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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1308.5850 | Roland Langrock | Roland Langrock, J. Grant C. Hopcraft, Paul G. Blackwell, Victoria
Goodall, Ruth King, Mu Niu, Toby A. Patterson, Martin W. Pedersen, Anna
Skarin, Robert S. Schick | Modelling group dynamic animal movement | null | Methods in Ecology and Evolution, 2014, Vol. 5, Issue 2, pages
190-199 | 10.1111/2041-210X.12155 | null | q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Group dynamic movement is a fundamental aspect of many species' movements.
The need to adequately model individuals' interactions with other group members
has been recognised, particularly in order to differentiate the role of social
forces in individual movement from environmental factors. However, to date,
practical statistical methods which can include group dynamics in animal
movement models have been lacking. We consider a flexible modelling framework
that distinguishes a group-level model, describing the movement of the group's
centre, and an individual-level model, such that each individual makes its
movement decisions relative to the group centroid. The basic idea is framed
within the flexible class of hidden Markov models, extending previous work on
modelling animal movement by means of multi-state random walks. While in
simulation experiments parameter estimators exhibit some bias in non-ideal
scenarios, we show that generally the estimation of models of this type is both
feasible and ecologically informative. We illustrate the approach using real
movement data from 11 reindeer (Rangifer tarandus). Results indicate a
directional bias towards a group centroid for reindeer in an encamped state.
Though the attraction to the group centroid is relatively weak, our model
successfully captures group-influenced movement dynamics. Specifically, as
compared to a regular mixture of correlated random walks, the group dynamic
model more accurately predicts the non-diffusive behaviour of a cohesive mobile
group.
| [
{
"created": "Tue, 27 Aug 2013 12:52:33 GMT",
"version": "v1"
}
] | 2015-05-21 | [
[
"Langrock",
"Roland",
""
],
[
"Hopcraft",
"J. Grant C.",
""
],
[
"Blackwell",
"Paul G.",
""
],
[
"Goodall",
"Victoria",
""
],
[
"King",
"Ruth",
""
],
[
"Niu",
"Mu",
""
],
[
"Patterson",
"Toby A.",
""
],
[
"Pedersen",
"Martin W.",
""
],
[
"Skarin",
"Anna",
""
],
[
"Schick",
"Robert S.",
""
]
] | Group dynamic movement is a fundamental aspect of many species' movements. The need to adequately model individuals' interactions with other group members has been recognised, particularly in order to differentiate the role of social forces in individual movement from environmental factors. However, to date, practical statistical methods which can include group dynamics in animal movement models have been lacking. We consider a flexible modelling framework that distinguishes a group-level model, describing the movement of the group's centre, and an individual-level model, such that each individual makes its movement decisions relative to the group centroid. The basic idea is framed within the flexible class of hidden Markov models, extending previous work on modelling animal movement by means of multi-state random walks. While in simulation experiments parameter estimators exhibit some bias in non-ideal scenarios, we show that generally the estimation of models of this type is both feasible and ecologically informative. We illustrate the approach using real movement data from 11 reindeer (Rangifer tarandus). Results indicate a directional bias towards a group centroid for reindeer in an encamped state. Though the attraction to the group centroid is relatively weak, our model successfully captures group-influenced movement dynamics. Specifically, as compared to a regular mixture of correlated random walks, the group dynamic model more accurately predicts the non-diffusive behaviour of a cohesive mobile group. |
1908.08482 | Christian Quirouette | Christian Quirouette, Nada P. Younis, Micaela B. Reddy, Catherine A.A.
Beauchemin | A mathematical model describing the localization and spread of influenza
A virus infection within the human respiratory tract | 27 pages, 11 figures, 2 supplementary videos | PLoS Comput Biol. 2020 Apr 13;16(4):e1007705 | 10.1371/journal.pcbi.1007705 | RIKEN-iTHEMS-Report-19 | q-bio.CB q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Within the human respiratory tract (HRT), viruses diffuse through the
periciliary fluid (PCF) bathing the epithelium, and travel upwards via
advection towards the nose and mouth, as the mucus escalator entrains the PCF.
While many mathematical models (MMs) to date have described the course of
influenza A virus (IAV) infections in vivo, none have considered the impact of
both diffusion and advection on the kinetics and localization of the infection.
The MM herein represents the HRT as a one-dimensional track extending from the
nose down to a depth of 30 cm, wherein stationary cells interact with the
concentration of IAV which move along within the PCF. When IAV advection and
diffusion are both considered, the former is found to dominate infection
kinetics, and a 10-fold increase in the virus production rate is required to
counter its effects. The MM predicts that advection prevents infection from
disseminating below the depth at which virus first deposits. Because virus is
entrained upwards, the upper HRT sees the most virus, whereas the lower HRT
sees far less. As such, infection peaks and resolves faster in the upper than
in the lower HRT, making it appear as though infection progresses from the
upper towards the lower HRT. When the spatial MM is expanded to include
cellular regeneration and an immune response, it can capture the time course of
infection with a seasonal and an avian IAV strain by shifting parameters in a
manner consistent with what is expected to differ between these two types of
infection. The impact of antiviral therapy with neuraminidase inhibitors was
also investigated. This new MM offers a convenient and unique platform from
which to study the localization and spread of respiratory viral infections
within the HRT.
| [
{
"created": "Thu, 22 Aug 2019 16:31:40 GMT",
"version": "v1"
}
] | 2020-04-15 | [
[
"Quirouette",
"Christian",
""
],
[
"Younis",
"Nada P.",
""
],
[
"Reddy",
"Micaela B.",
""
],
[
"Beauchemin",
"Catherine A. A.",
""
]
] | Within the human respiratory tract (HRT), viruses diffuse through the periciliary fluid (PCF) bathing the epithelium, and travel upwards via advection towards the nose and mouth, as the mucus escalator entrains the PCF. While many mathematical models (MMs) to date have described the course of influenza A virus (IAV) infections in vivo, none have considered the impact of both diffusion and advection on the kinetics and localization of the infection. The MM herein represents the HRT as a one-dimensional track extending from the nose down to a depth of 30 cm, wherein stationary cells interact with the concentration of IAV which move along within the PCF. When IAV advection and diffusion are both considered, the former is found to dominate infection kinetics, and a 10-fold increase in the virus production rate is required to counter its effects. The MM predicts that advection prevents infection from disseminating below the depth at which virus first deposits. Because virus is entrained upwards, the upper HRT sees the most virus, whereas the lower HRT sees far less. As such, infection peaks and resolves faster in the upper than in the lower HRT, making it appear as though infection progresses from the upper towards the lower HRT. When the spatial MM is expanded to include cellular regeneration and an immune response, it can capture the time course of infection with a seasonal and an avian IAV strain by shifting parameters in a manner consistent with what is expected to differ between these two types of infection. The impact of antiviral therapy with neuraminidase inhibitors was also investigated. This new MM offers a convenient and unique platform from which to study the localization and spread of respiratory viral infections within the HRT. |
1811.01425 | Francesco Maria Sabatini Dr | Francesco Maria Sabatini, Borja Jim\'enez-Alfaro, Sabina Burrascano,
Andrea Lora, Milan Chytr\'y | Beta-diversity of Central European forests decreases along an
elevational gradient due to the variation in local community assembly
processes | Accepted version 25 pages, 5 figures, 1 table | Ecography 41(6): 1038-1048 (2018) | 10.1111/ecog.02809 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Beta-diversity has been repeatedly shown to decline with increasing
elevation, but the causes of this pattern remain unclear, partly because they
are confounded by coincident variation in alpha- and gamma-diversity. We used
8,795 forest vegetation-plot records from the Czech National Phytosociological
Database to compare the observed patterns of beta diversity to null-model
expectations (beta-deviation) controlling for the effects of alpha- and
gamma-diversity. We tested whether \b{eta}-diversity patterns along a 1,200 m
elevation gradient exclusively depend on the effect of varying species pool
size, or also on the variation of the magnitude of community assembly
mechanisms determining the distribution of species across communities (e.g.,
environmental filtering, dispersal limitation). The null model we used is a
novel extension of an existing null-model designed for presence/absence data
and was specifically designed to disrupt the effect of community assembly
mechanisms, while retaining some key features of observed communities such as
average species richness and species abundance distribution. Analyses were
replicated in ten subregions with comparable elevation ranges. Beta-diversity
declined along the elevation gradient due to a decrease in gamma-diversity,
which was steeper than the decrease in alpha-diversity. This pattern persisted
after controlling for alpha- and gamma-diversity variation, and the results
were robust when different resampling schemes and diversity metrics were used.
We conclude that in temperate forests the pattern of decreasing beta-diversity
with elevation does not exclusively depend on variation in species pool size,
as has been hypothesized, but also on variation in community assembly
mechanisms. The results were consistent across resampling schemes and diversity
measures, thus supporting the use of vegetation plot databases for
understanding...
| [
{
"created": "Sun, 4 Nov 2018 19:52:19 GMT",
"version": "v1"
}
] | 2018-11-06 | [
[
"Sabatini",
"Francesco Maria",
""
],
[
"Jiménez-Alfaro",
"Borja",
""
],
[
"Burrascano",
"Sabina",
""
],
[
"Lora",
"Andrea",
""
],
[
"Chytrý",
"Milan",
""
]
] | Beta-diversity has been repeatedly shown to decline with increasing elevation, but the causes of this pattern remain unclear, partly because they are confounded by coincident variation in alpha- and gamma-diversity. We used 8,795 forest vegetation-plot records from the Czech National Phytosociological Database to compare the observed patterns of beta diversity to null-model expectations (beta-deviation) controlling for the effects of alpha- and gamma-diversity. We tested whether \b{eta}-diversity patterns along a 1,200 m elevation gradient exclusively depend on the effect of varying species pool size, or also on the variation of the magnitude of community assembly mechanisms determining the distribution of species across communities (e.g., environmental filtering, dispersal limitation). The null model we used is a novel extension of an existing null-model designed for presence/absence data and was specifically designed to disrupt the effect of community assembly mechanisms, while retaining some key features of observed communities such as average species richness and species abundance distribution. Analyses were replicated in ten subregions with comparable elevation ranges. Beta-diversity declined along the elevation gradient due to a decrease in gamma-diversity, which was steeper than the decrease in alpha-diversity. This pattern persisted after controlling for alpha- and gamma-diversity variation, and the results were robust when different resampling schemes and diversity metrics were used. We conclude that in temperate forests the pattern of decreasing beta-diversity with elevation does not exclusively depend on variation in species pool size, as has been hypothesized, but also on variation in community assembly mechanisms. The results were consistent across resampling schemes and diversity measures, thus supporting the use of vegetation plot databases for understanding... |
1211.1607 | Vincenzo Forgetta | Vincenzo Forgetta and Ken Dewar | CGB: A UNIX shell program to create custom instances of the UCSC Genome
Browser | 8 pages, 1 figure and 1 table | null | null | null | q-bio.GN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The UCSC Genome Browser is a popular tool for the exploration and analysis of
reference genomes. Mirrors of the UCSC Genome Browser and its contents exist at
multiple geographic locations, and this mirror procedure has been modified to
support genome sequences not maintained by UCSC and generated by individual
researchers. While straightforward, this procedure is lengthy and tedious and
would benefit from automation, especially when processing many genome
sequences. We present a Unix shell program that facilitates the creation of
custom instances of the UCSC Genome Browser for genome sequences not being
maintained by UCSC. It automates many steps of the browser creation process,
provides password protection for each browser instance, and automates the
creation of basic annotation tracks. As an example we generate a custom UCSC
Genome Browser for a bacterial genome obtained from a massively parallel
sequencing platform.
| [
{
"created": "Wed, 7 Nov 2012 17:10:14 GMT",
"version": "v1"
}
] | 2012-11-29 | [
[
"Forgetta",
"Vincenzo",
""
],
[
"Dewar",
"Ken",
""
]
] | The UCSC Genome Browser is a popular tool for the exploration and analysis of reference genomes. Mirrors of the UCSC Genome Browser and its contents exist at multiple geographic locations, and this mirror procedure has been modified to support genome sequences not maintained by UCSC and generated by individual researchers. While straightforward, this procedure is lengthy and tedious and would benefit from automation, especially when processing many genome sequences. We present a Unix shell program that facilitates the creation of custom instances of the UCSC Genome Browser for genome sequences not being maintained by UCSC. It automates many steps of the browser creation process, provides password protection for each browser instance, and automates the creation of basic annotation tracks. As an example we generate a custom UCSC Genome Browser for a bacterial genome obtained from a massively parallel sequencing platform. |
1301.2366 | Andrei Zinovyev Dr. | Andrei Zinovyev, Simon Fourquet, Laurent Tournier, Laurence Calzone
and Emmanuel Barillot | Cell death and life in cancer: mathematical modeling of cell fate
decisions | null | Advances in Experimental Medicine and Biology, Vol. 736 (Goryanin,
I. and Goryachev A., eds.), Springer, 2012, 682p | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Tumor development is characterized by a compromised balance between cell life
and death decision mechanisms, which are tighly regulated in normal cells.
