicted path-based explanations, and
further accelerate the process of drug discovery for emerging diseases.
| [
{
"created": "Wed, 30 Nov 2022 17:05:22 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Apr 2023 06:58:02 GMT",
"version": "v2"
}
] | 2023-04-26 | [
[
"Ma",
"Chunyu",
""
],
[
"Zhou",
"Zhihan",
""
],
[
"Liu",
"Han",
""
],
[
"Koslicki",
"David",
""
]
] | Background: Computational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approaches. However, the underlying mechanisms of action (MOAs) between repurposed drugs and their target diseases remain largely unknown, which is still a main obstacle for computational drug repurposing methods to be widely adopted in clinical settings. Results: In this work, we propose KGML-xDTD: a Knowledge Graph-based Machine Learning framework for explainably predicting Drugs Treating Diseases. It is a two-module framework that not only predicts the treatment probabilities between drugs/compounds and diseases but also biologically explains them via knowledge graph (KG) path-based, testable mechanisms of action (MOAs). We leverage knowledge-and-publication based information to extract biologically meaningful "demonstration paths" as the intermediate guidance in the Graph-based Reinforcement Learning (GRL) path-finding process. Comprehensive experiments and case study analyses show that the proposed framework can achieve state-of-the-art performance in both predictions of drug repurposing and recapitulation of human-curated drug MOA paths. Conclusions: KGML-xDTD is the first model framework that can offer KG-path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations, and further accelerate the process of drug discovery for emerging diseases. |
1802.09817 | Valmir C. Barbosa | Valmir C. Barbosa | Information-theoretic signatures of biodiversity in the barcoding gene | null | Journal of Theoretical Biology 451 (2018), 111-116 | 10.1016/j.jtbi.2018.05.008 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The COI mitochondrial gene is present in all animal phyla and in a few
others, and is the leading candidate for species identification through DNA
barcoding. Calculating a generalized form of total correlation on publicly
available data on the gene yields distinctive information-theoretic descriptors
of the phyla represented in the data. Moreover, performing principal component
analysis on standardized versions of these descriptors reveals a strong
correlation between the first principal component and the natural logarithm of
the number of known living species. The descriptors thus constitute clear
information-theoretic signatures of the processes whereby evolution has given
rise to current biodiversity.
| [
{
"created": "Tue, 27 Feb 2018 10:54:44 GMT",
"version": "v1"
}
] | 2018-05-16 | [
[
"Barbosa",
"Valmir C.",
""
]
] | The COI mitochondrial gene is present in all animal phyla and in a few others, and is the leading candidate for species identification through DNA barcoding. Calculating a generalized form of total correlation on publicly available data on the gene yields distinctive information-theoretic descriptors of the phyla represented in the data. Moreover, performing principal component analysis on standardized versions of these descriptors reveals a strong correlation between the first principal component and the natural logarithm of the number of known living species. The descriptors thus constitute clear information-theoretic signatures of the processes whereby evolution has given rise to current biodiversity. |
1411.5954 | Haleh Abdizadeh Sabanci University | Haleh Abdizadeh, Ali Rana Atilgan, Canan Atilgan | Relative Mobility of Human Transferrin Domains Accounts for Its
Efficient Recognition and Recycling | null | null | null | null | q-bio.BM | http://creativecommons.org/licenses/by-nc-sa/3.0/ | Human serum transferrin (hTf) transports ferric ions in the blood stream and
inflamed mucosal surfaces with high affinity and delivers them to cells via
receptor mediated endocytosis. A typical hTf is folded into two homologous
lobes; each lobe is further divided into two similar sized domains. Three
different crystal structures of hTf delineate large conformational changes
involved in iron binding/dissociation. However, whether the release process
follows the same trend at serum (~7.4) and endosomal (~5.6) pH remains
unanswered. The specialized role of the two lobes and if communication between
them leads to efficient and controlled release is also debated. Here, we study
the dynamics of the full structure as well as the separate lobes in different
closed, partially open, and open conformations under the nearly neutral pH
conditions in the blood serum and the more acidic one in the endosome. The
results corroborate experimental observations and underscore the distinguishing
effect of pH on the dynamics of hTf. Furthermore, in a total of 2 {\mu}s
molecular dynamics simulation of different forms of hTf, residue fluctuations
elucidate the cross talk between the two lobes correlated by the peptide linker
bridging the two lobes at serum pH, while their correlated motions is lost
under endosomal conditions. At serum pH, the presence of even a single iron on
either lobe leads C-lobe fluctuations to subside, making it the target for
recognition by human cells or hostile bacteria seeking iron sequestration. The
N-lobe, on the other hand, has a propensity to open, making iron readily
available when needed at regions of serum pH. At endosomal pH, both lobes
readily open, making irons available for delivery. The interplay between the
relative mobility of the lobes renders efficient mechanism for the recognition
and release of hTf at the cell surface, and therefore its recycling in the
organism.
| [
{
"created": "Fri, 21 Nov 2014 17:08:46 GMT",
"version": "v1"
}
] | 2014-11-24 | [
[
"Abdizadeh",
"Haleh",
""
],
[
"Atilgan",
"Ali Rana",
""
],
[
"Atilgan",
"Canan",
""
]
] | Human serum transferrin (hTf) transports ferric ions in the blood stream and inflamed mucosal surfaces with high affinity and delivers them to cells via receptor mediated endocytosis. A typical hTf is folded into two homologous lobes; each lobe is further divided into two similar sized domains. Three different crystal structures of hTf delineate large conformational changes involved in iron binding/dissociation. However, whether the release process follows the same trend at serum (~7.4) and endosomal (~5.6) pH remains unanswered. The specialized role of the two lobes and if communication between them leads to efficient and controlled release is also debated. Here, we study the dynamics of the full structure as well as the separate lobes in different closed, partially open, and open conformations under the nearly neutral pH conditions in the blood serum and the more acidic one in the endosome. The results corroborate experimental observations and underscore the distinguishing effect of pH on the dynamics of hTf. Furthermore, in a total of 2 {\mu}s molecular dynamics simulation of different forms of hTf, residue fluctuations elucidate the cross talk between the two lobes correlated by the peptide linker bridging the two lobes at serum pH, while their correlated motions is lost under endosomal conditions. At serum pH, the presence of even a single iron on either lobe leads C-lobe fluctuations to subside, making it the target for recognition by human cells or hostile bacteria seeking iron sequestration. The N-lobe, on the other hand, has a propensity to open, making iron readily available when needed at regions of serum pH. At endosomal pH, both lobes readily open, making irons available for delivery. The interplay between the relative mobility of the lobes renders efficient mechanism for the recognition and release of hTf at the cell surface, and therefore its recycling in the organism. |
2309.09056 | Anindita Bhadra | Sourabh Biswas, Kalyan Ghosh, Kaushikee Sarkar and Anindita Bhadra | Where do free-ranging dogs rest? A population level study reveals hidden
patterns in resting site choice | 2 figures, 2 tables, ESM | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Free-ranging dogs (FRDs) in human-dominated areas encounter obstacles such as
noise, pollution, limited food sources, and anthropogenic disturbance while
resting. Since FRDs have survived as a population in India, as in many other
parts of the Global South for centuries, they provide a unique opportunity to
study adaptation of animals to the human-dominated urban landscape. We
documented factors impacting resting behaviour and site preferences in three
states of India, for 284 dogs, leading to 6047 observations over 3 years. 7
physical parameters of the resting sites, along with the biological factors
like mating and pup-rearing and time of day affected their choice of resting
sites. The frequency-rank distribution of the unique combinations in which the
parameters were selected followed a Power law distribution, which suggests
underlying biological reasons for the observed preferences. Further, 3 of these
parameters showed maximum consistency of choice in terms of the sub-parameters
selected, explaining 30% of the observations. FRDs prefer to rest close to
their resource sites within the territory, at a place that enabled maximum
visibility of the surroundings. They chose such sites in the core of the
territory for sleeping. At other times, they chose such sites away from the
core, and were less restive, thus allowing for immediate response in case of
intrusion or threat. They generally avoided anthropogenic disturbance for
sleeping, and preferred areas with shade.Incorporating these aspects into urban
management plans can promote human-dog cooperation and reduce situations of
conflict. We envisage more inclusive urban areas in the future, that can allow
for co-existence of the humans and their oldest companions in the commensal
relationship that has been maintained for hundreds of generations of dogs in
this part of the world.
| [
{
"created": "Sat, 16 Sep 2023 17:33:40 GMT",
"version": "v1"
}
] | 2023-09-19 | [
[
"Biswas",
"Sourabh",
""
],
[
"Ghosh",
"Kalyan",
""
],
[
"Sarkar",
"Kaushikee",
""
],
[
"Bhadra",
"Anindita",
""
]
] | Free-ranging dogs (FRDs) in human-dominated areas encounter obstacles such as noise, pollution, limited food sources, and anthropogenic disturbance while resting. Since FRDs have survived as a population in India, as in many other parts of the Global South for centuries, they provide a unique opportunity to study adaptation of animals to the human-dominated urban landscape. We documented factors impacting resting behaviour and site preferences in three states of India, for 284 dogs, leading to 6047 observations over 3 years. 7 physical parameters of the resting sites, along with the biological factors like mating and pup-rearing and time of day affected their choice of resting sites. The frequency-rank distribution of the unique combinations in which the parameters were selected followed a Power law distribution, which suggests underlying biological reasons for the observed preferences. Further, 3 of these parameters showed maximum consistency of choice in terms of the sub-parameters selected, explaining 30% of the observations. FRDs prefer to rest close to their resource sites within the territory, at a place that enabled maximum visibility of the surroundings. They chose such sites in the core of the territory for sleeping. At other times, they chose such sites away from the core, and were less restive, thus allowing for immediate response in case of intrusion or threat. They generally avoided anthropogenic disturbance for sleeping, and preferred areas with shade.Incorporating these aspects into urban management plans can promote human-dog cooperation and reduce situations of conflict. We envisage more inclusive urban areas in the future, that can allow for co-existence of the humans and their oldest companions in the commensal relationship that has been maintained for hundreds of generations of dogs in this part of the world. |
2403.18401 | Etienne Couturier | Wei-Yuan Kong, Antonio Mosciatti Jofr\'e, Manon Quiros,
Marie-B\'eatrice Bogeat-Triboulot, Evelyne Kolb, Etienne Couturier | Force generation by a cylindrical cell under stationary osmolytes
synthesis | null | null | null | null | q-bio.SC | http://creativecommons.org/licenses/by/4.0/ | Turgor is the driving force of plant growth, making possible for roots to
overcome soil resistance or for stems to counteract gravity. Maintaining a
constant growth rate while avoiding the cell content dilution, which would
progressively stop the inward water flux, imposes the production or import of
osmolytes in proportion to the increase of volume. We coin this phenomenon
stationary osmoregulation. The article explores the quantitative consequences
of this hypothesis on the interaction of a cylindrical cell growing axially
against an obstacle.
