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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1301.7682 | Anatolij Gelimson | Anatolij Gelimson, Jonas Cremer, Erwin Frey | Mobility, fitness collection, and the breakdown of cooperation | 9 pages, 6 figures | Phys. Rev. E 87 (2013) 042711 | 10.1103/PhysRevE.87.042711 | null | q-bio.PE physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The spatial arrangement of individuals is thought to overcome the dilemma of
cooperation: When cooperators engage in clusters they might share the benefit
of cooperation while being more protected against non-cooperating individuals,
which benefit from cooperation but save the cost of cooperation. This is
paradigmatically shown by the spatial prisoner's dilemma model. Here, we study
this model in one and two spatial dimensions, but explicitly take into account
that in biological setups fitness collection and selection are separated
processes occurring mostly on vastly different time scales. This separation is
particularly important to understand the impact of mobility on the evolution of
cooperation. We find that even small diffusive mobility strongly restricts
cooperation since it enables non-cooperative individuals to invade cooperative
clusters. Thus, in most biological scenarios, where the mobility of competing
individuals is an irrefutable fact, the spatial prisoner's dilemma alone cannot
explain stable cooperation but additional mechanisms are necessary for spatial
structure to promote the evolution of cooperation. The breakdown of cooperation
is analyzed in detail. We confirm the existence of a phase transition, here
controlled by mobility and costs, which distinguishes between purely
cooperative and non-cooperative absorbing states. While in one dimension the
model is in the class of the Voter Model, it belongs to the Directed
Percolation (DP) universality class in two dimensions.
| [
{
"created": "Thu, 31 Jan 2013 16:58:40 GMT",
"version": "v1"
},
{
"created": "Fri, 1 Feb 2013 09:33:06 GMT",
"version": "v2"
},
{
"created": "Tue, 16 Apr 2013 21:25:13 GMT",
"version": "v3"
}
] | 2013-04-18 | [
[
"Gelimson",
"Anatolij",
""
],
[
"Cremer",
"Jonas",
""
],
[
"Frey",
"Erwin",
""
]
] | The spatial arrangement of individuals is thought to overcome the dilemma of cooperation: When cooperators engage in clusters they might share the benefit of cooperation while being more protected against non-cooperating individuals, which benefit from cooperation but save the cost of cooperation. This is paradigmatically shown by the spatial prisoner's dilemma model. Here, we study this model in one and two spatial dimensions, but explicitly take into account that in biological setups fitness collection and selection are separated processes occurring mostly on vastly different time scales. This separation is particularly important to understand the impact of mobility on the evolution of cooperation. We find that even small diffusive mobility strongly restricts cooperation since it enables non-cooperative individuals to invade cooperative clusters. Thus, in most biological scenarios, where the mobility of competing individuals is an irrefutable fact, the spatial prisoner's dilemma alone cannot explain stable cooperation but additional mechanisms are necessary for spatial structure to promote the evolution of cooperation. The breakdown of cooperation is analyzed in detail. We confirm the existence of a phase transition, here controlled by mobility and costs, which distinguishes between purely cooperative and non-cooperative absorbing states. While in one dimension the model is in the class of the Voter Model, it belongs to the Directed Percolation (DP) universality class in two dimensions. |
2307.05044 | Anna Fome | Anna Daniel Fome, Wolfgang Bock, and Axel Klar | Analysis of a competitive respiratory disease system with quarantine | null | null | null | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In the world of epidemics, the mathematical modeling of disease co-infection
is gaining importance due to its contributions to mathematics and public
health. Because the co-infection may have a double burden on families,
countries, and the universe, understanding its dynamics is paramount. We study
a SEIQR (susceptible-exposed-infectious-quarantined-recovered) deterministic
epidemic model with a single host population and multiple strains (-$c$ and
-$i$) to account for two competitive diseases with quarantine effects. To model
the role of quarantine and isolation efficacy in disease dynamics, we utilize a
linear function. Further, we shed light on the standard endemic threshold and
determine the conditions for extinction or coexistence with and without forming
co-infection. Next, we show the dependence of the criticality based on specific
parameters of the different pathogens. We found that the disease-free
equilibrium (DFE) of the single-strain model always exists and is globally
asymptotically stable (GAS) if $\tilde{\mathcal{R}}_k^q\leq 1$, else, a stable
endemic equilibrium. On top of that, the model has forward bifurcation at
$\tilde{\mathcal{R}}_k^q = 1$. In the case of a two-strain model, the strain
with a large reproduction number outcompetes the one with a smaller
reproduction number. Further, if the co-infected quarantine reproduction number
is less than one, the infections of already infected individuals will die out,
and co-infection will persist in the population otherwise. We note that the
quarantine and isolation of exposed and infected individuals will reduce the
number of secondary cases below one, consequently reducing the disease
complications if the total number of people in the quarantine is at most the
critical value.
| [
{
"created": "Tue, 11 Jul 2023 06:51:03 GMT",
"version": "v1"
}
] | 2023-07-12 | [
[
"Fome",
"Anna Daniel",
""
],
[
"Bock",
"Wolfgang",
""
],
[
"Klar",
"Axel",
""
]
] | In the world of epidemics, the mathematical modeling of disease co-infection is gaining importance due to its contributions to mathematics and public health. Because the co-infection may have a double burden on families, countries, and the universe, understanding its dynamics is paramount. We study a SEIQR (susceptible-exposed-infectious-quarantined-recovered) deterministic epidemic model with a single host population and multiple strains (-$c$ and -$i$) to account for two competitive diseases with quarantine effects. To model the role of quarantine and isolation efficacy in disease dynamics, we utilize a linear function. Further, we shed light on the standard endemic threshold and determine the conditions for extinction or coexistence with and without forming co-infection. Next, we show the dependence of the criticality based on specific parameters of the different pathogens. We found that the disease-free equilibrium (DFE) of the single-strain model always exists and is globally asymptotically stable (GAS) if $\tilde{\mathcal{R}}_k^q\leq 1$, else, a stable endemic equilibrium. On top of that, the model has forward bifurcation at $\tilde{\mathcal{R}}_k^q = 1$. In the case of a two-strain model, the strain with a large reproduction number outcompetes the one with a smaller reproduction number. Further, if the co-infected quarantine reproduction number is less than one, the infections of already infected individuals will die out, and co-infection will persist in the population otherwise. We note that the quarantine and isolation of exposed and infected individuals will reduce the number of secondary cases below one, consequently reducing the disease complications if the total number of people in the quarantine is at most the critical value. |
1306.3061 | Gasper Tkacik | Ga\v{s}per Tka\v{c}ik and Olivier Marre and Dario Amodei and Elad
Schneidman and William Bialek and Michael J Berry II | Searching for collective behavior in a network of real neurons | 24 pages, 19 figures | PLOS Comput Biol 10 (2014): e1003408 | 10.1371/journal.pcbi.1003408 | null | q-bio.NC cond-mat.stat-mech physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Maximum entropy models are the least structured probability distributions
that exactly reproduce a chosen set of statistics measured in an interacting
network. Here we use this principle to construct probabilistic models which
describe the correlated spiking activity of populations of up to 120 neurons in
the salamander retina as it responds to natural movies. Already in groups as
small as 10 neurons, interactions between spikes can no longer be regarded as
small perturbations in an otherwise independent system; for 40 or more neurons
pairwise interactions need to be supplemented by a global interaction that
controls the distribution of synchrony in the population. Here we show that
such "K-pairwise" models--being systematic extensions of the previously used
pairwise Ising models--provide an excellent account of the data. We explore the
properties of the neural vocabulary by: 1) estimating its entropy, which
constrains the population's capacity to represent visual information; 2)
classifying activity patterns into a small set of metastable collective modes;
3) showing that the neural codeword ensembles are extremely inhomogenous; 4)
demonstrating that the state of individual neurons is highly predictable from
the rest of the population, allowing the capacity for error correction.
| [
{
"created": "Thu, 13 Jun 2013 09:33:21 GMT",
"version": "v1"
}
] | 2014-01-28 | [
[
"Tkačik",
"Gašper",
""
],
[
"Marre",
"Olivier",
""
],
[
"Amodei",
"Dario",
""
],
[
"Schneidman",
"Elad",
""
],
[
"Bialek",
"William",
""
],
[
"Berry",
"Michael J",
"II"
]
] | Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such "K-pairwise" models--being systematic extensions of the previously used pairwise Ising models--provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population's capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction. |
q-bio/0505056 | Tini Garske | Tini Garske | Error thresholds in a mutation-selection model with Hopfield-type
fitness | 36 pages, 9 figures | null | null | null | q-bio.PE | null | A deterministic mutation-selection model in the sequence space approach is
investigated. Genotypes are identified with two-letter sequences. Mutation is
modelled as a Markov process, fitness functions are of Hopfield type, where the
fitness of a sequence is determined by the Hamming distances to a number of
predefined patterns. Using a maximum principle for the population mean fitness
in equilibrium, the error threshold phenomenon is studied for quadratic
Hopfield-type fitness functions with small numbers of patterns. Different from
previous investigations of the Hopfield model, the system shows error threshold
behaviour not for all fitness functions, but only for certain parameter values.
| [
{
"created": "Mon, 30 May 2005 16:02:21 GMT",
"version": "v1"
}
] | 2016-09-08 | [
[
"Garske",
"Tini",
""
]
] | A deterministic mutation-selection model in the sequence space approach is investigated. Genotypes are identified with two-letter sequences. Mutation is modelled as a Markov process, fitness functions are of Hopfield type, where the fitness of a sequence is determined by the Hamming distances to a number of predefined patterns. Using a maximum principle for the population mean fitness in equilibrium, the error threshold phenomenon is studied for quadratic Hopfield-type fitness functions with small numbers of patterns. Different from previous investigations of the Hopfield model, the system shows error threshold behaviour not for all fitness functions, but only for certain parameter values. |
1105.1513 | Ronan M.T. Fleming Dr | Ronan M. T. Fleming, Christopher M. Maes, Michael A. Saunders, Yinyu
Ye and Bernhard {\O}. Palsson | A variational principle for computing nonequilibrium fluxes and
potentials in genome-scale biochemical networks | 17 pages, 1 figure | null | null | null | q-bio.MN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We derive a convex optimization problem on a steady-state nonequilibrium
network of biochemical reactions, with the property that energy conservation
and the second law of thermodynamics both hold at the problem solution. This
suggests a new variational principle for biochemical networks that can be
implemented in a computationally tractable manner. We derive the Lagrange dual
of the optimization problem and use strong duality to demonstrate that a
biochemical analogue of Tellegen's theorem holds at optimality. Each optimal
flux is dependent on a free parameter that we relate to an elementary kinetic
parameter when mass action kinetics is assumed.
| [
{
"created": "Sun, 8 May 2011 13:28:41 GMT",
"version": "v1"
},
{
"created": "Mon, 19 Sep 2011 10:35:01 GMT",
"version": "v2"
}
] | 2011-09-20 | [
[
"Fleming",
"Ronan M. T.",
""
],
[
"Maes",
"Christopher M.",
""
],
[
"Saunders",
"Michael A.",
""
],
[
"Ye",
"Yinyu",
""
],
[
"Palsson",
"Bernhard Ø.",
""
]
] | We derive a convex optimization problem on a steady-state nonequilibrium network of biochemical reactions, with the property that energy conservation and the second law of thermodynamics both hold at the problem solution. This suggests a new variational principle for biochemical networks that can be implemented in a computationally tractable manner. We derive the Lagrange dual of the optimization problem and use strong duality to demonstrate that a biochemical analogue of Tellegen's theorem holds at optimality. Each optimal flux is dependent on a free parameter that we relate to an elementary kinetic parameter when mass action kinetics is assumed. |
2006.04464 | Vishwajeet Jha | Vishwajeet Jha | Forecasting the transmission of Covid-19 in India using a data driven
SEIRD model | null | null | null | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The infections and fatalities due to SARS-CoV-2 virus for cases specific to
India have been studied using a deterministic
susceptible-exposed-infected-recovered-dead (SEIRD) compartmental model. One of
the most significant epidemiological parameter, namely the effective
reproduction number of the infection is extracted from the daily growth rate
data of reported infections and it is included in the model with a time
variation. We evaluate the effect of control interventions implemented till now
and estimate the case numbers for infections and deaths averted by these
restrictive measures. We further provide a forecast on the extent of the future
Covid-19 transmission in India and predict the probable numbers of infections
and fatalities under various potential scenarios.
| [
{
"created": "Mon, 8 Jun 2020 10:42:40 GMT",
"version": "v1"
}
] | 2020-06-09 | [
[
"Jha",
"Vishwajeet",
""
]
] | The infections and fatalities due to SARS-CoV-2 virus for cases specific to India have been studied using a deterministic susceptible-exposed-infected-recovered-dead (SEIRD) compartmental model. One of the most significant epidemiological parameter, namely the effective reproduction number of the infection is extracted from the daily growth rate data of reported infections and it is included in the model with a time variation. We evaluate the effect of control interventions implemented till now and estimate the case numbers for infections and deaths averted by these restrictive measures. We further provide a forecast on the extent of the future Covid-19 transmission in India and predict the probable numbers of infections and fatalities under various potential scenarios. |
2106.05122 | Mattia Zanella | Giacomo Albi, Lorenzo Pareschi, Mattia Zanella | Modelling lockdown measures in epidemic outbreaks using selective
socio-economic containment with uncertainty | null | null | null | null | q-bio.PE math.OC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | After the introduction of drastic containment measures aimed at stopping the
epidemic contagion from SARS-CoV2, many governments have adopted a strategy
based on a periodic relaxation of such measures in the face of a severe
economic crisis caused by lockdowns. Assessing the impact of such openings in
relation to the risk of a resumption of the spread of the disease is an
extremely difficult problem due to the many unknowns concerning the actual
number of people infected, the actual reproduction number and infection
fatality rate of the disease. In this work, starting from a compartmental model
with a social structure and stochastic inputs, we derive models with multiple
feedback controls depending on the social activities that allow to assess the
impact of a selective relaxation of the containment measures in the presence of
uncertain data. Specific contact patterns in the home, work, school and other
locations have been considered. Results from different scenarios concerning the
first wave of the epidemic in some major countries, including Germany, France,
Italy, Spain, the United Kingdom and the United States, are presented and
discussed.
| [
{
"created": "Wed, 9 Jun 2021 15:00:22 GMT",
"version": "v1"
}
] | 2021-06-10 | [
[
"Albi",
"Giacomo",
""
],
[
"Pareschi",
"Lorenzo",
""
],
[
"Zanella",
"Mattia",
""
]
] | After the introduction of drastic containment measures aimed at stopping the epidemic contagion from SARS-CoV2, many governments have adopted a strategy based on a periodic relaxation of such measures in the face of a severe economic crisis caused by lockdowns. Assessing the impact of such openings in relation to the risk of a resumption of the spread of the disease is an extremely difficult problem due to the many unknowns concerning the actual number of people infected, the actual reproduction number and infection fatality rate of the disease. In this work, starting from a compartmental model with a social structure and stochastic inputs, we derive models with multiple feedback controls depending on the social activities that allow to assess the impact of a selective relaxation of the containment measures in the presence of uncertain data. Specific contact patterns in the home, work, school and other locations have been considered. Results from different scenarios concerning the first wave of the epidemic in some major countries, including Germany, France, Italy, Spain, the United Kingdom and the United States, are presented and discussed. |
1610.02249 | Esmaeil Seraj | Esmaeil Seraj (ECE GeorgiaTech) | Cerebral Signal Instantaneous Parameters Estimation MATLAB Toolbox -
User Guide Version 2.3 | null | null | null | null | q-bio.NC cs.HC cs.OH | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This document is meant to help individuals use the Cerebral Signal Phase
Analysis toolbox which implements different methods for estimating the
instantaneous phase and frequency of a signal and calculating some related
popular quantities.The toolbox -- which is distributed under the terms of the
GNU GENERAL PUBLIC LICENSE as a set of MATLAB routines -- can be downloaded at
the address http://oset.ir/category.php?dir=Tools.The purpose of this toolbox
is to calculate the instantaneous phase and frequency sequences of cerebral
signals (EEG, MEG, etc.) and some related popular features and quantities in
brain studies and Neuroscience such as Phase Shift, Phase Resetting, Phase
Locking Value (PLV), Phase Difference and more, to help researchers in these
fields.
| [
{
"created": "Fri, 7 Oct 2016 12:27:36 GMT",
"version": "v1"
},
{
"created": "Thu, 28 Dec 2017 13:53:44 GMT",
"version": "v2"
},
{
"created": "Tue, 24 Apr 2018 07:00:16 GMT",
"version": "v3"
},
{
"created": "Fri, 6 Jul 2018 01:26:42 GMT",
"version": "v4"
}
] | 2018-07-09 | [
[
"Seraj",
"Esmaeil",
"",
"ECE GeorgiaTech"
]
] | This document is meant to help individuals use the Cerebral Signal Phase Analysis toolbox which implements different methods for estimating the instantaneous phase and frequency of a signal and calculating some related popular quantities.The toolbox -- which is distributed under the terms of the GNU GENERAL PUBLIC LICENSE as a set of MATLAB routines -- can be downloaded at the address http://oset.ir/category.php?dir=Tools.The purpose of this toolbox is to calculate the instantaneous phase and frequency sequences of cerebral signals (EEG, MEG, etc.) and some related popular features and quantities in brain studies and Neuroscience such as Phase Shift, Phase Resetting, Phase Locking Value (PLV), Phase Difference and more, to help researchers in these fields. |
1712.05692 | Kevin Bleakley | Etienne Simon-Loriere, Veasna Duong, Ahmed Tawfik, Sivlin Ung, Sowath
Ly, Isabelle Casademont, Matthieu Prot, No\'emie Courtejoie, Kevin Bleakley
(LM-Orsay, SELECT), Philippe Buchy, Arnaud Tarantola, Philippe Dussart,
Tineke Cantaert, Anavaj Sakuntabhai | Increased adaptive immune responses and proper feedback regulation
protect against clinical dengue | null | Science Translational Medicine, American Association for the
Advancement of Science, 2017, 9 (405), pp.eaal5088 | 10.1126/scitranslmed.aal5088 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dengue is the most prevalent arthropod-borne viral disease. Clinical symptoms
of dengue virus (DENV) infection range from classical mild dengue fever to
severe, life-threatening dengue shock syndrome. However, most DENV infections
cause few or no symptoms. Asymptomatic DENV-infected patients provide a unique
opportunity to decipher the host immune responses leading to virus elimination
without negative impact on t v 'health. We used an integrated approach of
transcriptional profiling and immunological analysis comparing a Cambodian
population of strictly asymptomatic viremic individuals with clinical dengue
patients. Whereas inflammatory pathways and innate immune responses were
similar between asymptomatic individuals and clinical dengue patients,
expression of proteins related to antigen presentation and subsequent T and B
cell activation pathways were differentially regulated, independent of viral
load or previous DENV infection. Feedback mechanisms controlled the immune
response in asymptomatic viremic individuals as demonstrated by increased
activation of T cell apoptosis-related pathways and Fc$\gamma$RIIB signaling
associated with decreased anti-DENV specific antibody concentrations. Taken
together, our data illustrate that symptom-free DENV infection in children is
determined by increased activation of the adaptive immune compartment and
proper control mechanisms leading to elimination of viral infection without
excessive immune activation, having implications for novel vaccine development
strategies.
| [
{
"created": "Mon, 11 Dec 2017 12:34:49 GMT",
"version": "v1"
}
] | 2017-12-18 | [
[
"Simon-Loriere",
"Etienne",
"",
"LM-Orsay, SELECT"
],
[
"Duong",
"Veasna",
"",
"LM-Orsay, SELECT"
],
[
"Tawfik",
"Ahmed",
"",
"LM-Orsay, SELECT"
],
[
"Ung",
"Sivlin",
"",
"LM-Orsay, SELECT"
],
[
"Ly",
"Sowath",
"",
"LM... | Dengue is the most prevalent arthropod-borne viral disease. Clinical symptoms of dengue virus (DENV) infection range from classical mild dengue fever to severe, life-threatening dengue shock syndrome. However, most DENV infections cause few or no symptoms. Asymptomatic DENV-infected patients provide a unique opportunity to decipher the host immune responses leading to virus elimination without negative impact on t v 'health. We used an integrated approach of transcriptional profiling and immunological analysis comparing a Cambodian population of strictly asymptomatic viremic individuals with clinical dengue patients. Whereas inflammatory pathways and innate immune responses were similar between asymptomatic individuals and clinical dengue patients, expression of proteins related to antigen presentation and subsequent T and B cell activation pathways were differentially regulated, independent of viral load or previous DENV infection. Feedback mechanisms controlled the immune response in asymptomatic viremic individuals as demonstrated by increased activation of T cell apoptosis-related pathways and Fc$\gamma$RIIB signaling associated with decreased anti-DENV specific antibody concentrations. Taken together, our data illustrate that symptom-free DENV infection in children is determined by increased activation of the adaptive immune compartment and proper control mechanisms leading to elimination of viral infection without excessive immune activation, having implications for novel vaccine development strategies. |
2005.13208 | Kento Nakamura | Kento Nakamura and Tetsuya J. Kobayashi | A connection between bacterial chemotactic network and optimal filtering | null | Phys. Rev. Lett. 126, 128102 (2021) | 10.1103/PhysRevLett.126.128102 | null | q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The chemotactic network of Escherichia coli has been studied extensively both
biophysically and information-theoretically. Nevertheless, the connection
between these two aspects is still elusive. In this work, we report such a
connection by showing that a standard biochemical model of the chemotactic
network is mathematically equivalent to an information-theoretically optimal
filtering dynamics. Moreover, we demonstrate that an experimentally observed
nonlinear response relation can be reproduced from the optimal dynamics. These
results suggest that the biochemical network of E. coli chemotaxis is designed
to optimally extract gradient information in a noisy condition.
| [
{
"created": "Wed, 27 May 2020 07:15:01 GMT",
"version": "v1"
}
] | 2021-03-31 | [
[
"Nakamura",
"Kento",
""
],
[
"Kobayashi",
"Tetsuya J.",
""
]
] | The chemotactic network of Escherichia coli has been studied extensively both biophysically and information-theoretically. Nevertheless, the connection between these two aspects is still elusive. In this work, we report such a connection by showing that a standard biochemical model of the chemotactic network is mathematically equivalent to an information-theoretically optimal filtering dynamics. Moreover, we demonstrate that an experimentally observed nonlinear response relation can be reproduced from the optimal dynamics. These results suggest that the biochemical network of E. coli chemotaxis is designed to optimally extract gradient information in a noisy condition. |
1108.1630 | Richard A Neher | Richard A. Neher and Boris I. Shraiman | Statistical Genetics and Evolution of Quantitative Traits | to appear in Rev.Mod.Phys | Rev. Mod. Phys. 83, 1283-1300 (2011) | 10.1103/RevModPhys.83.1283 | NSF-KITP-11-049 | q-bio.PE cond-mat.stat-mech physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The distribution and heritability of many traits depends on numerous loci in
the genome. In general, the astronomical number of possible genotypes makes the
system with large numbers of loci difficult to describe. Multilocus evolution,
however, greatly simplifies in the limit of weak selection and frequent
recombination. In this limit, populations rapidly reach Quasi-Linkage
Equilibrium (QLE) in which the dynamics of the full genotype distribution,
including correlations between alleles at different loci, can be parameterized
by the allele frequencies. This review provides a simplified exposition of the
concept and mathematics of QLE which is central to the statistical description
of genotypes in sexual populations. We show how key results of Quantitative
Genetics such as the generalized Fisher's "Fundamental Theorem", along with
Wright's Adaptive Landscape, emerge within QLE from the dynamics of the
genotype distribution. We then discuss under what circumstances QLE is
applicable, and what the breakdown of QLE implies for the population structure
and the dynamics of selection. Understanding of the fundamental aspects of
multilocus evolution obtained through simplified models may be helpful in
providing conceptual and computational tools to address the challenges arising
in the studies of complex quantitative phenotypes of practical interest.
| [
{
"created": "Mon, 8 Aug 2011 08:43:56 GMT",
"version": "v1"
}
] | 2012-08-01 | [
[
"Neher",
"Richard A.",
""
],
[
"Shraiman",
"Boris I.",
""
]
] | The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach Quasi-Linkage Equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parameterized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. We show how key results of Quantitative Genetics such as the generalized Fisher's "Fundamental Theorem", along with Wright's Adaptive Landscape, emerge within QLE from the dynamics of the genotype distribution. We then discuss under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding of the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest. |
1812.02003 | Bernard Feldman | Bernard J. Feldman | Thermoregulation in mice, rats and humans: An insight into the evolution
of human hairlessness | null | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The thermoregulation system in animals removes body heat in hot temperatures
and retains body heat in cold temperatures. The better the animal removes heat,
the worse the animal retains heat and visa versa. It is the balance between
these two conflicting goals that determines the mammal's size, heart rate and
amount of hair. The rat's loss of tail hair and human's loss of its body hair
are responses to these conflicting thermoregulation needs as these animals
evolved to larger size over time.
| [
{
"created": "Tue, 4 Dec 2018 15:17:31 GMT",
"version": "v1"
}
] | 2018-12-06 | [
[
"Feldman",
"Bernard J.",
""
]
] | The thermoregulation system in animals removes body heat in hot temperatures and retains body heat in cold temperatures. The better the animal removes heat, the worse the animal retains heat and visa versa. It is the balance between these two conflicting goals that determines the mammal's size, heart rate and amount of hair. The rat's loss of tail hair and human's loss of its body hair are responses to these conflicting thermoregulation needs as these animals evolved to larger size over time. |
1109.2556 | Choongseok Park | Choongseok Park and Leonid L. Rubchinsky | Intermittent synchronization in a network of bursting neurons | 36 pages, 11 figures | Chaos, 21, 033125, 2011 | 10.1063/1.3633078 | null | q-bio.NC nlin.CD | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Synchronized oscillations in networks of inhibitory and excitatory coupled
bursting neurons are common in a variety of neural systems from central pattern
generators to human brain circuits. One example of the latter is the
subcortical network of the basal ganglia, formed by excitatory and inhibitory
bursters of the subthalamic nucleus and globus pallidus, involved in motor
control and affected in Parkinson's disease. Recent experiments have
demonstrated the intermittent nature of the phase-locking of neural activity in
this network. Here we explore one potential mechanism to explain the
intermittent phase-locking in a network. We simplify the network to obtain a
model of two inhibitory coupled elements and explore its dynamics. We used
geometric analysis and singular perturbation methods for dynamical systems to
reduce the full model to a simpler set of equations. Mathematical analysis was
completed using three slow variables with two different time scales.
Intermittently synchronous oscillations are generated by overlapped spiking
which crucially depends on the geometry of the slow phase plane and the
interplay between slow variables as well as the strength of synapses. Two slow
variables are responsible for the generation of activity patterns with
overlapped spiking and the other slower variable enhances the robustness of an
irregular and intermittent activity pattern. While the analyzed network and the
explored mechanism of intermittent synchrony appear to be quite generic, the
results of this analysis can be used to trace particular values of biophysical
parameters (synaptic strength and parameters of calcium dynamics), which are
known to be impacted in Parkinson's disease.
| [
{
"created": "Mon, 12 Sep 2011 18:18:34 GMT",
"version": "v1"
}
] | 2011-09-21 | [
[
"Park",
"Choongseok",
""
],
[
"Rubchinsky",
"Leonid L.",
""
]
] | Synchronized oscillations in networks of inhibitory and excitatory coupled bursting neurons are common in a variety of neural systems from central pattern generators to human brain circuits. One example of the latter is the subcortical network of the basal ganglia, formed by excitatory and inhibitory bursters of the subthalamic nucleus and globus pallidus, involved in motor control and affected in Parkinson's disease. Recent experiments have demonstrated the intermittent nature of the phase-locking of neural activity in this network. Here we explore one potential mechanism to explain the intermittent phase-locking in a network. We simplify the network to obtain a model of two inhibitory coupled elements and explore its dynamics. We used geometric analysis and singular perturbation methods for dynamical systems to reduce the full model to a simpler set of equations. Mathematical analysis was completed using three slow variables with two different time scales. Intermittently synchronous oscillations are generated by overlapped spiking which crucially depends on the geometry of the slow phase plane and the interplay between slow variables as well as the strength of synapses. Two slow variables are responsible for the generation of activity patterns with overlapped spiking and the other slower variable enhances the robustness of an irregular and intermittent activity pattern. While the analyzed network and the explored mechanism of intermittent synchrony appear to be quite generic, the results of this analysis can be used to trace particular values of biophysical parameters (synaptic strength and parameters of calcium dynamics), which are known to be impacted in Parkinson's disease. |
1212.3229 | Leah B. Shaw | Ilker Tunc and Leah B. Shaw | Effects of community structure on epidemic spread in an adaptive network | null | null | null | null | q-bio.PE cs.SI nlin.AO physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | When an epidemic spreads in a population, individuals may adaptively change
the structure of their social contact network to reduce risk of infection. Here
we study the spread of an epidemic on an adaptive network with community
structure. We model the effect of two communities with different average
degrees. The disease model is susceptible-infected-susceptible (SIS), and
adaptation is rewiring of links between susceptibles and infectives. The
bifurcation structure is obtained, and a mean field model is developed that
accurately predicts the steady state behavior of the system. We show that an
epidemic can alter the community structure.
| [
{
"created": "Wed, 12 Dec 2012 01:05:47 GMT",
"version": "v1"
}
] | 2012-12-14 | [
[
"Tunc",
"Ilker",
""
],
[
"Shaw",
"Leah B.",
""
]
] | When an epidemic spreads in a population, individuals may adaptively change the structure of their social contact network to reduce risk of infection. Here we study the spread of an epidemic on an adaptive network with community structure. We model the effect of two communities with different average degrees. The disease model is susceptible-infected-susceptible (SIS), and adaptation is rewiring of links between susceptibles and infectives. The bifurcation structure is obtained, and a mean field model is developed that accurately predicts the steady state behavior of the system. We show that an epidemic can alter the community structure. |
1609.05738 | Joseba Dalmau | Rapha\"el Cerf and Joseba Dalmau | The quasispecies distribution | null | null | null | null | q-bio.PE math.CO math.PR | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The quasispecies model was introduced in 1971 by Manfred Eigen to discuss the
first stages of life on Earth. It provides an appealing mathematical framework
to study the evolution of populations in biology, for instance viruses. We
present briefly the model and we focus on its stationary solutions. These
formulae have a surprisingly rich combinatorial structure, involving for
instance the Eulerian and Stirling numbers, as well as the up--down
coefficients of permutations.
| [
{
"created": "Mon, 19 Sep 2016 14:15:07 GMT",
"version": "v1"
}
] | 2016-09-20 | [
[
"Cerf",
"Raphaël",
""
],
[
"Dalmau",
"Joseba",
""
]
] | The quasispecies model was introduced in 1971 by Manfred Eigen to discuss the first stages of life on Earth. It provides an appealing mathematical framework to study the evolution of populations in biology, for instance viruses. We present briefly the model and we focus on its stationary solutions. These formulae have a surprisingly rich combinatorial structure, involving for instance the Eulerian and Stirling numbers, as well as the up--down coefficients of permutations. |
q-bio/0612031 | Maksim Kouza M | Maksim Kouza, Chi-Fon Chang, Shura Hayryan, Tsan-hung Yu, Mai Suan Li,
Tai-huang Huang, and Chin-Kun Hu | Folding of the Protein Domain hbSBD | 25 pages, 7 figures, 1 table, published in Biophysical Journal | Biophysical J. 89, 3353 (2005) | 10.1529/biophysj.105.065151 | null | q-bio.BM | null | The folding of the alpha-helice domain hbSBD of the mammalian mitochondrial
branched-chain alpha-ketoacid dehydrogenase (BCKD) complex is studied by the
circular dichroism technique in absence of urea. Thermal denaturation is used
to evaluate various thermodynamic parameters defining the equilibrium
unfolding, which is well described by the two-state model with the folding
temperature T_f = 317.8 K and the enthalpy change Delta H_g = 19.67 kcal/mol.