Understanding this process provides insights for developing new treatments for
fighting with cancer. We present a study of a mathematical model describing
cellular choice between survival and two alternative cell death modalities:
apoptosis and necrosis. The model is implemented in discrete modeling formalism
and allows to predict probabilities of having a particular cellular phenotype
in response to engagement of cell death receptors. Using an original parameter
sensitivity analysis developed for discrete dynamic systems, we determine the
critical parameters affecting cellular fate decision variables that appear to
be critical in the cellular fate decision and discuss how they are exploited by
existing cancer therapies.
| [
{
"created": "Fri, 11 Jan 2013 00:32:16 GMT",
"version": "v1"
}
] | 2013-01-14 | [
[
"Zinovyev",
"Andrei",
""
],
[
"Fourquet",
"Simon",
""
],
[
"Tournier",
"Laurent",
""
],
[
"Calzone",
"Laurence",
""
],
[
"Barillot",
"Emmanuel",
""
]
] | Tumor development is characterized by a compromised balance between cell life and death decision mechanisms, which are tighly regulated in normal cells. Understanding this process provides insights for developing new treatments for fighting with cancer. We present a study of a mathematical model describing cellular choice between survival and two alternative cell death modalities: apoptosis and necrosis. The model is implemented in discrete modeling formalism and allows to predict probabilities of having a particular cellular phenotype in response to engagement of cell death receptors. Using an original parameter sensitivity analysis developed for discrete dynamic systems, we determine the critical parameters affecting cellular fate decision variables that appear to be critical in the cellular fate decision and discuss how they are exploited by existing cancer therapies. |
2204.09798 | Josinaldo Menezes | J. Menezes, S. Rodrigues, S. Batista | Mobility unevenness in rock-paper-scissors models | 7 pages, 7 figures | Ecological Complexity 52, 101028 (2022) | 10.1016/j.ecocom.2022.101028 | null | q-bio.PE cond-mat.stat-mech nlin.AO nlin.PS physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate a tritrophic system whose cyclic dominance is modelled by the
rock-paper-scissors game. We consider that organisms of one or two species are
affected by movement limitations, which unbalances the cyclic spatial game.
Performing stochastic simulations, we show that mobility unevenness controls
the population dynamics. In the case of one slow species, the predominant
species depends on the level of mobility restriction, with the slow species
being preponderant if the mobility limitations are substantial. If two species
face mobility limitations, our outcomes show that being higher dispersive does
not constitute an advantage in terms of population growth. On the contrary, if
organisms move with higher mobility, they expose themselves to enemies more
frequently, being more vulnerable to being eliminated. Finally, our findings
show that biodiversity benefits in regions where species are slowed.
Biodiversity loss for high mobility organisms, common to cyclic systems, may be
avoided with coexistence probability being higher for robust mobility
limitations. Our results may help biologists understand the dynamics of
unbalanced spatial systems where organisms' dispersal is fundamental to
biodiversity conservation.
| [
{
"created": "Wed, 20 Apr 2022 21:59:01 GMT",
"version": "v1"
}
] | 2023-03-13 | [
[
"Menezes",
"J.",
""
],
[
"Rodrigues",
"S.",
""
],
[
"Batista",
"S.",
""
]
] | We investigate a tritrophic system whose cyclic dominance is modelled by the rock-paper-scissors game. We consider that organisms of one or two species are affected by movement limitations, which unbalances the cyclic spatial game. Performing stochastic simulations, we show that mobility unevenness controls the population dynamics. In the case of one slow species, the predominant species depends on the level of mobility restriction, with the slow species being preponderant if the mobility limitations are substantial. If two species face mobility limitations, our outcomes show that being higher dispersive does not constitute an advantage in terms of population growth. On the contrary, if organisms move with higher mobility, they expose themselves to enemies more frequently, being more vulnerable to being eliminated. Finally, our findings show that biodiversity benefits in regions where species are slowed. Biodiversity loss for high mobility organisms, common to cyclic systems, may be avoided with coexistence probability being higher for robust mobility limitations. Our results may help biologists understand the dynamics of unbalanced spatial systems where organisms' dispersal is fundamental to biodiversity conservation. |
0801.2708 | Ioana Bena Dr. | Ioana Bena, Michel Droz, Janusz Szwabinski, Andrzej Pekalski | How bad is to be slow-reacting ? On the effect of the delay in response
to a changing environment on a population's survival | 7 pages, 4 figures | null | null | null | q-bio.PE cond-mat.stat-mech physics.bio-ph | null | We consider a simple-model population, whose individuals react with a certain
delay to temporal variations of their habitat. We investigate the impact of
such a delayed-answer on the survival chances of the population, both in a
periodically changing environment, and in the case of an abrupt change of it.
It is found that for population with low degree of mutation-induced
variability, being "slow-reacting" decreases the extinction risk face to
environmental changes. On the contrary, for populations with high mutation
amplitude, the delayed reaction reduces the survival chances.
| [
{
"created": "Thu, 17 Jan 2008 15:50:41 GMT",
"version": "v1"
}
] | 2008-01-18 | [
[
"Bena",
"Ioana",
""
],
[
"Droz",
"Michel",
""
],
[
"Szwabinski",
"Janusz",
""
],
[
"Pekalski",
"Andrzej",
""
]
] | We consider a simple-model population, whose individuals react with a certain delay to temporal variations of their habitat. We investigate the impact of such a delayed-answer on the survival chances of the population, both in a periodically changing environment, and in the case of an abrupt change of it. It is found that for population with low degree of mutation-induced variability, being "slow-reacting" decreases the extinction risk face to environmental changes. On the contrary, for populations with high mutation amplitude, the delayed reaction reduces the survival chances. |
1508.00684 | Denys Dutykh | Ramon Escobedo (BCAM), Denys Dutykh (LAMA), Cristina Muro (AEPA), Lee
Spector, Raymond Coppinger | Group Size Effect on the Success of Wolves Hunting | 20 pages, 4 figures, 8 references. Other author's papers can be
downloaded at http://www.denys-dutykh.com/ | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Social foraging shows unexpected features such as the existence of a group
size threshold to accomplish a successful hunt. Above this threshold,
additional individuals do not increase the probability of capturing the prey.
Recent direct observations of wolves in Yellowstone Park show that the group
size threshold when hunting its most formidable prey, bison, is nearly three
times greater than when hunting elk, a prey that is considerably less
challenging to capture than bison. These observations provide empirical support
to a computational particle model of group hunting which was previously shown
to be effective in explaining why hunting success peaks at apparently small
pack sizes when hunting elk. The model is based on considering two critical
distances between wolves and prey: the minimal safe distance at which wolves
stand from the prey, and the avoidance distance at which wolves move away from
each other when they approach the prey. The minimal safe distance is longer
when the prey is more dangerous to hunt. We show that the model explains
effectively that the group size threshold is greater when the minimal safe
distance is longer. Although both distances are longer when the prey is more
dangerous, they contribute oppositely to the value of the group size threshold:
the group size threshold is smaller when the avoidance distance is longer. This
unexpected mechanism gives rise to a global increase of the group size
threshold when considering bison with respect to elk, but other prey more
dangerous than elk can lead to specific critical distances that can give rise
to the same group size threshold. Our results show that the computational model
can guide further research on group size effects, suggesting that more
experimental observations should be obtained for other kind of prey as e.g.
moose.
| [
{
"created": "Tue, 4 Aug 2015 07:20:08 GMT",
"version": "v1"
}
] | 2015-08-05 | [
[
"Escobedo",
"Ramon",
"",
"BCAM"
],
[
"Dutykh",
"Denys",
"",
"LAMA"
],
[
"Muro",
"Cristina",
"",
"AEPA"
],
[
"Spector",
"Lee",
""
],
[
"Coppinger",
"Raymond",
""
]
] | Social foraging shows unexpected features such as the existence of a group size threshold to accomplish a successful hunt. Above this threshold, additional individuals do not increase the probability of capturing the prey. Recent direct observations of wolves in Yellowstone Park show that the group size threshold when hunting its most formidable prey, bison, is nearly three times greater than when hunting elk, a prey that is considerably less challenging to capture than bison. These observations provide empirical support to a computational particle model of group hunting which was previously shown to be effective in explaining why hunting success peaks at apparently small pack sizes when hunting elk. The model is based on considering two critical distances between wolves and prey: the minimal safe distance at which wolves stand from the prey, and the avoidance distance at which wolves move away from each other when they approach the prey. The minimal safe distance is longer when the prey is more dangerous to hunt. We show that the model explains effectively that the group size threshold is greater when the minimal safe distance is longer. Although both distances are longer when the prey is more dangerous, they contribute oppositely to the value of the group size threshold: the group size threshold is smaller when the avoidance distance is longer. This unexpected mechanism gives rise to a global increase of the group size threshold when considering bison with respect to elk, but other prey more dangerous than elk can lead to specific critical distances that can give rise to the same group size threshold. Our results show that the computational model can guide further research on group size effects, suggesting that more experimental observations should be obtained for other kind of prey as e.g. moose. |
2110.13603 | Stav Marcus | Stav Marcus, Ari M. Turner and Guy Bunin | Local and collective transitions in sparsely-interacting ecological
communities | 15 pages, 11 figures | null | 10.1371/journal.pcbi.1010274 | null | q-bio.PE cond-mat.stat-mech physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Interactions in natural communities can be highly heterogeneous, with any
given species interacting appreciably with only some of the others, a situation
commonly represented by sparse interaction networks. We study the consequences
of sparse competitive interactions, in a theoretical model of a community
assembled from a species pool. We find that communities can be in a number of
different regimes, depending on the interaction strength. When interactions are
strong, the network of coexisting species breaks up into small subgraphs, while
for weaker interactions these graphs are larger and more complex, eventually
encompassing all species. This process is driven by emergence of new allowed
subgraphs as interaction strength decreases, leading to sharp changes in
diversity and other community properties, and at weaker interactions to two
distinct collective transitions: a percolation transition, and a transition
between having a unique equilibrium and having multiple alternative equilibria.
Understanding community structure is thus made up of two parts: first, finding
which subgraphs are allowed at a given interaction strength, and secondly, a
discrete problem of matching these structures over the entire community. In a
shift from the focus of many previous theories, these different regimes can be
traversed by modifying the interaction strength alone, without need for
heterogeneity in either interaction strengths or the number of competitors per
species.
| [
{
"created": "Tue, 26 Oct 2021 12:00:35 GMT",
"version": "v1"
}
] | 2022-10-12 | [
[
"Marcus",
"Stav",
""
],
[
"Turner",
"Ari M.",
""
],
[
"Bunin",
"Guy",
""
]
] | Interactions in natural communities can be highly heterogeneous, with any given species interacting appreciably with only some of the others, a situation commonly represented by sparse interaction networks. We study the consequences of sparse competitive interactions, in a theoretical model of a community assembled from a species pool. We find that communities can be in a number of different regimes, depending on the interaction strength. When interactions are strong, the network of coexisting species breaks up into small subgraphs, while for weaker interactions these graphs are larger and more complex, eventually encompassing all species. This process is driven by emergence of new allowed subgraphs as interaction strength decreases, leading to sharp changes in diversity and other community properties, and at weaker interactions to two distinct collective transitions: a percolation transition, and a transition between having a unique equilibrium and having multiple alternative equilibria. Understanding community structure is thus made up of two parts: first, finding which subgraphs are allowed at a given interaction strength, and secondly, a discrete problem of matching these structures over the entire community. In a shift from the focus of many previous theories, these different regimes can be traversed by modifying the interaction strength alone, without need for heterogeneity in either interaction strengths or the number of competitors per species. |
1507.06890 | Ziyue Gao | Ziyue Gao, Minyoung J. Wyman, Guy Sella and Molly Przeworski | Interpreting the dependence of mutation rates on age and time | 5 figures, 2 tables | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mutations can arise from the chance misincorporation of nucleotides during
DNA replication or from DNA lesions that are not repaired correctly. We
introduce a model that relates the source of mutations to their accumulation
with cell divisions, providing a framework for understanding how mutation rates
depend on sex, age and absolute time. We show that the accrual of mutations
should track cell divisions not only when mutations are replicative in origin
but also when they are non-replicative and repaired efficiently. One
implication is that the higher incidence of cancer in rapidly renewing tissues,
an observation ascribed to replication errors, could instead reflect exogenous
or endogenous mutagens. We further find that only mutations that arise from
inefficiently repaired lesions will accrue according to absolute time; thus, in
the absence of selection on mutation rates, the phylogenetic "molecular clock"
should not be expected to run steadily across species.