An instantaneous axial compression of a pressurized cylindrical cell
generates a force and a pressure jump which both decrease toward a lower value
once water has flowed out of the cell to reach the water potential equilibrium.
In a first part, the article derives analytical formula for these force and
over-pressure both before and after relaxation. In a second part, we describe
how the coupling of the Lockhart's growth law with the stationary
osmoregulation hypothesis predicts a transient slowdown in growth due to
contact before a re-acceleration in growth. We finally compare these
predictions with the output of an elastic growth model which ignores the
osmotic origin of growth: models only match in the early phase of contact for
high stiffness obstacle.
| [
{
"created": "Wed, 27 Mar 2024 09:42:56 GMT",
"version": "v1"
},
{
"created": "Wed, 3 Jul 2024 10:35:48 GMT",
"version": "v2"
}
] | 2024-07-04 | [
[
"Kong",
"Wei-Yuan",
""
],
[
"Jofré",
"Antonio Mosciatti",
""
],
[
"Quiros",
"Manon",
""
],
[
"Bogeat-Triboulot",
"Marie-Béatrice",
""
],
[
"Kolb",
"Evelyne",
""
],
[
"Couturier",
"Etienne",
""
]
] | Turgor is the driving force of plant growth, making possible for roots to overcome soil resistance or for stems to counteract gravity. Maintaining a constant growth rate while avoiding the cell content dilution, which would progressively stop the inward water flux, imposes the production or import of osmolytes in proportion to the increase of volume. We coin this phenomenon stationary osmoregulation. The article explores the quantitative consequences of this hypothesis on the interaction of a cylindrical cell growing axially against an obstacle. An instantaneous axial compression of a pressurized cylindrical cell generates a force and a pressure jump which both decrease toward a lower value once water has flowed out of the cell to reach the water potential equilibrium. In a first part, the article derives analytical formula for these force and over-pressure both before and after relaxation. In a second part, we describe how the coupling of the Lockhart's growth law with the stationary osmoregulation hypothesis predicts a transient slowdown in growth due to contact before a re-acceleration in growth. We finally compare these predictions with the output of an elastic growth model which ignores the osmotic origin of growth: models only match in the early phase of contact for high stiffness obstacle. |
1807.07632 | Ronald Fox | Ronald F. Fox | Critique of the Fox-Lu model for Hodgkin-Huxley fluctuations in neuron
ion channels | 13 pages | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Using a well known result that every FP equation has an antecedent Langevin
equation LE Fox and Lu proposed such a description for ion channels in 1994.
Their contraction followed the works of van Kampen and of T. Kurtz. The
contraction produces a diffusion term with a state dependent diffusion matrix,
D, that arises from the coupling matrix, S, in the LE. This S connected the
noise terms to the channel subunit variables in the LE. Fox and Lu and many
others later on observed that SS = D. Since D was determined by the contraction
of the MC equations into the FP equation, this left the problem of determining
the square root matrix, S, for every time step of the simulation. Since this is
time consuming, Fox and Lu introduced simplified models not requiring the
square root of a matrix. Subsequently, numerous studies were published that
showed the several shortcomings of these simplified models. In 2011, Goldwyn et
al. [6] rediscovered the overlooked original matrix dependent approach in the
Fox-Lu 1994 paper. They showed that it produced results in very good agreement
with the MC results. In 1991, Fox and Keizer [7] wrote a paper on an unrelated
topic that utilized the work of van Kampen and of Kurtz. In that work the
connection between D and S is SST = D. ST is the adjoint (transpose) of S. D
remains a positive definite symmetric matrix but S need not be. Fox has
reproduced the 2012 results of Orio and Soudry for potassium channels and has
also found in closed form the solution for the more complicated sodium
channels. The square root problem generally must be done numerically, but the
Cholesky is always doable in closed form. Thereby the S matrix for sodium is
given explicitly for the first time in this paper
| [
{
"created": "Wed, 18 Jul 2018 00:18:39 GMT",
"version": "v1"
},
{
"created": "Sat, 28 Jul 2018 12:10:58 GMT",
"version": "v2"
}
] | 2018-07-31 | [
[
"Fox",
"Ronald F.",
""
]
] | Using a well known result that every FP equation has an antecedent Langevin equation LE Fox and Lu proposed such a description for ion channels in 1994. Their contraction followed the works of van Kampen and of T. Kurtz. The contraction produces a diffusion term with a state dependent diffusion matrix, D, that arises from the coupling matrix, S, in the LE. This S connected the noise terms to the channel subunit variables in the LE. Fox and Lu and many others later on observed that SS = D. Since D was determined by the contraction of the MC equations into the FP equation, this left the problem of determining the square root matrix, S, for every time step of the simulation. Since this is time consuming, Fox and Lu introduced simplified models not requiring the square root of a matrix. Subsequently, numerous studies were published that showed the several shortcomings of these simplified models. In 2011, Goldwyn et al. [6] rediscovered the overlooked original matrix dependent approach in the Fox-Lu 1994 paper. They showed that it produced results in very good agreement with the MC results. In 1991, Fox and Keizer [7] wrote a paper on an unrelated topic that utilized the work of van Kampen and of Kurtz. In that work the connection between D and S is SST = D. ST is the adjoint (transpose) of S. D remains a positive definite symmetric matrix but S need not be. Fox has reproduced the 2012 results of Orio and Soudry for potassium channels and has also found in closed form the solution for the more complicated sodium channels. The square root problem generally must be done numerically, but the Cholesky is always doable in closed form. Thereby the S matrix for sodium is given explicitly for the first time in this paper |
1603.00904 | Vince Grolmusz | Bal\'azs Szalkai, B\'alint Varga, Vince Grolmusz | The Graph of Our Mind | arXiv admin note: substantial text overlap with arXiv:1512.01156,
arXiv:1501.00727 | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Graph theory in the last two decades penetrated sociology, molecular biology,
genetics, chemistry, computer engineering, and numerous other fields of
science. One of the more recent areas of its applications is the study of the
connections of the human brain. By the development of diffusion magnetic
resonance imaging (diffusion MRI), it is possible today to map the connections
between the 1-1.5 cm$^2$ regions of the gray matter of the human brain. These
connections can be viewed as a graph: the vertices are the anatomically
identified regions of the gray matter, and two vertices are connected by an
edge if the diffusion MRI-based workflow finds neuronal fiber tracts between
these areas. This way we can compute 1015-vertex graphs with tens of thousands
of edges. In a previous work, we have analyzed the male and female braingraphs
graph-theoretically, and we have found statistically significant differences in
numerous parameters between the sexes: the female braingraphs are better
expanders, have more edges, larger bipartition widths, and larger vertex cover
than the braingraphs of the male subjects. Our previous study has applied the
data of 96 subjects; here we present a much larger study of 426 subjects. Our
data source is an NIH-founded project, the "Human Connectome Project (HCP)"
public data release. As a service to the community, we have also made all of
the braingraphs computed by us from the HCP data publicly available at the
\url{http://braingraph.org} for independent validation and further
investigations.
| [
{
"created": "Wed, 2 Mar 2016 21:52:50 GMT",
"version": "v1"
},
{
"created": "Tue, 17 Mar 2020 22:35:59 GMT",
"version": "v2"
}
] | 2020-03-19 | [
[
"Szalkai",
"Balázs",
""
],
[
"Varga",
"Bálint",
""
],
[
"Grolmusz",
"Vince",
""
]
] | Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study of the connections of the human brain. By the development of diffusion magnetic resonance imaging (diffusion MRI), it is possible today to map the connections between the 1-1.5 cm$^2$ regions of the gray matter of the human brain. These connections can be viewed as a graph: the vertices are the anatomically identified regions of the gray matter, and two vertices are connected by an edge if the diffusion MRI-based workflow finds neuronal fiber tracts between these areas. This way we can compute 1015-vertex graphs with tens of thousands of edges. In a previous work, we have analyzed the male and female braingraphs graph-theoretically, and we have found statistically significant differences in numerous parameters between the sexes: the female braingraphs are better expanders, have more edges, larger bipartition widths, and larger vertex cover than the braingraphs of the male subjects. Our previous study has applied the data of 96 subjects; here we present a much larger study of 426 subjects. Our data source is an NIH-founded project, the "Human Connectome Project (HCP)" public data release. As a service to the community, we have also made all of the braingraphs computed by us from the HCP data publicly available at the \url{http://braingraph.org} for independent validation and further investigations. |
2308.16713 | Sheng Xu | Hongtai Jing, Zhengtao Gao, Sheng Xu, Tao Shen, Zhangzhi Peng, Shwai
He, Tao You, Shuang Ye, Wei Lin, Siqi Sun | Accurate Prediction of Antibody Function and Structure Using
Bio-Inspired Antibody Language Model | null | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In recent decades, antibodies have emerged as indispensable therapeutics for
combating diseases, particularly viral infections. However, their development
has been hindered by limited structural information and labor-intensive
engineering processes. Fortunately, significant advancements in deep learning
methods have facilitated the precise prediction of protein structure and
function by leveraging co-evolution information from homologous proteins.