The folding is also studied numerically using the off-lattice coarse-grained Go
model and the Langevin dynamics. The obtained results, including the population
of the native basin, the free energy landscape as a function of the number of
native contacts and the folding kinetics, also suggest that the hbSBD domain is
a two-state folder. These results are consistent with the biological function
of hbSBD in BCKD.
| [
{
"created": "Sun, 17 Dec 2006 13:03:27 GMT",
"version": "v1"
}
] | 2015-06-26 | [
[
"Kouza",
"Maksim",
""
],
[
"Chang",
"Chi-Fon",
""
],
[
"Hayryan",
"Shura",
""
],
[
"Yu",
"Tsan-hung",
""
],
[
"Li",
"Mai Suan",
""
],
[
"Huang",
"Tai-huang",
""
],
[
"Hu",
"Chin-Kun",
""
]
] | The folding of the alpha-helice domain hbSBD of the mammalian mitochondrial branched-chain alpha-ketoacid dehydrogenase (BCKD) complex is studied by the circular dichroism technique in absence of urea. Thermal denaturation is used to evaluate various thermodynamic parameters defining the equilibrium unfolding, which is well described by the two-state model with the folding temperature T_f = 317.8 K and the enthalpy change Delta H_g = 19.67 kcal/mol. The folding is also studied numerically using the off-lattice coarse-grained Go model and the Langevin dynamics. The obtained results, including the population of the native basin, the free energy landscape as a function of the number of native contacts and the folding kinetics, also suggest that the hbSBD domain is a two-state folder. These results are consistent with the biological function of hbSBD in BCKD. |
0907.1056 | Edgardo Ugalde | Ricardo Lima, Arnaud Meyroneinc, Edgardo Ugalde | Open Regulatory Networks and Modularity | 31 pages, 13 figures | null | null | null | q-bio.MN q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the dynamical properties of small regulatory networks treated as non
autonomous dynamical systems called modules when working inside larger networks
or, equivalently when subject to external signal inputs. Particular emphasis is
put on the interplay between the internal properties of the open systems and
the different possible inputs on them to deduce new functionalities of the
modules. We use discrete-time, piecewise-affine and piecewise-contracting
models with interactions of a regulatory nature to perform our study.
| [
{
"created": "Mon, 6 Jul 2009 18:00:24 GMT",
"version": "v1"
}
] | 2009-07-07 | [
[
"Lima",
"Ricardo",
""
],
[
"Meyroneinc",
"Arnaud",
""
],
[
"Ugalde",
"Edgardo",
""
]
] | We study the dynamical properties of small regulatory networks treated as non autonomous dynamical systems called modules when working inside larger networks or, equivalently when subject to external signal inputs. Particular emphasis is put on the interplay between the internal properties of the open systems and the different possible inputs on them to deduce new functionalities of the modules. We use discrete-time, piecewise-affine and piecewise-contracting models with interactions of a regulatory nature to perform our study. |
2303.02479 | Chandre Dharma-wardana | Chandre Dharma-wardana (NRC Canada) | Chronic Kidney Disease of Unknown Aetiolgy (CKDu)-the search for causes
and the impact of its politicization | A shorter, peer-reviewed version of this article appears as Chapter
17 of Medical Geology, Enroute to One Health, Eds, Prasad and Vithanage,
Wiley (2023) | Chapter 17 of Medical Geology, Enroute to One Health, Eds, Prasad
and Vithanage, Wiley (2023)
https://www.wiley.com/en-us/exportProduct/pdf/9781119867340 | null | null | q-bio.QM q-bio.TO | http://creativecommons.org/licenses/by/4.0/ | Kidney disease of unknown aetiology (CKDu) has been identified in many
countries extending from MesoAmerica and Egypt, to South-east Asia and China.
Although CKDu has been linked by various authors to farming, it is an artifact
of treating multi-modal disease distributions as unimodal. There is NO
correlation of CKDu with agriculture since affected farming villages are often
surrounded by other farming villages free of CKDu. Initial studies looked for a
correlation of CKDu with toxic heavy metal residues of arsenic, cadmium etc.,
or herbicides like glyphosate that may be present in the environment, as the
causative factors. There is now considerable consensus that their
concentrations are below danger thresholds, be it in Mesoamerica or south-east
Asia. The conceptual basis of a search for etiology within a systems approach
is discussed, and attempts to name the disease to bias the identification of
its etiology are reviewed. Current research has narrowed down the etiology to
geochemical electrolytic contaminants like fluorides and ionic components in
hard water, nanosilica (found in water as well as in the air), as well as renal
toxins similar to indoxyl sulphates that may arise from interactions of ions
with humic acids contained in aqueous organic matter. However, while
agrochemical toxins are increasingly considered less relevant to the etiology
of CKDu, it has become a firm public belief. In Sri Lanka this has spawned
ideology-based agricultural policies for partial and complete banning of
agrochemicals (2014-2021), followed by some back-tracking, disrupting the
economy and the food supply. A farmer's uprising in 2022 was spawned by poor
harvests. It triggered a larger popular uprising that led to the collapse of a
government wedded to romanticized eco-extremist agricultural policies in a
country already facing difficulties in the wake of Covid and Ukraine.
| [
{
"created": "Sat, 4 Mar 2023 18:59:41 GMT",
"version": "v1"
}
] | 2023-03-07 | [
[
"Dharma-wardana",
"Chandre",
"",
"NRC Canada"
]
] | Kidney disease of unknown aetiology (CKDu) has been identified in many countries extending from MesoAmerica and Egypt, to South-east Asia and China. Although CKDu has been linked by various authors to farming, it is an artifact of treating multi-modal disease distributions as unimodal. There is NO correlation of CKDu with agriculture since affected farming villages are often surrounded by other farming villages free of CKDu. Initial studies looked for a correlation of CKDu with toxic heavy metal residues of arsenic, cadmium etc., or herbicides like glyphosate that may be present in the environment, as the causative factors. There is now considerable consensus that their concentrations are below danger thresholds, be it in Mesoamerica or south-east Asia. The conceptual basis of a search for etiology within a systems approach is discussed, and attempts to name the disease to bias the identification of its etiology are reviewed. Current research has narrowed down the etiology to geochemical electrolytic contaminants like fluorides and ionic components in hard water, nanosilica (found in water as well as in the air), as well as renal toxins similar to indoxyl sulphates that may arise from interactions of ions with humic acids contained in aqueous organic matter. However, while agrochemical toxins are increasingly considered less relevant to the etiology of CKDu, it has become a firm public belief. In Sri Lanka this has spawned ideology-based agricultural policies for partial and complete banning of agrochemicals (2014-2021), followed by some back-tracking, disrupting the economy and the food supply. A farmer's uprising in 2022 was spawned by poor harvests. It triggered a larger popular uprising that led to the collapse of a government wedded to romanticized eco-extremist agricultural policies in a country already facing difficulties in the wake of Covid and Ukraine. |
2404.16582 | Hideaki Yamamoto | Nobuaki Monma, Hideaki Yamamoto, Naoya Fujiwara, Hakuba Murota,
Satoshi Moriya, Ayumi Hirano-Iwata, and Shigeo Sato | Directional intermodular coupling enriches functional complexity in
biological neuronal networks | 42 pages, 5 figures, 8 supplementary figures, 2 supplementary tables | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Hierarchically modular organization is a canonical network topology that is
evolutionarily conserved in the nervous systems of animals. Within the network,
neurons form directional connections defined by the growth of their axonal
terminals. However, this topology is dissimilar to the network formed by
dissociated neurons in culture because they form randomly connected networks on
homogeneous substrates. In this study, we fabricated microfluidic devices to
reconstitute hierarchically modular neuronal networks in culture (in vitro) and
investigated how non-random structures, such as directional connectivity
between modules, affect global network dynamics. Embedding directional
connections in a pseudo-feedforward manner suppressed excessive synchrony in
cultured neuronal networks and enhanced the integration-segregation balance.
Modeling the behavior of biological neuronal networks using spiking neural
networks (SNNs) further revealed that modularity and directionality cooperate
to shape such network dynamics. Finally, we demonstrate that for a given
network topology, the statistics of network dynamics, such as global network
activation, correlation coefficient, and functional complexity, can be
analytically predicted based on eigendecomposition of the transition matrix in
the state-transition model. Hence, the integration of bioengineering and cell
culture technologies enables us not only to reconstitute complex network
circuitry in the nervous system but also to understand the structure-function
relationships in biological neuronal networks by bridging theoretical modeling
with in vitro experiments.
| [
{
"created": "Thu, 25 Apr 2024 12:56:23 GMT",
"version": "v1"
}
] | 2024-04-26 | [
[
"Monma",
"Nobuaki",
""
],
[
"Yamamoto",
"Hideaki",
""
],
[
"Fujiwara",
"Naoya",
""
],
[
"Murota",
"Hakuba",
""
],
[
"Moriya",
"Satoshi",
""
],
[
"Hirano-Iwata",
"Ayumi",
""
],
[
"Sato",
"Shigeo",
""
]
] | Hierarchically modular organization is a canonical network topology that is evolutionarily conserved in the nervous systems of animals. Within the network, neurons form directional connections defined by the growth of their axonal terminals. However, this topology is dissimilar to the network formed by dissociated neurons in culture because they form randomly connected networks on homogeneous substrates. In this study, we fabricated microfluidic devices to reconstitute hierarchically modular neuronal networks in culture (in vitro) and investigated how non-random structures, such as directional connectivity between modules, affect global network dynamics. Embedding directional connections in a pseudo-feedforward manner suppressed excessive synchrony in cultured neuronal networks and enhanced the integration-segregation balance. Modeling the behavior of biological neuronal networks using spiking neural networks (SNNs) further revealed that modularity and directionality cooperate to shape such network dynamics. Finally, we demonstrate that for a given network topology, the statistics of network dynamics, such as global network activation, correlation coefficient, and functional complexity, can be analytically predicted based on eigendecomposition of the transition matrix in the state-transition model. Hence, the integration of bioengineering and cell culture technologies enables us not only to reconstitute complex network circuitry in the nervous system but also to understand the structure-function relationships in biological neuronal networks by bridging theoretical modeling with in vitro experiments. |
2106.08991 | Cameron Browne | Cameron J. Browne and Fadoua Yahia | Virus-immune dynamics determined by prey-predator interaction network
and epistasis in viral fitness landscape | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Population dynamics and evolutionary genetics underly the structure of
ecosystems, changing on the same timescale for interacting species with rapid
turnover, such as virus (e.g. HIV) and immune response. Thus, an important
problem in mathematical modeling is to connect ecology, evolution and genetics,
which often have been treated separately. Here, extending analysis of multiple
virus and immune response populations in a resource - prey (consumer) -
predator model from Browne and Smith \cite{browne2018dynamics}, we show that
long term dynamics of viral mutants evolving resistance at distinct epitopes
(viral proteins targeted by immune responses) are governed by epistasis in the
virus fitness landscape. In particular, the stability of persistent equilibrium
virus-immune (prey-predator) network structures, such as nested and one-to-one,
and bifurcations are determined by a collection of circuits defined by
combinations of viral fitnesses that are minimally additive within a hypercube
of binary sequences representing all possible viral epitope sequences ordered
according to immunodominance hierarchy. Numerical solutions of our ordinary
differential equation system, along with an extended stochastic version
including random mutation, demonstrate how pairwise or multiplicative epistatic
interactions shape viral evolution against concurrent immune responses and
convergence to the multi-variant steady state predicted by theoretical results.
Furthermore, simulations illustrate how periodic infusions of subdominant
immune responses can induce a bifurcation in the persistent viral strains,
offering superior host outcome over an alternative strategy of immunotherapy
with strongest immune response.
| [
{
"created": "Wed, 16 Jun 2021 17:46:11 GMT",
"version": "v1"
}
] | 2021-06-17 | [
[
"Browne",
"Cameron J.",
""
],
[
"Yahia",
"Fadoua",
""
]
] | Population dynamics and evolutionary genetics underly the structure of ecosystems, changing on the same timescale for interacting species with rapid turnover, such as virus (e.g. HIV) and immune response. Thus, an important problem in mathematical modeling is to connect ecology, evolution and genetics, which often have been treated separately. Here, extending analysis of multiple virus and immune response populations in a resource - prey (consumer) - predator model from Browne and Smith \cite{browne2018dynamics}, we show that long term dynamics of viral mutants evolving resistance at distinct epitopes (viral proteins targeted by immune responses) are governed by epistasis in the virus fitness landscape. In particular, the stability of persistent equilibrium virus-immune (prey-predator) network structures, such as nested and one-to-one, and bifurcations are determined by a collection of circuits defined by combinations of viral fitnesses that are minimally additive within a hypercube of binary sequences representing all possible viral epitope sequences ordered according to immunodominance hierarchy. Numerical solutions of our ordinary differential equation system, along with an extended stochastic version including random mutation, demonstrate how pairwise or multiplicative epistatic interactions shape viral evolution against concurrent immune responses and convergence to the multi-variant steady state predicted by theoretical results. Furthermore, simulations illustrate how periodic infusions of subdominant immune responses can induce a bifurcation in the persistent viral strains, offering superior host outcome over an alternative strategy of immunotherapy with strongest immune response. |
1707.05813 | Diego C\'esar Batista Mariano | Diego C. B. Mariano, Carmelina Leite, Lucianna H. S. Santos, Rafael E.
O. Rocha, and Raquel C. de Melo-Minardi | A guide to performing systematic literature reviews in bioinformatics | Technical report - RT.DCC.002/2017 | null | null | RT.DCC.002/2017 | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Bioinformatics research depends on high-quality databases to provide accurate
results. In silico experiments, correctly performed, may prospect novel
discoveries and elucidates pathways for biological experiments through data
analysis in large scale. However, most biological databases have presented
mistakes, such as data incorrectly classified or incomplete information. Also,
sometimes, data mining algorithms cannot treat these errors, leading to serious
problems for the in silico analysis. Manual curation of data extracted from
literature is a possible solution for this problem. Systematic Literature
Review (SLR), or Systematic Review, is a method to identify, evaluate and
summarize the state-of-the-art of a specific theme. Moreover, SLR allows the
collection from databases restrictively, which allows an analysis with lower
bias than traditional reviews. The SRL approaches have been widely used for
decision-making in medical and environmental studies. However, other research
areas, such as bioinformatics, do not have a specific step-by-step to guide
researchers undertaking the procedures of an SLR. In this study, we propose a
guideline, called BiSRL, to perform SLR in bioinformatics. Our procedures cover
the most traditional guides to produce SLRs adapted to bioinformatics. To
evaluate our method, we propose a case study to detect and summarize SLRs
developed for bioinformatics data. We used two databases: PubMed and
ScienceDirect. A total of 207 papers were screened in four steps: title,
abstract, diagonal and full-text reading. Four evaluators performed the SLR
independently to reduce bias risk. A total of 8 papers was included in the SLR
case study. The case study demonstrates how to implement the methods of BiSLR
to procedure SLR for bioinformatics. BiSLR may guide bioinformaticians to
perform systematic reviews reproducible to collect accurate data for higher
quality analysis.
| [
{
"created": "Tue, 18 Jul 2017 18:38:46 GMT",
"version": "v1"
}
] | 2017-07-20 | [
[
"Mariano",
"Diego C. B.",
""
],
[
"Leite",
"Carmelina",
""
],
[
"Santos",
"Lucianna H. S.",
""
],
[
"Rocha",
"Rafael E. O.",
""
],
[
"de Melo-Minardi",
"Raquel C.",
""
]
] | Bioinformatics research depends on high-quality databases to provide accurate results. In silico experiments, correctly performed, may prospect novel discoveries and elucidates pathways for biological experiments through data analysis in large scale. However, most biological databases have presented mistakes, such as data incorrectly classified or incomplete information. Also, sometimes, data mining algorithms cannot treat these errors, leading to serious problems for the in silico analysis. Manual curation of data extracted from literature is a possible solution for this problem. Systematic Literature Review (SLR), or Systematic Review, is a method to identify, evaluate and summarize the state-of-the-art of a specific theme. Moreover, SLR allows the collection from databases restrictively, which allows an analysis with lower bias than traditional reviews. The SRL approaches have been widely used for decision-making in medical and environmental studies. However, other research areas, such as bioinformatics, do not have a specific step-by-step to guide researchers undertaking the procedures of an SLR. In this study, we propose a guideline, called BiSRL, to perform SLR in bioinformatics. Our procedures cover the most traditional guides to produce SLRs adapted to bioinformatics. To evaluate our method, we propose a case study to detect and summarize SLRs developed for bioinformatics data. We used two databases: PubMed and ScienceDirect. A total of 207 papers were screened in four steps: title, abstract, diagonal and full-text reading. Four evaluators performed the SLR independently to reduce bias risk. A total of 8 papers was included in the SLR case study. The case study demonstrates how to implement the methods of BiSLR to procedure SLR for bioinformatics. BiSLR may guide bioinformaticians to perform systematic reviews reproducible to collect accurate data for higher quality analysis. |
1010.4722 | Alexander Bershadskii | A. Bershadskii and Y. Ikegaya | Chaotic neuron clock | null | Chaos, Solitons & Fractals 44 (2011) 342-347 | 10.1016/j.chaos.2011.03.001 | null | q-bio.NC nlin.CD | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A simple threshold model of neuron firing (with the neuron membrane
electrochemical potential governed by the chaotic Rossler attractor) has been
analyzed by mapping the generated irregular spiking time-series into telegraph
signals. In this model the fundamental frequency of the chaotic Rossler
attractor provides (with a period doubling) the strong periodic component of
the generated irregular signal. The exponentially decaying broad-band part of
the spectrum of the Rossler attractor has been transformed by the threshold
firing mechanism into a scaling tale. These results are compared with irregular
spiking time-series obtained in vitro from a spontaneous activity of
hippocampal (CA3) singular neurons (rat's brain slice culture). The comparison
shows good agreement between the model and experimentally obtained spectra.
| [
{
"created": "Fri, 22 Oct 2010 14:28:15 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Nov 2010 21:09:22 GMT",
"version": "v2"
},
{
"created": "Sun, 21 Nov 2010 18:15:10 GMT",
"version": "v3"
},
{
"created": "Thu, 3 Mar 2011 22:27:46 GMT",
"version": "v4"
}
] | 2011-04-19 | [
[
"Bershadskii",
"A.",
""
],
[
"Ikegaya",
"Y.",
""
]
] | A simple threshold model of neuron firing (with the neuron membrane electrochemical potential governed by the chaotic Rossler attractor) has been analyzed by mapping the generated irregular spiking time-series into telegraph signals. In this model the fundamental frequency of the chaotic Rossler attractor provides (with a period doubling) the strong periodic component of the generated irregular signal. The exponentially decaying broad-band part of the spectrum of the Rossler attractor has been transformed by the threshold firing mechanism into a scaling tale. These results are compared with irregular spiking time-series obtained in vitro from a spontaneous activity of hippocampal (CA3) singular neurons (rat's brain slice culture). The comparison shows good agreement between the model and experimentally obtained spectra. |
1404.3262 | Samantha Stam | Samantha Stam, Jon Alberts, Margaret L. Gardel, Edwin Munro | Force generation by Myosin II Filaments in Compliant Networks | null | null | null | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Myosin II isoforms with varying mechanochemistry and filament size interact
with filamentous actin (F-actin) networks to generate contractile forces in
cells. How their properties control force production in environments with
varying stiffness is poorly understood. Here, we incorporated literature values
for properties of myosin II isoforms into a cross-bridge model. Similar actin
gliding speeds and force-velocity curves expected from previous experiments
were observed. Motor force output on an elastic load was regulated by two
timescales--that of their attachment to F-actin, which varied sharply with the
ensemble size, motor duty ratio, and external load, and that of force build up,
which scaled with ensemble stall force, gliding speed, and load stiffness.
While such regulation did not require force-dependent kinetics, the myosin
catch bond produced positive feedback between attachment time and force to
trigger switch-like transitions from short attachments and small forces to high
force-generating runs at threshold parameter values. Parameters representing
skeletal muscle myosin, non-muscle myosin IIB, and non-muscle myosin IIA
revealed distinct regimes of behavior respectively: (1) large assemblies of
fast, low-duty ratio motors rapidly build stable forces over a large range of
environmental stiffness, (2) ensembles of slow, high-duty ratio motors serve as
high-affinity cross-links with force build-up times that exceed physiological
timescales, and (3) small assemblies of low-duty ratio motors operating at
intermediate speeds may respond sharply to changes in mechanical context--at
low forces or stiffness, they serve as low affinity cross-links but they can
transition to effective force production via the positive feedback mechanism
described above. These results reveal how myosin isoform properties may be
tuned to produce force and respond to mechanical cues in their environment.
| [
{
"created": "Sat, 12 Apr 2014 07:19:06 GMT",
"version": "v1"
},
{
"created": "Tue, 8 Jul 2014 14:16:44 GMT",
"version": "v2"
}
] | 2014-07-09 | [
[
"Stam",
"Samantha",
""
],
[
"Alberts",
"Jon",
""
],
[
"Gardel",
"Margaret L.",
""
],
[
"Munro",
"Edwin",
""
]
] | Myosin II isoforms with varying mechanochemistry and filament size interact with filamentous actin (F-actin) networks to generate contractile forces in cells. How their properties control force production in environments with varying stiffness is poorly understood. Here, we incorporated literature values for properties of myosin II isoforms into a cross-bridge model. Similar actin gliding speeds and force-velocity curves expected from previous experiments were observed. Motor force output on an elastic load was regulated by two timescales--that of their attachment to F-actin, which varied sharply with the ensemble size, motor duty ratio, and external load, and that of force build up, which scaled with ensemble stall force, gliding speed, and load stiffness. While such regulation did not require force-dependent kinetics, the myosin catch bond produced positive feedback between attachment time and force to trigger switch-like transitions from short attachments and small forces to high force-generating runs at threshold parameter values. Parameters representing skeletal muscle myosin, non-muscle myosin IIB, and non-muscle myosin IIA revealed distinct regimes of behavior respectively: (1) large assemblies of fast, low-duty ratio motors rapidly build stable forces over a large range of environmental stiffness, (2) ensembles of slow, high-duty ratio motors serve as high-affinity cross-links with force build-up times that exceed physiological timescales, and (3) small assemblies of low-duty ratio motors operating at intermediate speeds may respond sharply to changes in mechanical context--at low forces or stiffness, they serve as low affinity cross-links but they can transition to effective force production via the positive feedback mechanism described above. These results reveal how myosin isoform properties may be tuned to produce force and respond to mechanical cues in their environment. |
1407.7913 | Anna Stewart Ibarra | Anna M. Stewart Ibarra, Angel G. Munoz, Sadie J. Ryan, Mercy J.
Borbor, Efrain Beltran Ayala, Julia L. Finkelstein, Raul Mejia, Tania
Ordonez, G. Cristina Recalde Coronel, Keytia Rivero | Spatiotemporal clustering, climate periodicity, and social-ecological
risk factors for dengue during an outbreak in Machala, Ecuador, in 2010 | Available at BMC Infectious Diseases:
http://www.biomedcentral.com/1471-2334/14/610 | 2014. BMC Infectious Disease. 14:610 | 10.1186/s12879-014-0610-4 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The objective of this study was to characterize the spatiotemporal dynamics
and climatic and social-ecological risk factors associated with the largest
dengue epidemic to date in Machala, Ecuador, to inform the development of a
dengue EWS. The following data were included in analyses: neighborhood-level
georeferenced dengue cases, national census data, and entomological
surveillance data from 2010; time series of weekly dengue cases (aggregated to
the city-level) and meteorological data from 2003 to 2012. We applied LISA and
Morans I to analyze the spatial distribution of the 2010 dengue cases, and
developed multivariate logistic regression models through a multi-model
selection process to identify census variables and entomological covariates
associated with the presence of dengue at the neighborhood level. Using data
aggregated at the city-level, we conducted a time-series (wavelet) analysis of
weekly climate and dengue incidence (2003-2012) to identify significant time
periods (e.g., annual, biannual) when climate co-varied with dengue, and to
describe the climate conditions associated with the 2010 outbreak. We found
significant hotspots of dengue transmission near the center of Machala. The
best-fit model to predict the presence of dengue included older age and female
gender of the head of the household, greater access to piped water in the home,
poor housing condition, and less distance to the central hospital. Wavelet
analyses revealed that dengue transmission co-varied with rainfall and minimum
temperature at annual and biannual cycles, and we found that anomalously high
rainfall and temperatures were associated with the 2010 outbreak. Our findings
highlight the importance of geospatial information in dengue surveillance and
the potential to develop a climate-driven spatiotemporal prediction models to
inform disease prevention and control interventions.
| [
{
"created": "Wed, 30 Jul 2014 01:04:18 GMT",
"version": "v1"
},
{
"created": "Fri, 7 Nov 2014 00:45:49 GMT",
"version": "v2"
},
{
"created": "Tue, 13 Jan 2015 17:20:31 GMT",
"version": "v3"
}
] | 2015-01-14 | [
[
"Ibarra",
"Anna M. Stewart",
""
],
[
"Munoz",
"Angel G.",
""
],
[
"Ryan",
"Sadie J.",
""
],
[
"Borbor",
"Mercy J.",
""
],
[
"Ayala",
"Efrain Beltran",
""
],
[
"Finkelstein",
"Julia L.",
""
],
[
"Mejia",
"Raul",... | The objective of this study was to characterize the spatiotemporal dynamics and climatic and social-ecological risk factors associated with the largest dengue epidemic to date in Machala, Ecuador, to inform the development of a dengue EWS. The following data were included in analyses: neighborhood-level georeferenced dengue cases, national census data, and entomological surveillance data from 2010; time series of weekly dengue cases (aggregated to the city-level) and meteorological data from 2003 to 2012. We applied LISA and Morans I to analyze the spatial distribution of the 2010 dengue cases, and developed multivariate logistic regression models through a multi-model selection process to identify census variables and entomological covariates associated with the presence of dengue at the neighborhood level. Using data aggregated at the city-level, we conducted a time-series (wavelet) analysis of weekly climate and dengue incidence (2003-2012) to identify significant time periods (e.g., annual, biannual) when climate co-varied with dengue, and to describe the climate conditions associated with the 2010 outbreak. We found significant hotspots of dengue transmission near the center of Machala. The best-fit model to predict the presence of dengue included older age and female gender of the head of the household, greater access to piped water in the home, poor housing condition, and less distance to the central hospital. Wavelet analyses revealed that dengue transmission co-varied with rainfall and minimum temperature at annual and biannual cycles, and we found that anomalously high rainfall and temperatures were associated with the 2010 outbreak. Our findings highlight the importance of geospatial information in dengue surveillance and the potential to develop a climate-driven spatiotemporal prediction models to inform disease prevention and control interventions. |
2305.11194 | Aryo Gema | Aryo Pradipta Gema, Micha{\l} Kobiela, Achille Fraisse, Ajitha Rajan,
Diego A. Oyarz\'un, Javier Antonio Alfaro | Vaxformer: Antigenicity-controlled Transformer for Vaccine Design
Against SARS-CoV-2 | null | null | null | null | q-bio.BM cs.LG q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | The SARS-CoV-2 pandemic has emphasised the importance of developing a
universal vaccine that can protect against current and future variants of the
virus. The present study proposes a novel conditional protein Language Model
architecture, called Vaxformer, which is designed to produce natural-looking
antigenicity-controlled SARS-CoV-2 spike proteins. We evaluate the generated
protein sequences of the Vaxformer model using DDGun protein stability measure,
netMHCpan antigenicity score, and a structure fidelity score with AlphaFold to
gauge its viability for vaccine development. Our results show that Vaxformer
outperforms the existing state-of-the-art Conditional Variational Autoencoder
model to generate antigenicity-controlled SARS-CoV-2 spike proteins. These
findings suggest promising opportunities for conditional Transformer models to
expand our understanding of vaccine design and their role in mitigating global
health challenges. The code used in this study is available at
https://github.com/aryopg/vaxformer .
| [
{
"created": "Thu, 18 May 2023 13:36:57 GMT",
"version": "v1"
}
] | 2023-05-22 | [
[
"Gema",
"Aryo Pradipta",
""
],
[
"Kobiela",
"Michał",
""
],
[
"Fraisse",
"Achille",
""
],
[
"Rajan",
"Ajitha",
""
],
[
"Oyarzún",
"Diego A.",
""
],
[
"Alfaro",
"Javier Antonio",
""
]
] | The SARS-CoV-2 pandemic has emphasised the importance of developing a universal vaccine that can protect against current and future variants of the virus. The present study proposes a novel conditional protein Language Model architecture, called Vaxformer, which is designed to produce natural-looking antigenicity-controlled SARS-CoV-2 spike proteins. We evaluate the generated protein sequences of the Vaxformer model using DDGun protein stability measure, netMHCpan antigenicity score, and a structure fidelity score with AlphaFold to gauge its viability for vaccine development. Our results show that Vaxformer outperforms the existing state-of-the-art Conditional Variational Autoencoder model to generate antigenicity-controlled SARS-CoV-2 spike proteins. These findings suggest promising opportunities for conditional Transformer models to expand our understanding of vaccine design and their role in mitigating global health challenges. The code used in this study is available at https://github.com/aryopg/vaxformer . |
2005.06755 | Angelo Rosa Dr | Alessandra Merlotti and Angelo Rosa and Daniel Remondini | Merging 1D and 3D genomic information: Challenges in modelling and
validation | This review article contains 15 pages and 12 figures. It is part of a
series of invited contribution for the Special Issue "Transcriptional
Profiles and Regulatory Gene Networks" (June 2020) published in the journal
"Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms" | Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms
Volume 1863, Issue 6, June 2020, 194415 | 10.1016/j.bbagrm.2019.194415 | null | q-bio.GN physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Genome organization in eukaryotes during interphase stems from the delicate
balance between non-random correlations present in the DNA polynucleotide
linear sequence and the physico/chemical reactions which shape continuously the
form and structure of DNA and chromatin inside the nucleus of the cell. It is
now clear that these mechanisms have a key role in important processes like
gene regulation, yet the detailed ways they act simultaneously and, eventually,
come to influence each other even across very different length-scales remain
largely unexplored. In this paper, we recapitulate some of the main results
concerning gene regulatory and physical mechanisms, in relation to the
information encoded in the 1D sequence and the 3D folding structure of DNA. In
particular, we stress how reciprocal crossfeeding between 1D and 3D models may
provide original insight into how these complex processes work and influence
each other.
| [
{
"created": "Thu, 14 May 2020 07:03:07 GMT",
"version": "v1"
}
] | 2020-05-15 | [
[
"Merlotti",
"Alessandra",
""
],
[
"Rosa",
"Angelo",
""
],
[
"Remondini",
"Daniel",
""
]
] | Genome organization in eukaryotes during interphase stems from the delicate balance between non-random correlations present in the DNA polynucleotide linear sequence and the physico/chemical reactions which shape continuously the form and structure of DNA and chromatin inside the nucleus of the cell. It is now clear that these mechanisms have a key role in important processes like gene regulation, yet the detailed ways they act simultaneously and, eventually, come to influence each other even across very different length-scales remain largely unexplored. In this paper, we recapitulate some of the main results concerning gene regulatory and physical mechanisms, in relation to the information encoded in the 1D sequence and the 3D folding structure of DNA. In particular, we stress how reciprocal crossfeeding between 1D and 3D models may provide original insight into how these complex processes work and influence each other. |
1609.03257 | Nathan Baker | Luke J. Gosink, Christopher C. Overall, Sarah M. Reehl, Paul D.