| [
{
"created": "Fri, 24 Jul 2015 15:30:45 GMT",
"version": "v1"
}
] | 2015-07-27 | [
[
"Gao",
"Ziyue",
""
],
[
"Wyman",
"Minyoung J.",
""
],
[
"Sella",
"Guy",
""
],
[
"Przeworski",
"Molly",
""
]
] | Mutations can arise from the chance misincorporation of nucleotides during DNA replication or from DNA lesions that are not repaired correctly. We introduce a model that relates the source of mutations to their accumulation with cell divisions, providing a framework for understanding how mutation rates depend on sex, age and absolute time. We show that the accrual of mutations should track cell divisions not only when mutations are replicative in origin but also when they are non-replicative and repaired efficiently. One implication is that the higher incidence of cancer in rapidly renewing tissues, an observation ascribed to replication errors, could instead reflect exogenous or endogenous mutagens. We further find that only mutations that arise from inefficiently repaired lesions will accrue according to absolute time; thus, in the absence of selection on mutation rates, the phylogenetic "molecular clock" should not be expected to run steadily across species. |
1108.4951 | Areejit Samal | Areejit Samal, Andreas Wagner and Olivier C. Martin | Environmental versatility promotes modularity in genome-scale metabolic
networks | 34 pages, 4 main figures, 7 additional figures, 2 additional tables | BMC Systems Biology, 5:135 (2011) | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The ubiquity of modules in biological networks may result from an
evolutionary benefit of a modular organization. For instance, modularity may
increase the rate of adaptive evolution, because modules can be easily combined
into new arrangements that may benefit their carrier. Conversely, modularity
may emerge as a by-product of some trait. We here ask whether this last
scenario may play a role in genome-scale metabolic networks that need to
sustain life in one or more chemical environments. For such networks, we define
a network module as a maximal set of reactions that are fully coupled, i.e.,
whose fluxes can only vary in fixed proportions. This definition overcomes
limitations of purely graph based analyses of metabolism by exploiting the
functional links between reactions. We call a metabolic network viable in a
given chemical environment if it can synthesize all of an organism's biomass
compounds from nutrients in this environment. An organism's metabolism is
highly versatile if it can sustain life in many different chemical
environments. We here ask whether versatility affects the modularity of
metabolic networks.
| [
{
"created": "Wed, 24 Aug 2011 20:50:27 GMT",
"version": "v1"
}
] | 2011-08-26 | [
[
"Samal",
"Areejit",
""
],
[
"Wagner",
"Andreas",
""
],
[
"Martin",
"Olivier C.",
""
]
] | The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. |
1910.09738 | Ali Madani | Ali Madani, Cyna Shirazinejad, Jia Rui Ong, Hengameh Shams, Mohammad
Mofrad | ProDyn0: Inferring calponin homology domain stretching behavior using
graph neural networks | 8 pages, 2 figures, 2 tables | ICLR 2019: Representation learning on graphs and manifolds | null | null | q-bio.QM cs.LG | http://creativecommons.org/publicdomain/zero/1.0/ | Graph neural networks are a quickly emerging field for non-Euclidean data
that leverage the inherent graphical structure to predict node, edge, and
global-level properties of a system. Protein properties can not easily be
understood as a simple sum of their parts (i.e. amino acids), therefore,
understanding their dynamical properties in the context of graphs is attractive
for revealing how perturbations to their structure can affect their global
function. To tackle this problem, we generate a database of 2020 mutated
calponin homology (CH) domains undergoing large-scale separation in molecular
dynamics. To predict the mechanosensitive force response, we develop neural
message passing networks and residual gated graph convnets which predict the
protein dependent force separation at 86.63 percent, 81.59 kJ/mol/nm MAE, 76.99
psec MAE for force mode classification, max force magnitude, max force time
respectively-- significantly better than non-graph-based deep learning
techniques. Towards uniting geometric learning techniques and biophysical
observables, we premiere our simulation database as a benchmark dataset for
further development/evaluation of graph neural network architectures.
| [
{
"created": "Tue, 22 Oct 2019 02:42:58 GMT",
"version": "v1"
}
] | 2019-10-23 | [
[
"Madani",
"Ali",
""
],
[
"Shirazinejad",
"Cyna",
""
],
[
"Ong",
"Jia Rui",
""
],
[
"Shams",
"Hengameh",
""
],
[
"Mofrad",
"Mohammad",
""
]
] | Graph neural networks are a quickly emerging field for non-Euclidean data that leverage the inherent graphical structure to predict node, edge, and global-level properties of a system. Protein properties can not easily be understood as a simple sum of their parts (i.e. amino acids), therefore, understanding their dynamical properties in the context of graphs is attractive for revealing how perturbations to their structure can affect their global function. To tackle this problem, we generate a database of 2020 mutated calponin homology (CH) domains undergoing large-scale separation in molecular dynamics. To predict the mechanosensitive force response, we develop neural message passing networks and residual gated graph convnets which predict the protein dependent force separation at 86.63 percent, 81.59 kJ/mol/nm MAE, 76.99 psec MAE for force mode classification, max force magnitude, max force time respectively-- significantly better than non-graph-based deep learning techniques. Towards uniting geometric learning techniques and biophysical observables, we premiere our simulation database as a benchmark dataset for further development/evaluation of graph neural network architectures. |
2102.05452 | Nitai Bar | Nitai Bar, Jonathan A. Sobel, Thomas Penzel, Yosi Shamay, Joachim A.
Behar | From sleep medicine to medicine during sleep: A clinical perspective | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Sleep has a profound influence on the physiology of body systems and
biological processes. Molecular studies have shown circadian-regulated shifts
in protein expression patterns across human tissues, further emphasizing the
unique functional, behavioral and pharmacokinetic landscape of sleep. Thus,
many pathological processes are also expected to exhibit sleep-specific
manifestations. Nevertheless, sleep is seldom utilized for the study, detection
and treatment of non-sleep-specific pathologies. Modern advances in biosensor
technologies have enabled remote, non-invasive recording of a growing number of
physiologic parameters and biomarkers. Sleep is an ideal time frame for the
collection of long and clean physiological time series data which can then be
analyzed using data-driven algorithms such as deep learning. In this
perspective paper, we aim to highlight the potential of sleep as an auspicious
time for diagnosis, management and therapy of nonsleep-specific pathologies. We
introduce key clinical studies in selected medical fields, which leveraged
novel technologies and the advantageous period of sleep to diagnose, monitor
and treat pathologies. We then discuss possible opportunities to further
harness this new paradigm and modern technologies to explore human health and
disease during sleep and to advance the development of novel clinical
applications: From sleep medicine to medicine during sleep.
| [
{
"created": "Tue, 9 Feb 2021 18:45:42 GMT",
"version": "v1"
}
] | 2021-02-11 | [
[
"Bar",
"Nitai",
""
],
[
"Sobel",
"Jonathan A.",
""
],
[
"Penzel",
"Thomas",
""
],
[
"Shamay",
"Yosi",
""
],
[
"Behar",
"Joachim A.",
""
]
] | Sleep has a profound influence on the physiology of body systems and biological processes. Molecular studies have shown circadian-regulated shifts in protein expression patterns across human tissues, further emphasizing the unique functional, behavioral and pharmacokinetic landscape of sleep. Thus, many pathological processes are also expected to exhibit sleep-specific manifestations. Nevertheless, sleep is seldom utilized for the study, detection and treatment of non-sleep-specific pathologies. Modern advances in biosensor technologies have enabled remote, non-invasive recording of a growing number of physiologic parameters and biomarkers. Sleep is an ideal time frame for the collection of long and clean physiological time series data which can then be analyzed using data-driven algorithms such as deep learning. In this perspective paper, we aim to highlight the potential of sleep as an auspicious time for diagnosis, management and therapy of nonsleep-specific pathologies. We introduce key clinical studies in selected medical fields, which leveraged novel technologies and the advantageous period of sleep to diagnose, monitor and treat pathologies. We then discuss possible opportunities to further harness this new paradigm and modern technologies to explore human health and disease during sleep and to advance the development of novel clinical applications: From sleep medicine to medicine during sleep. |
2010.07162 | Konstantinos Spiliotis | Konstantinos Spiliotis and Jens Starke and Denise Franz and Angelika
Richter and R\"udiger K\"ohling | Deep brain stimulation for movement disorder treatment: Exploring
frequency-dependent efficacy in a computational network model | 40 pages, 16 figures | null | null | null | q-bio.NC math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A large scale computational model of the basal ganglia (BG) network is
proposed to describes movement disorder including deep brain stimulation (DBS).
The model of this complex network considers four areas of the basal ganglia
network: the subthalamic nucleus (STN) as target area of DBS, globus pallidus,
both pars externa and pars interna (GPe-GPi), and the thalamus (THA).
Parkinsonian conditions are simulated by assuming reduced dopaminergic input
and corresponding pronounced inhibitory or disinhibited projections to GPe and
GPi. Macroscopic quantities can be derived which correlate closely to thalamic
responses and hence motor programme fidelity. It can be demonstrated that
depending on different levels of striatal projections to the GPe and GPi, the
dynamics of these macroscopic quantities switch from normal conditions to
parkinsonian. Simulating DBS on the STN affects the dynamics of the entire
network, increasing the thalamic activity to levels close to normal, while
differing from both normal and parkinsonian dynamics. Using the mentioned
macroscopic quantities, the model proposes optimal DBS frequency ranges above
130 Hz.
| [
{
"created": "Wed, 14 Oct 2020 15:28:27 GMT",
"version": "v1"
},
{
"created": "Fri, 12 Mar 2021 14:57:39 GMT",
"version": "v2"
}
] | 2021-03-15 | [
[
"Spiliotis",
"Konstantinos",
""
],
[
"Starke",
"Jens",
""
],
[
"Franz",
"Denise",
""
],
[
"Richter",
"Angelika",
""
],
[
"Köhling",
"Rüdiger",
""
]
] | A large scale computational model of the basal ganglia (BG) network is proposed to describes movement disorder including deep brain stimulation (DBS). The model of this complex network considers four areas of the basal ganglia network: the subthalamic nucleus (STN) as target area of DBS, globus pallidus, both pars externa and pars interna (GPe-GPi), and the thalamus (THA). Parkinsonian conditions are simulated by assuming reduced dopaminergic input and corresponding pronounced inhibitory or disinhibited projections to GPe and GPi. Macroscopic quantities can be derived which correlate closely to thalamic responses and hence motor programme fidelity. It can be demonstrated that depending on different levels of striatal projections to the GPe and GPi, the dynamics of these macroscopic quantities switch from normal conditions to parkinsonian. Simulating DBS on the STN affects the dynamics of the entire network, increasing the thalamic activity to levels close to normal, while differing from both normal and parkinsonian dynamics. Using the mentioned macroscopic quantities, the model proposes optimal DBS frequency ranges above 130 Hz. |
1907.04319 | EPTCS | Ozan Kahramano\u{g}ullar{\i} (University of Trento, Department of
Mathematics) | On Quantitative Comparison of Chemical Reaction Network Models | In Proceedings HCVS/PERR 2019, arXiv:1907.03523 | EPTCS 296, 2019, pp. 14-27 | 10.4204/EPTCS.296.5 | null | q-bio.MN cs.DM cs.LO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Chemical reaction networks (CRNs) provide a convenient language for modelling
a broad variety of biological systems. These models are commonly studied with
respect to the time series they generate in deterministic or stochastic
simulations. Their dynamic behaviours are then analysed, often by using
deterministic methods based on differential equations with a focus on the
steady states. Here, we propose a method for comparing CRNs with respect to
their behaviour in stochastic simulations. Our method is based on using the
flux graphs that are delivered by stochastic simulations as abstract
representations of their dynamic behaviour. This allows us to compare the
behaviour of any two CRNs for any time interval, and define a notion of
equivalence on them that overlaps with graph isomorphism at the lowest level of
representation. The similarity between the compared CRNs can be quantified in
terms of their distance. The results can then be used to refine the models or
to replace a larger model with a smaller one that produces the same behaviour
or vice versa.
| [
{
"created": "Tue, 9 Jul 2019 06:01:27 GMT",
"version": "v1"
}
] | 2019-07-11 | [
[
"Kahramanoğulları",
"Ozan",
"",
"University of Trento, Department of\n Mathematics"
]
] | Chemical reaction networks (CRNs) provide a convenient language for modelling a broad variety of biological systems. These models are commonly studied with respect to the time series they generate in deterministic or stochastic simulations. Their dynamic behaviours are then analysed, often by using deterministic methods based on differential equations with a focus on the steady states. Here, we propose a method for comparing CRNs with respect to their behaviour in stochastic simulations. Our method is based on using the flux graphs that are delivered by stochastic simulations as abstract representations of their dynamic behaviour. This allows us to compare the behaviour of any two CRNs for any time interval, and define a notion of equivalence on them that overlaps with graph isomorphism at the lowest level of representation. The similarity between the compared CRNs can be quantified in terms of their distance. The results can then be used to refine the models or to replace a larger model with a smaller one that produces the same behaviour or vice versa. |
1309.2032 | Subhadip Raychaudhuri | Subhadip Raychaudhuri, Somkanya C Das | Monte Carlo study elucidates the type 1/type 2 choice in apoptotic death
signaling in normal and cancer cells | 35 pages, 15 figures | Cells 2013 2:361-392 | null | null | q-bio.MN physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Apoptotic cell death is coordinated through two distinct (type 1 and type 2)
intracellular signaling pathways. How the type 1/type 2 choice is made remains
a fundamental problem in the biology of apoptosis and has implications for
apoptosis related diseases and therapy. We study the problem of type 1/type 2
choice in silico utilizing a kinetic Monte Carlo model of cell death signaling.