Despite these advances, predicting the conformation of antibodies remains
challenging due to their unique evolution and the high flexibility of their
antigen-binding regions. Here, to address this challenge, we present the
Bio-inspired Antibody Language Model (BALM). This model is trained on a vast
dataset comprising 336 million 40% non-redundant unlabeled antibody sequences,
capturing both unique and conserved properties specific to antibodies. Notably,
BALM showcases exceptional performance across four antigen-binding prediction
tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM,
capable of swiftly predicting full atomic antibody structures from individual
sequences. Remarkably, BALMFold outperforms those well-established methods like
AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark,
demonstrating significant potential to advance innovative engineering and
streamline therapeutic antibody development by reducing the need for
unnecessary trials.
| [
{
"created": "Thu, 31 Aug 2023 13:26:41 GMT",
"version": "v1"
}
] | 2023-09-01 | [
[
"Jing",
"Hongtai",
""
],
[
"Gao",
"Zhengtao",
""
],
[
"Xu",
"Sheng",
""
],
[
"Shen",
"Tao",
""
],
[
"Peng",
"Zhangzhi",
""
],
[
"He",
"Shwai",
""
],
[
"You",
"Tao",
""
],
[
"Ye",
"Shuang",
""
],
[
"Lin",
"Wei",
""
],
[
"Sun",
"Siqi",
""
]
] | In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Antibody Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% non-redundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials. |
1804.03309 | Alessandro Bravetti | Alessandro Bravetti, Pablo Padilla | Thermodynamics and evolutionary biology through optimal control | 14 pages, comments are welcome | null | null | null | q-bio.PE math.OC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider a particular instance of the lift of controlled systems recently
proposed in the theory of irreversible thermodynamics and show that it leads to
a variational principle for an optimal control in the sense of Pontryagin. Then
we focus on two important applications: in thermodynamics and in evolutionary
biology. In the thermodynamic context, we show that this principle provides a
dynamical implementation of the Second Law, which stabilizes the equilibrium
manifold of a system. In the evolutionary context, we discuss several
interesting features: it provides a robust scheme for the coevolution of the
population and its fitness landscape; it has a clear informational
interpretation; it recovers Price equation naturally; and finally, it extends
standard evolutionary dynamics to include phenomena such as the emergence of
cooperation and the coexistence of qualitatively different phases of evolution,
which we speculate can be associated with Darwinism and punctuated equilibria.
| [
{
"created": "Tue, 10 Apr 2018 02:03:13 GMT",
"version": "v1"
}
] | 2018-04-11 | [
[
"Bravetti",
"Alessandro",
""
],
[
"Padilla",
"Pablo",
""
]
] | We consider a particular instance of the lift of controlled systems recently proposed in the theory of irreversible thermodynamics and show that it leads to a variational principle for an optimal control in the sense of Pontryagin. Then we focus on two important applications: in thermodynamics and in evolutionary biology. In the thermodynamic context, we show that this principle provides a dynamical implementation of the Second Law, which stabilizes the equilibrium manifold of a system. In the evolutionary context, we discuss several interesting features: it provides a robust scheme for the coevolution of the population and its fitness landscape; it has a clear informational interpretation; it recovers Price equation naturally; and finally, it extends standard evolutionary dynamics to include phenomena such as the emergence of cooperation and the coexistence of qualitatively different phases of evolution, which we speculate can be associated with Darwinism and punctuated equilibria. |
2103.14978 | Z\"ulal Bing\"ol | Z\"ulal Bing\"ol, Mohammed Alser, Onur Mutlu, Ozcan Ozturk, Can Alkan | GateKeeper-GPU: Fast and Accurate Pre-Alignment Filtering in Short Read
Mapping | 26 pages | IEEE Transactions on Computers, 73 (5): 1206-1218, 2024 | 10.1109/TC.2024.3365931 | null | q-bio.GN cs.AR | http://creativecommons.org/licenses/by-nc-sa/4.0/ | At the last step of short read mapping, the candidate locations of the reads
on the reference genome are verified to compute their differences from the
corresponding reference segments using sequence alignment algorithms.
Calculating the similarities and differences between two sequences is still
computationally expensive since approximate string matching techniques
traditionally inherit dynamic programming algorithms with quadratic time and
space complexity. We introduce GateKeeper-GPU, a fast and accurate
pre-alignment filter that efficiently reduces the need for expensive sequence
alignment. GateKeeper-GPU provides two main contributions: first, improving the
filtering accuracy of GateKeeper (a lightweight pre-alignment filter), and
second, exploiting the massive parallelism provided by the large number of GPU
threads of modern GPUs to examine numerous sequence pairs rapidly and
concurrently. By reducing the work, GateKeeper-GPU provides an acceleration of
2.9x to sequence alignment and up to 1.4x speedup to the end-to-end execution
time of a comprehensive read mapper (mrFAST). GateKeeper-GPU is available at
https://github.com/BilkentCompGen/GateKeeper-GPU.
| [
{
"created": "Sat, 27 Mar 2021 20:01:37 GMT",
"version": "v1"
},
{
"created": "Wed, 31 Mar 2021 08:55:06 GMT",
"version": "v2"
},
{
"created": "Thu, 22 Feb 2024 12:26:02 GMT",
"version": "v3"
}
] | 2024-07-04 | [
[
"Bingöl",
"Zülal",
""
],
[
"Alser",
"Mohammed",
""
],
[
"Mutlu",
"Onur",
""
],
[
"Ozturk",
"Ozcan",
""
],
[
"Alkan",
"Can",
""
]
] | At the last step of short read mapping, the candidate locations of the reads on the reference genome are verified to compute their differences from the corresponding reference segments using sequence alignment algorithms. Calculating the similarities and differences between two sequences is still computationally expensive since approximate string matching techniques traditionally inherit dynamic programming algorithms with quadratic time and space complexity. We introduce GateKeeper-GPU, a fast and accurate pre-alignment filter that efficiently reduces the need for expensive sequence alignment. GateKeeper-GPU provides two main contributions: first, improving the filtering accuracy of GateKeeper (a lightweight pre-alignment filter), and second, exploiting the massive parallelism provided by the large number of GPU threads of modern GPUs to examine numerous sequence pairs rapidly and concurrently. By reducing the work, GateKeeper-GPU provides an acceleration of 2.9x to sequence alignment and up to 1.4x speedup to the end-to-end execution time of a comprehensive read mapper (mrFAST). GateKeeper-GPU is available at https://github.com/BilkentCompGen/GateKeeper-GPU. |
1310.4946 | Philippe Terrier PhD | Fabienne Reynard and Philippe Terrier | Local dynamic stability of treadmill walking: intrasession and
week-to-week repeatability | author's version of a manuscript accepted for publication in the
journal of biomechanics | J Biomech. 2014 Jan 3;47(1):74-80 | 10.1016/j.jbiomech.2013.10.011 | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Repetitive falls degrade the quality of life of elderly people and of
patients suffering of various neurological disorders. In order to prevent falls
while walking, one should rely on relevant early indicators of impaired dynamic
balance. The local dynamic stability (LDS) represents the sensitivity of gait
to small perturbations: divergence exponents (maximal Lyapunov exponents)
assess how fast a dynamical system diverges from neighbor points. Although
numerous findings attest the validity of LDS as a fall risk index, reliability
results are still sparse. The present study explores the intrasession and
intersession repeatability of gait LDS using intraclass correlation
coefficients (ICC) and standard error of measurement (SEM). Ninety-five healthy
individuals performed 5min. treadmill walking in two sessions separated by 9
days. Trunk acceleration was measured with a 3D accelerometer. Three time
scales were used to estimate LDS: over 4 to 10 strides ({\lambda}4-10), over
one stride ({\lambda}1) and over one step ({\lambda}0.5). The intrasession
repeatability was assessed from three repetitions of either 35 strides or 70
strides taken within the 5min tests. The intersession repeatability compared
the two sessions, which totalized 210 strides. The intrasession ICCs
(70-strides estimates/35-strides estimates) were 0.52/0.18 for {\lambda}4-10
and 0.84/0.77 for {\lambda}1 and {\lambda}0.5. The intersession ICCs were
around 0.60. The SEM results revealed that {\lambda}0.5 measured in
medio-lateral direction exhibited the best reliability, sufficient to detect
moderate changes at individual level (20%). However, due to the low
intersession repeatability, one should average several measurements taken on
different days in order to better approximate the true LDS.