Whitney, David L. Mobley, Nathan A. Baker | Bayesian Model Averaging for Ensemble-Based Estimates of Solvation Free
Energies | null | null | null | null | q-bio.BM physics.comp-ph stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper applies the Bayesian Model Averaging (BMA) statistical ensemble
technique to estimate small molecule solvation free energies. There is a wide
range of methods available for predicting solvation free energies, ranging from
empirical statistical models to ab initio quantum mechanical approaches. Each
of these methods is based on a set of conceptual assumptions that can affect
predictive accuracy and transferability. Using an iterative statistical
process, we have selected and combined solvation energy estimates using an
ensemble of 17 diverse methods from the fourth Statistical Assessment of
Modeling of Proteins and Ligands (SAMPL) blind prediction study to form a
single, aggregated solvation energy estimate. The ensemble design process
evaluates the statistical information in each individual method as well as the
performance of the aggregate estimate obtained from the ensemble as a whole.
Methods that possess minimal or redundant information are pruned from the
ensemble and the evaluation process repeats until aggregate predictive
performance can no longer be improved. We show that this process results in a
final aggregate estimate that outperforms all individual methods by reducing
estimate errors by as much as 91% to 1.2 kcal/mol accuracy. We also compare our
iterative refinement approach to other statistical ensemble approaches and
demonstrate that this iterative process reduces estimate errors by as much as
61%. This work provides a new approach for accurate solvation free energy
prediction and lays the foundation for future work on aggregate models that can
balance computational cost with prediction accuracy.
| [
{
"created": "Mon, 12 Sep 2016 03:21:11 GMT",
"version": "v1"
},
{
"created": "Thu, 15 Dec 2016 02:40:35 GMT",
"version": "v2"
}
] | 2016-12-16 | [
[
"Gosink",
"Luke J.",
""
],
[
"Overall",
"Christopher C.",
""
],
[
"Reehl",
"Sarah M.",
""
],
[
"Whitney",
"Paul D.",
""
],
[
"Mobley",
"David L.",
""
],
[
"Baker",
"Nathan A.",
""
]
] | This paper applies the Bayesian Model Averaging (BMA) statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range of methods available for predicting solvation free energies, ranging from empirical statistical models to ab initio quantum mechanical approaches. Each of these methods is based on a set of conceptual assumptions that can affect predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the fourth Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) blind prediction study to form a single, aggregated solvation energy estimate. The ensemble design process evaluates the statistical information in each individual method as well as the performance of the aggregate estimate obtained from the ensemble as a whole. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal/mol accuracy. We also compare our iterative refinement approach to other statistical ensemble approaches and demonstrate that this iterative process reduces estimate errors by as much as 61%. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with prediction accuracy. |
0802.0308 | Bob Eisenberg | Bob Eisenberg | Bubble Gating Currents in Ionic Channels | Typo corrected | null | null | null | q-bio.BM q-bio.QM | null | Bubbles in ion channel proteins have been proposed to be the bistable gates
that control current flow. Gating currents associated with channel gating would
then be an electrical signature of bubble breaking and formation, arising from
the change in dielectric coefficient as the bubble breaks or forms. A bubble
would have a dielectric coefficient of 1. A filled bubble would have a
dielectric coefficient (say) between 30 and 80. Transporters, pumps, and
channels would be expected to have gating currents.
| [
{
"created": "Sun, 3 Feb 2008 22:19:22 GMT",
"version": "v1"
},
{
"created": "Tue, 5 Feb 2008 11:06:35 GMT",
"version": "v2"
}
] | 2008-02-05 | [
[
"Eisenberg",
"Bob",
""
]
] | Bubbles in ion channel proteins have been proposed to be the bistable gates that control current flow. Gating currents associated with channel gating would then be an electrical signature of bubble breaking and formation, arising from the change in dielectric coefficient as the bubble breaks or forms. A bubble would have a dielectric coefficient of 1. A filled bubble would have a dielectric coefficient (say) between 30 and 80. Transporters, pumps, and channels would be expected to have gating currents. |
q-bio/0510047 | Hossein Zare | Shmuel Friedland, Mostafa Kaveh, Amir Niknejad, Hossein Zare | An Algorithm for Missing Value Estimation for DNA Microarray Data | null | null | null | null | q-bio.GN math.NA | null | Gene expression data matrices often contain missing expression values. In
this paper, we describe a new algorithm, named improved fixed rank
approximation algorithm (IFRAA), for missing values estimations of the large
gene expression data matrices. We compare the present algorithm with the two
existing and widely used methods for reconstructing missing entries for DNA
microarray gene expression data: the Bayesian principal component analysis
(BPCA) and the local least squares imputation method (LLS). The three
algorithms were applied to four microarray data sets and two synthetic low-rank
data matrices. Certain percentages of the elements of these data sets were
randomly deleted, and the three algorithms were used to recover them. In
conclusion IFRAA appears to be the most reliable and accurate approach for
recovering missing DNA microarray gene expression data, or any other noisy data
matrices that are effectively low rank.
| [
{
"created": "Wed, 26 Oct 2005 18:59:13 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Friedland",
"Shmuel",
""
],
[
"Kaveh",
"Mostafa",
""
],
[
"Niknejad",
"Amir",
""
],
[
"Zare",
"Hossein",
""
]
] | Gene expression data matrices often contain missing expression values. In this paper, we describe a new algorithm, named improved fixed rank approximation algorithm (IFRAA), for missing values estimations of the large gene expression data matrices. We compare the present algorithm with the two existing and widely used methods for reconstructing missing entries for DNA microarray gene expression data: the Bayesian principal component analysis (BPCA) and the local least squares imputation method (LLS). The three algorithms were applied to four microarray data sets and two synthetic low-rank data matrices. Certain percentages of the elements of these data sets were randomly deleted, and the three algorithms were used to recover them. In conclusion IFRAA appears to be the most reliable and accurate approach for recovering missing DNA microarray gene expression data, or any other noisy data matrices that are effectively low rank. |
1705.10424 | Iaroslav Ispolatov | Alexander Martynov, Konstantin Severinov, and Yaroslav Ispolatov | Optimal number of spacers in CRISPR arrays | 26 pages, 8 figures | PLoS Comput Biol 13(12): e1005891 (2017) | 10.1371/journal.pcbi.1005891 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We estimate the number of spacers in a CRISPR array of a bacterium which
maximizes its protection against a viral attack. The optimality follows from a
competition between two trends: too few distinct spacers make the bacteria
vulnerable to an attack by a virus with mutated corresponding protospacers,
while an excessive variety of spacers dilutes the number of the CRISPR
complexes armed with the most recent and thus most effective spacers. We first
evaluate the optimal number of spacers in a simple scenario of an infection by
a single viral species and later consider a more general case of multiple viral
species. We find that depending on such parameters as the concentration of
CRISPR-CAS interference complexes and its preference to arm with more recently
acquired spacers, the rate of viral mutation, and the number of viral species,
the predicted optimal array length lies within a range quite reasonable from
the viewpoint of recent experiments.
| [
{
"created": "Tue, 30 May 2017 01:27:10 GMT",
"version": "v1"
}
] | 2017-12-22 | [
[
"Martynov",
"Alexander",
""
],
[
"Severinov",
"Konstantin",
""
],
[
"Ispolatov",
"Yaroslav",
""
]
] | We estimate the number of spacers in a CRISPR array of a bacterium which maximizes its protection against a viral attack. The optimality follows from a competition between two trends: too few distinct spacers make the bacteria vulnerable to an attack by a virus with mutated corresponding protospacers, while an excessive variety of spacers dilutes the number of the CRISPR complexes armed with the most recent and thus most effective spacers. We first evaluate the optimal number of spacers in a simple scenario of an infection by a single viral species and later consider a more general case of multiple viral species. We find that depending on such parameters as the concentration of CRISPR-CAS interference complexes and its preference to arm with more recently acquired spacers, the rate of viral mutation, and the number of viral species, the predicted optimal array length lies within a range quite reasonable from the viewpoint of recent experiments. |
1203.1909 | Thomas Risler | Andrei S. Kozlov, Thomas Risler, Armin J. Hinterwirth and A. J.
Hudspeth | Relative stereociliary motion in a hair bundle opposes amplification at
distortion frequencies | 33 pages in total, including the main article with one table and
three figures, as well as the supplemental information that itself contains
two figures | The Journal of Physiology 590 (2), 301-308 (2012) | 10.1113/jphysiol.2011.218362 | null | q-bio.SC physics.bio-ph physics.data-an q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Direct gating of mechanoelectrical-transduction channels by mechanical force
is a basic feature of hair cells that assures fast transduction and underpins
the mechanical amplification of acoustic inputs. But the associated
nonlinearity - the gating compliance - inevitably distorts signals. Because
reducing distortion would make the ear a better detector, we sought mechanisms
with that effect. Mimicking in vivo stimulation, we used stiff probes to
displace individual hair bundles at physiological amplitudes and measured the
coherence and phase of the relative stereociliary motions with a dual-beam
differential interferometer. Although stereocilia moved coherently and in phase
at the stimulus frequencies, large phase lags at the frequencies of the
internally generated distortion products indicated dissipative relative
motions. Tip links engaged these relative modes and decreased the coherence in
both stimulated and free hair bundles. These results show that a hair bundle
breaks into a highly dissipative serial arrangement of stereocilia at
distortion frequencies, precluding their amplification.
| [
{
"created": "Thu, 8 Mar 2012 20:30:07 GMT",
"version": "v1"
}
] | 2012-03-09 | [
[
"Kozlov",
"Andrei S.",
""
],
[
"Risler",
"Thomas",
""
],
[
"Hinterwirth",
"Armin J.",
""
],
[
"Hudspeth",
"A. J.",
""
]
] | Direct gating of mechanoelectrical-transduction channels by mechanical force is a basic feature of hair cells that assures fast transduction and underpins the mechanical amplification of acoustic inputs. But the associated nonlinearity - the gating compliance - inevitably distorts signals. Because reducing distortion would make the ear a better detector, we sought mechanisms with that effect. Mimicking in vivo stimulation, we used stiff probes to displace individual hair bundles at physiological amplitudes and measured the coherence and phase of the relative stereociliary motions with a dual-beam differential interferometer. Although stereocilia moved coherently and in phase at the stimulus frequencies, large phase lags at the frequencies of the internally generated distortion products indicated dissipative relative motions. Tip links engaged these relative modes and decreased the coherence in both stimulated and free hair bundles. These results show that a hair bundle breaks into a highly dissipative serial arrangement of stereocilia at distortion frequencies, precluding their amplification. |
1701.02072 | Hau-tieng Wu | Antonio Cicone and Hau-Tieng Wu | How nonlinear-type time-frequency analysis can help in sensing
instantaneous heart rate and instantaneous respiratory rate from
photoplethysmography in a reliable way | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Despite the population of the noninvasive, economic, comfortable, and
easy-to-install photoplethysmography (PPG), it is still lacking a
mathematically rigorous and stable algorithm which is able to simultaneously
extract from a single-channel PPG signal the instantaneous heart rate (IHR) and
the instantaneous respiratory rate (IRR). In this paper, a novel algorithm
called deppG is provided to tackle this challenge. deppG is composed of two
theoretically solid nonlinear-type time-frequency analyses techniques, the
de-shape short time Fourier transform and the synchrosqueezing transform, which
allows us to extract the instantaneous physiological information from the PPG
signal in a reliable way. To test its performance, in addition to validating
the algorithm by a simulated signal and discussing the meaning of
"instantaneous", the algorithm is applied to two publicly available batch
databases, the Capnobase and the ICASSP 2015 signal processing cup. The former
contains PPG signals relative to spontaneous or controlled breathing in static
patients, and the latter is made up of PPG signals collected from subjects
doing intense physical activities. The accuracies of the estimated IHR and IRR
are compared with the ones obtained by other methods, and represent the
state-of-the-art in this field of research. The results suggest the potential
of deppG to extract instantaneous physiological information from a signal
acquired from widely available wearable devices, even when a subject carries
out intense physical activities.
| [
{
"created": "Mon, 9 Jan 2017 06:39:31 GMT",
"version": "v1"
},
{
"created": "Fri, 1 Sep 2017 23:50:46 GMT",
"version": "v2"
}
] | 2017-09-05 | [
[
"Cicone",
"Antonio",
""
],
[
"Wu",
"Hau-Tieng",
""
]
] | Despite the population of the noninvasive, economic, comfortable, and easy-to-install photoplethysmography (PPG), it is still lacking a mathematically rigorous and stable algorithm which is able to simultaneously extract from a single-channel PPG signal the instantaneous heart rate (IHR) and the instantaneous respiratory rate (IRR). In this paper, a novel algorithm called deppG is provided to tackle this challenge. deppG is composed of two theoretically solid nonlinear-type time-frequency analyses techniques, the de-shape short time Fourier transform and the synchrosqueezing transform, which allows us to extract the instantaneous physiological information from the PPG signal in a reliable way. To test its performance, in addition to validating the algorithm by a simulated signal and discussing the meaning of "instantaneous", the algorithm is applied to two publicly available batch databases, the Capnobase and the ICASSP 2015 signal processing cup. The former contains PPG signals relative to spontaneous or controlled breathing in static patients, and the latter is made up of PPG signals collected from subjects doing intense physical activities. The accuracies of the estimated IHR and IRR are compared with the ones obtained by other methods, and represent the state-of-the-art in this field of research. The results suggest the potential of deppG to extract instantaneous physiological information from a signal acquired from widely available wearable devices, even when a subject carries out intense physical activities. |
1101.2229 | Susan Khor | Susan Khor | Why aren't the small worlds of protein contact networks smaller | v2 accepted by European Conference on Artifical Life 2011 | null | null | null | q-bio.MN cs.SI physics.bio-ph physics.soc-ph q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Computer experiments are performed to investigate why protein contact
networks (networks induced by spatial contacts between amino acid residues of a
protein) do not have shorter average shortest path lengths in spite of their
importance to protein folding. We find that shorter average inter-nodal
distances is no guarantee of finding a global optimum more easily. Results from
the experiments also led to observations which parallel an existing view that
neither short-range nor long-range interactions dominate the protein folding
process. Nonetheless, runs where there was a slight delay in the use of
long-range interactions yielded the best search performance. We incorporate
this finding into the optimization function by giving more weight to
short-range links. This produced results showing that randomizing long-range
links does not yield better search performance than protein contact networks au
natural even though randomizing long-range links significantly reduces average
path lengths and retains much of the clustering and positive degree-degree
correlation inherent in protein contact networks. Hence there can be
explanations, other than the excluded volume argument, beneath the topological
limits of protein contact networks.
| [
{
"created": "Tue, 11 Jan 2011 22:27:19 GMT",
"version": "v1"
},
{
"created": "Wed, 1 Jun 2011 17:06:56 GMT",
"version": "v2"
}
] | 2011-06-02 | [
[
"Khor",
"Susan",
""
]
] | Computer experiments are performed to investigate why protein contact networks (networks induced by spatial contacts between amino acid residues of a protein) do not have shorter average shortest path lengths in spite of their importance to protein folding. We find that shorter average inter-nodal distances is no guarantee of finding a global optimum more easily. Results from the experiments also led to observations which parallel an existing view that neither short-range nor long-range interactions dominate the protein folding process. Nonetheless, runs where there was a slight delay in the use of long-range interactions yielded the best search performance. We incorporate this finding into the optimization function by giving more weight to short-range links. This produced results showing that randomizing long-range links does not yield better search performance than protein contact networks au natural even though randomizing long-range links significantly reduces average path lengths and retains much of the clustering and positive degree-degree correlation inherent in protein contact networks. Hence there can be explanations, other than the excluded volume argument, beneath the topological limits of protein contact networks. |
1812.04299 | Ankit Gupta | Patrik D\"urrenberger, Ankit Gupta, and Mustafa Khammash | A finite state projection method for steady-state sensitivity analysis
of stochastic reaction networks | 5 figures | null | 10.1063/1.5085271 | null | q-bio.QM math.PR q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Consider the standard stochastic reaction network model where the dynamics is
given by a continuous-time Markov chain over a discrete lattice. For such
models, estimation of parameter sensitivities is an important problem, but the
existing computational approaches to solve this problem usually require
time-consuming Monte Carlo simulations of the reaction dynamics. Therefore
these simulation-based approaches can only be expected to work over finite
time-intervals, while it is often of interest in applications to examine the
sensitivity values at the steady-state after the Markov chain has relaxed to
its stationary distribution. The aim of this paper is to present a
computational method for the estimation of steady-state parameter
sensitivities, which instead of using simulations, relies on the recently
developed stationary Finite State Projection (sFSP) algorithm [J. Chem. Phys.
147, 154101 (2017)] that provides an accurate estimate of the stationary
distribution at a fixed set of parameters. We show that sensitivity values at
these parameters can be estimated from the solution of a Poisson equation
associated with the infinitesimal generator of the Markov chain. We develop an
approach to numerically solve the Poisson equation and this yields an efficient
estimator for steady-state parameter sensitivities. We illustrate this method
using several examples.
| [
{
"created": "Tue, 11 Dec 2018 09:40:28 GMT",
"version": "v1"
}
] | 2019-05-01 | [
[
"Dürrenberger",
"Patrik",
""
],
[
"Gupta",
"Ankit",
""
],
[
"Khammash",
"Mustafa",
""
]
] | Consider the standard stochastic reaction network model where the dynamics is given by a continuous-time Markov chain over a discrete lattice. For such models, estimation of parameter sensitivities is an important problem, but the existing computational approaches to solve this problem usually require time-consuming Monte Carlo simulations of the reaction dynamics. Therefore these simulation-based approaches can only be expected to work over finite time-intervals, while it is often of interest in applications to examine the sensitivity values at the steady-state after the Markov chain has relaxed to its stationary distribution. The aim of this paper is to present a computational method for the estimation of steady-state parameter sensitivities, which instead of using simulations, relies on the recently developed stationary Finite State Projection (sFSP) algorithm [J. Chem. Phys. 147, 154101 (2017)] that provides an accurate estimate of the stationary distribution at a fixed set of parameters. We show that sensitivity values at these parameters can be estimated from the solution of a Poisson equation associated with the infinitesimal generator of the Markov chain. We develop an approach to numerically solve the Poisson equation and this yields an efficient estimator for steady-state parameter sensitivities. We illustrate this method using several examples. |
1907.11055 | Daniele Peri | Daniele Peri, Manon Deville, Clair Poignard, Emanuela Signori, Roberto
Natalini | Numerical Optimization of Plasmid DNA Delivery Combined with
Hyaluronidase Injection for Electroporation Protocol | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The definition of an innovative therapeutic protocol requires the fine tuning
of all the involved operations in order to maximize the efficiency. In some
cases, the price of the experiments, or their duration, represents a great
obstacle and the full potential of the protocol risks to be reduced or even
hidden by a non-optimal application.
The implementation of a numerical model of the protocol may represent the
solution, allowing a systematic exploration of all the different alternatives,
shedding the light on the most promising combination and also identifying the
key elements/parameters.
In this paper, the injection of a plasmid, preceded by a hyaluronidase
injection, is simulated through a mathematical model. Some key elements of the
administration protocol are identified by means of a mathematical optimization
procedure, maximizing the efficacy of the therapy. As a side effect of the
extensive investigation, robust solutions able to reduce the effects of human
errors in the administration are also obtained.
| [
{
"created": "Mon, 8 Jul 2019 07:16:38 GMT",
"version": "v1"
}
] | 2019-07-26 | [
[
"Peri",
"Daniele",
""
],
[
"Deville",
"Manon",
""
],
[
"Poignard",
"Clair",
""
],
[
"Signori",
"Emanuela",
""
],
[
"Natalini",
"Roberto",
""
]
] | The definition of an innovative therapeutic protocol requires the fine tuning of all the involved operations in order to maximize the efficiency. In some cases, the price of the experiments, or their duration, represents a great obstacle and the full potential of the protocol risks to be reduced or even hidden by a non-optimal application. The implementation of a numerical model of the protocol may represent the solution, allowing a systematic exploration of all the different alternatives, shedding the light on the most promising combination and also identifying the key elements/parameters. In this paper, the injection of a plasmid, preceded by a hyaluronidase injection, is simulated through a mathematical model. Some key elements of the administration protocol are identified by means of a mathematical optimization procedure, maximizing the efficacy of the therapy. As a side effect of the extensive investigation, robust solutions able to reduce the effects of human errors in the administration are also obtained. |
1405.3270 | Ralf Engbert | Ralf Engbert, Hans A. Trukenbrod, Simon Barthelm\'e, Felix A. Wichmann | Spatial statistics and attentional dynamics in scene viewing | 29 pages, 9 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In humans and in foveated animals visual acuity is highly concentrated at the
center of gaze, so that choosing where to look next is an important example of
online, rapid decision making. Computational neuroscientists have developed
biologically-inspired models of visual attention, termed saliency maps, which
successfully predict where people fixate on average. Using point process theory
for spatial statistics, we show that scanpaths contain, however, important
statistical structure, such as spatial clustering on top of distributions of
gaze positions. Here we develop a dynamical model of saccadic selection that
accurately predicts the distribution of gaze positions as well as spatial
clustering along individual scanpaths. Our model relies on, first, activation
dynamics via spatially- limited (foveated) access to saliency information, and,
second, a leaky memory process controlling the re-inspection of target regions.
This theoretical framework models a form of context-dependent decision-making,
linking neural dynamics of attention to behavioral gaze data.
| [
{
"created": "Tue, 13 May 2014 19:36:26 GMT",
"version": "v1"
},
{
"created": "Thu, 4 Dec 2014 20:32:33 GMT",
"version": "v2"
}
] | 2014-12-05 | [
[
"Engbert",
"Ralf",
""
],
[
"Trukenbrod",
"Hans A.",
""
],
[
"Barthelmé",
"Simon",
""
],
[
"Wichmann",
"Felix A.",
""
]
] | In humans and in foveated animals visual acuity is highly concentrated at the center of gaze, so that choosing where to look next is an important example of online, rapid decision making. Computational neuroscientists have developed biologically-inspired models of visual attention, termed saliency maps, which successfully predict where people fixate on average. Using point process theory for spatial statistics, we show that scanpaths contain, however, important statistical structure, such as spatial clustering on top of distributions of gaze positions. Here we develop a dynamical model of saccadic selection that accurately predicts the distribution of gaze positions as well as spatial clustering along individual scanpaths. Our model relies on, first, activation dynamics via spatially- limited (foveated) access to saliency information, and, second, a leaky memory process controlling the re-inspection of target regions. This theoretical framework models a form of context-dependent decision-making, linking neural dynamics of attention to behavioral gaze data. |
1512.08101 | Remi Monasson | John Barton (DCE-MIT,MIT), Arup Chakraborty (MIT,MIT,DCE-MIT), Simona
Cocco (LPS), Hugo Jacquin (LPS), R\'emi Monasson (LPTENS) | On the entropy of protein families | to appear in Journal of Statistical Physics | null | 10.1007/s10955-015-1441-4 | null | q-bio.BM cond-mat.stat-mech | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Proteins are essential components of living systems, capable of performing a
huge variety of tasks at the molecular level, such as recognition, signalling,
copy, transport, ... The protein sequences realizing a given function may
largely vary across organisms, giving rise to a protein family. Here, we
estimate the entropy of those families based on different approaches, including
Hidden Markov Models used for protein databases and inferred statistical models
reproducing the low-order (1-and 2-point) statistics of multi-sequence
alignments. We also compute the entropic cost, that is, the loss in entropy
resulting from a constraint acting on the protein, such as the fixation of one
particular amino-acid on a specific site, and relate this notion to the escape
probability of the HIV virus. The case of lattice proteins, for which the
entropy can be computed exactly, allows us to provide another illustration of
the concept of cost, due to the competition of different folds. The relevance
of the entropy in relation to directed evolution experiments is stressed.
| [
{
"created": "Sat, 26 Dec 2015 11:43:27 GMT",
"version": "v1"
}
] | 2016-02-17 | [
[
"Barton",
"John",
"",
"DCE-MIT,MIT"
],
[
"Chakraborty",
"Arup",
"",
"MIT,MIT,DCE-MIT"
],
[
"Cocco",
"Simona",
"",
"LPS"
],
[
"Jacquin",
"Hugo",
"",
"LPS"
],
[
"Monasson",
"Rémi",
"",
"LPTENS"
]
] | Proteins are essential components of living systems, capable of performing a huge variety of tasks at the molecular level, such as recognition, signalling, copy, transport, ... The protein sequences realizing a given function may largely vary across organisms, giving rise to a protein family. Here, we estimate the entropy of those families based on different approaches, including Hidden Markov Models used for protein databases and inferred statistical models reproducing the low-order (1-and 2-point) statistics of multi-sequence alignments. We also compute the entropic cost, that is, the loss in entropy resulting from a constraint acting on the protein, such as the fixation of one particular amino-acid on a specific site, and relate this notion to the escape probability of the HIV virus. The case of lattice proteins, for which the entropy can be computed exactly, allows us to provide another illustration of the concept of cost, due to the competition of different folds. The relevance of the entropy in relation to directed evolution experiments is stressed. |
2302.08796 | Shuai Han | Shuai Han, Lukas Stelz, Horst Stoecker, Lingxiao Wang, Kai Zhou | Approaching epidemiological dynamics of COVID-19 with physics-informed
neural networks | 23 pages, 14 figures | null | null | null | q-bio.QM cs.LG math.DS physics.soc-ph q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A physics-informed neural network (PINN) embedded with the
susceptible-infected-removed (SIR) model is devised to understand the temporal
evolution dynamics of infectious diseases. Firstly, the effectiveness of this
approach is demonstrated on synthetic data as generated from the numerical
solution of the susceptible-asymptomatic-infected-recovered-dead (SAIRD) model.
Then, the method is applied to COVID-19 data reported for Germany and shows
that it can accurately identify and predict virus spread trends. The results
indicate that an incomplete physics-informed model can approach more
complicated dynamics efficiently. Thus, the present work demonstrates the high
potential of using machine learning methods, e.g., PINNs, to study and predict
epidemic dynamics in combination with compartmental models.
| [
{
"created": "Fri, 17 Feb 2023 10:36:58 GMT",
"version": "v1"
},
{
"created": "Mon, 20 Feb 2023 18:15:29 GMT",
"version": "v2"
}
] | 2023-02-21 | [
[
"Han",
"Shuai",
""
],
[
"Stelz",
"Lukas",
""
],
[
"Stoecker",
"Horst",
""
],
[
"Wang",
"Lingxiao",
""
],
[
"Zhou",
"Kai",
""
]
] | A physics-informed neural network (PINN) embedded with the susceptible-infected-removed (SIR) model is devised to understand the temporal evolution dynamics of infectious diseases. Firstly, the effectiveness of this approach is demonstrated on synthetic data as generated from the numerical solution of the susceptible-asymptomatic-infected-recovered-dead (SAIRD) model. Then, the method is applied to COVID-19 data reported for Germany and shows that it can accurately identify and predict virus spread trends. The results indicate that an incomplete physics-informed model can approach more complicated dynamics efficiently. Thus, the present work demonstrates the high potential of using machine learning methods, e.g., PINNs, to study and predict epidemic dynamics in combination with compartmental models. |
1708.09072 | Toby Lightheart | Toby Lightheart, Steven Grainger, Tien-Fu Lu | Continual One-Shot Learning of Hidden Spike-Patterns with Neural Network
Simulation Expansion and STDP Convergence Predictions | 41 pages, 16 figures | null | null | null | q-bio.NC cs.CV stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper presents a constructive algorithm that achieves successful
one-shot learning of hidden spike-patterns in a competitive detection task. It
has previously been shown (Masquelier et al., 2008) that spike-timing-dependent
plasticity (STDP) and lateral inhibition can result in neurons competitively
tuned to repeating spike-patterns concealed in high rates of overall
presynaptic activity. One-shot construction of neurons with synapse weights
calculated as estimates of converged STDP outcomes results in immediate
selective detection of hidden spike-patterns. The capability of continual
learning is demonstrated through the successful one-shot detection of new sets
of spike-patterns introduced after long intervals in the simulation time.