Our results show that the type 1/type 2 choice is linked to deterministic
versus stochastic cell death activation, elucidating a unique regulatory
control of the apoptotic pathways. Consistent with previous findings, our
results indicate that caspase 8 activation level is a key regulator of the
choice between deterministic type 1 and stochastic type 2 pathways,
irrespective of cell types. Expression levels of signaling molecules downstream
also regulate the type 1/type 2 choice. A simplified model of DISC clustering
elucidates the mechanism of increased active caspase 8 generation, and type 1
activation, in cancer cells having increased sensitivity to death receptor
activation. We demonstrate that rapid deterministic activation of the type 1
pathway can selectively target those cancer cells, especially if XIAP is also
inhibited; while inherent cell-to-cell variability would allow normal cells
stay protected.
| [
{
"created": "Mon, 9 Sep 2013 02:19:28 GMT",
"version": "v1"
}
] | 2013-09-10 | [
[
"Raychaudhuri",
"Subhadip",
""
],
[
"Das",
"Somkanya C",
""
]
] | Apoptotic cell death is coordinated through two distinct (type 1 and type 2) intracellular signaling pathways. How the type 1/type 2 choice is made remains a fundamental problem in the biology of apoptosis and has implications for apoptosis related diseases and therapy. We study the problem of type 1/type 2 choice in silico utilizing a kinetic Monte Carlo model of cell death signaling. Our results show that the type 1/type 2 choice is linked to deterministic versus stochastic cell death activation, elucidating a unique regulatory control of the apoptotic pathways. Consistent with previous findings, our results indicate that caspase 8 activation level is a key regulator of the choice between deterministic type 1 and stochastic type 2 pathways, irrespective of cell types. Expression levels of signaling molecules downstream also regulate the type 1/type 2 choice. A simplified model of DISC clustering elucidates the mechanism of increased active caspase 8 generation, and type 1 activation, in cancer cells having increased sensitivity to death receptor activation. We demonstrate that rapid deterministic activation of the type 1 pathway can selectively target those cancer cells, especially if XIAP is also inhibited; while inherent cell-to-cell variability would allow normal cells stay protected. |
1303.1904 | Hugues Berry | Anne-Sophie Coquel (Insa Lyon / INRIA Grenoble Rh\^one-Alpes / UCBL,
LIRIS), Jean-Pascal Jacob (MAP5), Ma\"el Primet (MAP5), Alice Demarez (MAP5),
Mariella Dimiccoli (MAP5), Thomas Julou (LPS), Lionel Moisan (MAP5), Ariel B.
Lindner, Hugues Berry (Insa Lyon / INRIA Grenoble Rh\^one-Alpes / UCBL) | Localization of protein aggregation in Escherichia coli is governed by
diffusion and nucleoid macromolecular crowding effect | PLoS Computational Biology (2013) | null | 10.1371/journal.pcbi.1003038 | null | q-bio.CB cs.CE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Aggregates of misfolded proteins are a hallmark of many age-related diseases.
Recently, they have been linked to aging of Escherichia coli (E. coli) where
protein aggregates accumulate at the old pole region of the aging bacterium.
Because of the potential of E. coli as a model organism, elucidating aging and
protein aggregation in this bacterium may pave the way to significant advances
in our global understanding of aging. A first obstacle along this path is to
decipher the mechanisms by which protein aggregates are targeted to specific
intercellular locations. Here, using an integrated approach based on
individual-based modeling, time-lapse fluorescence microscopy and automated
image analysis, we show that the movement of aging-related protein aggregates
in E. coli is purely diffusive (Brownian). Using single-particle tracking of
protein aggregates in live E. coli cells, we estimated the average size and
diffusion constant of the aggregates. Our results evidence that the aggregates
passively diffuse within the cell, with diffusion constants that depend on
their size in agreement with the Stokes-Einstein law. However, the aggregate
displacements along the cell long axis are confined to a region that roughly
corresponds to the nucleoid-free space in the cell pole, thus confirming the
importance of increased macromolecular crowding in the nucleoids. We thus used
3d individual-based modeling to show that these three ingredients (diffusion,
aggregation and diffusion hindrance in the nucleoids) are sufficient and
necessary to reproduce the available experimental data on aggregate
localization in the cells. Taken together, our results strongly support the
hypothesis that the localization of aging-related protein aggregates in the
poles of E. coli results from the coupling of passive diffusion- aggregation
with spatially non-homogeneous macromolecular crowding. They further support
the importance of "soft" intracellular structuring (based on macromolecular
crowding) in diffusion-based protein localization in E. coli.
| [
{
"created": "Fri, 8 Mar 2013 07:53:49 GMT",
"version": "v1"
}
] | 2015-06-15 | [
[
"Coquel",
"Anne-Sophie",
"",
"Insa Lyon / INRIA Grenoble Rhône-Alpes / UCBL,\n LIRIS"
],
[
"Jacob",
"Jean-Pascal",
"",
"MAP5"
],
[
"Primet",
"Maël",
"",
"MAP5"
],
[
"Demarez",
"Alice",
"",
"MAP5"
],
[
"Dimiccoli",
"Mariella",
"",
"MAP5"
],
[
"Julou",
"Thomas",
"",
"LPS"
],
[
"Moisan",
"Lionel",
"",
"MAP5"
],
[
"Lindner",
"Ariel B.",
"",
"Insa Lyon / INRIA Grenoble Rhône-Alpes / UCBL"
],
[
"Berry",
"Hugues",
"",
"Insa Lyon / INRIA Grenoble Rhône-Alpes / UCBL"
]
] | Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because of the potential of E. coli as a model organism, elucidating aging and protein aggregation in this bacterium may pave the way to significant advances in our global understanding of aging. A first obstacle along this path is to decipher the mechanisms by which protein aggregates are targeted to specific intercellular locations. Here, using an integrated approach based on individual-based modeling, time-lapse fluorescence microscopy and automated image analysis, we show that the movement of aging-related protein aggregates in E. coli is purely diffusive (Brownian). Using single-particle tracking of protein aggregates in live E. coli cells, we estimated the average size and diffusion constant of the aggregates. Our results evidence that the aggregates passively diffuse within the cell, with diffusion constants that depend on their size in agreement with the Stokes-Einstein law. However, the aggregate displacements along the cell long axis are confined to a region that roughly corresponds to the nucleoid-free space in the cell pole, thus confirming the importance of increased macromolecular crowding in the nucleoids. We thus used 3d individual-based modeling to show that these three ingredients (diffusion, aggregation and diffusion hindrance in the nucleoids) are sufficient and necessary to reproduce the available experimental data on aggregate localization in the cells. Taken together, our results strongly support the hypothesis that the localization of aging-related protein aggregates in the poles of E. coli results from the coupling of passive diffusion- aggregation with spatially non-homogeneous macromolecular crowding. They further support the importance of "soft" intracellular structuring (based on macromolecular crowding) in diffusion-based protein localization in E. coli. |
2306.11031 | Emil Mallmin | Emil Mallmin, Arne Traulsen and Silvia De Monte | Chaotic turnover of rare and abundant species in a strongly interacting
model community | 15 pages, 7 figures | null | null | null | q-bio.PE cond-mat.stat-mech | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Advances in metagenomic methods have revealed an astonishing number and
diversity of microbial lifeforms, most of which are rare relative to the
most-abundant, dominant taxa. The ecological and evolutionary mechanisms that
generate and sustain broadly observed microbial diversity patterns remain
debated. One possibility is that complex interactions between numerous taxa are
a main driver of the composition of a microbial community. Lotka-Volterra
equations with disordered interactions between species offer a minimal yet rich
modelling framework to investigate this hypothesis. We consider communities
with strong, mostly competitive interactions, where species-rich coexistence
equilibria are typically unstable. When species extinction is prevented by a
small rate of immigration, one generically finds a sustained chaotic phase,
where all species participate in a continuous turnover of who is rare and who
is dominant. The distribution of rare species' abundances -- in a snapshot of
the whole community, and for each species individually in time -- follows a
distribution with a prominent power-law trend with exponent $\nu>1$. We
formulate a focal-species model in terms of a logistic growth equation with
coloured noise that reproduces dynamical features of the disordered
Lotka-Volterra model. With its use, we discover that $\nu$ is mainly determined
by three effective parameters of the dominant community, such as its timescale
of turnover. Approximate proportionalities between the effective parameters
constrain the variation of $\nu$ across the range of interaction statistics
resulting in chaotic turnover. We discuss our findings in the context of marine
plankton communities, where chaos, boom-bust dynamics, and a power-law
abundance distribution have been observed.
| [
{
"created": "Mon, 19 Jun 2023 15:48:31 GMT",
"version": "v1"
}
] | 2023-06-21 | [
[
"Mallmin",
"Emil",
""
],
[
"Traulsen",
"Arne",
""
],
[
"De Monte",
"Silvia",
""
]
] | Advances in metagenomic methods have revealed an astonishing number and diversity of microbial lifeforms, most of which are rare relative to the most-abundant, dominant taxa. The ecological and evolutionary mechanisms that generate and sustain broadly observed microbial diversity patterns remain debated. One possibility is that complex interactions between numerous taxa are a main driver of the composition of a microbial community. Lotka-Volterra equations with disordered interactions between species offer a minimal yet rich modelling framework to investigate this hypothesis. We consider communities with strong, mostly competitive interactions, where species-rich coexistence equilibria are typically unstable. When species extinction is prevented by a small rate of immigration, one generically finds a sustained chaotic phase, where all species participate in a continuous turnover of who is rare and who is dominant. The distribution of rare species' abundances -- in a snapshot of the whole community, and for each species individually in time -- follows a distribution with a prominent power-law trend with exponent $\nu>1$. We formulate a focal-species model in terms of a logistic growth equation with coloured noise that reproduces dynamical features of the disordered Lotka-Volterra model. With its use, we discover that $\nu$ is mainly determined by three effective parameters of the dominant community, such as its timescale of turnover. Approximate proportionalities between the effective parameters constrain the variation of $\nu$ across the range of interaction statistics resulting in chaotic turnover. We discuss our findings in the context of marine plankton communities, where chaos, boom-bust dynamics, and a power-law abundance distribution have been observed. |
1703.04342 | Daihai He | Alice P.Y. Chiu, Duo Yu, Jonathan Dushoff and Daihai He | Patterns of Influenza Vaccination Coverage in the United States from
2009 to 2015 | 10 pages, 2 figures | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Background: Globally, influenza is a major cause of morbidity,
hospitalization and mortality. Influenza vaccination has shown substantial
protective effectiveness in the United States. We investigated state-level
patterns of coverage rates of seasonal and pandemic influenza vaccination,
among the overall population in the U.S. and specifically among children and
the elderly, from 2009/10 to 2014/15, and associations with ecological factors.
Methods and Findings: We obtained state-level influenza vaccination coverage
rates from national surveys, and state-level socio-demographic and health data
from a variety of sources. We employed a retrospective ecological study design,
and used mixed-model regression to determine the levels of ecological
association of the state-level vaccinations rates with these factors, both with
and without region as a factor for the three populations. We found that
health-care access is positively and significantly associated with mean
influenza vaccination coverage rates across all populations and models. We also
found that prevalence of asthma in adults are negatively and significantly
associated with mean influenza vaccination coverage rates in the elderly
populations. Conclusions: Health-care access has a robust, positive association
with state-level vaccination rates across different populations. This
highlights a potential population-level advantage of expanding health-care
access.
| [
{
"created": "Mon, 13 Mar 2017 11:40:53 GMT",
"version": "v1"
}
] | 2017-03-14 | [
[
"Chiu",
"Alice P. Y.",
""
],
[
"Yu",
"Duo",
""
],
[
"Dushoff",
"Jonathan",
""
],
[
"He",
"Daihai",
""
]
] | Background: Globally, influenza is a major cause of morbidity, hospitalization and mortality. Influenza vaccination has shown substantial protective effectiveness in the United States. We investigated state-level patterns of coverage rates of seasonal and pandemic influenza vaccination, among the overall population in the U.S. and specifically among children and the elderly, from 2009/10 to 2014/15, and associations with ecological factors. Methods and Findings: We obtained state-level influenza vaccination coverage rates from national surveys, and state-level socio-demographic and health data from a variety of sources. We employed a retrospective ecological study design, and used mixed-model regression to determine the levels of ecological association of the state-level vaccinations rates with these factors, both with and without region as a factor for the three populations. We found that health-care access is positively and significantly associated with mean influenza vaccination coverage rates across all populations and models. We also found that prevalence of asthma in adults are negatively and significantly associated with mean influenza vaccination coverage rates in the elderly populations. Conclusions: Health-care access has a robust, positive association with state-level vaccination rates across different populations. This highlights a potential population-level advantage of expanding health-care access. |
2007.01043 | Francesco Di Lauro Mr | Francesco Di Lauro, Jean-Charles Croix, Luc Berthouze and Istv\'an
Kiss | PDE-limits of stochastic SIS epidemics on networks | 16 pages, 7 figures, code available online | null | null | null | q-bio.PE math.PR physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Stochastic epidemic models on networks are inherently high-dimensional and
the resulting exact models are intractable numerically even for modest network
sizes. Mean-field models provide an alternative but can only capture average
quantities, thus offering little or no information about variability in the
outcome of the exact process. In this paper we conjecture and numerically prove
that it is possible to construct PDE-limits of the exact stochastic SIS
epidemics on regular and Erd\H{o}s-R\'enyi networks. To do this we first
approximate the exact stochastic process at population level by a
Birth-and-Death process (BD) (with a state space of $O(N)$ rather than
$O(2^N)$) whose coefficients are determined numerically from Gillespie
simulations of the exact epidemic on explicit networks. We numerically
demonstrate that the coefficients of the resulting BD process are
density-dependent, a crucial condition for the existence of a PDE limit.