| [
{
"created": "Fri, 18 Oct 2013 08:39:45 GMT",
"version": "v1"
}
] | 2014-02-17 | [
[
"Reynard",
"Fabienne",
""
],
[
"Terrier",
"Philippe",
""
]
] | Repetitive falls degrade the quality of life of elderly people and of patients suffering of various neurological disorders. In order to prevent falls while walking, one should rely on relevant early indicators of impaired dynamic balance. The local dynamic stability (LDS) represents the sensitivity of gait to small perturbations: divergence exponents (maximal Lyapunov exponents) assess how fast a dynamical system diverges from neighbor points. Although numerous findings attest the validity of LDS as a fall risk index, reliability results are still sparse. The present study explores the intrasession and intersession repeatability of gait LDS using intraclass correlation coefficients (ICC) and standard error of measurement (SEM). Ninety-five healthy individuals performed 5min. treadmill walking in two sessions separated by 9 days. Trunk acceleration was measured with a 3D accelerometer. Three time scales were used to estimate LDS: over 4 to 10 strides ({\lambda}4-10), over one stride ({\lambda}1) and over one step ({\lambda}0.5). The intrasession repeatability was assessed from three repetitions of either 35 strides or 70 strides taken within the 5min tests. The intersession repeatability compared the two sessions, which totalized 210 strides. The intrasession ICCs (70-strides estimates/35-strides estimates) were 0.52/0.18 for {\lambda}4-10 and 0.84/0.77 for {\lambda}1 and {\lambda}0.5. The intersession ICCs were around 0.60. The SEM results revealed that {\lambda}0.5 measured in medio-lateral direction exhibited the best reliability, sufficient to detect moderate changes at individual level (20%). However, due to the low intersession repeatability, one should average several measurements taken on different days in order to better approximate the true LDS. |
1903.08105 | Steffen Wolf | Matthias Post, Steffen Wolf, Gerhard Stock | Principal component analysis of nonequilibrium molecular dynamics
simulations | This article may be downloaded for personal use only. Any other use
requires prior permission of the author and AIP Publishing. This article
appeared in J. Chem. Phys., 150(20), 204110 and may be found at
https://aip.scitation.org/doi/10.1063/1.5089636 | J. Chem. Phys., 150(20), 204110 (2019) | 10.1063/1.5089636 | null | q-bio.BM cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Principal component analysis (PCA) represents a standard approach to identify
collective variables $\{x_i\}\!=\!\boldsymbol{x}$, which can be used to
construct the free energy landscape $\Delta G(\boldsymbol{x})$ of a molecular
system. While PCA is routinely applied to equilibrium molecular dynamics (MD)
simulations, it is less obvious how to extend the approach to nonequilibrium
simulation techniques. This includes, e.g., the definition of the statistical
averages employed in PCA, as well as the relation between the equilibrium free
energy landscape $\Delta G(\boldsymbol{x})$ and energy landscapes $\Delta{\cal
G} (\boldsymbol{x})$ obtained from nonequilibrium MD. As an example for a
nonequilibrium method, `targeted MD' is considered which employs a moving
distance constraint to enforce rare transitions along some biasing coordinate
$s$. The introduced bias can be described by a weighting function $P(s)$, which
provides a direct relation between equilibrium and nonequilibrium data, and
thus establishes a well-defined way to perform PCA on nonequilibrium data.
While the resulting distribution ${\cal P}(\boldsymbol{x})$ and energy
$\Delta{\cal G} \propto \ln {\cal P}$ will not reflect the equilibrium state of
the system, the nonequilibrium energy landscape $\Delta{\cal G}
(\boldsymbol{x})$ may directly reveal the molecular reaction mechanism. Applied
to targeted MD simulations of the unfolding of decaalanine, for example, a PCA
performed on backbone dihedral angles is shown to discriminate several
unfolding pathways. Although the formulation is in principle exact, its
practical use depends critically on the choice of the biasing coordinate $s$,
which should account for a naturally occurring motion between two well-defined
end-states of the system.
| [
{
"created": "Tue, 19 Mar 2019 16:50:37 GMT",
"version": "v1"
},
{
"created": "Thu, 2 May 2019 15:42:48 GMT",
"version": "v2"
},
{
"created": "Wed, 29 May 2019 10:43:47 GMT",
"version": "v3"
}
] | 2019-05-30 | [
[
"Post",
"Matthias",
""
],
[
"Wolf",
"Steffen",
""
],
[
"Stock",
"Gerhard",
""
]
] | Principal component analysis (PCA) represents a standard approach to identify collective variables $\{x_i\}\!=\!\boldsymbol{x}$, which can be used to construct the free energy landscape $\Delta G(\boldsymbol{x})$ of a molecular system. While PCA is routinely applied to equilibrium molecular dynamics (MD) simulations, it is less obvious how to extend the approach to nonequilibrium simulation techniques. This includes, e.g., the definition of the statistical averages employed in PCA, as well as the relation between the equilibrium free energy landscape $\Delta G(\boldsymbol{x})$ and energy landscapes $\Delta{\cal G} (\boldsymbol{x})$ obtained from nonequilibrium MD. As an example for a nonequilibrium method, `targeted MD' is considered which employs a moving distance constraint to enforce rare transitions along some biasing coordinate $s$. The introduced bias can be described by a weighting function $P(s)$, which provides a direct relation between equilibrium and nonequilibrium data, and thus establishes a well-defined way to perform PCA on nonequilibrium data. While the resulting distribution ${\cal P}(\boldsymbol{x})$ and energy $\Delta{\cal G} \propto \ln {\cal P}$ will not reflect the equilibrium state of the system, the nonequilibrium energy landscape $\Delta{\cal G} (\boldsymbol{x})$ may directly reveal the molecular reaction mechanism. Applied to targeted MD simulations of the unfolding of decaalanine, for example, a PCA performed on backbone dihedral angles is shown to discriminate several unfolding pathways. Although the formulation is in principle exact, its practical use depends critically on the choice of the biasing coordinate $s$, which should account for a naturally occurring motion between two well-defined end-states of the system. |
1701.00330 | Mainak Pal | Indrani Bose, Mainak Pal and Chiranjit Karmakar | Allee dynamics: Growth, extinction and range expansion | 11 pages, International Journal of Modern Physics C (2017) | null | 10.1142/S0129183117500747 | null | q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In population biology, the Allee dynamics refer to negative growth rates
below a critical population density. In this Letter, we study a
reaction-diffusion (RD) model of population growth and dispersion in one
dimension, which incorporates the Allee effect in both the growth and mortality
rates. In the absence of diffusion, the bifurcation diagram displays regions of
both finite population density and zero population density, i.e., extinction.
The early signatures of the transition to extinction at a bifurcation point are
computed in the presence of additive noise. For the full RD model, the
existence of travelling wave solutions of the population density is
demonstrated. The parameter regimes in which the travelling wave advances
(range expansion) and retreats are identified. In the weak Allee regime, the
transition from the pushed to the pulled wave is shown as a function of the
mortality rate constant. The results obtained are in agreement with the recent
experimental observations on budding yeast populations.
| [
{
"created": "Mon, 2 Jan 2017 08:05:49 GMT",
"version": "v1"
},
{
"created": "Mon, 12 Jun 2017 10:41:22 GMT",
"version": "v2"
}
] | 2017-08-02 | [
[
"Bose",
"Indrani",
""
],
[
"Pal",
"Mainak",
""
],
[
"Karmakar",
"Chiranjit",
""
]
] | In population biology, the Allee dynamics refer to negative growth rates below a critical population density. In this Letter, we study a reaction-diffusion (RD) model of population growth and dispersion in one dimension, which incorporates the Allee effect in both the growth and mortality rates. In the absence of diffusion, the bifurcation diagram displays regions of both finite population density and zero population density, i.e., extinction. The early signatures of the transition to extinction at a bifurcation point are computed in the presence of additive noise. For the full RD model, the existence of travelling wave solutions of the population density is demonstrated. The parameter regimes in which the travelling wave advances (range expansion) and retreats are identified. In the weak Allee regime, the transition from the pushed to the pulled wave is shown as a function of the mortality rate constant. The results obtained are in agreement with the recent experimental observations on budding yeast populations. |
2201.02668 | Alan Rogers | Alan R. Rogers | Using Genetic Data to Build Intuition about Population History | 9 pages, 7 figures | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Genetic data are now routinely used to study the history of population size,
subdivision, and gene flow. A variety of formal statistical methods is
available for testing hypotheses and fitting models to data. Yet it is often
unclear which hypotheses are worth testing, which models worth fitting. There
is a need for less formal methods that can be used in exploratory analysis of
genetic data. One approach to this problem uses *nucleotide site patterns*,
which provide a simple summary of the pattern in genetic data. This article
shows how to use them in exploratory data analysis.
| [
{
"created": "Fri, 7 Jan 2022 20:33:50 GMT",
"version": "v1"
}
] | 2022-01-11 | [
[
"Rogers",
"Alan R.",
""
]
] | Genetic data are now routinely used to study the history of population size, subdivision, and gene flow. A variety of formal statistical methods is available for testing hypotheses and fitting models to data. Yet it is often unclear which hypotheses are worth testing, which models worth fitting. There is a need for less formal methods that can be used in exploratory analysis of genetic data. One approach to this problem uses *nucleotide site patterns*, which provide a simple summary of the pattern in genetic data. This article shows how to use them in exploratory data analysis. |
1310.8268 | Bradly Alicea | Bradly Alicea | Cellular decision-making bias: the missing ingredient in cell functional
diversity | 18 pages; 6 figures, 2 tables, 4 supplemental figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cell functional diversity is a significant determinant on how biological
processes unfold. Most accounts of diversity involve a search for sequence or
expression differences. Perhaps there are more subtle mechanisms at work. Using
the metaphor of information processing and decision-making might provide a
clearer view of these subtleties. Understanding adaptive and transformative
processes (such as cellular reprogramming) as a series of simple decisions
allows us to use a technique called cellular signal detection theory (cellular
SDT) to detect potential bias in mechanisms that favor one outcome over
another. We can apply method of detecting cellular reprogramming bias to
cellular reprogramming and other complex molecular processes. To demonstrate
scope of this method, we will critically examine differences between cell
phenotypes reprogrammed to muscle fiber and neuron phenotypes. In cases where
the signature of phenotypic bias is cryptic, signatures of genomic bias
(pre-existing and induced) may provide an alternative. The examination of these
alternates will be explored using data from a series of fibroblast cell lines
before cellular reprogramming (pre-existing) and differences between fractions
of cellular RNA for individual genes after drug treatment (induced). In
conclusion, the usefulness and limitations of this method and associated
analogies will be discussed.