Simulation expansion (Lightheart et al., 2013) has been proposed as an approach
to the development of constructive algorithms that are compatible with
simulations of biological neural networks. A simulation of a biological neural
network may have orders of magnitude fewer neurons and connections than the
related biological neural systems; therefore, simulated neural networks can be
assumed to be a subset of a larger neural system. The constructive algorithm is
developed using simulation expansion concepts to perform an operation
equivalent to the exchange of neurons between the simulation and the larger
hypothetical neural system. The dynamic selection of neurons to simulate within
a larger neural system (hypothetical or stored in memory) may be a starting
point for a wide range of developments and applications in machine learning and
the simulation of biology.
| [
{
"created": "Wed, 30 Aug 2017 01:07:18 GMT",
"version": "v1"
}
] | 2017-08-31 | [
[
"Lightheart",
"Toby",
""
],
[
"Grainger",
"Steven",
""
],
[
"Lu",
"Tien-Fu",
""
]
] | This paper presents a constructive algorithm that achieves successful one-shot learning of hidden spike-patterns in a competitive detection task. It has previously been shown (Masquelier et al., 2008) that spike-timing-dependent plasticity (STDP) and lateral inhibition can result in neurons competitively tuned to repeating spike-patterns concealed in high rates of overall presynaptic activity. One-shot construction of neurons with synapse weights calculated as estimates of converged STDP outcomes results in immediate selective detection of hidden spike-patterns. The capability of continual learning is demonstrated through the successful one-shot detection of new sets of spike-patterns introduced after long intervals in the simulation time. Simulation expansion (Lightheart et al., 2013) has been proposed as an approach to the development of constructive algorithms that are compatible with simulations of biological neural networks. A simulation of a biological neural network may have orders of magnitude fewer neurons and connections than the related biological neural systems; therefore, simulated neural networks can be assumed to be a subset of a larger neural system. The constructive algorithm is developed using simulation expansion concepts to perform an operation equivalent to the exchange of neurons between the simulation and the larger hypothetical neural system. The dynamic selection of neurons to simulate within a larger neural system (hypothetical or stored in memory) may be a starting point for a wide range of developments and applications in machine learning and the simulation of biology. |
1411.5360 | Changbong Hyeon | Yoonji Lee and Sun Choi and Changbong Hyeon | Communication over the network of binary switches regulates the
activation of A$_{2A}$ adenosine receptor | 28 pages, 17 figures | PLoS Comp. Biol. (2015) 11(2): e1004044 | 10.1371/journal.pcbi.1004044 | null | q-bio.BM q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dynamics and functions of G-protein coupled receptors (GPCRs) are accurately
regulated by the type of ligands that bind to the orthosteric or allosteric
binding sites. To glean the structural and dynamical origin of ligand-dependent
modulation of GPCR activity, we performed total $\sim$ 5 $\mu$sec molecular
dynamics simulations of A$_{2A}$ adenosine receptor (A$_{2A}$AR) in its apo,
antagonist-bound, and agonist-bound forms in an explicit water and membrane
environment, and examined the corresponding dynamics and correlation between
the 10 key structural motifs that serve as the allosteric hotspots in
intramolecular signaling network. We dubbed these 10 structural motifs "binary
switches" as they display molecular interactions that switch between two
distinct states. By projecting the receptor dynamics on these binary switches
that yield $2^{10}$ microstates, we show that (i) the receptors in apo,
antagonist-bound, and agonist-bound states explore vastly different
conformational space; (ii) among the three receptor states the apo state
explores the broadest range of microstates; (iii) in the presence of the
agonist, the active conformation is maintained through coherent couplings among
the binary switches; and (iv) to be most specific, our analysis shows that
W246, located deep inside the binding cleft, can serve as both an agonist
sensor and actuator of ensuing intramolecular signaling for the receptor
activation.Finally, our analysis of multiple trajectories generated by
inserting an agonist to the apo state underscores that the transition of the
receptor from inactive to active form requires the disruption of ionic-lock in
the DRY motif.
| [
{
"created": "Wed, 19 Nov 2014 19:05:32 GMT",
"version": "v1"
}
] | 2016-12-28 | [
[
"Lee",
"Yoonji",
""
],
[
"Choi",
"Sun",
""
],
[
"Hyeon",
"Changbong",
""
]
] | Dynamics and functions of G-protein coupled receptors (GPCRs) are accurately regulated by the type of ligands that bind to the orthosteric or allosteric binding sites. To glean the structural and dynamical origin of ligand-dependent modulation of GPCR activity, we performed total $\sim$ 5 $\mu$sec molecular dynamics simulations of A$_{2A}$ adenosine receptor (A$_{2A}$AR) in its apo, antagonist-bound, and agonist-bound forms in an explicit water and membrane environment, and examined the corresponding dynamics and correlation between the 10 key structural motifs that serve as the allosteric hotspots in intramolecular signaling network. We dubbed these 10 structural motifs "binary switches" as they display molecular interactions that switch between two distinct states. By projecting the receptor dynamics on these binary switches that yield $2^{10}$ microstates, we show that (i) the receptors in apo, antagonist-bound, and agonist-bound states explore vastly different conformational space; (ii) among the three receptor states the apo state explores the broadest range of microstates; (iii) in the presence of the agonist, the active conformation is maintained through coherent couplings among the binary switches; and (iv) to be most specific, our analysis shows that W246, located deep inside the binding cleft, can serve as both an agonist sensor and actuator of ensuing intramolecular signaling for the receptor activation.Finally, our analysis of multiple trajectories generated by inserting an agonist to the apo state underscores that the transition of the receptor from inactive to active form requires the disruption of ionic-lock in the DRY motif. |
2204.04786 | Samuel Goldstein | Samuel Goldstein, Farshad Rafiei, Dobromir Rahnev | 3D-printed stand, timing interface, and coil localization tools for
concurrent TMS-fMRI experiments | 32 pages, 10 figures | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Concurrent TMS-fMRI involves administrating TMS while subjects are inside an
MRI scanner and allows the study of the effects of neurostimulation on
simultaneous brain activity. Despite its high promise, the technique has proven
challenging to implement for at least three reasons. First, it is difficult to
position and stabilize the TMS coil inside the MRI scanner in a way that
precisely targets a pre-specified brain region. Second, standard
task-presentation software suffers from imprecise timing, which can lead to TMS
causing large image artifacts. Third, it is difficult to verify the exact TMS
coil position during scanning. In this paper, we describe solutions to all
three of these challenges. First, we develop a 3D-printed TMS stand that is
fully adjustable and can reach most areas of the scalp. The stand is compatible
with various MR coils and features an adjustable mirror holder. Second, we
create an interface that can precisely time the TMS pulses with respect to the
fMRI image acquisition with a variance of under 1 ms. Third, we develop
software for precisely determining the TMS coil position inside the MRI scanner
and computing the location of maximal stimulation. All three tools are either
free or inexpensive. We provide detailed instructions for building and
implementing these tools to facilitate an efficient and reliable concurrent
TMS-fMRI setup.
| [
{
"created": "Sun, 10 Apr 2022 22:46:24 GMT",
"version": "v1"
}
] | 2022-04-12 | [
[
"Goldstein",
"Samuel",
""
],
[
"Rafiei",
"Farshad",
""
],
[
"Rahnev",
"Dobromir",
""
]
] | Concurrent TMS-fMRI involves administrating TMS while subjects are inside an MRI scanner and allows the study of the effects of neurostimulation on simultaneous brain activity. Despite its high promise, the technique has proven challenging to implement for at least three reasons. First, it is difficult to position and stabilize the TMS coil inside the MRI scanner in a way that precisely targets a pre-specified brain region. Second, standard task-presentation software suffers from imprecise timing, which can lead to TMS causing large image artifacts. Third, it is difficult to verify the exact TMS coil position during scanning. In this paper, we describe solutions to all three of these challenges. First, we develop a 3D-printed TMS stand that is fully adjustable and can reach most areas of the scalp. The stand is compatible with various MR coils and features an adjustable mirror holder. Second, we create an interface that can precisely time the TMS pulses with respect to the fMRI image acquisition with a variance of under 1 ms. Third, we develop software for precisely determining the TMS coil position inside the MRI scanner and computing the location of maximal stimulation. All three tools are either free or inexpensive. We provide detailed instructions for building and implementing these tools to facilitate an efficient and reliable concurrent TMS-fMRI setup. |
2306.11818 | Yong Ye | Yong Ye, Jiaying Zhou | Pattern formation in a predator-prey model with Allee effect and
hyperbolic mortality on networked and non-networked environments | 24 pages, 9 figures, submitted to Nonlinear Analysis: Modelling and
Control | null | null | null | q-bio.PE math.DS | http://creativecommons.org/licenses/by/4.0/ | With the development of network science, Turing pattern has been proven to be
formed in discrete media such as complex networks, opening up the possibility
of exploring it as a generation mechanism in the context of biology, chemistry,
and physics. Turing instability in the predator-prey system has been widely
studied in recent years. We hope to use the predator-prey interaction
relationship in biological populations to explain the influence of network
topology on pattern formation. In this paper, we establish a predator-prey
model with weak Allee effect, analyze and verify the Turing instability
conditions on the large ER (Erd\"{o}s-R\'{e}nyi) random network with the help
of Turing stability theory and numerical experiments, and obtain the Turing
instability region. The results indicate that diffusion plays a decisive role
in the generation of spatial patterns, whether in continuous or discrete media.
For spatiotemporal patterns, different initial values can also bring about
changes in the pattern. When we analyze the model based on the network
framework, we find that the average degree of the network has an important
impact on the model, and different average degrees will lead to changes in the
distribution pattern of the population.
| [
{
"created": "Tue, 20 Jun 2023 18:23:06 GMT",
"version": "v1"
},
{
"created": "Wed, 4 Oct 2023 05:31:31 GMT",
"version": "v2"
}
] | 2023-10-05 | [
[
"Ye",
"Yong",
""
],
[
"Zhou",
"Jiaying",
""
]
] | With the development of network science, Turing pattern has been proven to be formed in discrete media such as complex networks, opening up the possibility of exploring it as a generation mechanism in the context of biology, chemistry, and physics. Turing instability in the predator-prey system has been widely studied in recent years. We hope to use the predator-prey interaction relationship in biological populations to explain the influence of network topology on pattern formation. In this paper, we establish a predator-prey model with weak Allee effect, analyze and verify the Turing instability conditions on the large ER (Erd\"{o}s-R\'{e}nyi) random network with the help of Turing stability theory and numerical experiments, and obtain the Turing instability region. The results indicate that diffusion plays a decisive role in the generation of spatial patterns, whether in continuous or discrete media. For spatiotemporal patterns, different initial values can also bring about changes in the pattern. When we analyze the model based on the network framework, we find that the average degree of the network has an important impact on the model, and different average degrees will lead to changes in the distribution pattern of the population. |
1306.4402 | David Pincus | David L. Pincus and D. Thirumalai | Force-Induced Unzipping Transitions in an Athermal Crowded Environment | 27 pages, 7 figures | null | null | null | q-bio.BM cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Using theoretical arguments and extensive Monte Carlo (MC) simulations of a
coarse-grained three-dimensional off-lattice model of a \beta-hairpin, we
demonstrate that the equilibrium critical force, $F_c$, needed to unfold the
biopolymer increases non-linearly with increasing volume fraction occupied by
the spherical macromolecular crowding agent. Both scaling arguments and MC
simulations show that the critical force increases as $F_c \approx
\varphi_c^{\alpha}$. The exponent $\alpha$ is linked to the Flory exponent
relating the size of the unfolded state of the biopolymer and the number of
amino acids. The predicted power law dependence is confirmed in simulations of
the dependence of the isothermal extensibility and the fraction of native
contacts on $\varphi_c$. We also show using MC simulations that $F_c$ is
linearly dependent on the average osmotic pressure ($\mathrm{P}$) exerted by
the crowding agents on the \beta-hairpin. The highly significant linear
correlation coefficient of 0.99657 between $F_c$ and $\mathrm{P}$ makes it
straightforward to predict the dependence of the critical force on the density
of crowders. Our predictions are amenable to experimental verification using
Laser Optical Tweezers.
| [
{
"created": "Wed, 19 Jun 2013 00:51:32 GMT",
"version": "v1"
}
] | 2013-06-20 | [
[
"Pincus",
"David L.",
""
],
[
"Thirumalai",
"D.",
""
]
] | Using theoretical arguments and extensive Monte Carlo (MC) simulations of a coarse-grained three-dimensional off-lattice model of a \beta-hairpin, we demonstrate that the equilibrium critical force, $F_c$, needed to unfold the biopolymer increases non-linearly with increasing volume fraction occupied by the spherical macromolecular crowding agent. Both scaling arguments and MC simulations show that the critical force increases as $F_c \approx \varphi_c^{\alpha}$. The exponent $\alpha$ is linked to the Flory exponent relating the size of the unfolded state of the biopolymer and the number of amino acids. The predicted power law dependence is confirmed in simulations of the dependence of the isothermal extensibility and the fraction of native contacts on $\varphi_c$. We also show using MC simulations that $F_c$ is linearly dependent on the average osmotic pressure ($\mathrm{P}$) exerted by the crowding agents on the \beta-hairpin. The highly significant linear correlation coefficient of 0.99657 between $F_c$ and $\mathrm{P}$ makes it straightforward to predict the dependence of the critical force on the density of crowders. Our predictions are amenable to experimental verification using Laser Optical Tweezers. |
0807.0483 | Steven N. Evans | Kenneth W. Wachter, Steven N. Evans, David R. Steinsaltz | The Age-Specific Force of Natural Selection and Walls of Death | 27 pages | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | W. D. Hamilton's celebrated formula for the age-specific force of natural
selection furnishes predictions for senescent mortality due to mutation
accumulation, at the price of reliance on a linear approximation. Applying to
Hamilton's setting the full non-linear demographic model for mutation
accumulation of Evans et al. (2007), we find surprising differences. Non-linear
interactions cause the collapse of Hamilton-style predictions in the most
commonly studied case, refine predictions in other cases, and allow Walls of
Death at ages before the end of reproduction. Haldane's Principle for genetic
load has an exact but unfamiliar generalization.
| [
{
"created": "Thu, 3 Jul 2008 04:56:54 GMT",
"version": "v1"
}
] | 2008-07-04 | [
[
"Wachter",
"Kenneth W.",
""
],
[
"Evans",
"Steven N.",
""
],
[
"Steinsaltz",
"David R.",
""
]
] | W. D. Hamilton's celebrated formula for the age-specific force of natural selection furnishes predictions for senescent mortality due to mutation accumulation, at the price of reliance on a linear approximation. Applying to Hamilton's setting the full non-linear demographic model for mutation accumulation of Evans et al. (2007), we find surprising differences. Non-linear interactions cause the collapse of Hamilton-style predictions in the most commonly studied case, refine predictions in other cases, and allow Walls of Death at ages before the end of reproduction. Haldane's Principle for genetic load has an exact but unfamiliar generalization. |
1504.05775 | Benjamin M. Friedrich | Gary S. Klindt, Benjamin M. Friedrich | Flagellar swimmers oscillate between pusher- and puller-type swimming | 12 pages, 4 color figures | null | 10.1103/PhysRevE.92.063019 | null | q-bio.CB cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Self-propulsion of cellular microswimmers generates flow signatures, commonly
classified as pusher- and puller-type, which characterize hydrodynamic
interactions with other cells or boundaries. Using experimentally measured beat
patterns, we compute that flagellated alga and sperm oscillate between pusher
and puller. Beyond a typical distance of 100 um from the swimmer, inertia
attenuates oscillatory micro-flows. We show that hydrodynamic interactions
between swimmers oscillate in time and are of similar magnitude as stochastic
swimming fluctuations.
| [
{
"created": "Wed, 22 Apr 2015 13:00:59 GMT",
"version": "v1"
}
] | 2016-01-20 | [
[
"Klindt",
"Gary S.",
""
],
[
"Friedrich",
"Benjamin M.",
""
]
] | Self-propulsion of cellular microswimmers generates flow signatures, commonly classified as pusher- and puller-type, which characterize hydrodynamic interactions with other cells or boundaries. Using experimentally measured beat patterns, we compute that flagellated alga and sperm oscillate between pusher and puller. Beyond a typical distance of 100 um from the swimmer, inertia attenuates oscillatory micro-flows. We show that hydrodynamic interactions between swimmers oscillate in time and are of similar magnitude as stochastic swimming fluctuations. |
1505.05730 | Heather Kulik | Heather J. Kulik, Jianyu Zhang, Judith P. Klinman, and Todd J.
Martinez | How large should the QM region be in QM/MM calculations? The case of
catechol O-methyltransferase | 27 pages, 10 figures | null | 10.1021/acs.jpcb.6b07814 | null | q-bio.BM cond-mat.soft physics.chem-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations are widely
used in studies of enzymatic catalysis. Until recently, it has been cost
prohibitive to determine the asymptotic limit of key energetic and structural
properties with respect to increasingly large QM regions. Leveraging recent
advances in electronic structure efficiency and accuracy, we investigate
catalytic properties in catechol O-methyltransferase, a representative example
of a methyltransferase critical to human health. Using QM regions ranging in
size from reactants-only (64 atoms) to nearly one-third of the entire protein
(940 atoms), we show that properties such as the activation energy approach
within chemical accuracy of the large-QM asymptotic limits rather slowly,
requiring approximately 500-600 atoms if the QM residues are chosen simply by
distance from the substrate. This slow approach to asymptotic limit is due to
charge transfer from protein residues to the reacting substrates. Our large
QM/MM calculations enable identification of charge separation for fragments in
the transition state as a key component of enzymatic methyl transfer rate
enhancement. We introduce charge shift analysis that reveals the minimum number
of protein residues (ca. 11-16 residues or 200-300 atoms for COMT) needed for
quantitative agreement with large-QM simulations. The identified residues are
not those that would be typically selected using criteria such as chemical
intuition or proximity. These results provide a recipe for a more careful
determination of QM region sizes in future QM/MM studies of enzymes.
| [
{
"created": "Thu, 21 May 2015 13:32:19 GMT",
"version": "v1"
},
{
"created": "Thu, 4 Aug 2016 02:46:12 GMT",
"version": "v2"
}
] | 2016-10-11 | [
[
"Kulik",
"Heather J.",
""
],
[
"Zhang",
"Jianyu",
""
],
[
"Klinman",
"Judith P.",
""
],
[
"Martinez",
"Todd J.",
""
]
] | Hybrid quantum mechanical-molecular mechanical (QM/MM) simulations are widely used in studies of enzymatic catalysis. Until recently, it has been cost prohibitive to determine the asymptotic limit of key energetic and structural properties with respect to increasingly large QM regions. Leveraging recent advances in electronic structure efficiency and accuracy, we investigate catalytic properties in catechol O-methyltransferase, a representative example of a methyltransferase critical to human health. Using QM regions ranging in size from reactants-only (64 atoms) to nearly one-third of the entire protein (940 atoms), we show that properties such as the activation energy approach within chemical accuracy of the large-QM asymptotic limits rather slowly, requiring approximately 500-600 atoms if the QM residues are chosen simply by distance from the substrate. This slow approach to asymptotic limit is due to charge transfer from protein residues to the reacting substrates. Our large QM/MM calculations enable identification of charge separation for fragments in the transition state as a key component of enzymatic methyl transfer rate enhancement. We introduce charge shift analysis that reveals the minimum number of protein residues (ca. 11-16 residues or 200-300 atoms for COMT) needed for quantitative agreement with large-QM simulations. The identified residues are not those that would be typically selected using criteria such as chemical intuition or proximity. These results provide a recipe for a more careful determination of QM region sizes in future QM/MM studies of enzymes. |
0911.4082 | Hernan Rozenfeld | Hern\'an D. Rozenfeld, Lazaros K. Gallos, and Hern\'an A. Makse | Explosive Percolation in the Human Protein Homology Network | 13 pages, 6 figures | null | 10.1140/epjb/e2010-00156-8 | null | q-bio.MN cond-mat.dis-nn cond-mat.stat-mech q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the explosive character of the percolation transition in a
real-world network. We show that the emergence of a spanning cluster in the
Human Protein Homology Network (H-PHN) exhibits similar features to an
Achlioptas-type process and is markedly different from regular random
percolation. The underlying mechanism of this transition can be described by
slow-growing clusters that remain isolated until the later stages of the
process, when the addition of a small number of links leads to the rapid
interconnection of these modules into a giant cluster. Our results indicate
that the evolutionary-based process that shapes the topology of the H-PHN
through duplication-divergence events may occur in sudden steps, similarly to
what is seen in first-order phase transitions.
| [
{
"created": "Fri, 20 Nov 2009 16:48:29 GMT",
"version": "v1"
}
] | 2015-05-14 | [
[
"Rozenfeld",
"Hernán D.",
""
],
[
"Gallos",
"Lazaros K.",
""
],
[
"Makse",
"Hernán A.",
""
]
] | We study the explosive character of the percolation transition in a real-world network. We show that the emergence of a spanning cluster in the Human Protein Homology Network (H-PHN) exhibits similar features to an Achlioptas-type process and is markedly different from regular random percolation. The underlying mechanism of this transition can be described by slow-growing clusters that remain isolated until the later stages of the process, when the addition of a small number of links leads to the rapid interconnection of these modules into a giant cluster. Our results indicate that the evolutionary-based process that shapes the topology of the H-PHN through duplication-divergence events may occur in sudden steps, similarly to what is seen in first-order phase transitions. |
1312.7749 | Peter Waddell | Peter J. Waddell | Happy New Year Homo erectus? More evidence for interbreeding with
archaics predating the modern human/Neanderthal split | 29 pages, 10 figures, 6 tables | null | null | null | q-bio.PE q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A range of a priori hypotheses about the evolution of modern and archaic
genomes are further evaluated and tested. In addition to the well-known
splits/introgressions involving Neanderthal genes into out-of- Africa people,
or Denisovan genes into Oceanians, a further series of archaic splits and
hypotheses proposed in Waddell et al. (2011) are considered in detail. These
include signals of Denisovans with something markedly more archaic and possibly
something more archaic into Papuans as well. These are compared and contrasted
with some well-advertised introgressions such as Denisovan genes across East
Asia, archaic genes into San or non-tree mixing between Oceanians, East Asians
and Europeans. The general result is that these less appreciated and surprising
archaic splits have just as much or more support in genome sequence data.
Further, evaluation confirms the hypothesis that archaic genes are much rarer
on modern X chromosomes, and may even be near totally absent, suggesting strong
selection against their introgression. Modeling of relative split weights
allows an inference of the proportion of the genome the Denisovan seems to have
gotten from an older archaic, and the best estimate is around 2%. Using a mix
of quantitative and qualitative morphological data and novel phylogenetic
methods, robust support is found for multiple distinct middle Pleistocene
lineages. Of these, fossil hominids such as SH5, Petralona, and Dali, in
particular, look like prime candidates for contributing pre-Neanderthal/Modern
archaic genes to Denisovans, while the Jinniu-Shan fossil looks like the best
candidate for a close relative of the Denisovan. That the Papuans might have
received some truly archaic genes appears a good possibility and they might
even be from Homo erectus.
| [
{
"created": "Mon, 30 Dec 2013 15:53:42 GMT",
"version": "v1"
}
] | 2013-12-31 | [
[
"Waddell",
"Peter J.",
""
]
] | A range of a priori hypotheses about the evolution of modern and archaic genomes are further evaluated and tested. In addition to the well-known splits/introgressions involving Neanderthal genes into out-of- Africa people, or Denisovan genes into Oceanians, a further series of archaic splits and hypotheses proposed in Waddell et al. (2011) are considered in detail. These include signals of Denisovans with something markedly more archaic and possibly something more archaic into Papuans as well. These are compared and contrasted with some well-advertised introgressions such as Denisovan genes across East Asia, archaic genes into San or non-tree mixing between Oceanians, East Asians and Europeans. The general result is that these less appreciated and surprising archaic splits have just as much or more support in genome sequence data. Further, evaluation confirms the hypothesis that archaic genes are much rarer on modern X chromosomes, and may even be near totally absent, suggesting strong selection against their introgression. Modeling of relative split weights allows an inference of the proportion of the genome the Denisovan seems to have gotten from an older archaic, and the best estimate is around 2%. Using a mix of quantitative and qualitative morphological data and novel phylogenetic methods, robust support is found for multiple distinct middle Pleistocene lineages. Of these, fossil hominids such as SH5, Petralona, and Dali, in particular, look like prime candidates for contributing pre-Neanderthal/Modern archaic genes to Denisovans, while the Jinniu-Shan fossil looks like the best candidate for a close relative of the Denisovan. That the Papuans might have received some truly archaic genes appears a good possibility and they might even be from Homo erectus. |
2107.04119 | Rao Jiahua | Jiahua Rao, Shuangjia Zheng, Yuedong Yang | Quantitative Evaluation of Explainable Graph Neural Networks for
Molecular Property Prediction | null | null | null | null | q-bio.QM cs.LG | http://creativecommons.org/licenses/by/4.0/ | Advances in machine learning have led to graph neural network-based methods
for drug discovery, yielding promising results in molecular design, chemical
synthesis planning, and molecular property prediction. However, current graph
neural networks (GNNs) remain of limited acceptance in drug discovery is
limited due to their lack of interpretability. Although this major weakness has
been mitigated by the development of explainable artificial intelligence (XAI)
techniques, the "ground truth" assignment in most explainable tasks ultimately
rests with subjective judgments by humans so that the quality of model
interpretation is hard to evaluate in quantity. In this work, we first build
three levels of benchmark datasets to quantitatively assess the
interpretability of the state-of-the-art GNN models. Then we implemented recent
XAI methods in combination with different GNN algorithms to highlight the
benefits, limitations, and future opportunities for drug discovery. As a
result, GradInput and IG generally provide the best model interpretability for
GNNs, especially when combined with GraphNet and CMPNN. The integrated and
developed XAI package is fully open-sourced and can be used by practitioners to
train new models on other drug discovery tasks.
| [
{
"created": "Thu, 1 Jul 2021 04:49:29 GMT",
"version": "v1"
},
{
"created": "Mon, 12 Jul 2021 04:12:24 GMT",
"version": "v2"
}
] | 2021-07-13 | [
[
"Rao",
"Jiahua",
""
],
[
"Zheng",
"Shuangjia",
""
],
[
"Yang",
"Yuedong",
""
]
] | Advances in machine learning have led to graph neural network-based methods for drug discovery, yielding promising results in molecular design, chemical synthesis planning, and molecular property prediction. However, current graph neural networks (GNNs) remain of limited acceptance in drug discovery is limited due to their lack of interpretability. Although this major weakness has been mitigated by the development of explainable artificial intelligence (XAI) techniques, the "ground truth" assignment in most explainable tasks ultimately rests with subjective judgments by humans so that the quality of model interpretation is hard to evaluate in quantity. In this work, we first build three levels of benchmark datasets to quantitatively assess the interpretability of the state-of-the-art GNN models. Then we implemented recent XAI methods in combination with different GNN algorithms to highlight the benefits, limitations, and future opportunities for drug discovery. As a result, GradInput and IG generally provide the best model interpretability for GNNs, especially when combined with GraphNet and CMPNN. The integrated and developed XAI package is fully open-sourced and can be used by practitioners to train new models on other drug discovery tasks. |
1210.4485 | Benjamin de Bivort | Jamey Kain, Chris Stokes, Quentin Gaudry, Xiangzhi Song, James Foley,
Rachel Wilson, Benjamin de Bivort | Leg-tracking and automated behavioral classification in Drosophila | 22 pages, incl 4 figures | null | 10.1038/ncomms2908 | null | q-bio.NC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Here we present the first method for tracking each leg of a fruit fly
behaving spontaneously upon a trackball, in real time. Legs were tracked with
infrared-fluorescent dye invisible to the fly, and compatible with two-photon
microscopy and controlled visual stimuli. We developed machine learning
classifiers to identify instances of numerous behavioral features (e.g.
walking, turning, grooming) thus producing the highest resolution ethological
profiles for individual flies.
| [
{
"created": "Tue, 16 Oct 2012 16:41:57 GMT",
"version": "v1"
}
] | 2015-06-11 | [
[
"Kain",
"Jamey",
""
],
[
"Stokes",
"Chris",
""
],
[
"Gaudry",
"Quentin",
""
],
[
"Song",
"Xiangzhi",
""
],
[
"Foley",
"James",
""
],
[
"Wilson",
"Rachel",
""
],
[
"de Bivort",
"Benjamin",
""
]
] | Here we present the first method for tracking each leg of a fruit fly behaving spontaneously upon a trackball, in real time. Legs were tracked with infrared-fluorescent dye invisible to the fly, and compatible with two-photon microscopy and controlled visual stimuli. We developed machine learning classifiers to identify instances of numerous behavioral features (e.g. walking, turning, grooming) thus producing the highest resolution ethological profiles for individual flies. |
q-bio/0506001 | Marta Sales-Pardo | M. Sales-Pardo, R. Guimera, A.A. Moreira, J. Widom, and L.A.N. Amaral | Mesoscopic modeling for nucleic acid chain dynamics | 27 pages, 13 figures | Phys. Rev. E, 71 art. num. 051902 (2005) | 10.1103/PhysRevE.71.051902 | null | q-bio.BM | null | To gain a deeper insight into cellular processes such as transcription and
translation, one needs to uncover the mechanisms controlling the
configurational changes of nucleic acids. As a step toward this aim, we present
here a novel mesoscopic-level computational model that provides a new window
into nucleic acid dynamics. We model a single-stranded nucleic as a polymer
chain whose monomers are the nucleosides. Each monomer comprises a bead
representing the sugar molecule and a pin representing the base. The bead-pin
complex can rotate about the backbone of the chain. We consider pairwise
stacking and hydrogen-bonding interactions. We use a modified Monte Carlo
dynamics that splits the dynamics into translational bead motion and rotational
pin motion. By performing a number of tests we first show that our model is
physically sound. We then focus on the study of a the kinetics of a DNA
hairpin--a single-stranded molecule comprising two complementary segments
joined by a non-complementary loop--studied experimentally. We find that
results from our simulations agree with experimental observations,
demonstrating that our model is a suitable tool for the investigation of the
hybridization of single strands.
| [
{
"created": "Wed, 1 Jun 2005 23:30:13 GMT",
"version": "v1"
}
] | 2009-11-11 | [
[
"Sales-Pardo",
"M.",
""
],
[
"Guimera",
"R.",
""
],
[
"Moreira",
"A. A.",
""
],
[
"Widom",
"J.",
""
],
[
"Amaral",
"L. A. N.",
""
]
] | To gain a deeper insight into cellular processes such as transcription and translation, one needs to uncover the mechanisms controlling the configurational changes of nucleic acids. As a step toward this aim, we present here a novel mesoscopic-level computational model that provides a new window into nucleic acid dynamics. We model a single-stranded nucleic as a polymer chain whose monomers are the nucleosides. Each monomer comprises a bead representing the sugar molecule and a pin representing the base. The bead-pin complex can rotate about the backbone of the chain. We consider pairwise stacking and hydrogen-bonding interactions. We use a modified Monte Carlo dynamics that splits the dynamics into translational bead motion and rotational pin motion. By performing a number of tests we first show that our model is physically sound. We then focus on the study of a the kinetics of a DNA hairpin--a single-stranded molecule comprising two complementary segments joined by a non-complementary loop--studied experimentally. We find that results from our simulations agree with experimental observations, demonstrating that our model is a suitable tool for the investigation of the hybridization of single strands. |
2303.02787 | Naoto Hori | Naoto Hori, D. Thirumalai | Watching ion-driven kinetics of ribozyme folding and misfolding caused
by energetic and topological frustration one molecule at a time | Main text + Supplementary Information | null | null | null | q-bio.BM cond-mat.soft | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Folding of ribozymes into well-defined tertiary structures usually requires
divalent cations. How Mg$^{2+}$ ions direct the folding kinetics has been a
long-standing unsolved problem because experiments cannot detect the positions
and dynamics of ions. To address this problem, we used molecular simulations to
dissect the folding kinetics of the Azoarcus ribozyme by monitoring the path
each molecule takes to reach the folded state. We quantitatively establish that
Mg$^{2+}$ binding to specific sites, coupled with counter-ion release of
monovalent cations, stimulate the formation of secondary and tertiary
structures, leading to diverse pathways that include direct rapid folding and
trapping in misfolded structures. In some molecules, key tertiary structural
elements form when Mg$^{2+}$ ions bind to specific RNA sites at the earliest
stages of the folding, leading to specific collapse and rapid folding. In
others, the formation of non-native base pairs, whose rearrangement is needed
to reach the folded state, is the rate-limiting step. Escape from energetic
traps, driven by thermal fluctuations, occurs readily. In contrast, the
transition to the native state from long-lived topologically trapped
native-like metastable states is extremely slow. Specific collapse and
formation of energetically or topologically frustrated states occur early in
the assembly process.