Extensive numerical tests for Regular and Erd\H{o}s-R\'enyi networks show
excellent agreement between the outcome of simulations and the numerical
solution of the Fokker-Planck equations. Apart from a significant reduction in
dimensionality, the PDE also provides the means to derive the epidemic outbreak
threshold linking network and disease dynamics parameters, albeit in an
implicit way. Perhaps more importantly, it enables the formulation and
numerical evaluation of likelihoods for epidemic and network inference as
illustrated in a worked out example.
| [
{
"created": "Thu, 2 Jul 2020 12:01:14 GMT",
"version": "v1"
}
] | 2020-07-03 | [
[
"Di Lauro",
"Francesco",
""
],
[
"Croix",
"Jean-Charles",
""
],
[
"Berthouze",
"Luc",
""
],
[
"Kiss",
"István",
""
]
] | Stochastic epidemic models on networks are inherently high-dimensional and the resulting exact models are intractable numerically even for modest network sizes. Mean-field models provide an alternative but can only capture average quantities, thus offering little or no information about variability in the outcome of the exact process. In this paper we conjecture and numerically prove that it is possible to construct PDE-limits of the exact stochastic SIS epidemics on regular and Erd\H{o}s-R\'enyi networks. To do this we first approximate the exact stochastic process at population level by a Birth-and-Death process (BD) (with a state space of $O(N)$ rather than $O(2^N)$) whose coefficients are determined numerically from Gillespie simulations of the exact epidemic on explicit networks. We numerically demonstrate that the coefficients of the resulting BD process are density-dependent, a crucial condition for the existence of a PDE limit. Extensive numerical tests for Regular and Erd\H{o}s-R\'enyi networks show excellent agreement between the outcome of simulations and the numerical solution of the Fokker-Planck equations. Apart from a significant reduction in dimensionality, the PDE also provides the means to derive the epidemic outbreak threshold linking network and disease dynamics parameters, albeit in an implicit way. Perhaps more importantly, it enables the formulation and numerical evaluation of likelihoods for epidemic and network inference as illustrated in a worked out example. |
1812.11290 | Vahe Galstyan Mr. | Vahe Galstyan, Luke Funk, Tal Einav, Rob Phillips | Combinatorial Control through Allostery | null | null | null | null | q-bio.BM physics.bio-ph physics.chem-ph | http://creativecommons.org/licenses/by/4.0/ | Many instances of cellular signaling and transcriptional regulation involve
switch-like molecular responses to the presence or absence of input ligands. To
understand how these responses come about and how they can be harnessed, we
develop a statistical mechanical model to characterize the types of Boolean
logic that can arise from allosteric molecules following the
Monod-Wyman-Changeux (MWC) model. Building upon previous work, we show how an
allosteric molecule regulated by two inputs can elicit AND, OR, NAND and NOR
responses, but is unable to realize XOR or XNOR gates. Next, we demonstrate the
ability of an MWC molecule to perform ratiometric sensing - a response behavior
where activity depends monotonically on the ratio of ligand concentrations. We
then extend our analysis to more general schemes of combinatorial control
involving either additional binding sites for the two ligands or an additional
third ligand and show how these additions can cause a switch in the logic
behavior of the molecule. Overall, our results demonstrate the wide variety of
control schemes that biological systems can implement using simple mechanisms.
| [
{
"created": "Sat, 29 Dec 2018 05:43:48 GMT",
"version": "v1"
}
] | 2019-01-01 | [
[
"Galstyan",
"Vahe",
""
],
[
"Funk",
"Luke",
""
],
[
"Einav",
"Tal",
""
],
[
"Phillips",
"Rob",
""
]
] | Many instances of cellular signaling and transcriptional regulation involve switch-like molecular responses to the presence or absence of input ligands. To understand how these responses come about and how they can be harnessed, we develop a statistical mechanical model to characterize the types of Boolean logic that can arise from allosteric molecules following the Monod-Wyman-Changeux (MWC) model. Building upon previous work, we show how an allosteric molecule regulated by two inputs can elicit AND, OR, NAND and NOR responses, but is unable to realize XOR or XNOR gates. Next, we demonstrate the ability of an MWC molecule to perform ratiometric sensing - a response behavior where activity depends monotonically on the ratio of ligand concentrations. We then extend our analysis to more general schemes of combinatorial control involving either additional binding sites for the two ligands or an additional third ligand and show how these additions can cause a switch in the logic behavior of the molecule. Overall, our results demonstrate the wide variety of control schemes that biological systems can implement using simple mechanisms. |
0706.1908 | Jason Locasale W | Jason W. Locasale | Computational investigations into the orgins of 'short term' biochemical
memory in T cell activation | 11 pages, published July 18th 2007 | Locasale JW (2007) Computational Investigations into the Origins
of Short-Term Biochemical Memory in T cell Activation. PLoS ONE 2(7): e627 | 10.1371/journal.pone.0000627 | null | q-bio.MN physics.bio-ph q-bio.CB q-bio.SC | null | Recent studies have reported that T cells can integrate signals between
interrupted encounters with Antigen Presenting Cells (APCs) in such a way that
the process of signal integration exhibits a form of memory. Here, we carry out
a computational study using a simple mathematical model of T cell activation to
investigate the ramifications of interrupted T cell-APC contacts on signal
integration. We consider several mechanisms of how signal integration at these
time scales may be achieved and conclude that feedback control of immediate
early gene products (IEGs) appears to be a highly plausible mechanism that
allows for effective signal integration and cytokine production from multiple
exposures to APCs. Analysis of these computer simulations provides an
experimental roadmap involving several testable predictions.
| [
{
"created": "Wed, 13 Jun 2007 14:10:12 GMT",
"version": "v1"
},
{
"created": "Fri, 15 Jun 2007 16:28:17 GMT",
"version": "v2"
},
{
"created": "Wed, 18 Jul 2007 18:23:23 GMT",
"version": "v3"
}
] | 2007-07-18 | [
[
"Locasale",
"Jason W.",
""
]
] | Recent studies have reported that T cells can integrate signals between interrupted encounters with Antigen Presenting Cells (APCs) in such a way that the process of signal integration exhibits a form of memory. Here, we carry out a computational study using a simple mathematical model of T cell activation to investigate the ramifications of interrupted T cell-APC contacts on signal integration. We consider several mechanisms of how signal integration at these time scales may be achieved and conclude that feedback control of immediate early gene products (IEGs) appears to be a highly plausible mechanism that allows for effective signal integration and cytokine production from multiple exposures to APCs. Analysis of these computer simulations provides an experimental roadmap involving several testable predictions. |
q-bio/0401044 | Lorenzo Farina | Lorenzo Farina, and Ilaria Mogno | A Fast Reconstruction Algorithm for Gene Networks | 12 pages, 3 figures | null | null | null | q-bio.QM q-bio.GN | null | This paper deals with gene networks whose dynamics is assumed to be generated
by a continuous-time, linear, time invariant, finite dimensional system (LTI)
at steady state. In particular, we deal with the problem of network
reconstruction in the typical practical situation in which the number of
available data is largely insufficient to uniquely determine the network. In
order to try to remove this ambiguity, we will exploit the biologically a
priori assumption of network sparseness, and propose a new algorithm for
network reconstruction having a very low computational complexity (linear in
the number of genes) so to be able to deal also with very large networks (say,
thousands of genes). Its performances are also tested both on artificial data
(generated with linear models) and on real data obtained by Gardner et al. from
the SOS pathway in Escherichia coli.
| [
{
"created": "Fri, 30 Jan 2004 18:55:33 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Farina",
"Lorenzo",
""
],
[
"Mogno",
"Ilaria",
""
]
] | This paper deals with gene networks whose dynamics is assumed to be generated by a continuous-time, linear, time invariant, finite dimensional system (LTI) at steady state. In particular, we deal with the problem of network reconstruction in the typical practical situation in which the number of available data is largely insufficient to uniquely determine the network. In order to try to remove this ambiguity, we will exploit the biologically a priori assumption of network sparseness, and propose a new algorithm for network reconstruction having a very low computational complexity (linear in the number of genes) so to be able to deal also with very large networks (say, thousands of genes). Its performances are also tested both on artificial data (generated with linear models) and on real data obtained by Gardner et al. from the SOS pathway in Escherichia coli. |
1701.03164 | Danielle Oliveira Costa Santos Dr. | A.J. da Silva, S. Floquet, D.O.C. Santos | Statistical crossover and nonextensive behavior of the neuronal
short-term depression | 13 pages, 4 figures, J Biol Phys (2017) | null | 10.1007/s10867-017-9474-3 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The theoretical basis of neuronal coding, associated with short term
degradation in synaptic transmission, is a matter of debate in the literature.
In fact, electrophysiological signals are commonly characterized as inversely
proportional to stimulus intensity. Among theoretical descriptions of this
phenomenon, models based on $1/f$-dependency are employed to investigate the
biophysical properties of the short term synaptic depression. In this work we
formulated a model based on a paradigmatic \textit{q}-differential equation to
obtain a generalized formalism useful for investigation of nonextensivity in
this specific type of synaptic plasticity. Our analysis reveals nonextensivity
in data from electrophysiological recordings and also a statistical crossover
in neurotransmission. In particular, statistical transitions providesadditional
support to the hypothesis of heterogeneous release probability of
neurotransmitters. On the other hand, the simple vesicle model agrees with data
only at low frequency stimulations. Thus, the present work presents a method to
demonstrate that short-term depression is not only governed by random
mechanisms but also by a nonextensive behavior. Our findings also conciliate
morphological and electrophysiological investigations into a coherent
biophysical scenario.
| [
{
"created": "Tue, 27 Dec 2016 13:16:06 GMT",
"version": "v1"
},
{
"created": "Sun, 5 Feb 2017 12:09:22 GMT",
"version": "v2"
},
{
"created": "Tue, 14 Nov 2017 21:36:15 GMT",
"version": "v3"
},
{
"created": "Fri, 17 Nov 2017 21:48:46 GMT",
"version": "v4"
}
] | 2017-11-21 | [
[
"da Silva",
"A. J.",
""
],
[
"Floquet",
"S.",
""
],
[
"Santos",
"D. O. C.",
""
]
] | The theoretical basis of neuronal coding, associated with short term degradation in synaptic transmission, is a matter of debate in the literature. In fact, electrophysiological signals are commonly characterized as inversely proportional to stimulus intensity. Among theoretical descriptions of this phenomenon, models based on $1/f$-dependency are employed to investigate the biophysical properties of the short term synaptic depression. In this work we formulated a model based on a paradigmatic \textit{q}-differential equation to obtain a generalized formalism useful for investigation of nonextensivity in this specific type of synaptic plasticity. Our analysis reveals nonextensivity in data from electrophysiological recordings and also a statistical crossover in neurotransmission. In particular, statistical transitions providesadditional support to the hypothesis of heterogeneous release probability of neurotransmitters. On the other hand, the simple vesicle model agrees with data only at low frequency stimulations. Thus, the present work presents a method to demonstrate that short-term depression is not only governed by random mechanisms but also by a nonextensive behavior. Our findings also conciliate morphological and electrophysiological investigations into a coherent biophysical scenario. |
q-bio/0511015 | SANDra KANani | Sandra Kanani, Alain Pumir, Valentine Krinsky | Genetically engineered cardiac pacemaker: stem cells transfected with
HCN2 gene and myocytes - a model | null | null | null | null | q-bio.CB | null | Artificial biological pacemakers were developed and tested in canine
ventricles. Next steps will require obtaining oscillations sensitive to
external regulations, and robust with respect to long term drifts of expression
levels of pacemaker currents and gap junctions. We introduce mathematical
models intended to be used in parallel with the experiments.
The models describe human mesenchymal stem cells ({\it hMSC}) transfected
with HCN2 genes and connected to myocytes. They are intended to mimic
experiments with oscillation induction in a cell pair, in cell culture and in
the cardiac tissue. We give examples of oscillations in a cell pair, in a 1 dim
cell culture, and oscillation dependence on number of pacemaker channels per
cell and number of gap junctions. The models permit to mimic experiments with
levels of gene expressions not achieved yet, and to predict if the work to
achieve this levels will significantly increase the quality of oscillations.