| [
{
"created": "Wed, 30 Oct 2013 19:05:03 GMT",
"version": "v1"
},
{
"created": "Sat, 2 Nov 2013 19:00:34 GMT",
"version": "v2"
}
] | 2013-11-05 | [
[
"Alicea",
"Bradly",
""
]
] | Cell functional diversity is a significant determinant on how biological processes unfold. Most accounts of diversity involve a search for sequence or expression differences. Perhaps there are more subtle mechanisms at work. Using the metaphor of information processing and decision-making might provide a clearer view of these subtleties. Understanding adaptive and transformative processes (such as cellular reprogramming) as a series of simple decisions allows us to use a technique called cellular signal detection theory (cellular SDT) to detect potential bias in mechanisms that favor one outcome over another. We can apply method of detecting cellular reprogramming bias to cellular reprogramming and other complex molecular processes. To demonstrate scope of this method, we will critically examine differences between cell phenotypes reprogrammed to muscle fiber and neuron phenotypes. In cases where the signature of phenotypic bias is cryptic, signatures of genomic bias (pre-existing and induced) may provide an alternative. The examination of these alternates will be explored using data from a series of fibroblast cell lines before cellular reprogramming (pre-existing) and differences between fractions of cellular RNA for individual genes after drug treatment (induced). In conclusion, the usefulness and limitations of this method and associated analogies will be discussed. |
2004.14949 | Kexin Huang | Kexin Huang, Cao Xiao, Lucas Glass, Marinka Zitnik, Jimeng Sun | SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks | Published in Nature Scientific Reports:
https://www.nature.com/articles/s41598-020-77766-9 | null | null | null | q-bio.MN cs.LG | http://creativecommons.org/licenses/by/4.0/ | Molecular interaction networks are powerful resources for the discovery. They
are increasingly used with machine learning methods to predict biologically
meaningful interactions. While deep learning on graphs has dramatically
advanced the prediction prowess, current graph neural network (GNN) methods are
optimized for prediction on the basis of direct similarity between interacting
nodes. In biological networks, however, similarity between nodes that do not
directly interact has proved incredibly useful in the last decade across a
variety of interaction networks. Here, we present SkipGNN, a graph neural
network approach for the prediction of molecular interactions. SkipGNN predicts
molecular interactions by not only aggregating information from direct
interactions but also from second-order interactions, which we call skip
similarity. In contrast to existing GNNs, SkipGNN receives neural messages from
two-hop neighbors as well as immediate neighbors in the interaction network and
non-linearly transforms the messages to obtain useful information for
prediction. To inject skip similarity into a GNN, we construct a modified
version of the original network, called the skip graph. We then develop an
iterative fusion scheme that optimizes a GNN using both the skip graph and the
original graph. Experiments on four interaction networks, including drug-drug,
drug-target, protein-protein, and gene-disease interactions, show that SkipGNN
achieves superior and robust performance, outperforming existing methods by up
to 28.8\% of area under the precision recall curve (PR-AUC). Furthermore, we
show that unlike popular GNNs, SkipGNN learns biologically meaningful
embeddings and performs especially well on noisy, incomplete interaction
networks.
| [
{
"created": "Thu, 30 Apr 2020 16:55:58 GMT",
"version": "v1"
},
{
"created": "Wed, 9 Dec 2020 18:31:39 GMT",
"version": "v2"
}
] | 2020-12-10 | [
[
"Huang",
"Kexin",
""
],
[
"Xiao",
"Cao",
""
],
[
"Glass",
"Lucas",
""
],
[
"Zitnik",
"Marinka",
""
],
[
"Sun",
"Jimeng",
""
]
] | Molecular interaction networks are powerful resources for the discovery. They are increasingly used with machine learning methods to predict biologically meaningful interactions. While deep learning on graphs has dramatically advanced the prediction prowess, current graph neural network (GNN) methods are optimized for prediction on the basis of direct similarity between interacting nodes. In biological networks, however, similarity between nodes that do not directly interact has proved incredibly useful in the last decade across a variety of interaction networks. Here, we present SkipGNN, a graph neural network approach for the prediction of molecular interactions. SkipGNN predicts molecular interactions by not only aggregating information from direct interactions but also from second-order interactions, which we call skip similarity. In contrast to existing GNNs, SkipGNN receives neural messages from two-hop neighbors as well as immediate neighbors in the interaction network and non-linearly transforms the messages to obtain useful information for prediction. To inject skip similarity into a GNN, we construct a modified version of the original network, called the skip graph. We then develop an iterative fusion scheme that optimizes a GNN using both the skip graph and the original graph. Experiments on four interaction networks, including drug-drug, drug-target, protein-protein, and gene-disease interactions, show that SkipGNN achieves superior and robust performance, outperforming existing methods by up to 28.8\% of area under the precision recall curve (PR-AUC). Furthermore, we show that unlike popular GNNs, SkipGNN learns biologically meaningful embeddings and performs especially well on noisy, incomplete interaction networks. |
2301.08996 | Lingyun Xiong | Lingyun Xiong, Alan Garfinkel | Are physiological oscillations 'physiological'? | null | null | null | null | q-bio.TO q-bio.CB q-bio.SC | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Despite widespread and striking examples of physiological oscillations, their
functional role is often unclear. Even glycolysis, the paradigm example of
oscillatory biochemistry, has seen questions about its oscillatory function.
Here, we take a systems approach to summarize evidence that oscillations play
critical physiological roles. Oscillatory behavior enables systems to avoid
desensitization, to avoid chronically high and therefore toxic levels of
chemicals, and to become more resistant to noise. Oscillation also enables
complex physiological systems to reconcile incompatible conditions such as
oxidation and reduction, by cycling between them, and to synchronize the
oscillations of many small units into one large effect. In pancreatic beta
cells, glycolytic oscillations are in synchrony with calcium and mitochondrial
oscillations to drive pulsatile insulin release, which is pivotal for the liver
to regulate blood glucose dynamics. In addition, oscillation can keep
biological time, essential for embryonic development in promoting cell
diversity and pattern formation. The functional importance of oscillatory
processes requires a rethinking of the traditional doctrine of homeostasis,
holding that physiological quantities are maintained at constant equilibrium
values, a view that has largely failed us in the clinic. A more dynamic
approach will enable us to view health and disease through a new light and
initiate a paradigm shift in treating diseases, including depression and
cancer. This modern synthesis also takes a deeper look into the mechanisms that
create, sustain and abolish oscillatory processes, which requires the language
of nonlinear dynamics, well beyond the linearization techniques of equilibrium
control theory.
| [
{
"created": "Sat, 21 Jan 2023 19:31:36 GMT",
"version": "v1"
},
{
"created": "Tue, 24 Jan 2023 22:43:14 GMT",
"version": "v2"
}
] | 2023-01-26 | [
[
"Xiong",
"Lingyun",
""
],
[
"Garfinkel",
"Alan",
""
]
] | Despite widespread and striking examples of physiological oscillations, their functional role is often unclear. Even glycolysis, the paradigm example of oscillatory biochemistry, has seen questions about its oscillatory function. Here, we take a systems approach to summarize evidence that oscillations play critical physiological roles. Oscillatory behavior enables systems to avoid desensitization, to avoid chronically high and therefore toxic levels of chemicals, and to become more resistant to noise. Oscillation also enables complex physiological systems to reconcile incompatible conditions such as oxidation and reduction, by cycling between them, and to synchronize the oscillations of many small units into one large effect. In pancreatic beta cells, glycolytic oscillations are in synchrony with calcium and mitochondrial oscillations to drive pulsatile insulin release, which is pivotal for the liver to regulate blood glucose dynamics. In addition, oscillation can keep biological time, essential for embryonic development in promoting cell diversity and pattern formation. The functional importance of oscillatory processes requires a rethinking of the traditional doctrine of homeostasis, holding that physiological quantities are maintained at constant equilibrium values, a view that has largely failed us in the clinic. A more dynamic approach will enable us to view health and disease through a new light and initiate a paradigm shift in treating diseases, including depression and cancer. This modern synthesis also takes a deeper look into the mechanisms that create, sustain and abolish oscillatory processes, which requires the language of nonlinear dynamics, well beyond the linearization techniques of equilibrium control theory. |
2107.11075 | Ofer Feinerman | Efrat Greenwald, Lior Baltiansky, Ofer Feinerman | Individual crop loads provide local control for collective food intake
in ant colonies | null | Elife 7 (2018): e31730 | 10.7554/eLife.31730 | null | q-bio.PE physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Nutritional regulation by ants emerges from a distributed process: food is
collected by a small fraction of workers, stored within the crops of
individuals, and spreads via local ant-to-ant interactions. The precise
individual level underpinnings of this collective regulation have remained
unclear mainly due to difficulties in measuring food within ants crops. Here we
image fluorescent liquid food in individually tagged Camponotus sanctus ants,
and track the real-time food flow from foragers to their gradually satiating
colonies. We show how the feedback between colony satiation level and food
inflow is mediated by individual crop loads; specifically, the crop loads of
recipient ants control food flow rates, while those of foragers regulate the
frequency of foraging trips. Interestingly, these effects do not rise from pure
physical limitations of crop capacity. Our findings suggest that the emergence
of food intake regulation does not require individual foragers to assess the
global state of the colony.