| [
{
"created": "Sun, 5 Mar 2023 22:28:41 GMT",
"version": "v1"
},
{
"created": "Mon, 21 Aug 2023 17:48:04 GMT",
"version": "v2"
}
] | 2023-08-22 | [
[
"Hori",
"Naoto",
""
],
[
"Thirumalai",
"D.",
""
]
] | Folding of ribozymes into well-defined tertiary structures usually requires divalent cations. How Mg$^{2+}$ ions direct the folding kinetics has been a long-standing unsolved problem because experiments cannot detect the positions and dynamics of ions. To address this problem, we used molecular simulations to dissect the folding kinetics of the Azoarcus ribozyme by monitoring the path each molecule takes to reach the folded state. We quantitatively establish that Mg$^{2+}$ binding to specific sites, coupled with counter-ion release of monovalent cations, stimulate the formation of secondary and tertiary structures, leading to diverse pathways that include direct rapid folding and trapping in misfolded structures. In some molecules, key tertiary structural elements form when Mg$^{2+}$ ions bind to specific RNA sites at the earliest stages of the folding, leading to specific collapse and rapid folding. In others, the formation of non-native base pairs, whose rearrangement is needed to reach the folded state, is the rate-limiting step. Escape from energetic traps, driven by thermal fluctuations, occurs readily. In contrast, the transition to the native state from long-lived topologically trapped native-like metastable states is extremely slow. Specific collapse and formation of energetically or topologically frustrated states occur early in the assembly process. |
2103.09974 | Lingsong Meng | Lingsong Meng, Dorina Avram, George Tseng, Zhiguang Huo | Outcome-guided Sparse K-means for Disease Subtype Discovery via
Integrating Phenotypic Data with High-dimensional Transcriptomic Data | null | (2021) Journal of the Royal Statistical Society Series C (Applied
Statistics), 1-24 | 10.1111/rssc.12536 | null | q-bio.QM q-bio.GN stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The discovery of disease subtypes is an essential step for developing
precision medicine, and disease subtyping via omics data has become a popular
approach. While promising, subtypes obtained from existing approaches are not
necessarily associated with clinical outcomes. With the rich clinical data
along with the omics data in modern epidemiology cohorts, it is urgent to
develop an outcome-guided clustering algorithm to fully integrate the
phenotypic data with the high-dimensional omics data. Hence, we extended a
sparse K-means method to an outcome-guided sparse K-means (GuidedSparseKmeans)
method. An unified objective function was proposed, which was comprised of (i)
weighted K-means to perform sample clusterings; (ii) lasso regularizations to
perform gene selection from the high-dimensional omics data; (iii)
incorporation of a phenotypic variable from the clinical dataset to facilitate
biologically meaningful clustering results. By iteratively optimizing the
objective function, we will simultaneously obtain a phenotype-related sample
clustering results and gene selection results. We demonstrated the superior
performance of the GuidedSparseKmeans by comparing with existing clustering
methods in simulations and applications of high-dimensional transcriptomic data
of breast cancer and Alzheimer's disease. Our algorithm has been implemented
into an R package, which is publicly available on GitHub
(https://github.com/LingsongMeng/GuidedSparseKmeans).
| [
{
"created": "Thu, 18 Mar 2021 01:35:57 GMT",
"version": "v1"
},
{
"created": "Mon, 28 Feb 2022 03:56:25 GMT",
"version": "v2"
}
] | 2022-03-01 | [
[
"Meng",
"Lingsong",
""
],
[
"Avram",
"Dorina",
""
],
[
"Tseng",
"George",
""
],
[
"Huo",
"Zhiguang",
""
]
] | The discovery of disease subtypes is an essential step for developing precision medicine, and disease subtyping via omics data has become a popular approach. While promising, subtypes obtained from existing approaches are not necessarily associated with clinical outcomes. With the rich clinical data along with the omics data in modern epidemiology cohorts, it is urgent to develop an outcome-guided clustering algorithm to fully integrate the phenotypic data with the high-dimensional omics data. Hence, we extended a sparse K-means method to an outcome-guided sparse K-means (GuidedSparseKmeans) method. An unified objective function was proposed, which was comprised of (i) weighted K-means to perform sample clusterings; (ii) lasso regularizations to perform gene selection from the high-dimensional omics data; (iii) incorporation of a phenotypic variable from the clinical dataset to facilitate biologically meaningful clustering results. By iteratively optimizing the objective function, we will simultaneously obtain a phenotype-related sample clustering results and gene selection results. We demonstrated the superior performance of the GuidedSparseKmeans by comparing with existing clustering methods in simulations and applications of high-dimensional transcriptomic data of breast cancer and Alzheimer's disease. Our algorithm has been implemented into an R package, which is publicly available on GitHub (https://github.com/LingsongMeng/GuidedSparseKmeans). |
1012.4726 | Rosemary Braun | Rosemary Braun and Kenneth Buetow | Pathways of Distinction Analysis: a new technique for multi-SNP analysis
of GWAS data | Revision | null | null | null | q-bio.QM q-bio.GN q-bio.MN stat.AP stat.CO | http://creativecommons.org/licenses/publicdomain/ | Genome-wide association studies have become increasingly common due to
advances in technology and have permitted the identification of differences in
single nucleotide polymorphism (SNP) alleles that are associated with diseases.
However, while typical GWAS analysis techniques treat markers individually,
complex diseases are unlikely to have a single causative gene. There is thus a
pressing need for multi-SNP analysis methods that can reveal system-level
differences in cases and controls. Here, we present a novel multi-SNP GWAS
analysis method called Pathways of Distinction Analysis (PoDA). The method uses
GWAS data and known pathway-gene and gene-SNP associations to identify pathways
that permit, ideally, the distinction of cases from controls. The technique is
based upon the hypothesis that if a pathway is related to disease risk, cases
will appear more similar to other cases than to controls for the SNPs
associated with that pathway. By systematically applying the method to all
pathways of potential interest, we can identify those for which the hypothesis
holds true, i.e., pathways containing SNPs for which the samples exhibit
greater within-class similarity than across classes. Importantly, PoDA improves
on existing single-SNP and SNP-set enrichment analyses in that it does not
require the SNPs in a pathway to exhibit independent main effects. This permits
PoDA to reveal pathways in which epistatic interactions drives risk. In this
paper, we detail the PoDA method and apply it to two GWA studies: one of breast
cancer, and the other of liver cancer. The results obtained strongly suggest
that there exist pathway-wide genomic differences that contribute to disease
susceptibility. PoDA thus provides an analytical tool that is complementary to
existing techniques and has the power to enrich our understanding of disease
genomics at the systems-level.
| [
{
"created": "Tue, 21 Dec 2010 16:50:59 GMT",
"version": "v1"
},
{
"created": "Thu, 17 Mar 2011 22:09:54 GMT",
"version": "v2"
}
] | 2015-09-24 | [
[
"Braun",
"Rosemary",
""
],
[
"Buetow",
"Kenneth",
""
]
] | Genome-wide association studies have become increasingly common due to advances in technology and have permitted the identification of differences in single nucleotide polymorphism (SNP) alleles that are associated with diseases. However, while typical GWAS analysis techniques treat markers individually, complex diseases are unlikely to have a single causative gene. There is thus a pressing need for multi-SNP analysis methods that can reveal system-level differences in cases and controls. Here, we present a novel multi-SNP GWAS analysis method called Pathways of Distinction Analysis (PoDA). The method uses GWAS data and known pathway-gene and gene-SNP associations to identify pathways that permit, ideally, the distinction of cases from controls. The technique is based upon the hypothesis that if a pathway is related to disease risk, cases will appear more similar to other cases than to controls for the SNPs associated with that pathway. By systematically applying the method to all pathways of potential interest, we can identify those for which the hypothesis holds true, i.e., pathways containing SNPs for which the samples exhibit greater within-class similarity than across classes. Importantly, PoDA improves on existing single-SNP and SNP-set enrichment analyses in that it does not require the SNPs in a pathway to exhibit independent main effects. This permits PoDA to reveal pathways in which epistatic interactions drives risk. In this paper, we detail the PoDA method and apply it to two GWA studies: one of breast cancer, and the other of liver cancer. The results obtained strongly suggest that there exist pathway-wide genomic differences that contribute to disease susceptibility. PoDA thus provides an analytical tool that is complementary to existing techniques and has the power to enrich our understanding of disease genomics at the systems-level. |
2010.01441 | Gopinath Chennupati | Nasrin Akhter and Gopinath Chennupati and Hristo Djidjev and Amarda
Shehu | Decoy Selection for Protein Structure Prediction Via Extreme Gradient
Boosting and Ranking | Accepted for BMC Bioinformatics | null | null | null | q-bio.BM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Identifying one or more biologically-active/native decoys from millions of
non-native decoys is one of the major challenges in computational structural
biology. The extreme lack of balance in positive and negative samples (native
and non-native decoys) in a decoy set makes the problem even more complicated.
Consensus methods show varied success in handling the challenge of decoy
selection despite some issues associated with clustering large decoy sets and
decoy sets that do not show much structural similarity. Recent investigations
into energy landscape-based decoy selection approaches show promises. However,
lack of generalization over varied test cases remains a bottleneck for these
methods. We propose a novel decoy selection method, ML-Select, a machine
learning framework that exploits the energy landscape associated with the
structure space probed through a template-free decoy generation. The proposed
method outperforms both clustering and energy ranking-based methods, all the
while consistently offering better performance on varied test-cases. Moreover,
ML-Select shows promising results even for the decoy sets consisting of mostly
low-quality decoys. ML-Select is a useful method for decoy selection. This work
suggests further research in finding more effective ways to adopt machine
learning frameworks in achieving robust performance for decoy selection in
template-free protein structure prediction.
| [
{
"created": "Sat, 3 Oct 2020 23:09:06 GMT",
"version": "v1"
}
] | 2020-10-06 | [
[
"Akhter",
"Nasrin",
""
],
[
"Chennupati",
"Gopinath",
""
],
[
"Djidjev",
"Hristo",
""
],
[
"Shehu",
"Amarda",
""
]
] | Identifying one or more biologically-active/native decoys from millions of non-native decoys is one of the major challenges in computational structural biology. The extreme lack of balance in positive and negative samples (native and non-native decoys) in a decoy set makes the problem even more complicated. Consensus methods show varied success in handling the challenge of decoy selection despite some issues associated with clustering large decoy sets and decoy sets that do not show much structural similarity. Recent investigations into energy landscape-based decoy selection approaches show promises. However, lack of generalization over varied test cases remains a bottleneck for these methods. We propose a novel decoy selection method, ML-Select, a machine learning framework that exploits the energy landscape associated with the structure space probed through a template-free decoy generation. The proposed method outperforms both clustering and energy ranking-based methods, all the while consistently offering better performance on varied test-cases. Moreover, ML-Select shows promising results even for the decoy sets consisting of mostly low-quality decoys. ML-Select is a useful method for decoy selection. This work suggests further research in finding more effective ways to adopt machine learning frameworks in achieving robust performance for decoy selection in template-free protein structure prediction. |
2009.03278 | Marcos Edel Martinez-Montero Dr. | M.T. Gonzalez-Arnao, M.M. Ravelo, C.U. Villavicencio, M.E.
Martinez-Montero, F. Engelmann | Cryopreservation of pineapple (Ananas comosus) apices | 8 pages, 6 tables | CRYO-LETTERS, Volume: 19, Issue: 6, Pages: 375-382, Published:
NOV-DEC 1998, Document Type:Article Published by Cryo-Letters, 7, Wootton
Way, Cambridge CB3 9LX, U.K | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The encapsulation-dehydration and vitrification techniques were experimented
for freezing apices of pineapple in vitro plantlets. Positive results were
achieved using vitrification only. Optimal conditions included a 2-d preculture
of apices on medium supplemented with 0.3M sucrose, loading treatment for 25
min in medium with 0.75M sucrose + 1M glycerol and dehydration with PVS2
vitrification solution at 0 degrees C for 7 h before rapid freezing in liquid
nitrogen. This method resulted in 65, 35 and 25% survival with apices of
varieties Puerto Rico, Perolera and Smooth Cayenne, respectively. Recovery of
cryopreserved apices took place directly, without transitory callus formation.
| [
{
"created": "Sat, 29 Aug 2020 05:51:56 GMT",
"version": "v1"
}
] | 2020-09-08 | [
[
"Gonzalez-Arnao",
"M. T.",
""
],
[
"Ravelo",
"M. M.",
""
],
[
"Villavicencio",
"C. U.",
""
],
[
"Martinez-Montero",
"M. E.",
""
],
[
"Engelmann",
"F.",
""
]
] | The encapsulation-dehydration and vitrification techniques were experimented for freezing apices of pineapple in vitro plantlets. Positive results were achieved using vitrification only. Optimal conditions included a 2-d preculture of apices on medium supplemented with 0.3M sucrose, loading treatment for 25 min in medium with 0.75M sucrose + 1M glycerol and dehydration with PVS2 vitrification solution at 0 degrees C for 7 h before rapid freezing in liquid nitrogen. This method resulted in 65, 35 and 25% survival with apices of varieties Puerto Rico, Perolera and Smooth Cayenne, respectively. Recovery of cryopreserved apices took place directly, without transitory callus formation. |
1406.2502 | David Schnoerr | David Schnoerr, Guido Sanguinetti, Ramon Grima | The complex chemical Langevin equation | 47 pages, 8 figures | J. Chem. Phys. 141, 024103 (2014) | 10.1063/1.4885345 | null | q-bio.QM cond-mat.stat-mech physics.chem-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The chemical Langevin equation (CLE) is a popular simulation method to probe
the stochastic dynamics of chemical systems. The CLE's main disadvantage is its
break down in finite time due to the problem of evaluating square roots of
negative quantities whenever the molecule numbers become sufficiently small. We
show that this issue is not a numerical integration problem, rather in many
systems it is intrinsic to all representations of the CLE. Various methods of
correcting the CLE have been proposed which avoid its break down. We show that
these methods introduce undesirable artefacts in the CLE's predictions. In
particular, for unimolecular systems, these correction methods lead to CLE
predictions for the mean concentrations and variance of fluctuations which
disagree with those of the chemical master equation. We show that, by extending
the domain of the CLE to complex space, break down is eliminated, and the CLE's
accuracy for unimolecular systems is restored. Although the molecule numbers
are generally complex, we show that the "complex CLE" predicts real-valued
quantities for the mean concentrations, the moments of intrinsic noise, power
spectra and first passage times, hence admitting a physical interpretation. It
is also shown to provide a more accurate approximation of the chemical master
equation of simple biochemical circuits involving bimolecular reactions than
the various corrected forms of the real-valued CLE, the linear-noise
approximation and a commonly used two moment-closure approximation.
| [
{
"created": "Tue, 10 Jun 2014 10:50:22 GMT",
"version": "v1"
},
{
"created": "Mon, 21 Jul 2014 14:13:42 GMT",
"version": "v2"
}
] | 2014-07-22 | [
[
"Schnoerr",
"David",
""
],
[
"Sanguinetti",
"Guido",
""
],
[
"Grima",
"Ramon",
""
]
] | The chemical Langevin equation (CLE) is a popular simulation method to probe the stochastic dynamics of chemical systems. The CLE's main disadvantage is its break down in finite time due to the problem of evaluating square roots of negative quantities whenever the molecule numbers become sufficiently small. We show that this issue is not a numerical integration problem, rather in many systems it is intrinsic to all representations of the CLE. Various methods of correcting the CLE have been proposed which avoid its break down. We show that these methods introduce undesirable artefacts in the CLE's predictions. In particular, for unimolecular systems, these correction methods lead to CLE predictions for the mean concentrations and variance of fluctuations which disagree with those of the chemical master equation. We show that, by extending the domain of the CLE to complex space, break down is eliminated, and the CLE's accuracy for unimolecular systems is restored. Although the molecule numbers are generally complex, we show that the "complex CLE" predicts real-valued quantities for the mean concentrations, the moments of intrinsic noise, power spectra and first passage times, hence admitting a physical interpretation. It is also shown to provide a more accurate approximation of the chemical master equation of simple biochemical circuits involving bimolecular reactions than the various corrected forms of the real-valued CLE, the linear-noise approximation and a commonly used two moment-closure approximation. |
2209.08974 | Maria Bruna | Robert A. McDonald, Rosanna Neuhausler, Martin Robinson, Laurel G.
Larsen, Heather A. Harrington, Maria Bruna | Zigzag persistence for coral reef resilience using a stochastic spatial
model | null | null | null | null | q-bio.QM math.AT q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | A complex interplay between species governs the evolution of spatial patterns
in ecology. An open problem in the biological sciences is characterising
spatio-temporal data and understanding how changes at the local scale affect
global dynamics/behaviour. Here, we extend a well-studied temporal mathematical
model of coral reef dynamics to include stochastic and spatial interactions and
generate data to study different ecological scenarios. We present descriptors
to characterise patterns in heterogeneous spatio-temporal data surpassing
spatially averaged measures. We apply these descriptors to simulated coral data
and demonstrate the utility of two topological data analysis
techniques--persistent homology and zigzag persistence--for characterising
mechanisms of reef resilience. We show that the introduction of local
competition between species leads to the appearance of coral clusters in the
reef. We use our analyses to distinguish temporal dynamics stemming from
different initial configurations of coral, showing that the neighbourhood
composition of coral sites determines their long-term survival. Using zigzag
persistence, we determine which spatial configurations protect coral from
extinction in different environments. Finally, we apply this toolkit of
multi-scale methods to empirical coral reef data, which distinguish
spatio-temporal reef dynamics in different locations, and demonstrate the
applicability to a range of datasets.
| [
{
"created": "Mon, 19 Sep 2022 12:46:57 GMT",
"version": "v1"
},
{
"created": "Sat, 12 Aug 2023 12:34:44 GMT",
"version": "v2"
}
] | 2023-08-15 | [
[
"McDonald",
"Robert A.",
""
],
[
"Neuhausler",
"Rosanna",
""
],
[
"Robinson",
"Martin",
""
],
[
"Larsen",
"Laurel G.",
""
],
[
"Harrington",
"Heather A.",
""
],
[
"Bruna",
"Maria",
""
]
] | A complex interplay between species governs the evolution of spatial patterns in ecology. An open problem in the biological sciences is characterising spatio-temporal data and understanding how changes at the local scale affect global dynamics/behaviour. Here, we extend a well-studied temporal mathematical model of coral reef dynamics to include stochastic and spatial interactions and generate data to study different ecological scenarios. We present descriptors to characterise patterns in heterogeneous spatio-temporal data surpassing spatially averaged measures. We apply these descriptors to simulated coral data and demonstrate the utility of two topological data analysis techniques--persistent homology and zigzag persistence--for characterising mechanisms of reef resilience. We show that the introduction of local competition between species leads to the appearance of coral clusters in the reef. We use our analyses to distinguish temporal dynamics stemming from different initial configurations of coral, showing that the neighbourhood composition of coral sites determines their long-term survival. Using zigzag persistence, we determine which spatial configurations protect coral from extinction in different environments. Finally, we apply this toolkit of multi-scale methods to empirical coral reef data, which distinguish spatio-temporal reef dynamics in different locations, and demonstrate the applicability to a range of datasets. |
2307.14077 | Laurent Perrinet | Antoine Grimaldi and Laurent U Perrinet | Learning heterogeneous delays in a layer of spiking neurons for fast
motion detection | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by-sa/4.0/ | The precise timing of spikes emitted by neurons plays a crucial role in
shaping the response of efferent biological neurons. This temporal dimension of
neural activity holds significant importance in understanding information
processing in neurobiology, especially for the performance of neuromorphic
hardware, such as event-based cameras. Nonetheless, many artificial neural
models disregard this critical temporal dimension of neural activity. In this
study, we present a model designed to efficiently detect temporal spiking
motifs using a layer of spiking neurons equipped with heterogeneous synaptic
delays. Our model capitalizes on the diverse synaptic delays present on the
dendritic tree, enabling specific arrangements of temporally precise synaptic
inputs to synchronize upon reaching the basal dendritic tree. We formalize this
process as a time-invariant logistic regression, which can be trained using
labeled data. To demonstrate its practical efficacy, we apply the model to
naturalistic videos transformed into event streams, simulating the output of
the biological retina or event-based cameras. To evaluate the robustness of the
model in detecting visual motion, we conduct experiments by selectively pruning
weights and demonstrate that the model remains efficient even under
significantly reduced workloads. In conclusion, by providing a comprehensive,
event-driven computational building block, the incorporation of heterogeneous
delays has the potential to greatly improve the performance of future spiking
neural network algorithms, particularly in the context of neuromorphic chips.
| [
{
"created": "Wed, 26 Jul 2023 10:01:04 GMT",
"version": "v1"
}
] | 2023-07-27 | [
[
"Grimaldi",
"Antoine",
""
],
[
"Perrinet",
"Laurent U",
""
]
] | The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiology, especially for the performance of neuromorphic hardware, such as event-based cameras. Nonetheless, many artificial neural models disregard this critical temporal dimension of neural activity. In this study, we present a model designed to efficiently detect temporal spiking motifs using a layer of spiking neurons equipped with heterogeneous synaptic delays. Our model capitalizes on the diverse synaptic delays present on the dendritic tree, enabling specific arrangements of temporally precise synaptic inputs to synchronize upon reaching the basal dendritic tree. We formalize this process as a time-invariant logistic regression, which can be trained using labeled data. To demonstrate its practical efficacy, we apply the model to naturalistic videos transformed into event streams, simulating the output of the biological retina or event-based cameras. To evaluate the robustness of the model in detecting visual motion, we conduct experiments by selectively pruning weights and demonstrate that the model remains efficient even under significantly reduced workloads. In conclusion, by providing a comprehensive, event-driven computational building block, the incorporation of heterogeneous delays has the potential to greatly improve the performance of future spiking neural network algorithms, particularly in the context of neuromorphic chips. |
q-bio/0509025 | Sudip Kundu | Md. Aftabuddin and Sudip Kundu | Weighted and unweighted network of amino acids within protein | null | null | 10.1016/j.physa.2006.03.056 | null | q-bio.MN q-bio.BM | null | The information regarding the structure of a single protein is encoded in the
network of interacting amino acids. Considering each protein as a weighted and
unweighted network of amino acids we have analyzed a total of forty nine
protein structures that covers the three branches of life on earth. Our results
show that the probability degree distribution of network connectivity follows
Poisson's distribution; whereas the probability strength distribution does not
follow any known distribution. However, the average strength of amino acid node
depends on its degree (k). For some of the proteins, the strength of a node
increases linearly with k. On the other hand, for a set of other proteins,
although the strength increases linaerly with k for smaller values of k, we
have not obtained any clear functional relationship of strength with degree at
higher values of k. The results also show that the weight of the amino acid
nodes belonging to the highly connected nodes tend to have a higher value. The
result that the average clustering coefficient of weighted network is less than
that of unweighted network implies that the topological clustering is generated
by edges with low weights. The ratio of average clustering coefficients of
protein network to that of the corresponding classical random network varies
linearly with the number (N) of amino acids of a protein; whereas the ratio of
characteristic path lengths varies logarithmically with N. The power law
behaviour of clustering coefficients of weighted and unweighted network as a
function of degree k indicates that the network has a signature of hierarchical
network. It has also been observed that the network is of assortative type.
| [
{
"created": "Wed, 21 Sep 2005 11:24:03 GMT",
"version": "v1"
}
] | 2015-06-26 | [
[
"Aftabuddin",
"Md.",
""
],
[
"Kundu",
"Sudip",
""
]
] | The information regarding the structure of a single protein is encoded in the network of interacting amino acids. Considering each protein as a weighted and unweighted network of amino acids we have analyzed a total of forty nine protein structures that covers the three branches of life on earth. Our results show that the probability degree distribution of network connectivity follows Poisson's distribution; whereas the probability strength distribution does not follow any known distribution. However, the average strength of amino acid node depends on its degree (k). For some of the proteins, the strength of a node increases linearly with k. On the other hand, for a set of other proteins, although the strength increases linaerly with k for smaller values of k, we have not obtained any clear functional relationship of strength with degree at higher values of k. The results also show that the weight of the amino acid nodes belonging to the highly connected nodes tend to have a higher value. The result that the average clustering coefficient of weighted network is less than that of unweighted network implies that the topological clustering is generated by edges with low weights. The ratio of average clustering coefficients of protein network to that of the corresponding classical random network varies linearly with the number (N) of amino acids of a protein; whereas the ratio of characteristic path lengths varies logarithmically with N. The power law behaviour of clustering coefficients of weighted and unweighted network as a function of degree k indicates that the network has a signature of hierarchical network. It has also been observed that the network is of assortative type. |
1409.2544 | Nora Youngs | Nora Youngs | The neural ring: using algebraic geometry to analyze neural codes | Doctoral dissertation, Univ Nebraska 2014. arXiv admin note: text
overlap with arXiv:1212.5188 by other authors | null | null | null | q-bio.NC math.AC math.AG math.CO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Neurons in the brain represent external stimuli via neural codes. These codes
often arise from stimulus-response maps, associating to each neuron a convex
receptive field. An important problem confronted by the brain is to infer
properties of a represented stimulus space without knowledge of the receptive
fields, using only the intrinsic structure of the neural code. How does the
brain do this? To address this question, it is important to determine what
stimulus space features can - in principle - be extracted from neural codes.