This give arguments for selecting the directions of the experimental work.
| [
{
"created": "Mon, 14 Nov 2005 11:22:50 GMT",
"version": "v1"
},
{
"created": "Tue, 15 Nov 2005 10:14:21 GMT",
"version": "v2"
},
{
"created": "Wed, 16 Nov 2005 15:16:58 GMT",
"version": "v3"
}
] | 2007-05-23 | [
[
"Kanani",
"Sandra",
""
],
[
"Pumir",
"Alain",
""
],
[
"Krinsky",
"Valentine",
""
]
] | Artificial biological pacemakers were developed and tested in canine ventricles. Next steps will require obtaining oscillations sensitive to external regulations, and robust with respect to long term drifts of expression levels of pacemaker currents and gap junctions. We introduce mathematical models intended to be used in parallel with the experiments. The models describe human mesenchymal stem cells ({\it hMSC}) transfected with HCN2 genes and connected to myocytes. They are intended to mimic experiments with oscillation induction in a cell pair, in cell culture and in the cardiac tissue. We give examples of oscillations in a cell pair, in a 1 dim cell culture, and oscillation dependence on number of pacemaker channels per cell and number of gap junctions. The models permit to mimic experiments with levels of gene expressions not achieved yet, and to predict if the work to achieve this levels will significantly increase the quality of oscillations. This give arguments for selecting the directions of the experimental work. |
0907.1159 | Vasile Morariu | Vasile V. Morariu, Luiza Buimaga-Iarinca | Autoregressive Modeling of Coding Sequence Lengths in Bacterial Genome | 11 pages, 5 figures, 2 tables | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Previous investigation of coding sequence lengths (CDS) in the bacterial
circular chromosome revealed short range correlation in the series of these
data. We have further analyzed the averaged periodograms of these series and we
found that the organization of CDS can be well described by first order
autoregressive processes. This involves interaction between the neighboring
terms. The autoregressive analysis may have great potential in modeling various
physical and biological processes like light emission of galaxies, protein
organization, cell flickering, cognitive processes and perhaps others.
| [
{
"created": "Tue, 7 Jul 2009 08:05:45 GMT",
"version": "v1"
}
] | 2009-07-08 | [
[
"Morariu",
"Vasile V.",
""
],
[
"Buimaga-Iarinca",
"Luiza",
""
]
] | Previous investigation of coding sequence lengths (CDS) in the bacterial circular chromosome revealed short range correlation in the series of these data. We have further analyzed the averaged periodograms of these series and we found that the organization of CDS can be well described by first order autoregressive processes. This involves interaction between the neighboring terms. The autoregressive analysis may have great potential in modeling various physical and biological processes like light emission of galaxies, protein organization, cell flickering, cognitive processes and perhaps others. |
1705.08753 | Rukhsan Ul Haq Wani | Rukhsan Ul Haq and Shalini Harkar | Quantum theory of time perception: phases,clocks and quantum algebra | 8pp,typos corrected,references added | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Experience of time is one of the primordial human experiences which is deeply
tied to human consciousness. But despite this intimate relation of time with
human conscious experience, time has proved to be very elusive. Particularly in
physics, though there is already some understanding of time, there are still so
many paradoxes that plague this understanding. In this paper we take rather a
different route to question of time. We first attempt to come up with a
theoretical understanding of time perception. Quite interestingly we find that
quantum theory provides an algebraic formulation within which we can understand
some essential aspects of time perception by human mind. We then ask whether a
similar formalism can furnish the understanding of time as well and find
connections of our formulation of time with similar works by other researchers.
Our underlying approach to question of time has been inspired by R. W. Hamilton
who considers algebra as science of pure time. Hence our work has an extensive
algebraic flavor. Our work also incorporates another approach based on
Kauffman's iterant algebra which relates time to underlying recursions and
oscillations. We believe that our work will initiate more investigations in
this direction.
| [
{
"created": "Mon, 1 May 2017 13:08:10 GMT",
"version": "v1"
},
{
"created": "Thu, 15 Jun 2017 14:54:38 GMT",
"version": "v2"
}
] | 2017-06-16 | [
[
"Haq",
"Rukhsan Ul",
""
],
[
"Harkar",
"Shalini",
""
]
] | Experience of time is one of the primordial human experiences which is deeply tied to human consciousness. But despite this intimate relation of time with human conscious experience, time has proved to be very elusive. Particularly in physics, though there is already some understanding of time, there are still so many paradoxes that plague this understanding. In this paper we take rather a different route to question of time. We first attempt to come up with a theoretical understanding of time perception. Quite interestingly we find that quantum theory provides an algebraic formulation within which we can understand some essential aspects of time perception by human mind. We then ask whether a similar formalism can furnish the understanding of time as well and find connections of our formulation of time with similar works by other researchers. Our underlying approach to question of time has been inspired by R. W. Hamilton who considers algebra as science of pure time. Hence our work has an extensive algebraic flavor. Our work also incorporates another approach based on Kauffman's iterant algebra which relates time to underlying recursions and oscillations. We believe that our work will initiate more investigations in this direction. |
0808.3622 | Steven N. Evans | Kenneth W. Wachter and David R. Steinsaltz and Steven N. Evans | Vital rates from the action of mutation accumulation | 17 pages, 7 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | New models for evolutionary processes of mutation accumulation allow
hypotheses about the age-specificity of mutational effects to be translated
into predictions of heterogeneous population hazard functions. We apply these
models to questions in the biodemography of longevity, including proposed
explanations of Gompertz hazards and mortality plateaus, and use them to
explore the possibility of melding evolutionary and functional models of aging.
| [
{
"created": "Wed, 27 Aug 2008 03:27:24 GMT",
"version": "v1"
},
{
"created": "Thu, 27 Aug 2009 18:00:11 GMT",
"version": "v2"
}
] | 2009-08-27 | [
[
"Wachter",
"Kenneth W.",
""
],
[
"Steinsaltz",
"David R.",
""
],
[
"Evans",
"Steven N.",
""
]
] | New models for evolutionary processes of mutation accumulation allow hypotheses about the age-specificity of mutational effects to be translated into predictions of heterogeneous population hazard functions. We apply these models to questions in the biodemography of longevity, including proposed explanations of Gompertz hazards and mortality plateaus, and use them to explore the possibility of melding evolutionary and functional models of aging. |
1403.4636 | Adam Cohen | Peng Zou (Harvard University), Yongxin Zhao (University of Alberta),
Adam D. Douglass (University of Utah), Daniel R. Hochbaum (Harvard
University), Daan Brinks (Harvard University), Christopher A. Werley (Harvard
University), D. Jed Harrison (University of Alberta), Robert E. Campbell
(University of Alberta), Adam E. Cohen (Harvard University) | Bright and fast voltage reporters across the visible spectrum via
electrochromic FRET (eFRET) | * Denotes equal contribution. For correspondence regarding the
library screen: robert.e.campbell@ualberta.ca; For other correspondence:
cohen@chemistry.harvard.edu | null | null | null | q-bio.BM physics.bio-ph q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present a palette of brightly fluorescent genetically encoded voltage
indicators (GEVIs) with excitation and emission peaks spanning the visible
spectrum, sensitivities from 6 - 10% Delta F/F per 100 mV, and half-maximal
response times from 1 - 7 ms. A fluorescent protein is fused to an
Archaerhodopsin-derived voltage sensor. Voltage-induced shifts in the
absorption spectrum of the rhodopsin lead to voltage-dependent nonradiative
quenching of the appended fluorescent protein. Through a library screen, we
identified linkers and fluorescent protein combinations which reported neuronal
action potentials in cultured rat hippocampal neurons with a single-trial
signal-to-noise ratio from 6.6 to 11.6 in a 1 kHz imaging bandwidth at modest
illumination intensity. The freedom to choose a voltage indicator from an array
of colors facilitates multicolor voltage imaging, as well as combination with
other optical reporters and optogenetic actuators.
| [
{
"created": "Tue, 18 Mar 2014 22:39:50 GMT",
"version": "v1"
}
] | 2014-03-20 | [
[
"Zou",
"Peng",
"",
"Harvard University"
],
[
"Zhao",
"Yongxin",
"",
"University of Alberta"
],
[
"Douglass",
"Adam D.",
"",
"University of Utah"
],
[
"Hochbaum",
"Daniel R.",
"",
"Harvard\n University"
],
[
"Brinks",
"Daan",
"",
"Harvard University"
],
[
"Werley",
"Christopher A.",
"",
"Harvard\n University"
],
[
"Harrison",
"D. Jed",
"",
"University of Alberta"
],
[
"Campbell",
"Robert E.",
"",
"University of Alberta"
],
[
"Cohen",
"Adam E.",
"",
"Harvard University"
]
] | We present a palette of brightly fluorescent genetically encoded voltage indicators (GEVIs) with excitation and emission peaks spanning the visible spectrum, sensitivities from 6 - 10% Delta F/F per 100 mV, and half-maximal response times from 1 - 7 ms. A fluorescent protein is fused to an Archaerhodopsin-derived voltage sensor. Voltage-induced shifts in the absorption spectrum of the rhodopsin lead to voltage-dependent nonradiative quenching of the appended fluorescent protein. Through a library screen, we identified linkers and fluorescent protein combinations which reported neuronal action potentials in cultured rat hippocampal neurons with a single-trial signal-to-noise ratio from 6.6 to 11.6 in a 1 kHz imaging bandwidth at modest illumination intensity. The freedom to choose a voltage indicator from an array of colors facilitates multicolor voltage imaging, as well as combination with other optical reporters and optogenetic actuators. |
1705.03321 | Hamid Reza Hassanzadeh | Hamid Reza Hassanzadeh, Pushkar Kolhe, Charles L. Isbell, May D. Wang | MotifMark: Finding Regulatory Motifs in DNA Sequences | null | null | null | null | q-bio.QM cs.LG q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The interaction between proteins and DNA is a key driving force in a
significant number of biological processes such as transcriptional regulation,
repair, recombination, splicing, and DNA modification. The identification of
DNA-binding sites and the specificity of target proteins in binding to these
regions are two important steps in understanding the mechanisms of these
biological activities. A number of high-throughput technologies have recently
emerged that try to quantify the affinity between proteins and DNA motifs.
Despite their success, these technologies have their own limitations and fall
short in precise characterization of motifs, and as a result, require further
downstream analysis to extract useful and interpretable information from a
haystack of noisy and inaccurate data. Here we propose MotifMark, a new
algorithm based on graph theory and machine learning, that can find binding
sites on candidate probes and rank their specificity in regard to the
underlying transcription factor. We developed a pipeline to analyze
experimental data derived from compact universal protein binding microarrays
and benchmarked it against two of the most accurate motif search methods. Our
results indicate that MotifMark can be a viable alternative technique for
prediction of motif from protein binding microarrays and possibly other related
high-throughput techniques.
| [
{
"created": "Thu, 4 May 2017 14:50:12 GMT",
"version": "v1"
}
] | 2017-05-10 | [
[
"Hassanzadeh",
"Hamid Reza",
""
],
[
"Kolhe",
"Pushkar",
""
],
[
"Isbell",
"Charles L.",
""
],
[
"Wang",
"May D.",
""
]
] | The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the specificity of target proteins in binding to these regions are two important steps in understanding the mechanisms of these biological activities. A number of high-throughput technologies have recently emerged that try to quantify the affinity between proteins and DNA motifs. Despite their success, these technologies have their own limitations and fall short in precise characterization of motifs, and as a result, require further downstream analysis to extract useful and interpretable information from a haystack of noisy and inaccurate data. Here we propose MotifMark, a new algorithm based on graph theory and machine learning, that can find binding sites on candidate probes and rank their specificity in regard to the underlying transcription factor. We developed a pipeline to analyze experimental data derived from compact universal protein binding microarrays and benchmarked it against two of the most accurate motif search methods. Our results indicate that MotifMark can be a viable alternative technique for prediction of motif from protein binding microarrays and possibly other related high-throughput techniques. |
1401.0413 | Emilio Hernandez-Garcia | Emilio Hernandez-Garcia, Els Heinsalu, Cristobal Lopez | Spatial patterns of competing random walkers | 38 pages, including 6 figures | Ecological Complexity 21, 166-176 (2015) | 10.1016/j.ecocom.2014.06.005 | null | q-bio.PE cond-mat.stat-mech nlin.PS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We review recent results obtained from simple individual-based models of
biological competition in which birth and death rates of an organism depend on
the presence of other competing organisms close to it. In addition the
individuals perform random walks of different types (Gaussian diffusion and
L\'{e}vy flights). We focus on how competition and random motions affect each
other, from which spatial instabilities and extinctions arise. Under suitable
conditions, competitive interactions lead to clustering of individuals and
periodic pattern formation. Random motion has a homogenizing effect and then
delays this clustering instability. When individuals from species differing in
their random walk characteristics are allowed to compete together, the ones
with a tendency to form narrower clusters get a competitive advantage over the
others. Mean-field deterministic equations are analyzed and compared with the
outcome of the individual-based simulations.