| [
{
"created": "Fri, 23 Jul 2021 08:35:48 GMT",
"version": "v1"
}
] | 2021-07-26 | [
[
"Greenwald",
"Efrat",
""
],
[
"Baltiansky",
"Lior",
""
],
[
"Feinerman",
"Ofer",
""
]
] | Nutritional regulation by ants emerges from a distributed process: food is collected by a small fraction of workers, stored within the crops of individuals, and spreads via local ant-to-ant interactions. The precise individual level underpinnings of this collective regulation have remained unclear mainly due to difficulties in measuring food within ants crops. Here we image fluorescent liquid food in individually tagged Camponotus sanctus ants, and track the real-time food flow from foragers to their gradually satiating colonies. We show how the feedback between colony satiation level and food inflow is mediated by individual crop loads; specifically, the crop loads of recipient ants control food flow rates, while those of foragers regulate the frequency of foraging trips. Interestingly, these effects do not rise from pure physical limitations of crop capacity. Our findings suggest that the emergence of food intake regulation does not require individual foragers to assess the global state of the colony. |
1608.04433 | Daniel Breen | Daniel Breen, Sasha Shirman, Eve Armstrong, Nirag Kadakia, Henry
Abarbanel | HVC Interneuron Properties from Statistical Data Assimilation | 28 pages, 32 figures. Not yet submitted to any journal | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Data assimilation (DA) solves the inverse problem of inferring initial
conditions given data and a model. Here we use biophysically motivated
Hodgkin-Huxley (HH) models of avian HVCI neurons, experimentally obtained
recordings of these neurons, and our data assimilation algorithm to infer the
full set of parameters and a minimal set of ionic currents precisely
reproducing the observed waveform information. We find many distinct validated
sets of parameters selected by our DA method and choice of model. We conclude
exploring variations on the inverse problem applied to neurons producing
accurate or inaccurate results; by manipulating data presented to the
algorithm, varying sample rate and waveform; and by manipulating the model by
adding and subtracting ionic currents.
| [
{
"created": "Mon, 15 Aug 2016 23:02:29 GMT",
"version": "v1"
}
] | 2016-08-17 | [
[
"Breen",
"Daniel",
""
],
[
"Shirman",
"Sasha",
""
],
[
"Armstrong",
"Eve",
""
],
[
"Kadakia",
"Nirag",
""
],
[
"Abarbanel",
"Henry",
""
]
] | Data assimilation (DA) solves the inverse problem of inferring initial conditions given data and a model. Here we use biophysically motivated Hodgkin-Huxley (HH) models of avian HVCI neurons, experimentally obtained recordings of these neurons, and our data assimilation algorithm to infer the full set of parameters and a minimal set of ionic currents precisely reproducing the observed waveform information. We find many distinct validated sets of parameters selected by our DA method and choice of model. We conclude exploring variations on the inverse problem applied to neurons producing accurate or inaccurate results; by manipulating data presented to the algorithm, varying sample rate and waveform; and by manipulating the model by adding and subtracting ionic currents. |
2303.02678 | McCullen Sandora | McCullen Sandora, Vladimir Airapetian, Luke Barnes, Geraint F. Lewis,
Ileana P\'erez-Rodr\'iguez | Multiverse Predictions for Habitability: Origin of Life Scenarios | 27 pages, 4 figures | Universe 2023, 9, 42 | 10.3390/universe9010042 | null | q-bio.PE astro-ph.EP physics.bio-ph | http://creativecommons.org/licenses/by/4.0/ | If the origin of life is rare and sensitive to the local conditions at the
site of its emergence, then, using the principle of mediocrity within a
multiverse framework, we may expect to find ourselves in a universe that is
better than usual at creating these necessary conditions. We use this reasoning
to investigate several origin of life scenarios to determine whether they are
compatible with the multiverse, including the prebiotic soup scenario,
hydrothermal vents, delivery of prebiotic material from impacts, and
panspermia. We find that most of these scenarios induce a preference toward
weaker-gravity universes, and that panspermia and scenarios involving solar
radiation or large impacts as a disequilibrium source are disfavored.
Additionally, we show that several hypothesized habitability criteria which are
disfavored when the origin of life is not taken into account become compatible
with the multiverse, and that the emergence of life and emergence of
intelligence cannot both be sensitive to disequilibrium production conditions.
| [
{
"created": "Sun, 5 Mar 2023 14:29:44 GMT",
"version": "v1"
}
] | 2023-03-07 | [
[
"Sandora",
"McCullen",
""
],
[
"Airapetian",
"Vladimir",
""
],
[
"Barnes",
"Luke",
""
],
[
"Lewis",
"Geraint F.",
""
],
[
"Pérez-Rodríguez",
"Ileana",
""
]
] | If the origin of life is rare and sensitive to the local conditions at the site of its emergence, then, using the principle of mediocrity within a multiverse framework, we may expect to find ourselves in a universe that is better than usual at creating these necessary conditions. We use this reasoning to investigate several origin of life scenarios to determine whether they are compatible with the multiverse, including the prebiotic soup scenario, hydrothermal vents, delivery of prebiotic material from impacts, and panspermia. We find that most of these scenarios induce a preference toward weaker-gravity universes, and that panspermia and scenarios involving solar radiation or large impacts as a disequilibrium source are disfavored. Additionally, we show that several hypothesized habitability criteria which are disfavored when the origin of life is not taken into account become compatible with the multiverse, and that the emergence of life and emergence of intelligence cannot both be sensitive to disequilibrium production conditions. |
1705.08246 | Thierry Mora | Quentin Marcou, Thierry Mora, Aleksandra M Walczak | IGoR: a tool for high-throughput immune repertoire analysis | null | Nature Communications 9, 561 (2018) | 10.1038/s41467-018-02832-w | null | q-bio.GN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | High throughput immune repertoire sequencing is promising to lead to new
statistical diagnostic tools for medicine and biology. Successful
implementations of these methods require a correct characterization, analysis
and interpretation of these datasets. We present IGoR -- a new comprehensive
tool that takes B or T-cell receptors sequence reads and quantitatively
characterizes the statistics of receptor generation from both cDNA and gDNA. It
probabilistically annotates sequences and its modular structure can investigate
models of increasing biological complexity for different organisms. For B-cells
IGoR returns the hypermutation statistics, which we use to reveal
co-localization of hypermutations along the sequence. We demonstrate that IGoR
outperforms existing tools in accuracy and estimate the sample sizes needed for
reliable repertoire characterization.
| [
{
"created": "Tue, 23 May 2017 13:37:19 GMT",
"version": "v1"
}
] | 2018-04-13 | [
[
"Marcou",
"Quentin",
""
],
[
"Mora",
"Thierry",
""
],
[
"Walczak",
"Aleksandra M",
""
]
] | High throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis and interpretation of these datasets. We present IGoR -- a new comprehensive tool that takes B or T-cell receptors sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can investigate models of increasing biological complexity for different organisms. For B-cells IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization. |
2108.00904 | Carlotta Langer | Carlotta Langer and Nihat Ay | How Morphological Computation shapes Integrated Information in Embodied
Agents | null | Front. Psychol. 12:716433 (2021) | 10.3389/fpsyg.2021.716433 | null | q-bio.NC cs.IT math.IT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Integrated Information Theory provides a quantitative approach to
consciousness and can be applied to neural networks. An embodied agent
controlled by such a network influences and is being influenced by its
environment. This involves, on the one hand, morphological computation within
goal directed action and, on the other hand, integrated information within the
controller, the agent's brain. In this article, we combine different methods in
order to examine the information flows among and within the body, the brain and
the environment of an agent. This allows us to relate various information flows
to each other. We test this framework in a simple experimental setup. There, we
calculate the optimal policy for goal-directed behavior based on the "planning
as inference" method, in which the information-geometric em-algorithm is used
to optimize the likelihood of the goal. Morphological computation and
integrated information are then calculated with respect to the optimal
policies. Comparing the dynamics of these measures under changing morphological
circumstances highlights the antagonistic relationship between these two
concepts. The more morphological computation is involved, the less information
integration within the brain is required. In order to determine the influence
of the brain on the behavior of the agent it is necessary to additionally
measure the information flow to and from the brain.
| [
{
"created": "Mon, 2 Aug 2021 13:48:45 GMT",
"version": "v1"
},
{
"created": "Thu, 23 Sep 2021 11:04:11 GMT",
"version": "v2"
},
{
"created": "Mon, 29 Nov 2021 08:02:17 GMT",
"version": "v3"
}
] | 2021-11-30 | [
[
"Langer",
"Carlotta",
""
],
[
"Ay",
"Nihat",
""
]
] | The Integrated Information Theory provides a quantitative approach to consciousness and can be applied to neural networks. An embodied agent controlled by such a network influences and is being influenced by its environment. This involves, on the one hand, morphological computation within goal directed action and, on the other hand, integrated information within the controller, the agent's brain. In this article, we combine different methods in order to examine the information flows among and within the body, the brain and the environment of an agent. This allows us to relate various information flows to each other. We test this framework in a simple experimental setup. There, we calculate the optimal policy for goal-directed behavior based on the "planning as inference" method, in which the information-geometric em-algorithm is used to optimize the likelihood of the goal. Morphological computation and integrated information are then calculated with respect to the optimal policies. Comparing the dynamics of these measures under changing morphological circumstances highlights the antagonistic relationship between these two concepts. The more morphological computation is involved, the less information integration within the brain is required. In order to determine the influence of the brain on the behavior of the agent it is necessary to additionally measure the information flow to and from the brain. |
q-bio/0506038 | Reiko Tanaka | Reiko Tanaka, Tau-Mu Yi and John Doyle | Some protein interaction data do not exhibit power law statistics | 4 pages, 2 figures | FEBS Letters 579 (2005) 514--5144 | 10.1016/j.febslet.2005.08.024 | null | q-bio.MN | null | It has been claimed that protein-protein interaction (PPI) networks are
scale-free based on the observation that the node degree sequence follows a
power law. Here we argue that these claims are likely to be based on erroneous
statistical analysis. Typically, the supporting data are presented using
frequency-degree plots. We show that such plots can be misleading, and should
correctly be replaced by rank-degree plots. We provide two PPI network examples
in which the frequency-degree plots appear linear on a log-log scale, but the
rank-degree plots demonstrate that the node degree sequence is far from a power
law. We conclude that at least these PPI networks are not scale-free.