This motivates us to define the neural ring and a related neural ideal,
algebraic objects that encode the full combinatorial data of a neural code. We
find that these objects can be expressed in a "canonical form" that directly
translates to a minimal description of the receptive field structure intrinsic
to the neural code. We consider the algebraic properties of homomorphisms
between neural rings, which naturally relate to maps between neural codes. We
show that maps between two neural codes are in bijection with ring
homomorphisms between the respective neural rings, and define the notion of
neural ring homomorphism, a special restricted class of ring homomorphisms
which preserve neuron structure. We also find connections to Stanley-Reisner
rings, and use ideas similar to those in the theory of monomial ideals to
obtain an algorithm for computing the canonical form associated to any neural
code, providing the groundwork for inferring stimulus space features from
neural activity alone.
| [
{
"created": "Mon, 8 Sep 2014 22:53:53 GMT",
"version": "v1"
}
] | 2014-09-10 | [
[
"Youngs",
"Nora",
""
]
] | Neurons in the brain represent external stimuli via neural codes. These codes often arise from stimulus-response maps, associating to each neuron a convex receptive field. An important problem confronted by the brain is to infer properties of a represented stimulus space without knowledge of the receptive fields, using only the intrinsic structure of the neural code. How does the brain do this? To address this question, it is important to determine what stimulus space features can - in principle - be extracted from neural codes. This motivates us to define the neural ring and a related neural ideal, algebraic objects that encode the full combinatorial data of a neural code. We find that these objects can be expressed in a "canonical form" that directly translates to a minimal description of the receptive field structure intrinsic to the neural code. We consider the algebraic properties of homomorphisms between neural rings, which naturally relate to maps between neural codes. We show that maps between two neural codes are in bijection with ring homomorphisms between the respective neural rings, and define the notion of neural ring homomorphism, a special restricted class of ring homomorphisms which preserve neuron structure. We also find connections to Stanley-Reisner rings, and use ideas similar to those in the theory of monomial ideals to obtain an algorithm for computing the canonical form associated to any neural code, providing the groundwork for inferring stimulus space features from neural activity alone. |
0907.0017 | Eduardo D. Sontag | Giovanni Russo, Mario di Bernardo, and Eduardo D. Sontag | Global entrainment of transcriptional systems to periodic inputs | null | null | 10.1371/journal.pcbi.1000739 | null | q-bio.QM q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper addresses the problem of giving conditions for transcriptional
systems to be globally entrained to external periodic inputs. By using
contraction theory, a powerful tool from dynamical systems theory, it is shown
that certain systems driven by external periodic signals have the property that
all solutions converge to a fixed limit cycle. General results are proved, and
the properties are verified in the specific case of some models of
transcriptional systems. The basic mathematical results needed from contraction
theory are proved in the paper, making it self-contained.
| [
{
"created": "Tue, 30 Jun 2009 20:12:08 GMT",
"version": "v1"
}
] | 2015-05-13 | [
[
"Russo",
"Giovanni",
""
],
[
"di Bernardo",
"Mario",
""
],
[
"Sontag",
"Eduardo D.",
""
]
] | This paper addresses the problem of giving conditions for transcriptional systems to be globally entrained to external periodic inputs. By using contraction theory, a powerful tool from dynamical systems theory, it is shown that certain systems driven by external periodic signals have the property that all solutions converge to a fixed limit cycle. General results are proved, and the properties are verified in the specific case of some models of transcriptional systems. The basic mathematical results needed from contraction theory are proved in the paper, making it self-contained. |
q-bio/0612028 | Sumedha | Sumedha, Olivier C Martin and Andreas Wagner | New structural variation in evolutionary searches of RNA neutral
networks | to be published in Biosystems | Biosystems 90, 475-485(2007) | null | null | q-bio.PE | null | RNA secondary structure is an important computational model to understand how
genetic variation maps into phenotypic (structural) variation. Evolutionary
innovation in RNA structures is facilitated by neutral networks, large
connected sets of RNA sequences that fold into the same structure. Our work
extends and deepens previous studies on neutral networks. First, we show that
even the 1-mutant neighborhood of a given sequence (genotype) G0 with structure
(phenotype) P contains many structural variants that are not close to P. This
holds for biological and generic RNA sequences alike. Second, we analyze the
relation between new structures in the 1-neighborhoods of genotypes Gk that are
only a moderate Hamming distance k away from G0, and the structure of G0
itself, both for biological and for generic RNA structures. Third, we analyze
the relation between mutational robustness of a sequence and the distances of
structural variants near this sequence. Our findings underscore the role of
neutral networks in evolutionary innovation, and the role that high robustness
can play in diminishing the potential for such innovation.
| [
{
"created": "Fri, 15 Dec 2006 15:19:18 GMT",
"version": "v1"
}
] | 2008-01-22 | [
[
"Sumedha",
"",
""
],
[
"Martin",
"Olivier C",
""
],
[
"Wagner",
"Andreas",
""
]
] | RNA secondary structure is an important computational model to understand how genetic variation maps into phenotypic (structural) variation. Evolutionary innovation in RNA structures is facilitated by neutral networks, large connected sets of RNA sequences that fold into the same structure. Our work extends and deepens previous studies on neutral networks. First, we show that even the 1-mutant neighborhood of a given sequence (genotype) G0 with structure (phenotype) P contains many structural variants that are not close to P. This holds for biological and generic RNA sequences alike. Second, we analyze the relation between new structures in the 1-neighborhoods of genotypes Gk that are only a moderate Hamming distance k away from G0, and the structure of G0 itself, both for biological and for generic RNA structures. Third, we analyze the relation between mutational robustness of a sequence and the distances of structural variants near this sequence. Our findings underscore the role of neutral networks in evolutionary innovation, and the role that high robustness can play in diminishing the potential for such innovation. |
2308.03278 | Kerui Huang | Kerui Huang, Jianhong Tian, Lei Sun, Li Zeng, Peng Xie, Aihua Deng,
Ping Mo, Zhibo Zhou, Ming Jiang, Yun Wang, Xiaocheng Jiang | Key Gene Mining in Transcriptional Regulation for Specific Biological
Processes with Small Sample Sizes Using Multi-network pipeline Transformer | 34 pages,6 figures | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Gene mining is an important topic in the field of life sciences, but
traditional machine learning methods cannot consider the regulatory
relationships between genes. Deep learning methods perform poorly in small
sample sizes. This study proposed a deep learning method, called
TransGeneSelector, that can mine critical regulatory genes involved in certain
life processes using a small-sample transcriptome dataset. The method combines
a WGAN-GP data augmentation network, a sample filtering network, and a
Transformer classifier network, which successfully classified the state
(germinating or dry seeds) of Arabidopsis thaliana seed in a dataset of 79
samples, showing performance comparable to that of Random Forests. Further,
through the use of SHapley Additive exPlanations method, TransGeneSelector
successfully mined genes involved in seed germination. Through the construction
of gene regulatory networks and the enrichment analysis of KEGG, as well as
RT-qPCR quantitative analysis, it was confirmed that these genes are at a more
upstream regulatory level than those Random Forests mined, and the top 11 genes
that were uniquely mined by TransGeneSelector were found to be related to the
KAI2 signaling pathway, which is of great regulatory importance for
germination-related genes. This study provides a practical tool for life
science researchers to mine key genes from transcriptome data.
| [
{
"created": "Mon, 7 Aug 2023 03:37:38 GMT",
"version": "v1"
}
] | 2023-08-08 | [
[
"Huang",
"Kerui",
""
],
[
"Tian",
"Jianhong",
""
],
[
"Sun",
"Lei",
""
],
[
"Zeng",
"Li",
""
],
[
"Xie",
"Peng",
""
],
[
"Deng",
"Aihua",
""
],
[
"Mo",
"Ping",
""
],
[
"Zhou",
"Zhibo",
""
... | Gene mining is an important topic in the field of life sciences, but traditional machine learning methods cannot consider the regulatory relationships between genes. Deep learning methods perform poorly in small sample sizes. This study proposed a deep learning method, called TransGeneSelector, that can mine critical regulatory genes involved in certain life processes using a small-sample transcriptome dataset. The method combines a WGAN-GP data augmentation network, a sample filtering network, and a Transformer classifier network, which successfully classified the state (germinating or dry seeds) of Arabidopsis thaliana seed in a dataset of 79 samples, showing performance comparable to that of Random Forests. Further, through the use of SHapley Additive exPlanations method, TransGeneSelector successfully mined genes involved in seed germination. Through the construction of gene regulatory networks and the enrichment analysis of KEGG, as well as RT-qPCR quantitative analysis, it was confirmed that these genes are at a more upstream regulatory level than those Random Forests mined, and the top 11 genes that were uniquely mined by TransGeneSelector were found to be related to the KAI2 signaling pathway, which is of great regulatory importance for germination-related genes. This study provides a practical tool for life science researchers to mine key genes from transcriptome data. |
2406.18044 | Mathieu Fourment | Mathieu Fourment, Matthew Macaulay, Christiaan J Swanepoel, Xiang Ji,
Marc A Suchard, Frederick A Matsen IV | Torchtree: flexible phylogenetic model development and inference using
PyTorch | 23 pages, 3 tables, and 4 figures in main text, plus supplementary
materials | null | null | null | q-bio.PE stat.CO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Bayesian inference has predominantly relied on the Markov chain Monte Carlo
(MCMC) algorithm for many years. However, MCMC is computationally laborious,
especially for complex phylogenetic models of time trees. This bottleneck has
led to the search for alternatives, such as variational Bayes, which can scale
better to large datasets. In this paper, we introduce torchtree, a framework
written in Python that allows developers to easily implement rich phylogenetic
models and algorithms using a fixed tree topology. One can either use automatic
differentiation, or leverage torchtree's plug-in system to compute gradients
analytically for model components for which automatic differentiation is slow.
We demonstrate that the torchtree variational inference framework performs
similarly to BEAST in terms of speed and approximation accuracy. Furthermore,
we explore the use of the forward KL divergence as an optimizing criterion for
variational inference, which can handle discontinuous and non-differentiable
models. Our experiments show that inference using the forward KL divergence
tends to be faster per iteration compared to the evidence lower bound (ELBO)
criterion, although the ELBO-based inference may converge faster in some cases.
Overall, torchtree provides a flexible and efficient framework for phylogenetic
model development and inference using PyTorch.
| [
{
"created": "Wed, 26 Jun 2024 03:42:16 GMT",
"version": "v1"
}
] | 2024-06-27 | [
[
"Fourment",
"Mathieu",
""
],
[
"Macaulay",
"Matthew",
""
],
[
"Swanepoel",
"Christiaan J",
""
],
[
"Ji",
"Xiang",
""
],
[
"Suchard",
"Marc A",
""
],
[
"Matsen",
"Frederick A",
"IV"
]
] | Bayesian inference has predominantly relied on the Markov chain Monte Carlo (MCMC) algorithm for many years. However, MCMC is computationally laborious, especially for complex phylogenetic models of time trees. This bottleneck has led to the search for alternatives, such as variational Bayes, which can scale better to large datasets. In this paper, we introduce torchtree, a framework written in Python that allows developers to easily implement rich phylogenetic models and algorithms using a fixed tree topology. One can either use automatic differentiation, or leverage torchtree's plug-in system to compute gradients analytically for model components for which automatic differentiation is slow. We demonstrate that the torchtree variational inference framework performs similarly to BEAST in terms of speed and approximation accuracy. Furthermore, we explore the use of the forward KL divergence as an optimizing criterion for variational inference, which can handle discontinuous and non-differentiable models. Our experiments show that inference using the forward KL divergence tends to be faster per iteration compared to the evidence lower bound (ELBO) criterion, although the ELBO-based inference may converge faster in some cases. Overall, torchtree provides a flexible and efficient framework for phylogenetic model development and inference using PyTorch. |
1801.01821 | Sacha van Albada | Sacha Jennifer van Albada, Richard T. Gray, Peter M. Drysdale, Peter
A. Robinson | Mean-field modeling of the basal ganglia-thalamocortical system. II.
Dynamics of parkinsonian oscillations | null | J. Theor. Biol. 257:664-688 (2009) | 10.1016/j.jtbi.2008.12.013 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Neuronal correlates of Parkinson's disease (PD) include a slowing of the
electroencephalogram (EEG) and enhanced synchrony at 3-7 and 7-30 Hz in the
basal ganglia, thalamus, and cortex. This study describes the dynamics of a
physiologically based mean-field model of the basal ganglia-thalamocortical
system, and shows how it accounts for key electrophysiological correlates of
PD. Its connectivity comprises partially segregated direct and indirect
pathways through the striatum, a hyperdirect pathway involving a
corticosubthalamic projection, thalamostriatal feedback, and local inhibition
in striatum and external pallidum (GPe). In a companion paper, realistic
steady-state firing rates were obtained for the healthy state, and after
dopamine loss modeled by weaker direct and stronger indirect pathways, reduced
intrapallidal inhibition, lower firing thresholds of the GPe and subthalamic
nucleus (STN), a stronger striato-GPe projection, and weaker cortical
interactions. Here we show that oscillations around 5 and 20 Hz can arise with
a strong indirect pathway, which also increases synchrony throughout the basal
ganglia. Further, increased theta power with nigrostriatal degeneration
correlates with reduced alpha power and peak frequency, matching experiments.
Unlike the hyperdirect pathway, the indirect pathway sustains oscillations with
realistic phase relationships. Changes in basal ganglia responses to transient
stimuli accord with experimental data. Reduced cortical gains due to both
nigrostriatal and mesocortical dopamine loss lead to slower cortical activity
changes and may be related to bradykinesia. Finally, increased EEG power found
in some studies may be partly explained by a lower effective GPe firing
threshold, reduced GPe-GPe inhibition, and/or weaker intracortical connections
in PD. Strict separation of the direct and indirect pathways is not necessary
for these results.
| [
{
"created": "Fri, 5 Jan 2018 16:29:48 GMT",
"version": "v1"
}
] | 2018-01-08 | [
[
"van Albada",
"Sacha Jennifer",
""
],
[
"Gray",
"Richard T.",
""
],
[
"Drysdale",
"Peter M.",
""
],
[
"Robinson",
"Peter A.",
""
]
] | Neuronal correlates of Parkinson's disease (PD) include a slowing of the electroencephalogram (EEG) and enhanced synchrony at 3-7 and 7-30 Hz in the basal ganglia, thalamus, and cortex. This study describes the dynamics of a physiologically based mean-field model of the basal ganglia-thalamocortical system, and shows how it accounts for key electrophysiological correlates of PD. Its connectivity comprises partially segregated direct and indirect pathways through the striatum, a hyperdirect pathway involving a corticosubthalamic projection, thalamostriatal feedback, and local inhibition in striatum and external pallidum (GPe). In a companion paper, realistic steady-state firing rates were obtained for the healthy state, and after dopamine loss modeled by weaker direct and stronger indirect pathways, reduced intrapallidal inhibition, lower firing thresholds of the GPe and subthalamic nucleus (STN), a stronger striato-GPe projection, and weaker cortical interactions. Here we show that oscillations around 5 and 20 Hz can arise with a strong indirect pathway, which also increases synchrony throughout the basal ganglia. Further, increased theta power with nigrostriatal degeneration correlates with reduced alpha power and peak frequency, matching experiments. Unlike the hyperdirect pathway, the indirect pathway sustains oscillations with realistic phase relationships. Changes in basal ganglia responses to transient stimuli accord with experimental data. Reduced cortical gains due to both nigrostriatal and mesocortical dopamine loss lead to slower cortical activity changes and may be related to bradykinesia. Finally, increased EEG power found in some studies may be partly explained by a lower effective GPe firing threshold, reduced GPe-GPe inhibition, and/or weaker intracortical connections in PD. Strict separation of the direct and indirect pathways is not necessary for these results. |
1612.00732 | Delfim F. M. Torres | Cristiana J. Silva, Delfim F. M. Torres | A SICA compartmental model in epidemiology with application to HIV/AIDS
in Cape Verde | This is a preprint of a paper whose final and definite form is with
'Ecological Complexity', ISSN 1476-945X, available at
[http://dx.doi.org/10.1016/j.ecocom.2016.12.001]. Submitted 29/April/2016;
Revised 21/Oct/2016; Accepted 02/Dec/2016 | Ecological Complexity 30 (2017), 70--75 | 10.1016/j.ecocom.2016.12.001 | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We propose a new mathematical model for the transmission dynamics of the
human immunodeficiency virus (HIV). Global stability of the unique endemic
equilibrium is proved. Then, based on data provided by the "Progress Report on
the AIDS response in Cape Verde 2015", we calibrate our model to the cumulative
cases of infection by HIV and AIDS from 1987 to 2014 and we show that our model
predicts well such reality. Finally, a sensitivity analysis is done for the
case study in Cape Verde. We conclude that the goal of the United Nations to
end the AIDS epidemic by 2030 is a nontrivial task.
| [
{
"created": "Fri, 2 Dec 2016 16:27:43 GMT",
"version": "v1"
}
] | 2017-05-30 | [
[
"Silva",
"Cristiana J.",
""
],
[
"Torres",
"Delfim F. M.",
""
]
] | We propose a new mathematical model for the transmission dynamics of the human immunodeficiency virus (HIV). Global stability of the unique endemic equilibrium is proved. Then, based on data provided by the "Progress Report on the AIDS response in Cape Verde 2015", we calibrate our model to the cumulative cases of infection by HIV and AIDS from 1987 to 2014 and we show that our model predicts well such reality. Finally, a sensitivity analysis is done for the case study in Cape Verde. We conclude that the goal of the United Nations to end the AIDS epidemic by 2030 is a nontrivial task. |
2111.00594 | Ahmed Mohamed Harbo | Ahmed Mohamed Taher and Ibrahim Omar Saeed | Bioremediation of Contaminated Soil with Crude Oil Using Consortium of
bacteria | 4 pages | null | 10.1063/5.0094117 | null | q-bio.BM | http://creativecommons.org/licenses/by/4.0/ | This study included isolate petroleum hydrocarbons degradable bacteria and
develops a consortium or a mixture of bacteria with high biodegradation
capabilities which can be used in biological treatment units of the
contaminated soils before release. In this studyt ten bacterial strains were
isolated from soils contaminated with crude oil, by primary and secondary
screening, and by using the sterile saline solution with 1% of crude oil, five
bacterial isolates that can degrade oil were identified. The bacterial isolates
were isolated from polluted soils with crude oil, the samples were collected
from different areas of the Baiji refinery, and samples of heavy crude oil
extracted from Qayyarah fields were used in designing the biodegradation
experiments, the five isolates were diagnosed based on phenotypic, culture and
biochemical characterizes, and detection of the gene sequence of bacterial
isolates (16SrRNA). The (16SrRNA) gene sequence of the bacterial isolates was
recorded under the accession numbers LC596402, LC596403, LC596406, LC596404,
LC596405, for the genus (AM-I-1, AM-I-2, AM-I-5) and the species (AM-I-3,
AM-I-4) that following Bacillus Sp respectively, in the NCBI's GenBank, the
efficiency of the five isolates were examined for utilizing petroleum
hydrocarbons using a sterile mineral salt medium MS supplemented with crude oil
as the sole source of carbon with different concentrations, the results showed
that the decomposition of petroleum hydrocarbons at the concentrations (0.5, 1,
1.5, 2, 3) % reached (57.32, 69.36,63.71, 75.20, 68.60) %, respectively, for
mixed isolates, depending on the results of the gas chromatography (GC)
analysis.
| [
{
"created": "Sun, 31 Oct 2021 21:13:33 GMT",
"version": "v1"
}
] | 2024-06-19 | [
[
"Taher",
"Ahmed Mohamed",
""
],
[
"Saeed",
"Ibrahim Omar",
""
]
] | This study included isolate petroleum hydrocarbons degradable bacteria and develops a consortium or a mixture of bacteria with high biodegradation capabilities which can be used in biological treatment units of the contaminated soils before release. In this studyt ten bacterial strains were isolated from soils contaminated with crude oil, by primary and secondary screening, and by using the sterile saline solution with 1% of crude oil, five bacterial isolates that can degrade oil were identified. The bacterial isolates were isolated from polluted soils with crude oil, the samples were collected from different areas of the Baiji refinery, and samples of heavy crude oil extracted from Qayyarah fields were used in designing the biodegradation experiments, the five isolates were diagnosed based on phenotypic, culture and biochemical characterizes, and detection of the gene sequence of bacterial isolates (16SrRNA). The (16SrRNA) gene sequence of the bacterial isolates was recorded under the accession numbers LC596402, LC596403, LC596406, LC596404, LC596405, for the genus (AM-I-1, AM-I-2, AM-I-5) and the species (AM-I-3, AM-I-4) that following Bacillus Sp respectively, in the NCBI's GenBank, the efficiency of the five isolates were examined for utilizing petroleum hydrocarbons using a sterile mineral salt medium MS supplemented with crude oil as the sole source of carbon with different concentrations, the results showed that the decomposition of petroleum hydrocarbons at the concentrations (0.5, 1, 1.5, 2, 3) % reached (57.32, 69.36,63.71, 75.20, 68.60) %, respectively, for mixed isolates, depending on the results of the gas chromatography (GC) analysis. |
1604.05364 | John Rhodes | Elizabeth S. Allman, James H. Degnan, John A. Rhodes | Species tree inference from gene splits by Unrooted STAR methods | 7 pages, 1 figure | null | null | null | q-bio.PE math.ST stat.TH | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The $\text{NJ}_{st}$ method was proposed by Liu and Yu to infer a species
tree topology from unrooted topological gene trees. While its statistical
consistency under the multispecies coalescent model was established only for a
4-taxon tree, simulations demonstrated its good performance on gene trees
inferred from sequences for many taxa. Here we prove the statistical
consistency of the method for an arbitrarily large species tree. Our approach
connects $\text{NJ}_{st}$ to a generalization of the STAR method of Liu, Pearl
and Edwards, and a previous theoretical analysis of it. We further show
$\text{NJ}_{st}$ utilizes only the distribution of splits in the gene trees,
and not their individual topologies. Finally, we discuss how multiple samples
per taxon per gene should be handled for statistical consistency.
| [
{
"created": "Mon, 18 Apr 2016 22:20:33 GMT",
"version": "v1"
}
] | 2016-04-20 | [
[
"Allman",
"Elizabeth S.",
""
],
[
"Degnan",
"James H.",
""
],
[
"Rhodes",
"John A.",
""
]
] | The $\text{NJ}_{st}$ method was proposed by Liu and Yu to infer a species tree topology from unrooted topological gene trees. While its statistical consistency under the multispecies coalescent model was established only for a 4-taxon tree, simulations demonstrated its good performance on gene trees inferred from sequences for many taxa. Here we prove the statistical consistency of the method for an arbitrarily large species tree. Our approach connects $\text{NJ}_{st}$ to a generalization of the STAR method of Liu, Pearl and Edwards, and a previous theoretical analysis of it. We further show $\text{NJ}_{st}$ utilizes only the distribution of splits in the gene trees, and not their individual topologies. Finally, we discuss how multiple samples per taxon per gene should be handled for statistical consistency. |
1605.06430 | Jorge Vel\'azquez-Castro PhD | Emilene Pliego Pliego, Jorge Velazquez-Castro, Andres Fraguela-Collar | Seasonality on the life cycle of Aedes aegypti mosquito and its effects
on dengue outbreaks | submitted to Applied Mathematical Modelling | null | null | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Dengue is a vector-borne disease transmitted by the mosquito Aedes aegypti.
It has been observed that its incidence is strongly influenced by temperature
and other abiotic factors like rainfall and humidity. In this work we compare
the effects of seasonality in temperature that affect the entomological
parameters of the mosquito with precipitation that affects the hatchery
capacity. We also analyze its joint action using a dynamical model for the life
cycle of Aedes aegypti and historical weather data from 8 regions of Mexico. We
found that the joint action of different mechanisms can enhance the prevalence
of the disease, but also inhibit it when they act in an asynchronous way. We
found that for the studied regions, the seasonality of the low temperature
rather than mean temperature is the main driving force of Dengue outbreaks. We
also analyzed the role of the diapause in these kinds of outbreaks. The
methodology developed here can be used to discover the underlying mechanism of
Dengue outbreaks in different regions and thus help to apply targeted control
measures.
| [
{
"created": "Fri, 20 May 2016 16:38:23 GMT",
"version": "v1"
}
] | 2016-05-23 | [
[
"Pliego",
"Emilene Pliego",
""
],
[
"Velazquez-Castro",
"Jorge",
""
],
[
"Fraguela-Collar",
"Andres",
""
]
] | Dengue is a vector-borne disease transmitted by the mosquito Aedes aegypti. It has been observed that its incidence is strongly influenced by temperature and other abiotic factors like rainfall and humidity. In this work we compare the effects of seasonality in temperature that affect the entomological parameters of the mosquito with precipitation that affects the hatchery capacity. We also analyze its joint action using a dynamical model for the life cycle of Aedes aegypti and historical weather data from 8 regions of Mexico. We found that the joint action of different mechanisms can enhance the prevalence of the disease, but also inhibit it when they act in an asynchronous way. We found that for the studied regions, the seasonality of the low temperature rather than mean temperature is the main driving force of Dengue outbreaks. We also analyzed the role of the diapause in these kinds of outbreaks. The methodology developed here can be used to discover the underlying mechanism of Dengue outbreaks in different regions and thus help to apply targeted control measures. |
1808.00775 | Robert Schwieger | Robert Schwieger and Heike Siebert | Representing Model Ensembles as Boolean Functions | 14 pages, 3 figures | Advances in Systems and Synthetic Biology, 2018 | null | null | q-bio.MN math.LO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Families of ODE models characterized by a common sign structure of their
Jacobi matrix are investigated within the formalism of qualitative differential
equations. In the context of regulatory networks the sign structure of the
Jacobi matrix carries the information about which components of the network
inhibit or activate each other. Information about constraints on the behavior
of models in this family is stored in a so called qualitative state transition
graph. We showed previously that a similar approach can be used to analyze a
model pool of Boolean functions characterized by a common interaction graph.
Here we show that the opposite approach is fruitful as well. We show that the
qualitative state transition graph can be reduced to a "skeleton" represented
by a Boolean function conserving the reachability properties. This reduction
has the advantage that approaches such as model checking and network inference
methods can be applied to the "skeleton" within the framework of Boolean
networks. Furthermore, our work constitutes an alternative to approach to link
Boolean networks and differential equations.
| [
{
"created": "Thu, 2 Aug 2018 12:09:56 GMT",
"version": "v1"
}
] | 2018-08-03 | [
[
"Schwieger",
"Robert",
""
],
[
"Siebert",
"Heike",
""
]
] | Families of ODE models characterized by a common sign structure of their Jacobi matrix are investigated within the formalism of qualitative differential equations. In the context of regulatory networks the sign structure of the Jacobi matrix carries the information about which components of the network inhibit or activate each other. Information about constraints on the behavior of models in this family is stored in a so called qualitative state transition graph. We showed previously that a similar approach can be used to analyze a model pool of Boolean functions characterized by a common interaction graph. Here we show that the opposite approach is fruitful as well. We show that the qualitative state transition graph can be reduced to a "skeleton" represented by a Boolean function conserving the reachability properties. This reduction has the advantage that approaches such as model checking and network inference methods can be applied to the "skeleton" within the framework of Boolean networks. Furthermore, our work constitutes an alternative to approach to link Boolean networks and differential equations. |
2003.12886 | Avi Flamholz | Yinon M. Bar-On, Avi I. Flamholz, Rob Phillips, Ron Milo | SARS-CoV-2 (COVID-19) by the numbers | null | null | null | null | q-bio.OT | http://creativecommons.org/licenses/by/4.0/ | The current SARS-CoV-2 pandemic is a harsh reminder of the fact that, whether
in a single human host or a wave of infection across continents, viral dynamics
is often a story about the numbers. In this snapshot, our aim is to provide a
one-stop, curated graphical source for the key numbers that help us understand
the virus driving our current global crisis. The discussion is framed around
two broad themes: 1) the biology of the virus itself and 2) the characteristics
of the infection of a single human host. Our one-page summary provides the key
numbers pertaining to SARS-CoV-2, based mostly on peer-reviewed literature. The
numbers reported in summary format are substantiated by the annotated
references below. Readers are urged to remember that much uncertainty remains
and knowledge of this pandemic and the virus driving it is rapidly evolving. In
the paragraphs below we provide "back of the envelope" calculations that
exemplify the insights that can be gained from knowing some key numbers and
using quantitative logic. These calculations serve to improve our intuition
through sanity checks, but do not replace detailed epidemiological analysis.
| [
{
"created": "Sat, 28 Mar 2020 20:49:04 GMT",
"version": "v1"
},
{
"created": "Tue, 31 Mar 2020 03:04:03 GMT",
"version": "v2"
}
] | 2020-04-01 | [
[
"Bar-On",
"Yinon M.",
""
],
[
"Flamholz",
"Avi I.",
""
],
[
"Phillips",
"Rob",
""
],
[
"Milo",
"Ron",
""
]
] | The current SARS-CoV-2 pandemic is a harsh reminder of the fact that, whether in a single human host or a wave of infection across continents, viral dynamics is often a story about the numbers. In this snapshot, our aim is to provide a one-stop, curated graphical source for the key numbers that help us understand the virus driving our current global crisis. The discussion is framed around two broad themes: 1) the biology of the virus itself and 2) the characteristics of the infection of a single human host. Our one-page summary provides the key numbers pertaining to SARS-CoV-2, based mostly on peer-reviewed literature. The numbers reported in summary format are substantiated by the annotated references below. Readers are urged to remember that much uncertainty remains and knowledge of this pandemic and the virus driving it is rapidly evolving. In the paragraphs below we provide "back of the envelope" calculations that exemplify the insights that can be gained from knowing some key numbers and using quantitative logic. These calculations serve to improve our intuition through sanity checks, but do not replace detailed epidemiological analysis. |
q-bio/0405019 | Trinh Xuan Hoang | Trinh Xuan Hoang, Antonio Trovato, Flavio Seno, Jayanth R. Banavar,
Amos Maritan | Geometry and symmetry presculpt the free-energy landscape of proteins | 23 pages, 5 figures | PNAS 101, 7960-7964 (2004) | 10.1073/pnas.0402525101 | null | q-bio.BM | null | We present a simple physical model which demonstrates that the native state
folds of proteins can emerge on the basis of considerations of geometry and
symmetry. We show that the inherent anisotropy of a chain molecule, the
geometrical and energetic constraints placed by the hydrogen bonds and sterics,
and hydrophobicity are sufficient to yield a free energy landscape with broad
minima even for a homopolymer. These minima correspond to marginally compact
structures comprising the menu of folds that proteins choose from to house
their native-states in. Our results provide a general framework for
understanding the common characteristics of globular proteins.
| [
{
"created": "Tue, 25 May 2004 20:50:50 GMT",
"version": "v1"
}
] | 2009-11-10 | [
[
"Hoang",
"Trinh Xuan",
""
],
[
"Trovato",
"Antonio",
""
],
[
"Seno",
"Flavio",
""
],
[
"Banavar",
"Jayanth R.",
""
],
[
"Maritan",
"Amos",
""
]
] | We present a simple physical model which demonstrates that the native state folds of proteins can emerge on the basis of considerations of geometry and symmetry. We show that the inherent anisotropy of a chain molecule, the geometrical and energetic constraints placed by the hydrogen bonds and sterics, and hydrophobicity are sufficient to yield a free energy landscape with broad minima even for a homopolymer. These minima correspond to marginally compact structures comprising the menu of folds that proteins choose from to house their native-states in. Our results provide a general framework for understanding the common characteristics of globular proteins. |
1604.05080 | Johannes Schemmel | Simon Friedmann, Johannes Schemmel, Andreas Gruebl, Andreas Hartel,
Matthias Hock and Karlheinz Meier | Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System | null | null | null | null | q-bio.NC cond-mat.dis-nn cs.NE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present results from a new approach to learning and plasticity in
neuromorphic hardware systems: to enable flexibility in implementable learning
mechanisms while keeping high efficiency associated with neuromorphic
implementations, we combine a general-purpose processor with full-custom analog
elements.
This processor is operating in parallel with a fully parallel neuromorphic
system consisting of an array of synapses connected to analog, continuous time
neuron circuits. Novel analog correlation sensor circuits process spike events
for each synapse in parallel and in real-time.
The processor uses this pre-processing to compute new weights possibly using
additional information following its program.
Therefore, learning rules can be defined in software giving a large degree of
flexibility.
Synapses realize correlation detection geared towards Spike-Timing Dependent
Plasticity (STDP) as central computational primitive in the analog domain.
Operating at a speed-up factor of 1000 compared to biological time-scale, we
measure time-constants from tens to hundreds of micro-seconds.
We analyze variability across multiple chips and demonstrate learning using a
multiplicative STDP rule.