| [
{
"created": "Thu, 2 Jan 2014 11:08:02 GMT",
"version": "v1"
},
{
"created": "Fri, 23 May 2014 14:06:39 GMT",
"version": "v2"
}
] | 2015-03-03 | [
[
"Hernandez-Garcia",
"Emilio",
""
],
[
"Heinsalu",
"Els",
""
],
[
"Lopez",
"Cristobal",
""
]
] | We review recent results obtained from simple individual-based models of biological competition in which birth and death rates of an organism depend on the presence of other competing organisms close to it. In addition the individuals perform random walks of different types (Gaussian diffusion and L\'{e}vy flights). We focus on how competition and random motions affect each other, from which spatial instabilities and extinctions arise. Under suitable conditions, competitive interactions lead to clustering of individuals and periodic pattern formation. Random motion has a homogenizing effect and then delays this clustering instability. When individuals from species differing in their random walk characteristics are allowed to compete together, the ones with a tendency to form narrower clusters get a competitive advantage over the others. Mean-field deterministic equations are analyzed and compared with the outcome of the individual-based simulations. |
2301.01445 | Evan Patterson | Rebekah Aduddell, James Fairbanks, Amit Kumar, Pablo S. Ocal, Evan
Patterson, Brandon T. Shapiro | A compositional account of motifs, mechanisms, and dynamics in
biochemical regulatory networks | Final version published in Compositionality | Compositionality, Volume 6 (2024) (May 13, 2024)
compositionality:13637 | 10.32408/compositionality-6-2 | null | q-bio.MN math.CT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Regulatory networks depict promoting or inhibiting interactions between
molecules in a biochemical system. We introduce a category-theoretic formalism
for regulatory networks, using signed graphs to model the networks and signed
functors to describe occurrences of one network in another, especially
occurrences of network motifs. With this foundation, we establish functorial
mappings between regulatory networks and other mathematical models in
biochemistry. We construct a functor from reaction networks, modeled as Petri
nets with signed links, to regulatory networks, enabling us to precisely define
when a reaction network could be a physical mechanism underlying a regulatory
network. Turning to quantitative models, we associate a regulatory network with
a Lotka-Volterra system of differential equations, defining a functor from the
category of signed graphs to a category of parameterized dynamical systems. We
extend this result from closed to open systems, demonstrating that
Lotka-Volterra dynamics respects not only inclusions and collapsings of
regulatory networks, but also the process of building up complex regulatory
networks by gluing together simpler pieces. Formally, we use the theory of
structured cospans to produce a lax double functor from the double category of
open signed graphs to that of open parameterized dynamical systems. Throughout
the paper, we ground the categorical formalism in examples inspired by systems
biology.
| [
{
"created": "Wed, 4 Jan 2023 04:32:08 GMT",
"version": "v1"
},
{
"created": "Tue, 28 Mar 2023 22:35:34 GMT",
"version": "v2"
},
{
"created": "Sun, 5 May 2024 21:26:08 GMT",
"version": "v3"
}
] | 2024-08-07 | [
[
"Aduddell",
"Rebekah",
""
],
[
"Fairbanks",
"James",
""
],
[
"Kumar",
"Amit",
""
],
[
"Ocal",
"Pablo S.",
""
],
[
"Patterson",
"Evan",
""
],
[
"Shapiro",
"Brandon T.",
""
]
] | Regulatory networks depict promoting or inhibiting interactions between molecules in a biochemical system. We introduce a category-theoretic formalism for regulatory networks, using signed graphs to model the networks and signed functors to describe occurrences of one network in another, especially occurrences of network motifs. With this foundation, we establish functorial mappings between regulatory networks and other mathematical models in biochemistry. We construct a functor from reaction networks, modeled as Petri nets with signed links, to regulatory networks, enabling us to precisely define when a reaction network could be a physical mechanism underlying a regulatory network. Turning to quantitative models, we associate a regulatory network with a Lotka-Volterra system of differential equations, defining a functor from the category of signed graphs to a category of parameterized dynamical systems. We extend this result from closed to open systems, demonstrating that Lotka-Volterra dynamics respects not only inclusions and collapsings of regulatory networks, but also the process of building up complex regulatory networks by gluing together simpler pieces. Formally, we use the theory of structured cospans to produce a lax double functor from the double category of open signed graphs to that of open parameterized dynamical systems. Throughout the paper, we ground the categorical formalism in examples inspired by systems biology. |
2305.11198 | J Gregory Caporaso | Christopher R. Keefe, Matthew R. Dillon, Chloe Herman, Mary Jewell,
Colin V. Wood, Evan Bolyen, J. Gregory Caporaso | Facilitating Bioinformatics Reproducibility | 5 pages, 2 figures | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Study reproducibility is essential to corroborate, build on, and learn from
the results of scientific research but is notoriously challenging in
bioinformatics, which often involves large data sets and complex analytic
workflows involving many different tools. Additionally many biologists aren't
trained in how to effectively record their bioinformatics analysis steps to
ensure reproducibility, so critical information is often missing. Software
tools used in bioinformatics can automate provenance tracking of the results
they generate, removing most barriers to bioinformatics reproducibility. Here
we present an implementation of that idea, Provenance Replay, a tool for
generating new executable code from results generated with the QIIME 2
bioinformatics platform, and discuss considerations for bioinformatics
developers who wish to implement similar functionality in their software.
| [
{
"created": "Thu, 18 May 2023 14:33:23 GMT",
"version": "v1"
}
] | 2023-05-22 | [
[
"Keefe",
"Christopher R.",
""
],
[
"Dillon",
"Matthew R.",
""
],
[
"Herman",
"Chloe",
""
],
[
"Jewell",
"Mary",
""
],
[
"Wood",
"Colin V.",
""
],
[
"Bolyen",
"Evan",
""
],
[
"Caporaso",
"J. Gregory",
""
]
] | Study reproducibility is essential to corroborate, build on, and learn from the results of scientific research but is notoriously challenging in bioinformatics, which often involves large data sets and complex analytic workflows involving many different tools. Additionally many biologists aren't trained in how to effectively record their bioinformatics analysis steps to ensure reproducibility, so critical information is often missing. Software tools used in bioinformatics can automate provenance tracking of the results they generate, removing most barriers to bioinformatics reproducibility. Here we present an implementation of that idea, Provenance Replay, a tool for generating new executable code from results generated with the QIIME 2 bioinformatics platform, and discuss considerations for bioinformatics developers who wish to implement similar functionality in their software. |
2402.15360 | Amanda Navine | Amanda K. Navine, Tom Denton, Matthew J. Weldy, Patrick J. Hart | All Thresholds Barred: Direct Estimation of Call Density in Bioacoustic
Data | 14 pages, 6 figures, 3 tables; submitted to Frontiers in Bird
Science; Our Hawaiian PAM dataset and classifier scores, as well as
annotation information for the three study species, can be found on Zenodo at
https://doi.org/10.5281/zenodo.10581530. The fully annotated Powdermill
dataset assembled by Chronister et al. that was used in this study is
available at https://doi.org/10.1002/ecy.3329 | null | null | null | q-bio.QM cs.LG cs.SD eess.AS | http://creativecommons.org/licenses/by/4.0/ | Passive acoustic monitoring (PAM) studies generate thousands of hours of
audio, which may be used to monitor specific animal populations, conduct broad
biodiversity surveys, detect threats such as poachers, and more. Machine
learning classifiers for species identification are increasingly being used to
process the vast amount of audio generated by bioacoustic surveys, expediting
analysis and increasing the utility of PAM as a management tool. In common
practice, a threshold is applied to classifier output scores, and scores above
the threshold are aggregated into a detection count. The choice of threshold
produces biased counts of vocalizations, which are subject to false
positive/negative rates that may vary across subsets of the dataset. In this
work, we advocate for directly estimating call density: The proportion of
detection windows containing the target vocalization, regardless of classifier
score. Our approach targets a desirable ecological estimator and provides a
more rigorous grounding for identifying the core problems caused by
distribution shifts -- when the defining characteristics of the data
distribution change -- and designing strategies to mitigate them. We propose a
validation scheme for estimating call density in a body of data and obtain,
through Bayesian reasoning, probability distributions of confidence scores for
both the positive and negative classes. We use these distributions to predict
site-level densities, which may be subject to distribution shifts. We test our
proposed methods on a real-world study of Hawaiian birds and provide simulation
results leveraging existing fully annotated datasets, demonstrating robustness
to variations in call density and classifier model quality.
| [
{
"created": "Fri, 23 Feb 2024 14:52:44 GMT",
"version": "v1"
}
] | 2024-02-26 | [
[
"Navine",
"Amanda K.",
""
],
[
"Denton",
"Tom",
""
],
[
"Weldy",
"Matthew J.",
""
],
[
"Hart",
"Patrick J.",
""
]
] | Passive acoustic monitoring (PAM) studies generate thousands of hours of audio, which may be used to monitor specific animal populations, conduct broad biodiversity surveys, detect threats such as poachers, and more. Machine learning classifiers for species identification are increasingly being used to process the vast amount of audio generated by bioacoustic surveys, expediting analysis and increasing the utility of PAM as a management tool. In common practice, a threshold is applied to classifier output scores, and scores above the threshold are aggregated into a detection count. The choice of threshold produces biased counts of vocalizations, which are subject to false positive/negative rates that may vary across subsets of the dataset. In this work, we advocate for directly estimating call density: The proportion of detection windows containing the target vocalization, regardless of classifier score. Our approach targets a desirable ecological estimator and provides a more rigorous grounding for identifying the core problems caused by distribution shifts -- when the defining characteristics of the data distribution change -- and designing strategies to mitigate them. We propose a validation scheme for estimating call density in a body of data and obtain, through Bayesian reasoning, probability distributions of confidence scores for both the positive and negative classes. We use these distributions to predict site-level densities, which may be subject to distribution shifts. We test our proposed methods on a real-world study of Hawaiian birds and provide simulation results leveraging existing fully annotated datasets, demonstrating robustness to variations in call density and classifier model quality. |
1908.02334 | Emily Diller | Emily E Diller, Sha Cao, Beth Ey, Robert Lober, Jason G Parker | Predicted disease compositions of human gliomas estimated from
multiparametric MRI can predict endothelial proliferation, tumor grade, and
overall survival | 13 pages, 3 figures, 5 tables | null | null | null | q-bio.QM cs.LG eess.IV physics.med-ph stat.AP stat.ML | http://creativecommons.org/licenses/by/4.0/ | Background and Purpose: Biopsy is the main determinants of glioma clinical
management, but require invasive sampling that fail to detect relevant features
because of tumor heterogeneity. The purpose of this study was to evaluate the
accuracy of a voxel-wise, multiparametric MRI radiomic method to predict
features and develop a minimally invasive method to objectively assess
neoplasms.
Methods: Multiparametric MRI were registered to T1-weighted gadolinium
contrast-enhanced data using a 12 degree-of-freedom affine model. The
retrospectively collected MRI data included T1-weighted, T1-weighted gadolinium
contrast-enhanced, T2-weighted, fluid attenuated inversion recovery, and
multi-b-value diffusion-weighted acquired at 1.5T or 3.0T. Clinical experts
provided voxel-wise annotations for five disease states on a subset of patients
to establish a training feature vector of 611,930 observations. Then, a
k-nearest-neighbor (k-NN) classifier was trained using a 25% hold-out design.
The trained k-NN model was applied to 13,018,171 observations from seventeen
histologically confirmed glioma patients. Linear regression tested overall
survival (OS) relationship to predicted disease compositions (PDC) and
diagnostic age (alpha = 0.05). Canonical discriminant analysis tested if PDC
and diagnostic age could differentiate clinical, genetic, and microscopic
factors (alpha = 0.05).
Results: The model predicted voxel annotation class with a Dice similarity
coefficient of 94.34% +/- 2.98. Linear combinations of PDCs and diagnostic age
predicted OS (p = 0.008), grade (p = 0.014), and endothelia proliferation (p =
0.003); but fell short predicting gene mutations for TP53BP1 and IDH1.
Conclusions: This voxel-wise, multi-parametric MRI radiomic strategy holds
potential as a non-invasive decision-making aid for clinicians managing
patients with glioma.
| [
{
"created": "Tue, 6 Aug 2019 19:10:32 GMT",
"version": "v1"
}
] | 2019-08-08 | [
[
"Diller",
"Emily E",
""
],
[
"Cao",
"Sha",
""
],
[
"Ey",
"Beth",
""
],
[
"Lober",
"Robert",
""
],
[
"Parker",
"Jason G",
""
]
] | Background and Purpose: Biopsy is the main determinants of glioma clinical management, but require invasive sampling that fail to detect relevant features because of tumor heterogeneity. The purpose of this study was to evaluate the accuracy of a voxel-wise, multiparametric MRI radiomic method to predict features and develop a minimally invasive method to objectively assess neoplasms. Methods: Multiparametric MRI were registered to T1-weighted gadolinium contrast-enhanced data using a 12 degree-of-freedom affine model. The retrospectively collected MRI data included T1-weighted, T1-weighted gadolinium contrast-enhanced, T2-weighted, fluid attenuated inversion recovery, and multi-b-value diffusion-weighted acquired at 1.5T or 3.0T. Clinical experts provided voxel-wise annotations for five disease states on a subset of patients to establish a training feature vector of 611,930 observations. Then, a k-nearest-neighbor (k-NN) classifier was trained using a 25% hold-out design. The trained k-NN model was applied to 13,018,171 observations from seventeen histologically confirmed glioma patients. Linear regression tested overall survival (OS) relationship to predicted disease compositions (PDC) and diagnostic age (alpha = 0.05). Canonical discriminant analysis tested if PDC and diagnostic age could differentiate clinical, genetic, and microscopic factors (alpha = 0.05). Results: The model predicted voxel annotation class with a Dice similarity coefficient of 94.34% +/- 2.98. Linear combinations of PDCs and diagnostic age predicted OS (p = 0.008), grade (p = 0.014), and endothelia proliferation (p = 0.003); but fell short predicting gene mutations for TP53BP1 and IDH1. Conclusions: This voxel-wise, multi-parametric MRI radiomic strategy holds potential as a non-invasive decision-making aid for clinicians managing patients with glioma. |
2402.13555 | Xiangzhe Kong | Xiangzhe Kong, Yinjun Jia, Wenbing Huang, Yang Liu | Full-Atom Peptide Design with Geometric Latent Diffusion | 25 pages | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Peptide design plays a pivotal role in therapeutics, allowing brand new
possibility to leverage target binding sites that are previously undruggable.