| [
{
"created": "Mon, 27 Jun 2005 04:28:36 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Tanaka",
"Reiko",
""
],
[
"Yi",
"Tau-Mu",
""
],
[
"Doyle",
"John",
""
]
] | It has been claimed that protein-protein interaction (PPI) networks are scale-free based on the observation that the node degree sequence follows a power law. Here we argue that these claims are likely to be based on erroneous statistical analysis. Typically, the supporting data are presented using frequency-degree plots. We show that such plots can be misleading, and should correctly be replaced by rank-degree plots. We provide two PPI network examples in which the frequency-degree plots appear linear on a log-log scale, but the rank-degree plots demonstrate that the node degree sequence is far from a power law. We conclude that at least these PPI networks are not scale-free. |
1908.05693 | Irem Altan | Irem Altan, Jennifer McManus, Patrick Charbonneau | Using schematic models to understand the microscopic basis for inverted
solubility in $\gamma$D-crystallin | null | The Journal of Physical Chemistry B 2019 123 (47), 10061-10072 | 10.1021/acs.jpcb.9b07774 | null | q-bio.BM cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Inverted solubility--a crystal melting upon cooling--is observed in a handful
of proteins, such as carbomonoxy hemoglobin and $\gamma$D-crystallin. In human
$\gamma$D-crystallin, the phenomenon is associated with the mutation of the
23$^\mathrm{rd}$ residue, a proline, to a threonine, serine or valine. One
proposed microscopic mechanism for this effect entails an increase in
hydrophobicity upon mutagenesis. Recent crystal structures of a double mutant
that includes the P23T mutation allows for a more careful investigation of this
proposal. Here, we first measure the surface hydrophobicity of various mutant
structures of this protein and determine that it does not discernibly increase
upon the mutating the 23$^\mathrm{rd}$ residue. We then investigate the
solubility inversion regime with a schematic patchy particle model that
includes one of three models for temperature-dependent patch energies: two of
the hydrophobic effect, and a more generic description. We conclude that while
solubility inversion due to the hydrophobic effect may be possible, microscopic
evidence to support it in $\gamma$D-crystallin is weak. More generally, we find
that solubility inversion requires a fine balance between patch strengths and
the temperature-dependent contribution, which may explain why inverted
solubility is not commonly observed in proteins. In any event, we also find
that the temperature-dependent interaction has only a negligible impact on the
critical properties of the $\gamma$D-crystallin, in line with previous
experimental observations.
| [
{
"created": "Thu, 15 Aug 2019 18:05:06 GMT",
"version": "v1"
}
] | 2020-03-04 | [
[
"Altan",
"Irem",
""
],
[
"McManus",
"Jennifer",
""
],
[
"Charbonneau",
"Patrick",
""
]
] | Inverted solubility--a crystal melting upon cooling--is observed in a handful of proteins, such as carbomonoxy hemoglobin and $\gamma$D-crystallin. In human $\gamma$D-crystallin, the phenomenon is associated with the mutation of the 23$^\mathrm{rd}$ residue, a proline, to a threonine, serine or valine. One proposed microscopic mechanism for this effect entails an increase in hydrophobicity upon mutagenesis. Recent crystal structures of a double mutant that includes the P23T mutation allows for a more careful investigation of this proposal. Here, we first measure the surface hydrophobicity of various mutant structures of this protein and determine that it does not discernibly increase upon the mutating the 23$^\mathrm{rd}$ residue. We then investigate the solubility inversion regime with a schematic patchy particle model that includes one of three models for temperature-dependent patch energies: two of the hydrophobic effect, and a more generic description. We conclude that while solubility inversion due to the hydrophobic effect may be possible, microscopic evidence to support it in $\gamma$D-crystallin is weak. More generally, we find that solubility inversion requires a fine balance between patch strengths and the temperature-dependent contribution, which may explain why inverted solubility is not commonly observed in proteins. In any event, we also find that the temperature-dependent interaction has only a negligible impact on the critical properties of the $\gamma$D-crystallin, in line with previous experimental observations. |
2101.06057 | Richard Gast | Richard Gast, Thomas R. Kn\"osche, Helmut Schmidt | Mean-field approximations of networks of spiking neurons with short-term
synaptic plasticity | 15 pages, 7 figures | null | 10.1103/PhysRevE.104.044310 | null | q-bio.NC cond-mat.dis-nn | http://creativecommons.org/licenses/by/4.0/ | Low-dimensional descriptions of neural network dynamics are an effective tool
for bridging different scales of organization of brain structure and function.
Recent advances in deriving mean-field descriptions for networks of coupled
oscillators have sparked the development of a new generation of neural mass
models. Of notable interest are mean-field descriptions of all-to-all coupled
quadratic integrate-and-fire (QIF) neurons, which have already seen numerous
extensions and applications. These extensions include different forms of
short-term adaptation (STA) considered to play an important role in generating
and sustaining dynamic regimes of interest in the brain. It is an open
question, however, whether the incorporation of pre-synaptic forms of synaptic
plasticity driven by single neuron activity would still permit the derivation
of mean-field equations using the same method. Here, we discuss this problem
using an established model of short-term synaptic plasticity at the single
neuron level, for which we present two different approaches for the derivation
of the mean-field equations. We compare these models with a recently proposed
mean-field approximation that assumes stochastic spike timings. In general, the
latter fails to accurately reproduce the macroscopic activity in networks of
deterministic QIF neurons with distributed parameters. We show that the
mean-field models we propose provide a more accurate description of the network
dynamics, although they are mathematically more involved. Using bifurcation
analysis, we find that QIF networks with pre-synaptic short-term plasticity can
express regimes of periodic bursting activity as well as bi-stable regimes.
Together, we provide novel insight into the macroscopic effects of short-term
synaptic plasticity in spiking neural networks, as well as two different
mean-field descriptions for future investigations of such networks.
| [
{
"created": "Fri, 15 Jan 2021 10:59:25 GMT",
"version": "v1"
},
{
"created": "Mon, 14 Jun 2021 15:13:27 GMT",
"version": "v2"
}
] | 2021-11-03 | [
[
"Gast",
"Richard",
""
],
[
"Knösche",
"Thomas R.",
""
],
[
"Schmidt",
"Helmut",
""
]
] | Low-dimensional descriptions of neural network dynamics are an effective tool for bridging different scales of organization of brain structure and function. Recent advances in deriving mean-field descriptions for networks of coupled oscillators have sparked the development of a new generation of neural mass models. Of notable interest are mean-field descriptions of all-to-all coupled quadratic integrate-and-fire (QIF) neurons, which have already seen numerous extensions and applications. These extensions include different forms of short-term adaptation (STA) considered to play an important role in generating and sustaining dynamic regimes of interest in the brain. It is an open question, however, whether the incorporation of pre-synaptic forms of synaptic plasticity driven by single neuron activity would still permit the derivation of mean-field equations using the same method. Here, we discuss this problem using an established model of short-term synaptic plasticity at the single neuron level, for which we present two different approaches for the derivation of the mean-field equations. We compare these models with a recently proposed mean-field approximation that assumes stochastic spike timings. In general, the latter fails to accurately reproduce the macroscopic activity in networks of deterministic QIF neurons with distributed parameters. We show that the mean-field models we propose provide a more accurate description of the network dynamics, although they are mathematically more involved. Using bifurcation analysis, we find that QIF networks with pre-synaptic short-term plasticity can express regimes of periodic bursting activity as well as bi-stable regimes. Together, we provide novel insight into the macroscopic effects of short-term synaptic plasticity in spiking neural networks, as well as two different mean-field descriptions for future investigations of such networks. |
2108.12402 | William Alexander | William H. Alexander, Samuel J. Gershman | Representation learning with reward prediction errors | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | The Reward Prediction Error hypothesis proposes that phasic activity in the
midbrain dopaminergic system reflects prediction errors needed for learning in
reinforcement learning. Besides the well-documented association between
dopamine and reward processing, dopamine is implicated in a variety of
functions without a clear relationship to reward prediction error. Fluctuations
in dopamine levels influence the subjective perception of time, dopamine bursts
precede the generation of motor responses, and the dopaminergic system
innervates regions of the brain, including hippocampus and areas in prefrontal
cortex, whose function is not uniquely tied to reward. In this manuscript, we
propose that a common theme linking these functions is representation, and that
prediction errors signaled by the dopamine system, in addition to driving
associative learning, can also support the acquisition of adaptive state
representations. In a series of simulations, we show how this extension can
account for the role of dopamine in temporal and spatial representation, motor
response, and abstract categorization tasks. By extending the role of dopamine
signals to learning state representations, we resolve a critical challenge to
the Reward Prediction Error hypothesis of dopamine function.
| [
{
"created": "Fri, 27 Aug 2021 17:21:45 GMT",
"version": "v1"
},
{
"created": "Wed, 20 Jul 2022 16:28:19 GMT",
"version": "v2"
},
{
"created": "Fri, 22 Jul 2022 18:18:08 GMT",
"version": "v3"
}
] | 2022-07-26 | [
[
"Alexander",
"William H.",
""
],
[
"Gershman",
"Samuel J.",
""
]
] | The Reward Prediction Error hypothesis proposes that phasic activity in the midbrain dopaminergic system reflects prediction errors needed for learning in reinforcement learning. Besides the well-documented association between dopamine and reward processing, dopamine is implicated in a variety of functions without a clear relationship to reward prediction error. Fluctuations in dopamine levels influence the subjective perception of time, dopamine bursts precede the generation of motor responses, and the dopaminergic system innervates regions of the brain, including hippocampus and areas in prefrontal cortex, whose function is not uniquely tied to reward. In this manuscript, we propose that a common theme linking these functions is representation, and that prediction errors signaled by the dopamine system, in addition to driving associative learning, can also support the acquisition of adaptive state representations. In a series of simulations, we show how this extension can account for the role of dopamine in temporal and spatial representation, motor response, and abstract categorization tasks. By extending the role of dopamine signals to learning state representations, we resolve a critical challenge to the Reward Prediction Error hypothesis of dopamine function. |
2303.00803 | Jana S. Huisman | Olivia Kosterlitz and Jana S. Huisman | Guidelines for the estimation and reporting of plasmid conjugation rates | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Conjugation is a central characteristic of plasmid biology and an important
mechanism of horizontal gene transfer in bacteria. However, there is little
consensus on how to accurately estimate and report plasmid conjugation rates,
in part due to the wide range of available methods. Given the similarity
between approaches, we propose general reporting guidelines for plasmid
conjugation experiments. These constitute best practices based on recent
literature about plasmid conjugation and methods to measure conjugation rates.