We conclude, that the presented approach will enable flexible and efficient
learning as a platform for neuroscientific research and technological
applications.
| [
{
"created": "Mon, 18 Apr 2016 10:49:38 GMT",
"version": "v1"
},
{
"created": "Thu, 13 Oct 2016 09:15:12 GMT",
"version": "v2"
}
] | 2016-10-14 | [
[
"Friedmann",
"Simon",
""
],
[
"Schemmel",
"Johannes",
""
],
[
"Gruebl",
"Andreas",
""
],
[
"Hartel",
"Andreas",
""
],
[
"Hock",
"Matthias",
""
],
[
"Meier",
"Karlheinz",
""
]
] | We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high efficiency associated with neuromorphic implementations, we combine a general-purpose processor with full-custom analog elements. This processor is operating in parallel with a fully parallel neuromorphic system consisting of an array of synapses connected to analog, continuous time neuron circuits. Novel analog correlation sensor circuits process spike events for each synapse in parallel and in real-time. The processor uses this pre-processing to compute new weights possibly using additional information following its program. Therefore, learning rules can be defined in software giving a large degree of flexibility. Synapses realize correlation detection geared towards Spike-Timing Dependent Plasticity (STDP) as central computational primitive in the analog domain. Operating at a speed-up factor of 1000 compared to biological time-scale, we measure time-constants from tens to hundreds of micro-seconds. We analyze variability across multiple chips and demonstrate learning using a multiplicative STDP rule. We conclude, that the presented approach will enable flexible and efficient learning as a platform for neuroscientific research and technological applications. |
1309.1895 | Vince Grolmusz | Gabor Ivan, Daniel Banky, Vince Grolmusz | Fast and Exact Sequence Alignment with the Smith-Waterman Algorithm: The
SwissAlign Webserver | null | null | null | null | q-bio.GN q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It is demonstrated earlier that the exact Smith-Waterman algorithm yields
more accurate results than the members of the heuristic BLAST family of
algorithms. Unfortunately, the Smith-Waterman algorithm is much slower than the
BLAST and its clones. Here we present a technique and a webserver that uses the
exact Smith-Waterman algorithm, and it is approximately as fast as the BLAST
algorithm. The technique unites earlier methods of extensive preprocessing of
the target sequence database, and CPU-specific coding of the Smith-Waterman
algorithm. The SwissAlign webserver is available at the
http://swissalign.pitgroup.org address.
| [
{
"created": "Sat, 7 Sep 2013 19:02:32 GMT",
"version": "v1"
}
] | 2013-09-10 | [
[
"Ivan",
"Gabor",
""
],
[
"Banky",
"Daniel",
""
],
[
"Grolmusz",
"Vince",
""
]
] | It is demonstrated earlier that the exact Smith-Waterman algorithm yields more accurate results than the members of the heuristic BLAST family of algorithms. Unfortunately, the Smith-Waterman algorithm is much slower than the BLAST and its clones. Here we present a technique and a webserver that uses the exact Smith-Waterman algorithm, and it is approximately as fast as the BLAST algorithm. The technique unites earlier methods of extensive preprocessing of the target sequence database, and CPU-specific coding of the Smith-Waterman algorithm. The SwissAlign webserver is available at the http://swissalign.pitgroup.org address. |
2310.14392 | Jose A Capitan | Carlos A. Servan, Jose A. Capitan, Zachary R. Miller and Stefano
Allesina | Effects of phylogeny on coexistence in model communities | null | null | null | null | q-bio.PE cond-mat.stat-mech | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Species' interactions are shaped by their traits. Thus, we expect traits --
in particular, trait (dis)similarity -- to play a central role in determining
whether a particular set of species coexists. Traits are, in turn, the outcome
of an eco-evolutionary process summarized by a phylogenetic tree. Therefore,
the phylogenetic tree associated with a set of species should carry information
about the dynamics and assembly properties of the community. Many studies have
highlighted the potentially complex ways in which this phylogenetic information
is translated into species' ecological properties. However, much less emphasis
has been placed on developing clear, quantitative expectations for community
properties under a particular hypothesis. To address this gap, we couple a
simple model of trait evolution on a phylogenetic tree with Lotka-Volterra
community dynamics. This allows us to derive properties of a community of
coexisting species as a function of the number of traits, tree topology and the
size of the species pool. Our analysis highlights how phylogenies, through
traits, affect the coexistence of a set of species. Together, these results
provide much-needed baseline expectations for the ways in which evolutionary
history, summarized by phylogeny, is reflected in the size and structure of
ecological communities.
| [
{
"created": "Sun, 22 Oct 2023 19:26:47 GMT",
"version": "v1"
},
{
"created": "Thu, 4 Jan 2024 10:01:42 GMT",
"version": "v2"
},
{
"created": "Mon, 17 Jun 2024 17:09:12 GMT",
"version": "v3"
},
{
"created": "Sat, 10 Aug 2024 18:09:21 GMT",
"version": "v4"
}
] | 2024-08-13 | [
[
"Servan",
"Carlos A.",
""
],
[
"Capitan",
"Jose A.",
""
],
[
"Miller",
"Zachary R.",
""
],
[
"Allesina",
"Stefano",
""
]
] | Species' interactions are shaped by their traits. Thus, we expect traits -- in particular, trait (dis)similarity -- to play a central role in determining whether a particular set of species coexists. Traits are, in turn, the outcome of an eco-evolutionary process summarized by a phylogenetic tree. Therefore, the phylogenetic tree associated with a set of species should carry information about the dynamics and assembly properties of the community. Many studies have highlighted the potentially complex ways in which this phylogenetic information is translated into species' ecological properties. However, much less emphasis has been placed on developing clear, quantitative expectations for community properties under a particular hypothesis. To address this gap, we couple a simple model of trait evolution on a phylogenetic tree with Lotka-Volterra community dynamics. This allows us to derive properties of a community of coexisting species as a function of the number of traits, tree topology and the size of the species pool. Our analysis highlights how phylogenies, through traits, affect the coexistence of a set of species. Together, these results provide much-needed baseline expectations for the ways in which evolutionary history, summarized by phylogeny, is reflected in the size and structure of ecological communities. |
0801.0311 | Tatyana Sharpee | Tatyana O. Sharpee | Comparison of objective functions for estimating linear-nonlinear models | to appear in Advances in Neural Information Processing Systems 21
(NIPS, 2007) | null | null | null | q-bio.NC q-bio.QM | null | This paper compares a family of methods for characterizing neural feature
selectivity with natural stimuli in the framework of the linear-nonlinear
model. In this model, the neural firing rate is a nonlinear function of a small
number of relevant stimulus components. The relevant stimulus dimensions can be
found by maximizing one of the family of objective functions, Renyi divergences
of different orders. We show that maximizing one of them, Renyi divergence of
order 2, is equivalent to least-square fitting of the linear-nonlinear model to
neural data. Next, we derive reconstruction errors in relevant dimensions found
by maximizing Renyi divergences of arbitrary order in the asymptotic limit of
large spike numbers. We find that the smallest rrors are obtained with Renyi
divergence of order 1, also known as Kullback-Leibler divergence. This
corresponds to finding relevant dimensions by maximizing mutual information. We
numerically test how these optimization schemes perform in the regime of low
signal-to-noise ratio (small number of spikes and increasing neural noise) for
model visual neurons. We find that optimization schemes based on either least
square fitting or information maximization perform well even when number of
spikes is small. Information maximization provides slightly, but significantly,
better reconstructions than least square fitting. This makes the problem of
finding relevant dimensions, together with the problem of lossy compression,
one of examples where information-theoretic measures are no more data limited
than those derived from least squares.
| [
{
"created": "Wed, 2 Jan 2008 07:13:48 GMT",
"version": "v1"
}
] | 2008-01-03 | [
[
"Sharpee",
"Tatyana O.",
""
]
] | This paper compares a family of methods for characterizing neural feature selectivity with natural stimuli in the framework of the linear-nonlinear model. In this model, the neural firing rate is a nonlinear function of a small number of relevant stimulus components. The relevant stimulus dimensions can be found by maximizing one of the family of objective functions, Renyi divergences of different orders. We show that maximizing one of them, Renyi divergence of order 2, is equivalent to least-square fitting of the linear-nonlinear model to neural data. Next, we derive reconstruction errors in relevant dimensions found by maximizing Renyi divergences of arbitrary order in the asymptotic limit of large spike numbers. We find that the smallest rrors are obtained with Renyi divergence of order 1, also known as Kullback-Leibler divergence. This corresponds to finding relevant dimensions by maximizing mutual information. We numerically test how these optimization schemes perform in the regime of low signal-to-noise ratio (small number of spikes and increasing neural noise) for model visual neurons. We find that optimization schemes based on either least square fitting or information maximization perform well even when number of spikes is small. Information maximization provides slightly, but significantly, better reconstructions than least square fitting. This makes the problem of finding relevant dimensions, together with the problem of lossy compression, one of examples where information-theoretic measures are no more data limited than those derived from least squares. |
2011.05140 | Yvonne Krumbeck | Yvonne Krumbeck, Qian Yang, George W. A. Constable, Tim Rogers | Fluctuation spectra of large random dynamical systems reveal hidden
structure in ecological networks | 17 pages, 7 figures, revised submission, added sections on data
application and expanding notion of temporal stability | null | 10.1038/s41467-021-23757-x | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Understanding the relationship between complexity and stability in large
dynamical systems -- such as ecosystems -- remains a key open question in
complexity theory which has inspired a rich body of work developed over more
than fifty years. The vast majority of this theory addresses asymptotic linear
stability around equilibrium points, but the idea of `stability' in fact has
other uses in the empirical ecological literature. The important notion of
`temporal stability' describes the character of fluctuations in population
dynamics, driven by intrinsic or extrinsic noise. Here we apply tools from
random matrix theory to the problem of temporal stability, deriving analytical
predictions for the fluctuation spectra of complex ecological networks. We show
that different network structures leave distinct signatures in the spectrum of
fluctuations, and demonstrate the application of our theory to the analysis
ecological timeseries data of plankton abundances.
| [
{
"created": "Tue, 10 Nov 2020 15:09:57 GMT",
"version": "v1"
},
{
"created": "Wed, 12 May 2021 16:49:54 GMT",
"version": "v2"
}
] | 2021-07-14 | [
[
"Krumbeck",
"Yvonne",
""
],
[
"Yang",
"Qian",
""
],
[
"Constable",
"George W. A.",
""
],
[
"Rogers",
"Tim",
""
]
] | Understanding the relationship between complexity and stability in large dynamical systems -- such as ecosystems -- remains a key open question in complexity theory which has inspired a rich body of work developed over more than fifty years. The vast majority of this theory addresses asymptotic linear stability around equilibrium points, but the idea of `stability' in fact has other uses in the empirical ecological literature. The important notion of `temporal stability' describes the character of fluctuations in population dynamics, driven by intrinsic or extrinsic noise. Here we apply tools from random matrix theory to the problem of temporal stability, deriving analytical predictions for the fluctuation spectra of complex ecological networks. We show that different network structures leave distinct signatures in the spectrum of fluctuations, and demonstrate the application of our theory to the analysis ecological timeseries data of plankton abundances. |
2007.15093 | Thierry Dufour | Javier Vaquero, Florian Jud\'ee, Marie Vallette, Henri Decauchy, Ander
Arbelaiz, Lynda Aoudjehane, Olivier Scatton, Ester Gonzalez-Sanchez, Fatiha
Merabtene, J\'er\'emy Augustin, Chantal Housset, Thierry Dufour, Laura
Fouassier | Cold-atmospheric plasma induces tumor cell death in preclinical in vivo
and in vitro models of human cholangiocarcinoma | null | Cancers, 12, 1280, 2020 | 10.3390/cancers12051280 | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Through the last decade, cold atmospheric plasma (CAP) has emerged as an
innovative therapeutic option for cancer treatment. Recently, we have set up a
potentially safe atmospheric pressure plasma jet device that displays
antitumoral properties in a preclinical model of cholangiocarcinoma (CCA), a
rare and very aggressive cancer emerging from the biliary tree with few
efficient treatments. In the present study, we aimed at deciphering the
molecular mechanisms underlying the antitumor effects of CAP towards CCA both
in an in vivo and in vitro context. In vivo, using subcutaneous xenografts into
immunocompromised mice, CAP treatment of CCA induced DNA lesions and tumor cell
apoptosis, as evaluated by 8-oxoguanine and cleaved caspase-3
immunohistochemistry, respectively. Analysis of the tumor microenvironment
showed changes in markers related to macrophage polarization. In vitro,
incubation of CCA cells with CAP-treated culture media (i.e. plasma-activated
media, PAM) led to a dose response decrease in cell survival. At molecular
level, CAP treatment induced double-strand DNA breaks, followed by an increased
phosphorylation and activation of the cell cycle master regulators CHK1 and
p53, leading to cell cycle arrest and cell death by apoptosis. In conclusion,
CAP is a novel therapeutic option to consider for CCA in the future.
| [
{
"created": "Mon, 27 Jul 2020 20:51:52 GMT",
"version": "v1"
}
] | 2020-07-31 | [
[
"Vaquero",
"Javier",
""
],
[
"Judée",
"Florian",
""
],
[
"Vallette",
"Marie",
""
],
[
"Decauchy",
"Henri",
""
],
[
"Arbelaiz",
"Ander",
""
],
[
"Aoudjehane",
"Lynda",
""
],
[
"Scatton",
"Olivier",
""
],
... | Through the last decade, cold atmospheric plasma (CAP) has emerged as an innovative therapeutic option for cancer treatment. Recently, we have set up a potentially safe atmospheric pressure plasma jet device that displays antitumoral properties in a preclinical model of cholangiocarcinoma (CCA), a rare and very aggressive cancer emerging from the biliary tree with few efficient treatments. In the present study, we aimed at deciphering the molecular mechanisms underlying the antitumor effects of CAP towards CCA both in an in vivo and in vitro context. In vivo, using subcutaneous xenografts into immunocompromised mice, CAP treatment of CCA induced DNA lesions and tumor cell apoptosis, as evaluated by 8-oxoguanine and cleaved caspase-3 immunohistochemistry, respectively. Analysis of the tumor microenvironment showed changes in markers related to macrophage polarization. In vitro, incubation of CCA cells with CAP-treated culture media (i.e. plasma-activated media, PAM) led to a dose response decrease in cell survival. At molecular level, CAP treatment induced double-strand DNA breaks, followed by an increased phosphorylation and activation of the cell cycle master regulators CHK1 and p53, leading to cell cycle arrest and cell death by apoptosis. In conclusion, CAP is a novel therapeutic option to consider for CCA in the future. |
2107.13393 | Yoonsuck Choe | Yoonsuck Choe | Meaning Versus Information, Prediction Versus Memory, and Question
Versus Answer | 14 pages | null | 10.1016/B978-0-12-815480-9.00014-1 | null | q-bio.NC cs.AI cs.LG cs.RO | http://creativecommons.org/licenses/by/4.0/ | Brain science and artificial intelligence have made great progress toward the
understanding and engineering of the human mind. The progress has accelerated
significantly since the turn of the century thanks to new methods for probing
the brain (both structure and function), and rapid development in deep learning
research. However, despite these new developments, there are still many open
questions, such as how to understand the brain at the system level, and various
robustness issues and limitations of deep learning. In this informal essay, I
will talk about some of the concepts that are central to brain science and
artificial intelligence, such as information and memory, and discuss how a
different view on these concepts can help us move forward, beyond current
limits of our understanding in these fields.
| [
{
"created": "Tue, 29 Jun 2021 18:22:49 GMT",
"version": "v1"
}
] | 2021-07-29 | [
[
"Choe",
"Yoonsuck",
""
]
] | Brain science and artificial intelligence have made great progress toward the understanding and engineering of the human mind. The progress has accelerated significantly since the turn of the century thanks to new methods for probing the brain (both structure and function), and rapid development in deep learning research. However, despite these new developments, there are still many open questions, such as how to understand the brain at the system level, and various robustness issues and limitations of deep learning. In this informal essay, I will talk about some of the concepts that are central to brain science and artificial intelligence, such as information and memory, and discuss how a different view on these concepts can help us move forward, beyond current limits of our understanding in these fields. |
1511.03840 | Akinori Awazu | Koudai Hirao, Atsushi J Nagano, Akinori Awazu | Noise-plasticity correlations of gene expression in the multicellular
organism Arabidopsis thaliana | null | Arabidopsis thaliana. Journal of theoretical biology, 387, 13-22
(2015) | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Gene expression levels exhibit stochastic variations among genetically
identical organisms under the same environmental conditions (called gene
expression "noise" or phenotype "fluctuation"). In yeast and Escherichia coli,
positive correlations have been found between such gene expression noise and
"plasticity" with environmental variations. To determine the universality of
such correlations in both unicellular and multicellular organisms, we focused
on the relationships between gene expression "noise" and "plasticity" in
Arabidopsis thaliana, a multicellular model organism. In recent studies on
yeast and E. coli, only some gene groups with specific properties of promoter
architecture, average expression levels, and functions exhibited strong
noise-plasticity correlations. However, we found strong noise-plasticity
correlations for most gene groups in Arabidopsis; additionally, promoter
architecture, functional essentiality of genes, and circadian rhythm appeared
to have only a weak influence on the correlation strength. The differences in
the characteristics of noise-plasticity correlations may result from
three-dimensional chromosomal structures and/or circadian rhythm.
| [
{
"created": "Thu, 12 Nov 2015 10:34:05 GMT",
"version": "v1"
}
] | 2015-11-13 | [
[
"Hirao",
"Koudai",
""
],
[
"Nagano",
"Atsushi J",
""
],
[
"Awazu",
"Akinori",
""
]
] | Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions (called gene expression "noise" or phenotype "fluctuation"). In yeast and Escherichia coli, positive correlations have been found between such gene expression noise and "plasticity" with environmental variations. To determine the universality of such correlations in both unicellular and multicellular organisms, we focused on the relationships between gene expression "noise" and "plasticity" in Arabidopsis thaliana, a multicellular model organism. In recent studies on yeast and E. coli, only some gene groups with specific properties of promoter architecture, average expression levels, and functions exhibited strong noise-plasticity correlations. However, we found strong noise-plasticity correlations for most gene groups in Arabidopsis; additionally, promoter architecture, functional essentiality of genes, and circadian rhythm appeared to have only a weak influence on the correlation strength. The differences in the characteristics of noise-plasticity correlations may result from three-dimensional chromosomal structures and/or circadian rhythm. |
2305.04053 | Konstantin Blyuss | K.B. Blyuss, Y.N. Kyrychko, O.B. Blyuss | Complex dynamics near extinction in a predator-prey model with ratio
dependence and Holling type III functional response | 14 pages, 5 figures | Front. Appl. Math. Stat. 8, 1083815 (2022) | 10.3389/fams.2022.1083815 | null | q-bio.PE nlin.CD | http://creativecommons.org/licenses/by/4.0/ | In this paper, we analyse a recently proposed predator-prey model with ratio
dependence and Holling type III functional response, with particular emphasis
on the dynamics close to extinction. By using Briot-Bouquet transformation we
transform the model into a system, where the extinction steady state is
represented by up to three distinct steady states, whose existence is
determined by the values of appropriate Lambert W functions. We investigate how
stability of extinction and coexistence steady states is affected by the rate
of predation, predator fecundity, and the parameter characterising the strength
of functional response. The results suggest that the extinction steady state
can be stable for sufficiently high predation rate and for sufficiently small
predator fecundity. Moreover, in certain parameter regimes, a stable extinction
steady state can coexist with a stable prey-only equilibrium or with a stable
coexistence equilibrium, and it is rather the initial conditions that determine
whether prey and predator populations will be maintained at some steady level,
or both of them will become extinct. Another possibility is for coexistence
steady state to be unstable, in which case sustained periodic oscillations
around it are observed. Numerical simulations are performed to illustrate the
behaviour for all dynamical regimes, and in each case a corresponding phase
plane of the transformed system is presented to show a correspondence with
stable and unstable extinction steady state.
| [
{
"created": "Sat, 6 May 2023 13:57:54 GMT",
"version": "v1"
}
] | 2023-05-09 | [
[
"Blyuss",
"K. B.",
""
],
[
"Kyrychko",
"Y. N.",
""
],
[
"Blyuss",
"O. B.",
""
]
] | In this paper, we analyse a recently proposed predator-prey model with ratio dependence and Holling type III functional response, with particular emphasis on the dynamics close to extinction. By using Briot-Bouquet transformation we transform the model into a system, where the extinction steady state is represented by up to three distinct steady states, whose existence is determined by the values of appropriate Lambert W functions. We investigate how stability of extinction and coexistence steady states is affected by the rate of predation, predator fecundity, and the parameter characterising the strength of functional response. The results suggest that the extinction steady state can be stable for sufficiently high predation rate and for sufficiently small predator fecundity. Moreover, in certain parameter regimes, a stable extinction steady state can coexist with a stable prey-only equilibrium or with a stable coexistence equilibrium, and it is rather the initial conditions that determine whether prey and predator populations will be maintained at some steady level, or both of them will become extinct. Another possibility is for coexistence steady state to be unstable, in which case sustained periodic oscillations around it are observed. Numerical simulations are performed to illustrate the behaviour for all dynamical regimes, and in each case a corresponding phase plane of the transformed system is presented to show a correspondence with stable and unstable extinction steady state. |
2002.08265 | Manuel Sebastian Mariani | Manuel S. Mariani, Mar\'ia J. Palazzi, Albert Sol\'e-Ribalta, Javier
Borge-Holthoefer, Claudio J. Tessone | Absence of a resolution limit in in-block nestedness | 12 pages, 4 figures, 1 table | Communications in Nonlinear Science and Numerical Simulation 94
(2021) 105545 | 10.1016/j.cnsns.2020.105545 | null | q-bio.QM cs.SI physics.data-an physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Originally a speculative pattern in ecological networks, the hybrid or
compound nested-modular pattern has been confirmed, during the last decade, as
a relevant structural arrangement that emerges in a variety of contexts --in
ecological mutualistic system and beyond. This implies shifting the focus from
the measurement of nestedness as a global property (macro level), to the
detection of blocks (meso level) that internally exhibit a high degree of
nestedness. Unfortunately, the availability and understanding of the methods to
properly detect in-block nested partitions lie behind the empirical findings:
while a precise quality function of in-block nestedness has been proposed, we
lack an understanding of its possible inherent constraints. Specifically, while
it is well known that Newman-Girvan's modularity, and related quality
functions, notoriously suffer from a resolution limit that impairs their
ability to detect small blocks, the potential existence of resolution limits
for in-block nestedness is unexplored. Here, we provide empirical, numerical
and analytical evidence that the in-block nestedness function lacks a
resolution limit, and thus our capacity to detect correct partitions in
networks via its maximization depends solely on the accuracy of the
optimization algorithms.
| [
{
"created": "Wed, 19 Feb 2020 16:17:16 GMT",
"version": "v1"
}
] | 2020-10-27 | [
[
"Mariani",
"Manuel S.",
""
],
[
"Palazzi",
"María J.",
""
],
[
"Solé-Ribalta",
"Albert",
""
],
[
"Borge-Holthoefer",
"Javier",
""
],
[
"Tessone",
"Claudio J.",
""
]
] | Originally a speculative pattern in ecological networks, the hybrid or compound nested-modular pattern has been confirmed, during the last decade, as a relevant structural arrangement that emerges in a variety of contexts --in ecological mutualistic system and beyond. This implies shifting the focus from the measurement of nestedness as a global property (macro level), to the detection of blocks (meso level) that internally exhibit a high degree of nestedness. Unfortunately, the availability and understanding of the methods to properly detect in-block nested partitions lie behind the empirical findings: while a precise quality function of in-block nestedness has been proposed, we lack an understanding of its possible inherent constraints. Specifically, while it is well known that Newman-Girvan's modularity, and related quality functions, notoriously suffer from a resolution limit that impairs their ability to detect small blocks, the potential existence of resolution limits for in-block nestedness is unexplored. Here, we provide empirical, numerical and analytical evidence that the in-block nestedness function lacks a resolution limit, and thus our capacity to detect correct partitions in networks via its maximization depends solely on the accuracy of the optimization algorithms. |
1901.10803 | Tommaso Lorenzi | Mark A. J. Chaplain, Chiara Giverso, Tommaso Lorenzi, Luigi Preziosi | Derivation and application of effective interface conditions for
continuum mechanical models of cell invasion through thin membranes | null | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider a continuum mechanical model of cell invasion through thin
membranes. The model consists of a transmission problem for cell volume
fraction complemented with continuity of stresses and mass flux across the
surfaces of the membranes. We reduce the original problem to a limiting
transmission problem whereby each thin membrane is replaced by an effective
interface, and we develop a formal asymptotic method that enables the
derivation of a set of biophysically consistent transmission conditions to
close the limiting problem. The formal results obtained are validated via
numerical simulations showing that the relative error between the solutions to
the original transmission problem and the solutions to the limiting problem
vanishes when the thickness of the membranes tends to zero. In order to show
potential applications of our effective interface conditions, we employ the
limiting transmission problem to model cancer cell invasion through the
basement membrane and the metastatic spread of ovarian carcinoma.
| [
{
"created": "Fri, 18 Jan 2019 12:04:35 GMT",
"version": "v1"
},
{
"created": "Sat, 2 Feb 2019 17:42:18 GMT",
"version": "v2"
},
{
"created": "Fri, 5 Jul 2019 15:49:31 GMT",
"version": "v3"
},
{
"created": "Sun, 4 Aug 2019 12:20:11 GMT",
"version": "v4"
}
] | 2019-08-06 | [
[
"Chaplain",
"Mark A. J.",
""
],
[
"Giverso",
"Chiara",
""
],
[
"Lorenzi",
"Tommaso",
""
],
[
"Preziosi",
"Luigi",
""
]
] | We consider a continuum mechanical model of cell invasion through thin membranes. The model consists of a transmission problem for cell volume fraction complemented with continuity of stresses and mass flux across the surfaces of the membranes. We reduce the original problem to a limiting transmission problem whereby each thin membrane is replaced by an effective interface, and we develop a formal asymptotic method that enables the derivation of a set of biophysically consistent transmission conditions to close the limiting problem. The formal results obtained are validated via numerical simulations showing that the relative error between the solutions to the original transmission problem and the solutions to the limiting problem vanishes when the thickness of the membranes tends to zero. In order to show potential applications of our effective interface conditions, we employ the limiting transmission problem to model cancer cell invasion through the basement membrane and the metastatic spread of ovarian carcinoma. |
1407.8256 | Andrew Bruce Duncan | Andrew Duncan, Shuohao Liao, Tomas Vejchodsky, Radek Erban, Ramon
Grima | Noise-induced multistability in chemical systems: Discrete vs Continuum
modeling | 5 pages, 2 figures | null | 10.1103/PhysRevE.91.042111 | null | q-bio.QM q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The noisy dynamics of chemical systems is commonly studied using either the
chemical master equation (CME) or the chemical Fokker-Planck equation (CFPE).
The latter is a continuum approximation of the discrete CME approach. We here
show that the CFPE may fail to capture the CME's prediction of noise-induced
multistability. In particular we find a simple chemical system for which the
CME's marginal probability distribution changes from unimodal to multimodal as
the system-size decreases below a critical value, while the CFPE's marginal
probability distribution is unimodal for all physically meaningful system
sizes.
| [
{
"created": "Thu, 31 Jul 2014 01:53:10 GMT",
"version": "v1"
}
] | 2015-06-22 | [
[
"Duncan",
"Andrew",
""
],
[
"Liao",
"Shuohao",
""
],
[
"Vejchodsky",
"Tomas",
""
],
[
"Erban",
"Radek",
""
],
[
"Grima",
"Ramon",
""
]
] | The noisy dynamics of chemical systems is commonly studied using either the chemical master equation (CME) or the chemical Fokker-Planck equation (CFPE). The latter is a continuum approximation of the discrete CME approach. We here show that the CFPE may fail to capture the CME's prediction of noise-induced multistability. In particular we find a simple chemical system for which the CME's marginal probability distribution changes from unimodal to multimodal as the system-size decreases below a critical value, while the CFPE's marginal probability distribution is unimodal for all physically meaningful system sizes. |
2004.05129 | Youngmin Park | Youngmin Park and Thomas G. Fai | Dynamics of Vesicles Driven Into Closed Constrictions by Molecular
Motors | 34 pages, 9 figures | Bull. Math. Biol. 82, 141 (2020) | 10.1007/s11538-020-00820-0 | null | q-bio.CB q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the dynamics of a model of membrane vesicle transport into dendritic
spines, which are bulbous intracellular compartments in neurons driven by
molecular motors. We reduce the lubrication model proposed in [Fai et al.,
Active elastohydrodynamics of vesicles in narrow, blind constrictions. Phys.
Rev. Fluids, 2 (2017), 113601] to a fast-slow system, yielding an analytically
and numerically tractable equation equivalent to the original model in the
overdamped limit. The model's key parameters are the ratio of motors that
prefer to push toward the head of the dendritic spine to the ratio of motors
that prefer to push in the opposite direction. We perform a numerical
bifurcation analysis in these parameters and find that steady-state vesicle
velocities appear and disappear through several saddle-node bifurcations. This
process allows us to identify the region of parameter space in which multiple
stable velocities exist. We show by direct calculations that there can only be
unidirectional motion for sufficiently close vesicle-to-spine diameter ratios.
Our analysis predicts the critical vesicle-to-spine diameter ratio, at which
there is a transition from unidirectional to bidirectional motion, consistent
with experimental observations of vesicle trajectories in the literature.
| [
{
"created": "Fri, 10 Apr 2020 17:18:01 GMT",
"version": "v1"
},
{
"created": "Wed, 26 Aug 2020 00:33:04 GMT",
"version": "v2"
}
] | 2020-11-19 | [
[
"Park",
"Youngmin",
""
],
[
"Fai",
"Thomas G.",
""
]
] | We study the dynamics of a model of membrane vesicle transport into dendritic spines, which are bulbous intracellular compartments in neurons driven by molecular motors. We reduce the lubrication model proposed in [Fai et al., Active elastohydrodynamics of vesicles in narrow, blind constrictions. Phys. Rev. Fluids, 2 (2017), 113601] to a fast-slow system, yielding an analytically and numerically tractable equation equivalent to the original model in the overdamped limit. The model's key parameters are the ratio of motors that prefer to push toward the head of the dendritic spine to the ratio of motors that prefer to push in the opposite direction. We perform a numerical bifurcation analysis in these parameters and find that steady-state vesicle velocities appear and disappear through several saddle-node bifurcations. This process allows us to identify the region of parameter space in which multiple stable velocities exist. We show by direct calculations that there can only be unidirectional motion for sufficiently close vesicle-to-spine diameter ratios. Our analysis predicts the critical vesicle-to-spine diameter ratio, at which there is a transition from unidirectional to bidirectional motion, consistent with experimental observations of vesicle trajectories in the literature. |
1705.04603 | Mara Scussolini | Mara Scussolini, Sara Garbarino, Gianmario Sambuceti, Giacomo Caviglia
and Michele Piana | Parametric Imaging of FDG-PET Data Using Physiology and Iterative
Regularization: Application to the Hepatic and Renal Systems | arXiv admin note: substantial text overlap with arXiv:1702.06067 | null | null | null | q-bio.TO math.NA q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The present paper proposes a novel computational method for parametric
imaging of nuclear medicine data. The mathematical procedure is general enough
to work for compartmental models of diverse complexity and is effective in the
determination of the parametric maps of all kinetic parameters governing tracer
flow. We consider applications to [18F]-fluorodeoxyglucose Positron Emission
Tomography (FDG-PET) data and analyze the two-compartment catenary model
describing the standard FDG metabolization by an homogeneous tissue, e.g. the
liver, and the three-compartment non-catenary model representing the renal
physiology. The proposed imaging method starts from the reconstructed FDG-PET
images of tracer concentration and preliminarily applies image processing
algorithms for noise reduction and image segmentation processes for selecting
the region enclosing the organ of physiologic interest. The optimization scheme
solves pixelwise the non-linear inverse problem of determining the kinetic
parameters from dynamic concentration data through a Gauss-Newton iterative
algorithm with a penalty term accounting for the ill-posedness of the problem.