In addition to the general guidelines, we discuss common theoretical
assumptions underlying existing methods to estimate conjugation rates and
provide recommendations on how to avoid violating these assumptions. We hope
this will aid the implementation and evaluation of conjugation rate
measurements, and initiate a broader discussion regarding the practice of
quantifying plasmid conjugation rates.
| [
{
"created": "Wed, 1 Mar 2023 20:13:30 GMT",
"version": "v1"
}
] | 2023-03-03 | [
[
"Kosterlitz",
"Olivia",
""
],
[
"Huisman",
"Jana S.",
""
]
] | Conjugation is a central characteristic of plasmid biology and an important mechanism of horizontal gene transfer in bacteria. However, there is little consensus on how to accurately estimate and report plasmid conjugation rates, in part due to the wide range of available methods. Given the similarity between approaches, we propose general reporting guidelines for plasmid conjugation experiments. These constitute best practices based on recent literature about plasmid conjugation and methods to measure conjugation rates. In addition to the general guidelines, we discuss common theoretical assumptions underlying existing methods to estimate conjugation rates and provide recommendations on how to avoid violating these assumptions. We hope this will aid the implementation and evaluation of conjugation rate measurements, and initiate a broader discussion regarding the practice of quantifying plasmid conjugation rates. |
1608.04054 | Nathan Baker | Lisa E. Feldberg, David H. Brookes, Eng-Hui Yap, Elizabeth Jurrus,
Nathan Baker, Teresa Head-Gordon | PB-AM: An Open-Source, Fully Analytical Linear Poisson-Boltzmann Solver | null | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present the open source distributed software package Poisson-Boltzmann
Analytical Method (PB-AM), a fully analytical solution to the linearized
Poisson Boltzmann equation, for molecules represented as non-overlapping
spherical cavities. The PB-AM software package includes the generation of
outputs files appropriate for visualization using VMD, a Brownian dynamics
scheme that uses periodic boundary conditions to simulate dynamics, the ability
to specify docking criteria, and offers two different kinetics schemes to
evaluate biomolecular association rate constants. Given that PB-AM defines
mutual polarization completely and accurately, it can be refactored as a
many-body expansion to explore 2- and 3-body polarization. Additionally, the
software has been integrated into the Adaptive Poisson-Boltzmann Solver (APBS)
software package to make it more accessible to a larger group of scientists,
educators and students that are more familiar with the APBS framework.
| [
{
"created": "Sun, 14 Aug 2016 03:22:33 GMT",
"version": "v1"
},
{
"created": "Sat, 24 Sep 2016 03:18:15 GMT",
"version": "v2"
}
] | 2016-09-27 | [
[
"Feldberg",
"Lisa E.",
""
],
[
"Brookes",
"David H.",
""
],
[
"Yap",
"Eng-Hui",
""
],
[
"Jurrus",
"Elizabeth",
""
],
[
"Baker",
"Nathan",
""
],
[
"Head-Gordon",
"Teresa",
""
]
] | We present the open source distributed software package Poisson-Boltzmann Analytical Method (PB-AM), a fully analytical solution to the linearized Poisson Boltzmann equation, for molecules represented as non-overlapping spherical cavities. The PB-AM software package includes the generation of outputs files appropriate for visualization using VMD, a Brownian dynamics scheme that uses periodic boundary conditions to simulate dynamics, the ability to specify docking criteria, and offers two different kinetics schemes to evaluate biomolecular association rate constants. Given that PB-AM defines mutual polarization completely and accurately, it can be refactored as a many-body expansion to explore 2- and 3-body polarization. Additionally, the software has been integrated into the Adaptive Poisson-Boltzmann Solver (APBS) software package to make it more accessible to a larger group of scientists, educators and students that are more familiar with the APBS framework. |
2010.04530 | Pietro Hiram Guzzi | Concettina Guerra and Pietro Hiram Guzzi | Evaluation of the Topological Agreement of Network Alignments | null | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Aligning protein interaction networks (PPI) of two or more organisms consists
of finding a mapping of the nodes (proteins) of the networks that captures
important structural and functional associations (similarity). It is a well
studied but difficult problem. It is provably NP-hard in some instances thus
computationally very demanding. The problem comes in several versions: global
versus local alignment; pairwise versus multiple alignment; one-to-one versus
many-to-many alignment. Heuristics to address the various instances of the
problem abound and they achieve some degree of success when their performance
is measured in terms of node and/or edges conservation. However, as the
evolutionary distance between the organisms being considered increases the
results tend to degrade. Moreover, poor performance is achieved when the
considered networks have remarkably different sizes in the number of nodes
and/or edges. Here we address the challenge of analyzing and comparing
different approaches to global network alignment, when a one-to-one mapping is
sought. We consider and propose various measures to evaluate the agreement
between alignments obtained by existing approaches. We show that some such
measures indicate an agreement that is often about the same than what would be
obtained by chance. That tends to occur even when the mappings exhibit a good
performance based on standard measures.
| [
{
"created": "Fri, 9 Oct 2020 12:43:45 GMT",
"version": "v1"
}
] | 2020-10-12 | [
[
"Guerra",
"Concettina",
""
],
[
"Guzzi",
"Pietro Hiram",
""
]
] | Aligning protein interaction networks (PPI) of two or more organisms consists of finding a mapping of the nodes (proteins) of the networks that captures important structural and functional associations (similarity). It is a well studied but difficult problem. It is provably NP-hard in some instances thus computationally very demanding. The problem comes in several versions: global versus local alignment; pairwise versus multiple alignment; one-to-one versus many-to-many alignment. Heuristics to address the various instances of the problem abound and they achieve some degree of success when their performance is measured in terms of node and/or edges conservation. However, as the evolutionary distance between the organisms being considered increases the results tend to degrade. Moreover, poor performance is achieved when the considered networks have remarkably different sizes in the number of nodes and/or edges. Here we address the challenge of analyzing and comparing different approaches to global network alignment, when a one-to-one mapping is sought. We consider and propose various measures to evaluate the agreement between alignments obtained by existing approaches. We show that some such measures indicate an agreement that is often about the same than what would be obtained by chance. That tends to occur even when the mappings exhibit a good performance based on standard measures. |
1006.0727 | Giovanni Paternostro | Jacob D. Feala, Jorge Cortes, Phillip M. Duxbury, Andrew D. McCulloch,
Carlo Piermarocchi, Giovanni Paternostro | Biological control networks suggest the use of biomimetic sets for
combinatorial therapies | 33 pages | PLoS ONE 7(1): e29374 (2012) | 10.1371/journal.pone.0029374 | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cells are regulated by networks of controllers having many targets, and
targets affected by many controllers, but these "many-to-many" combinatorial
control systems are poorly understood. Here we analyze distinct cellular
networks (transcription factors, microRNAs, and protein kinases) and a
drug-target network. Certain network properties seem universal across systems
and species, suggesting the existence of common control strategies in biology.
The number of controllers is ~8% of targets and the density of links is 2.5%
\pm 1.2%. Links per node are predominantly exponentially distributed, implying
conservation of the average, which we explain using a mathematical model of
robustness in control networks. These findings suggest that optimal
pharmacological strategies may benefit from a similar, many-to-many
combinatorial structure, and molecular tools are available to test this
approach.
| [
{
"created": "Thu, 3 Jun 2010 19:56:45 GMT",
"version": "v1"
},
{
"created": "Tue, 21 Dec 2010 23:01:57 GMT",
"version": "v2"
}
] | 2012-01-06 | [
[
"Feala",
"Jacob D.",
""
],
[
"Cortes",
"Jorge",
""
],
[
"Duxbury",
"Phillip M.",
""
],
[
"McCulloch",
"Andrew D.",
""
],
[
"Piermarocchi",
"Carlo",
""
],
[
"Paternostro",
"Giovanni",
""
]
] | Cells are regulated by networks of controllers having many targets, and targets affected by many controllers, but these "many-to-many" combinatorial control systems are poorly understood. Here we analyze distinct cellular networks (transcription factors, microRNAs, and protein kinases) and a drug-target network. Certain network properties seem universal across systems and species, suggesting the existence of common control strategies in biology. The number of controllers is ~8% of targets and the density of links is 2.5% \pm 1.2%. Links per node are predominantly exponentially distributed, implying conservation of the average, which we explain using a mathematical model of robustness in control networks. These findings suggest that optimal pharmacological strategies may benefit from a similar, many-to-many combinatorial structure, and molecular tools are available to test this approach. |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.