We tested our imaging approach on FDG-PET data of murine models obtained by
means of a dedicated microPET system, and we analyzed different PET slices
containing axial sections of the liver and axial sections of the kidneys. The
reconstructed parametric images proved to be reliable and qualitatively
effective in the description of the local FDG metabolism with respect to the
different physiologies.
| [
{
"created": "Thu, 11 May 2017 15:51:47 GMT",
"version": "v1"
}
] | 2017-05-15 | [
[
"Scussolini",
"Mara",
""
],
[
"Garbarino",
"Sara",
""
],
[
"Sambuceti",
"Gianmario",
""
],
[
"Caviglia",
"Giacomo",
""
],
[
"Piana",
"Michele",
""
]
] | The present paper proposes a novel computational method for parametric imaging of nuclear medicine data. The mathematical procedure is general enough to work for compartmental models of diverse complexity and is effective in the determination of the parametric maps of all kinetic parameters governing tracer flow. We consider applications to [18F]-fluorodeoxyglucose Positron Emission Tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue, e.g. the liver, and the three-compartment non-catenary model representing the renal physiology. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation processes for selecting the region enclosing the organ of physiologic interest. The optimization scheme solves pixelwise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a Gauss-Newton iterative algorithm with a penalty term accounting for the ill-posedness of the problem. We tested our imaging approach on FDG-PET data of murine models obtained by means of a dedicated microPET system, and we analyzed different PET slices containing axial sections of the liver and axial sections of the kidneys. The reconstructed parametric images proved to be reliable and qualitatively effective in the description of the local FDG metabolism with respect to the different physiologies. |
0906.5550 | Baruch Meerson | Baruch Meerson and Pavel V. Sasorov | WKB theory of epidemic fade-out in stochastic populations | 4 pages, 4 figures | Phys. Rev. E 80, 041130 (2009) | 10.1103/PhysRevE.80.041130 | null | q-bio.PE cond-mat.stat-mech | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Stochastic effects may cause fade-out of an infectious disease in a
population immediately after an epidemic outbreak. We develop WKB theory to
determine the most probable path of the system toward epidemic fade-out and to
evaluate the fade-out probability. The most probable path is an instanton-like
orbit in the phase space of the underlying Hamiltonian flow.
| [
{
"created": "Tue, 30 Jun 2009 14:49:00 GMT",
"version": "v1"
},
{
"created": "Wed, 16 Sep 2009 12:33:53 GMT",
"version": "v2"
}
] | 2015-05-13 | [
[
"Meerson",
"Baruch",
""
],
[
"Sasorov",
"Pavel V.",
""
]
] | Stochastic effects may cause fade-out of an infectious disease in a population immediately after an epidemic outbreak. We develop WKB theory to determine the most probable path of the system toward epidemic fade-out and to evaluate the fade-out probability. The most probable path is an instanton-like orbit in the phase space of the underlying Hamiltonian flow. |
2203.13138 | Ngoc Pham | D.T. Pham, Z.E. Musielak | Lagrangian Formalism in Biology: I. Standard Lagrangians and their Role
in Population Dynamics | 17 pages, 1 table | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | The Lagrangian formalism is developed for the population dynamics of
interacting species that are described by several well-known models. The
formalism is based on standard Lagrangians, which represent differences between
the physical kinetic and potential energy-like terms. A method to derive these
Lagrangians is presented and applied to selected theoretical models of the
population dynamics. The role of the derived Lagrangians and the energy-like
terms in the population dynamics is investigated and discussed. It is suggested
that the obtained standard Lagrangians can be used to identify physical
similarities between different population models.
| [
{
"created": "Thu, 24 Mar 2022 15:51:59 GMT",
"version": "v1"
}
] | 2022-03-25 | [
[
"Pham",
"D. T.",
""
],
[
"Musielak",
"Z. E.",
""
]
] | The Lagrangian formalism is developed for the population dynamics of interacting species that are described by several well-known models. The formalism is based on standard Lagrangians, which represent differences between the physical kinetic and potential energy-like terms. A method to derive these Lagrangians is presented and applied to selected theoretical models of the population dynamics. The role of the derived Lagrangians and the energy-like terms in the population dynamics is investigated and discussed. It is suggested that the obtained standard Lagrangians can be used to identify physical similarities between different population models. |
1111.1256 | Marvin Chester | Marvin Chester | A Law of Nature? | Revised equation-numbering to correspond to published version | Open Journal of Ecology 1, 77-84 (2011) | 10.4236/oje.2011.13011 | null | q-bio.PE physics.bio-ph q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Is there an overriding principle of nature, hitherto overlooked, that governs
all population behavior? A single principle that drives all the regimes
observed in nature - exponential-like growth, saturated growth, population
decline, population extinction, oscillatory behavior? In current orthodox
population theory, this diverse range of population behaviors is described by
many different equations - each with its own specific justification. The
signature of an overriding principle would be a differential equation which, in
a single statement, embraces all the panoply of regimes. A candidate such
governing equation is proposed. The principle from which the equation is
derived is this: The effect on the environment of a population's success is to
alter that environment in a way that opposes the success.
| [
{
"created": "Fri, 4 Nov 2011 21:27:14 GMT",
"version": "v1"
},
{
"created": "Thu, 26 Jan 2012 00:41:58 GMT",
"version": "v2"
}
] | 2012-03-01 | [
[
"Chester",
"Marvin",
""
]
] | Is there an overriding principle of nature, hitherto overlooked, that governs all population behavior? A single principle that drives all the regimes observed in nature - exponential-like growth, saturated growth, population decline, population extinction, oscillatory behavior? In current orthodox population theory, this diverse range of population behaviors is described by many different equations - each with its own specific justification. The signature of an overriding principle would be a differential equation which, in a single statement, embraces all the panoply of regimes. A candidate such governing equation is proposed. The principle from which the equation is derived is this: The effect on the environment of a population's success is to alter that environment in a way that opposes the success. |
1409.7942 | Jose Acebal Dr | L. S. Barsante, K. S. Paix\~ao, K. H. Laass, R. T. N. Cardoso, \'A. E.
Eiras, J. L. Acebal | A model to predict the population size of the dengue fever vector based
on rainfall data | 21 pages, 8 figures. Submitted to Mathematical Biosciences Journal | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | According to the World Health Organization, dengue fever is the most
important mosquito-borne disease of humans, and it is currently estimated that
there may be 50 - 100 million yearly dengue infections worldwide. For the
purpose to provide new techniques to public health policies in course, we
introduce a predictive non-linear population dynamics model to describe the
population size of four stages of the development of \emph{Aedes aegypti},
having the coefficients set to be dependent on the rainfall index data. In
spite of the population dynamics of the \emph{Ae. aegypti} be mainly ruled by
the rainfall regime, most models are dedicated exclusively to effects of
temperature and only few models are dedicated to influence of rainfall. Vector
control actions are also implemented in many periods of the year in order to
compare relative efficiency of public health policies. The analysis of
equilibrium and stability was performed. Field rainfall time series data from
the City of Lavras (Minas Gerais, Brazil) was used for the model evaluation.
The model was validated in a comparison with experimental mosquito abundance
data acquired by field health agents. We evaluated and validated an
entomological conjecture that claims that control actions should be performed
during the dry season, instead of the common procedure adopted by vector
control programs, in which those are mainly applied in the rainy season.
| [
{
"created": "Sun, 28 Sep 2014 18:48:27 GMT",
"version": "v1"
}
] | 2016-08-10 | [
[
"Barsante",
"L. S.",
""
],
[
"Paixão",
"K. S.",
""
],
[
"Laass",
"K. H.",
""
],
[
"Cardoso",
"R. T. N.",
""
],
[
"Eiras",
"Á. E.",
""
],
[
"Acebal",
"J. L.",
""
]
] | According to the World Health Organization, dengue fever is the most important mosquito-borne disease of humans, and it is currently estimated that there may be 50 - 100 million yearly dengue infections worldwide. For the purpose to provide new techniques to public health policies in course, we introduce a predictive non-linear population dynamics model to describe the population size of four stages of the development of \emph{Aedes aegypti}, having the coefficients set to be dependent on the rainfall index data. In spite of the population dynamics of the \emph{Ae. aegypti} be mainly ruled by the rainfall regime, most models are dedicated exclusively to effects of temperature and only few models are dedicated to influence of rainfall. Vector control actions are also implemented in many periods of the year in order to compare relative efficiency of public health policies. The analysis of equilibrium and stability was performed. Field rainfall time series data from the City of Lavras (Minas Gerais, Brazil) was used for the model evaluation. The model was validated in a comparison with experimental mosquito abundance data acquired by field health agents. We evaluated and validated an entomological conjecture that claims that control actions should be performed during the dry season, instead of the common procedure adopted by vector control programs, in which those are mainly applied in the rainy season. |
1210.3062 | Michael Courtney | Joshua Courtney, Taylor Klinkmann, Joseph Torano,2 and Michael
Courtney | Weight-Length Relationships in Gafftopsail Catfish (Bagre marinus) and
Hardhead Catfish (Ariopsis felis) in Louisiana Waters | Two figures, five pages | null | null | null | q-bio.PE q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In spite of the abundance and commercial importance of these two species,
there is little published weight-length data for the gafftopsail catfish (Bagre
marinus) and hardhead catfish (Ariopsis felis). For this study 84 catfish were
caught (hook and line) from the Calcasieu Estuary in Southwest Louisiana near
the Gulf of Mexico and estuaries and near shore waters close to bayou
Lafourche. Using least squares regression, best fit curves were determined for
weight (W) vs. total length (L) relationships in gafftopsail catfish, W(L) =
1000(L/484.73)^3.2660, while the best-fit equation for the hardhead was W(L) =
1000(L/469.53)^3.0188, where W is the weight in grams and L is the total length
in millimeters. Results showed that, when compared to gafftopsail and hardhead
catfish caught in Florida, Louisiana gafftopsail catfish tend to weigh less at
similar lengths; whereas, the Louisiana hardhead catfish tend to weigh about
the same. Results also show that the total length (TL) can be related to the
fork length (FL) as TL = 1.184 FL in gafftopsail catfish with R^2 = 0.9922 and
TL = 1.140 FL with R^2 = 0.9667 in hardhead catfish.
| [
{
"created": "Wed, 10 Oct 2012 21:04:34 GMT",
"version": "v1"
}
] | 2012-10-12 | [
[
"Courtney",
"Joshua",
""
],
[
"Klinkmann",
"Taylor",
""
],
[
"Torano",
"Joseph",
""
],
[
"2",
"",
""
],
[
"Courtney",
"Michael",
""
]
] | In spite of the abundance and commercial importance of these two species, there is little published weight-length data for the gafftopsail catfish (Bagre marinus) and hardhead catfish (Ariopsis felis). For this study 84 catfish were caught (hook and line) from the Calcasieu Estuary in Southwest Louisiana near the Gulf of Mexico and estuaries and near shore waters close to bayou Lafourche. Using least squares regression, best fit curves were determined for weight (W) vs. total length (L) relationships in gafftopsail catfish, W(L) = 1000(L/484.73)^3.2660, while the best-fit equation for the hardhead was W(L) = 1000(L/469.53)^3.0188, where W is the weight in grams and L is the total length in millimeters. Results showed that, when compared to gafftopsail and hardhead catfish caught in Florida, Louisiana gafftopsail catfish tend to weigh less at similar lengths; whereas, the Louisiana hardhead catfish tend to weigh about the same. Results also show that the total length (TL) can be related to the fork length (FL) as TL = 1.184 FL in gafftopsail catfish with R^2 = 0.9922 and TL = 1.140 FL with R^2 = 0.9667 in hardhead catfish. |
2103.00399 | Lin Yang | Jiacheng Li, Chengyu Hou, Menghao Wang, Chencheng Liao, Shuai Guo,
Liping Shi, Xiaoliang Ma, Hongchi Zhang, Shenda Jiang, Bing Zheng, Lin Ye,
Lin Yang, Xiaodong He | Hydrophobic interaction determines docking affinity of SARS CoV 2
variants with antibodies | arXiv admin note: substantial text overlap with arXiv:2008.11883 | null | null | null | q-bio.BM | http://creativecommons.org/licenses/by/4.0/ | Preliminary epidemiologic, phylogenetic and clinical findings suggest that
several novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
variants have increased transmissibility and decreased efficacy of several
existing vaccines. Four mutations in the receptor-binding domain (RBD) of the
spike protein that are reported to contribute to increased transmission.
Understanding physical mechanism responsible for the affinity enhancement
between the SARS-CoV-2 variants and ACE2 is the "urgent challenge" for
developing blockers, vaccines and therapeutic antibodies against the
coronavirus disease 2019 (COVID-19) pandemic. Based on a
hydrophobic-interaction-based protein docking mechanism, this study reveals
that the mutation N501Y obviously increased the hydrophobic attraction and
decrease hydrophilic repulsion between the RBD and ACE2 that most likely caused
the transmissibility increment of the variants. By analyzing the
mutation-induced hydrophobic surface changes in the attraction and repulsion at
the binding site of the complexes of the SARS-CoV-2 variants and antibodies, we
found out that all the mutations of N501Y, E484K, K417N and L452R can
selectively decrease or increase their binding affinity with some antibodies.
| [
{
"created": "Sun, 28 Feb 2021 05:26:24 GMT",
"version": "v1"
}
] | 2021-03-02 | [
[
"Li",
"Jiacheng",
""
],
[
"Hou",
"Chengyu",
""
],
[
"Wang",
"Menghao",
""
],
[
"Liao",
"Chencheng",
""
],
[
"Guo",
"Shuai",
""
],
[
"Shi",
"Liping",
""
],
[
"Ma",
"Xiaoliang",
""
],
[
"Zhang",
"... | Preliminary epidemiologic, phylogenetic and clinical findings suggest that several novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have increased transmissibility and decreased efficacy of several existing vaccines. Four mutations in the receptor-binding domain (RBD) of the spike protein that are reported to contribute to increased transmission. Understanding physical mechanism responsible for the affinity enhancement between the SARS-CoV-2 variants and ACE2 is the "urgent challenge" for developing blockers, vaccines and therapeutic antibodies against the coronavirus disease 2019 (COVID-19) pandemic. Based on a hydrophobic-interaction-based protein docking mechanism, this study reveals that the mutation N501Y obviously increased the hydrophobic attraction and decrease hydrophilic repulsion between the RBD and ACE2 that most likely caused the transmissibility increment of the variants. By analyzing the mutation-induced hydrophobic surface changes in the attraction and repulsion at the binding site of the complexes of the SARS-CoV-2 variants and antibodies, we found out that all the mutations of N501Y, E484K, K417N and L452R can selectively decrease or increase their binding affinity with some antibodies. |
2001.08028 | Lancelot Da Costa | Lancelot Da Costa, Thomas Parr, Biswa Sengupta, Karl Friston | Neural dynamics under active inference: plausibility and efficiency of
information processing | 12 pages, 3 figures | Entropy 2021 | 10.3390/e23040454 | null | q-bio.NC q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Active inference is a normative framework for explaining behaviour under the
free energy principle -- a theory of self-organisation originating in
neuroscience. It specifies neuronal dynamics for state-estimation in terms of a
descent on (variational) free energy -- a measure of the fit between an
internal (generative) model and sensory observations. The free energy gradient
is a prediction error -- plausibly encoded in the average membrane potentials
of neuronal populations. Conversely, the expected probability of a state can be
expressed in terms of neuronal firing rates. We show that this is consistent
with current models of neuronal dynamics and establish face validity by
synthesising plausible electrophysiological responses. We then show that these
neuronal dynamics approximate natural gradient descent, a well-known
optimisation algorithm from information geometry that follows the steepest
descent of the objective in information space. We compare the information
length of belief updating in both schemes, a measure of the distance traveled
in information space that has a direct interpretation in terms of metabolic
cost. We show that neural dynamics under active inference are metabolically
efficient and suggest that neural representations in biological agents may
evolve by approximating steepest descent in information space towards the point
of optimal inference.
| [
{
"created": "Wed, 22 Jan 2020 14:15:05 GMT",
"version": "v1"
},
{
"created": "Sun, 31 Jan 2021 19:29:43 GMT",
"version": "v2"
}
] | 2021-10-26 | [
[
"Da Costa",
"Lancelot",
""
],
[
"Parr",
"Thomas",
""
],
[
"Sengupta",
"Biswa",
""
],
[
"Friston",
"Karl",
""
]
] | Active inference is a normative framework for explaining behaviour under the free energy principle -- a theory of self-organisation originating in neuroscience. It specifies neuronal dynamics for state-estimation in terms of a descent on (variational) free energy -- a measure of the fit between an internal (generative) model and sensory observations. The free energy gradient is a prediction error -- plausibly encoded in the average membrane potentials of neuronal populations. Conversely, the expected probability of a state can be expressed in terms of neuronal firing rates. We show that this is consistent with current models of neuronal dynamics and establish face validity by synthesising plausible electrophysiological responses. We then show that these neuronal dynamics approximate natural gradient descent, a well-known optimisation algorithm from information geometry that follows the steepest descent of the objective in information space. We compare the information length of belief updating in both schemes, a measure of the distance traveled in information space that has a direct interpretation in terms of metabolic cost. We show that neural dynamics under active inference are metabolically efficient and suggest that neural representations in biological agents may evolve by approximating steepest descent in information space towards the point of optimal inference. |
q-bio/0503031 | Gabriele Scheler | Gabriele Scheler | Extracellular-to-intracellular signal transfer via G-proteins | 4 pages, submitted to IEEE Biocomputing | null | null | null | q-bio.MN q-bio.NC | null | We look at the problem of signal transduction by extracellular agonist
binding to a receptor protein at the membrane (sensor) via binding of
G-proteins (effectors) to a highly integrative target molecule, such as the
second messenger cAMP (target). We explore the effects of binding times,
effector assignment and effector pool size on the shape of the output signal
under different input scenarios. We conclude that low rates of information
transfer may sometimes coincide with a high probability or efficiency of
plasticity induction.
| [
{
"created": "Mon, 21 Mar 2005 20:09:10 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Scheler",
"Gabriele",
""
]
] | We look at the problem of signal transduction by extracellular agonist binding to a receptor protein at the membrane (sensor) via binding of G-proteins (effectors) to a highly integrative target molecule, such as the second messenger cAMP (target). We explore the effects of binding times, effector assignment and effector pool size on the shape of the output signal under different input scenarios. We conclude that low rates of information transfer may sometimes coincide with a high probability or efficiency of plasticity induction. |
0706.1330 | Mensur Omerbashich | M. Omerbashich | Note on: Considering the Case for Biodiversity Cycles: Reexamining the
Evidence for Periodicity in the Fossil Record, by Lieberman and Melott, arXiv
preprint 0704.2896 | A one-page note. For the supplementary information for this note,
including the cited Reply and Errata, see math-ph/0608014 | null | null | null | q-bio.PE astro-ph physics.geo-ph | null | Lieberman and Melott built their recent arXiv preprint 0704.2896 on my
published paper and (a preprint of) a subsequent comment by Liebermans
associate Cornette. But had this group waited for the Cornette comment to
actually appear in print together with the expected Reply, they would have
learned that his comment exposes Cornettes confusion that likely was due to
journal misprint of my figure. Thus 0704.2896 is baseless. Despite receiving
the extended Reply with Errata, these authors still fail to recognize that
detrending of paleontological records-which they erroneously promote as a
must-is an arbitrary rather than a universal operation.
| [
{
"created": "Sat, 9 Jun 2007 23:19:27 GMT",
"version": "v1"
}
] | 2007-06-12 | [
[
"Omerbashich",
"M.",
""
]
] | Lieberman and Melott built their recent arXiv preprint 0704.2896 on my published paper and (a preprint of) a subsequent comment by Liebermans associate Cornette. But had this group waited for the Cornette comment to actually appear in print together with the expected Reply, they would have learned that his comment exposes Cornettes confusion that likely was due to journal misprint of my figure. Thus 0704.2896 is baseless. Despite receiving the extended Reply with Errata, these authors still fail to recognize that detrending of paleontological records-which they erroneously promote as a must-is an arbitrary rather than a universal operation. |
2302.01337 | Ali Firooz | Ali Firooz, Avery T. Funkhouser, Julie C. Martin, W. Jeffery
Edenfield, Homayoun Valafar, and Anna V. Blenda | Comprehensive and user-analytics-friendly cancer patient database for
physicians and researchers | 7 pages, 12 figures, peer reviewed and accepted in "International
Conference on Computational Science and Computational Intelligence (CSCI 22)" | Proceedings of the 2022 International Conference on Computational
Science and Computational Intelligence (CSCI) | 10.1109/CSCI58124.2022.00289 | null | q-bio.QM cs.CY | http://creativecommons.org/licenses/by/4.0/ | Nuanced cancer patient care is needed, as the development and clinical course
of cancer is multifactorial with influences from the general health status of
the patient, germline and neoplastic mutations, co-morbidities, and
environment. To effectively tailor an individualized treatment to each patient,
such multifactorial data must be presented to providers in an easy-to-access
and easy-to-analyze fashion. To address the need, a relational database has
been developed integrating status of cancer-critical gene mutations, serum
galectin profiles, serum and tumor glycomic profiles, with clinical,
demographic, and lifestyle data points of individual cancer patients. The
database, as a backend, provides physicians and researchers with a single,
easily accessible repository of cancer profiling data to aid-in and enhance
individualized treatment. Our interactive database allows care providers to
amalgamate cohorts from these groups to find correlations between different
data types with the possibility of finding "molecular signatures" based upon a
combination of genetic mutations, galectin serum levels, glycan compositions,
and patient clinical data and lifestyle choices. Our project provides a
framework for an integrated, interactive, and growing database to analyze
molecular and clinical patterns across cancer stages and subtypes and provides
opportunities for increased diagnostic and prognostic power.
| [
{
"created": "Wed, 1 Feb 2023 20:10:06 GMT",
"version": "v1"
}
] | 2023-09-26 | [
[
"Firooz",
"Ali",
""
],
[
"Funkhouser",
"Avery T.",
""
],
[
"Martin",
"Julie C.",
""
],
[
"Edenfield",
"W. Jeffery",
""
],
[
"Valafar",
"Homayoun",
""
],
[
"Blenda",
"Anna V.",
""
]
] | Nuanced cancer patient care is needed, as the development and clinical course of cancer is multifactorial with influences from the general health status of the patient, germline and neoplastic mutations, co-morbidities, and environment. To effectively tailor an individualized treatment to each patient, such multifactorial data must be presented to providers in an easy-to-access and easy-to-analyze fashion. To address the need, a relational database has been developed integrating status of cancer-critical gene mutations, serum galectin profiles, serum and tumor glycomic profiles, with clinical, demographic, and lifestyle data points of individual cancer patients. The database, as a backend, provides physicians and researchers with a single, easily accessible repository of cancer profiling data to aid-in and enhance individualized treatment. Our interactive database allows care providers to amalgamate cohorts from these groups to find correlations between different data types with the possibility of finding "molecular signatures" based upon a combination of genetic mutations, galectin serum levels, glycan compositions, and patient clinical data and lifestyle choices. Our project provides a framework for an integrated, interactive, and growing database to analyze molecular and clinical patterns across cancer stages and subtypes and provides opportunities for increased diagnostic and prognostic power. |
1212.5619 | Martin Nawrot | Anneke Meyer, Giovanni Galizia, Martin P. Nawrot | Odor response features of projection neurons and local interneurons in
the honeybee antennal lobe | 9 pages, 3 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Local computation in microcircuits is an essential feature of distributed
information processing in vertebrate and invertebrate brains. The insect
antennal lobe represents a spatially confined local network that processes
high-dimensional and redundant peripheral input to compute an efficient odor
code. Social insects can rely on a particularly rich olfactory receptor
repertoire and they exhibit complex odor-guided behaviors. This corresponds
with a high anatomical complexity of their AL network. In the honeybee, a large
number of glomeruli that receive sensory input are interconnected by a dense
network of local interneurons (LNs). Uniglomerular projection neurons (PNs)
integrate sensory and recurrent network input into an efficient spatio-temporal
odor code. To investigate the specific computational roles of LNs and PNs we
measured eleven features of sub- and suprathreshold single cell responses to in
vivo odor stimulation. Using a semi-supervised cluster analysis we identified a
combination of five characteristic features that enabled the accurate
separation of morphologically identified LNs and PNs. The two clusters differed
significantly in all five features. In the absence of stimulation PNs showed a
higher subthreshold activation, assumed higher peak response rates and more
regular spiking pattern. LNs reacted considerably faster to the onset of a
stimulus and their responses were more reliable across stimulus repetitions. We
discuss possible mechanisms that can explain our results, and we interpret
cell-type specific characteristics with respect to their functional relevance.
| [
{
"created": "Fri, 21 Dec 2012 22:09:04 GMT",
"version": "v1"
}
] | 2012-12-27 | [
[
"Meyer",
"Anneke",
""
],
[
"Galizia",
"Giovanni",
""
],
[
"Nawrot",
"Martin P.",
""
]
] | Local computation in microcircuits is an essential feature of distributed information processing in vertebrate and invertebrate brains. The insect antennal lobe represents a spatially confined local network that processes high-dimensional and redundant peripheral input to compute an efficient odor code. Social insects can rely on a particularly rich olfactory receptor repertoire and they exhibit complex odor-guided behaviors. This corresponds with a high anatomical complexity of their AL network. In the honeybee, a large number of glomeruli that receive sensory input are interconnected by a dense network of local interneurons (LNs). Uniglomerular projection neurons (PNs) integrate sensory and recurrent network input into an efficient spatio-temporal odor code. To investigate the specific computational roles of LNs and PNs we measured eleven features of sub- and suprathreshold single cell responses to in vivo odor stimulation. Using a semi-supervised cluster analysis we identified a combination of five characteristic features that enabled the accurate separation of morphologically identified LNs and PNs. The two clusters differed significantly in all five features. In the absence of stimulation PNs showed a higher subthreshold activation, assumed higher peak response rates and more regular spiking pattern. LNs reacted considerably faster to the onset of a stimulus and their responses were more reliable across stimulus repetitions. We discuss possible mechanisms that can explain our results, and we interpret cell-type specific characteristics with respect to their functional relevance. |
0811.2189 | Michael Gudo | Michael Gudo, Tareq Syed | 100 Years of Deuterostomia (Grobben, 1908): Cladogenetic and Anagenetic
Relations within the Notoneuralia Domain | 14 pages, 8 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Results from molecular systematics and comparative developmental genetics
changed the picture of metazoan and especially bilaterian radiation. According
to this new animal phylogeny (introduced by Adoutte et al. 1999/2000), Grobbens
(1908) widely favoured protostome-deuterostome division of the Bilateria can be
upheld, but only with major rearrangements within these superphyla. On the
cladogenetic level, the Protostomia are split into two unexpected subgroups,
the Lophotrochozoa and Ecdysozoa. The deuterostomes are split into the
subgroups Chordata and Ambulacraria, which is not novel since Grobben (1908)
introduced the Deuterostomia in this way (together with the Chaetognatha as a
third line). However, many details of the new deuterostome phylogeny do not fit
traditional, morphology-based reconstructions. As a consequence, three
relatively unexpected proposals for early deuterostome evolution are favoured
today: An ambulacraria-scenario, a xenoturbellid-scenario, and a
chordate-scenario. The first two proposals are often discussed in the
literature, while the chordate-scenario is almost completely neglected.
Therefore, the paper presented focuses on the chordate scenario, i.e. the
hypothesis of an acrania-like ur-deuterostomian. It is argued that the
acrania-hypothesis is clearly preferable when biomechanic options of a
polysegmented, hydroskeletal body plan are taken into account. The so called
hydroskeleton hypothesis, rooted in the work of W. F. Gutmann, is the most
detailed anagenetic scenario which depicts an acrania-like ur-deuterostome.
| [
{
"created": "Thu, 13 Nov 2008 18:19:09 GMT",
"version": "v1"
}
] | 2008-11-14 | [
[
"Gudo",
"Michael",
""
],
[
"Syed",
"Tareq",
""
]
] | Results from molecular systematics and comparative developmental genetics changed the picture of metazoan and especially bilaterian radiation. According to this new animal phylogeny (introduced by Adoutte et al. 1999/2000), Grobbens (1908) widely favoured protostome-deuterostome division of the Bilateria can be upheld, but only with major rearrangements within these superphyla. On the cladogenetic level, the Protostomia are split into two unexpected subgroups, the Lophotrochozoa and Ecdysozoa. The deuterostomes are split into the subgroups Chordata and Ambulacraria, which is not novel since Grobben (1908) introduced the Deuterostomia in this way (together with the Chaetognatha as a third line). However, many details of the new deuterostome phylogeny do not fit traditional, morphology-based reconstructions. As a consequence, three relatively unexpected proposals for early deuterostome evolution are favoured today: An ambulacraria-scenario, a xenoturbellid-scenario, and a chordate-scenario. The first two proposals are often discussed in the literature, while the chordate-scenario is almost completely neglected. Therefore, the paper presented focuses on the chordate scenario, i.e. the hypothesis of an acrania-like ur-deuterostomian. It is argued that the acrania-hypothesis is clearly preferable when biomechanic options of a polysegmented, hydroskeletal body plan are taken into account. The so called hydroskeleton hypothesis, rooted in the work of W. F. Gutmann, is the most detailed anagenetic scenario which depicts an acrania-like ur-deuterostome. |
1308.4433 | Andrew Bordner | Andrew J. Bordner and Barry Zorman | Predicting non-neutral missense mutations and their biochemical
consequences using genome-scale homology modeling of human protein complexes | 40 pages, 9 figures | null | null | null | q-bio.BM q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Computational methods are needed to differentiate the small fraction of
missense mutations that contribute to disease by disrupting protein function
from neutral variants. We describe several complementary methods using
large-scale homology modeling of human protein complexes to detect non-neutral
mutations. Importantly, unlike sequence conservation-based methods, this
structure-based approach provides experimentally testable biochemical
mechanisms for mutations in disease. Specifically, we infer metal ion, small
molecule, protein-protein, and nucleic acid binding sites by homology and find
that disease-associated missense mutations are more prevalent in each class of
binding site than are neutral mutations. Importantly, our approach identifies
considerably more binding sites than those annotated in the RefSeq database.
Furthermore, an analysis of metal ion and protein-protein binding sites
predicted by machine learning shows a similar preponderance of
disease-associated mutations in these sites. We also derive a statistical score
for predicting how mutations affect metal ion binding and find many dbSNP
mutations that likely disrupt ion binding but were not previously considered
deleterious. We also cluster mutations in the protein structure to discover
putative functional regions. Finally, we develop a machine learning predictor
for detecting disease-associated missense mutations and show that it
outperforms two other prediction methods on an independent test set.
| [
{
"created": "Tue, 20 Aug 2013 21:12:13 GMT",
"version": "v1"
}
] | 2013-08-22 | [
[
"Bordner",
"Andrew J.",
""
],
[
"Zorman",
"Barry",
""
]
] | Computational methods are needed to differentiate the small fraction of missense mutations that contribute to disease by disrupting protein function from neutral variants. We describe several complementary methods using large-scale homology modeling of human protein complexes to detect non-neutral mutations. Importantly, unlike sequence conservation-based methods, this structure-based approach provides experimentally testable biochemical mechanisms for mutations in disease. Specifically, we infer metal ion, small molecule, protein-protein, and nucleic acid binding sites by homology and find that disease-associated missense mutations are more prevalent in each class of binding site than are neutral mutations. Importantly, our approach identifies considerably more binding sites than those annotated in the RefSeq database. Furthermore, an analysis of metal ion and protein-protein binding sites predicted by machine learning shows a similar preponderance of disease-associated mutations in these sites. We also derive a statistical score for predicting how mutations affect metal ion binding and find many dbSNP mutations that likely disrupt ion binding but were not previously considered deleterious. We also cluster mutations in the protein structure to discover putative functional regions. Finally, we develop a machine learning predictor for detecting disease-associated missense mutations and show that it outperforms two other prediction methods on an independent test set. |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.