Most existing methods are either inefficient or only concerned with the
target-agnostic design of 1D sequences. In this paper, we propose a generative
model for full-atom \textbf{Pep}tide design with \textbf{G}eometric
\textbf{LA}tent \textbf{D}iffusion (PepGLAD). We first establish a benchmark
consisting of both 1D sequences and 3D structures from Protein Data Bank (PDB)
and literature for systematic evaluation. We then identify two major challenges
of leveraging current diffusion-based models for peptide design: the full-atom
geometry and the variable binding geometry. To tackle the first challenge,
PepGLAD derives a variational autoencoder that first encodes full-atom residues
of variable size into fixed-dimensional latent representations, and then
decodes back to the residue space after conducting the diffusion process in the
latent space. For the second issue, PepGLAD explores a receptor-specific affine
transformation to convert the 3D coordinates into a shared standard space,
enabling better generalization ability across different binding shapes.
Experimental Results show that our method not only improves diversity and
binding affinity significantly in the task of sequence-structure co-design, but
also excels at recovering reference structures for binding conformation
generation.
| [
{
"created": "Wed, 21 Feb 2024 06:25:35 GMT",
"version": "v1"
},
{
"created": "Wed, 22 May 2024 03:20:40 GMT",
"version": "v2"
}
] | 2024-05-24 | [
[
"Kong",
"Xiangzhe",
""
],
[
"Jia",
"Yinjun",
""
],
[
"Huang",
"Wenbing",
""
],
[
"Liu",
"Yang",
""
]
] | Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable. Most existing methods are either inefficient or only concerned with the target-agnostic design of 1D sequences. In this paper, we propose a generative model for full-atom \textbf{Pep}tide design with \textbf{G}eometric \textbf{LA}tent \textbf{D}iffusion (PepGLAD). We first establish a benchmark consisting of both 1D sequences and 3D structures from Protein Data Bank (PDB) and literature for systematic evaluation. We then identify two major challenges of leveraging current diffusion-based models for peptide design: the full-atom geometry and the variable binding geometry. To tackle the first challenge, PepGLAD derives a variational autoencoder that first encodes full-atom residues of variable size into fixed-dimensional latent representations, and then decodes back to the residue space after conducting the diffusion process in the latent space. For the second issue, PepGLAD explores a receptor-specific affine transformation to convert the 3D coordinates into a shared standard space, enabling better generalization ability across different binding shapes. Experimental Results show that our method not only improves diversity and binding affinity significantly in the task of sequence-structure co-design, but also excels at recovering reference structures for binding conformation generation. |
2306.01313 | Ivana Pajic-Lijakovic Dr. | Ivana Pajic-Lijakovic and Milan Milivojevic | Cell jamming and unjamming in development: physical aspects | 18 pages, 4 figures | null | null | null | q-bio.CB | http://creativecommons.org/licenses/by/4.0/ | Collective cell migration is essential for a wide range of biological
processes such as: morphogenesis, wound healing, and cancer spreading. However,
it is well known that migrating epithelial collectives frequently undergo
jamming, stay trapped some period of time, and then start migration again.
Consequently, only a part of epithelial cells actively contributes to the
tissue development. In contrast to epithelial cells, migrating mesenchymal
collectives successfully avoid the jamming. It has been confirmed that the
epithelial unjamming cannot be treated as the epithelial-to-mesenchymal
transition. Some other mechanism is responsible for the epithelial
jamming/unjamming. Despite extensive research devoted to study the cell
jamming/unjamming, we still do not understand the origin of this phenomenon.
The origin is connected to physical factors such as: the cell compressive
residual stress accumulation and surface characteristics of migrating
(unjamming) and resting (jamming) epithelial clusters which depend primarily on
the strength of cell-cell adhesion contacts and cell contractility. The main
goal of this theoretical consideration is to clarify these cause-consequence
relations.
| [
{
"created": "Fri, 2 Jun 2023 07:24:18 GMT",
"version": "v1"
}
] | 2023-06-05 | [
[
"Pajic-Lijakovic",
"Ivana",
""
],
[
"Milivojevic",
"Milan",
""
]
] | Collective cell migration is essential for a wide range of biological processes such as: morphogenesis, wound healing, and cancer spreading. However, it is well known that migrating epithelial collectives frequently undergo jamming, stay trapped some period of time, and then start migration again. Consequently, only a part of epithelial cells actively contributes to the tissue development. In contrast to epithelial cells, migrating mesenchymal collectives successfully avoid the jamming. It has been confirmed that the epithelial unjamming cannot be treated as the epithelial-to-mesenchymal transition. Some other mechanism is responsible for the epithelial jamming/unjamming. Despite extensive research devoted to study the cell jamming/unjamming, we still do not understand the origin of this phenomenon. The origin is connected to physical factors such as: the cell compressive residual stress accumulation and surface characteristics of migrating (unjamming) and resting (jamming) epithelial clusters which depend primarily on the strength of cell-cell adhesion contacts and cell contractility. The main goal of this theoretical consideration is to clarify these cause-consequence relations. |
2405.20359 | Cristina-Maria Valcu | Cristina-Maria Valcu, Richard A. Scheltema, Ralf M. Schweiggert, Mihai
Valcu, Kim Teltscher, Dirk M. Walther, Reinhold Carle and Bart Kempenaers | Life history shapes variation in egg composition in the blue tit
Cyanistes caeruleus | null | Communications Biology (2019) 2:6 | 10.1038/s42003-018-0247-8 | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Maternal investment directly shapes early developmental conditions and
therefore has longterm fitness consequences for the offspring. In oviparous
species prenatal maternal investment is fixed at the time of laying. To ensure
the best survival chances for most of their offspring, females must equip their
eggs with the resources required to perform well under various circumstances,
yet the actual mechanisms remain unknown. Here we describe the blue tit egg
albumen and yolk proteomes and evaluate their potential to mediate maternal
effects. We show that variation in egg composition (proteins, lipids,
carotenoids) primarily depends on laying order and female age. Egg proteomic
profiles are mainly driven by laying order, and investment in the egg proteome
is functionally biased among eggs. Our results suggest that maternal effects on
egg composition result from both passive and active (partly compensatory)
mechanisms, and that variation in egg composition creates diverse biochemical
environments for embryonic development.
| [
{
"created": "Thu, 30 May 2024 07:54:25 GMT",
"version": "v1"
}
] | 2024-06-03 | [
[
"Valcu",
"Cristina-Maria",
""
],
[
"Scheltema",
"Richard A.",
""
],
[
"Schweiggert",
"Ralf M.",
""
],
[
"Valcu",
"Mihai",
""
],
[
"Teltscher",
"Kim",
""
],
[
"Walther",
"Dirk M.",
""
],
[
"Carle",
"Reinhold",
""
],
[
"Kempenaers",
"Bart",
""
]
] | Maternal investment directly shapes early developmental conditions and therefore has longterm fitness consequences for the offspring. In oviparous species prenatal maternal investment is fixed at the time of laying. To ensure the best survival chances for most of their offspring, females must equip their eggs with the resources required to perform well under various circumstances, yet the actual mechanisms remain unknown. Here we describe the blue tit egg albumen and yolk proteomes and evaluate their potential to mediate maternal effects. We show that variation in egg composition (proteins, lipids, carotenoids) primarily depends on laying order and female age. Egg proteomic profiles are mainly driven by laying order, and investment in the egg proteome is functionally biased among eggs. Our results suggest that maternal effects on egg composition result from both passive and active (partly compensatory) mechanisms, and that variation in egg composition creates diverse biochemical environments for embryonic development. |
2405.06645 | Darin Tsui | Darin Tsui, Amirali Aghazadeh | On Recovering Higher-order Interactions from Protein Language Models | null | null | null | null | q-bio.BM cs.AI cs.LG | http://creativecommons.org/licenses/by/4.0/ | Protein language models leverage evolutionary information to perform
state-of-the-art 3D structure and zero-shot variant prediction. Yet, extracting
and explaining all the mutational interactions that govern model predictions
remains difficult as it requires querying the entire amino acid space for $n$
sites using $20^n$ sequences, which is computationally expensive even for
moderate values of $n$ (e.g., $n\sim10$). Although approaches to lower the
sample complexity exist, they often limit the interpretability of the model to
just single and pairwise interactions. Recently, computationally scalable
algorithms relying on the assumption of sparsity in the Fourier domain have
emerged to learn interactions from experimental data. However, extracting
interactions from language models poses unique challenges: it's unclear if
sparsity is always present or if it is the only metric needed to assess the
utility of Fourier algorithms. Herein, we develop a framework to do a
systematic Fourier analysis of the protein language model ESM2 applied on three
proteins-green fluorescent protein (GFP), tumor protein P53 (TP53), and G
domain B1 (GB1)-across various sites for 228 experiments. We demonstrate that
ESM2 is dominated by three regions in the sparsity-ruggedness plane, two of
which are better suited for sparse Fourier transforms. Validations on two
sample proteins demonstrate recovery of all interactions with $R^2=0.72$ in the
more sparse region and $R^2=0.66$ in the more dense region, using only 7
million out of $20^{10}\sim10^{13}$ ESM2 samples, reducing the computational
time by a staggering factor of 15,000. All codes and data are available on our
GitHub repository https://github.com/amirgroup-codes/InteractionRecovery.
| [
{
"created": "Fri, 15 Mar 2024 16:35:47 GMT",
"version": "v1"
}
] | 2024-05-14 | [
[
"Tsui",
"Darin",
""
],
[
"Aghazadeh",
"Amirali",
""
]
] | Protein language models leverage evolutionary information to perform state-of-the-art 3D structure and zero-shot variant prediction. Yet, extracting and explaining all the mutational interactions that govern model predictions remains difficult as it requires querying the entire amino acid space for $n$ sites using $20^n$ sequences, which is computationally expensive even for moderate values of $n$ (e.g., $n\sim10$). Although approaches to lower the sample complexity exist, they often limit the interpretability of the model to just single and pairwise interactions. Recently, computationally scalable algorithms relying on the assumption of sparsity in the Fourier domain have emerged to learn interactions from experimental data. However, extracting interactions from language models poses unique challenges: it's unclear if sparsity is always present or if it is the only metric needed to assess the utility of Fourier algorithms. Herein, we develop a framework to do a systematic Fourier analysis of the protein language model ESM2 applied on three proteins-green fluorescent protein (GFP), tumor protein P53 (TP53), and G domain B1 (GB1)-across various sites for 228 experiments. We demonstrate that ESM2 is dominated by three regions in the sparsity-ruggedness plane, two of which are better suited for sparse Fourier transforms. Validations on two sample proteins demonstrate recovery of all interactions with $R^2=0.72$ in the more sparse region and $R^2=0.66$ in the more dense region, using only 7 million out of $20^{10}\sim10^{13}$ ESM2 samples, reducing the computational time by a staggering factor of 15,000. All codes and data are available on our GitHub repository https://github.com/amirgroup-codes/InteractionRecovery. |
1807.01768 | Anna Maltsev | Anna Maltsev, Michael Stern, Victor Maltsev | Mechanisms of Calcium Leak from Cardiac Sarcoplasmic Reticulum Revealed
by Statistical Mechanics | 20 pages, 6 figures, supplemental material | null | 10.1016/j.bpj.2018.11.277 | null | q-bio.SC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Heart muscle contraction is normally activated by a synchronized Ca release
from sarcoplasmic reticulum (SR), a major intracellular Ca store. However,
under abnormal conditions Ca leaks from the SR, decreasing heart contraction
amplitude and increasing risk of life-threatening arrhythmia. The mechanisms
and regimes of SR operation generating the abnormal Ca leak remain unclear.
Here we employed both numerical and analytical modeling to get mechanistic
insights into the emergent Ca leak phenomenon. Our numerical simulations using
a detailed realistic model of Ca release unit (CRU) reveal sharp transitions
resulting in Ca leak. The emergence of leak is closely mapped mathematically to
the Ising model from statistical mechanics. The system steady-state behavior is
determined by two aggregate parameters: the analogues of magnetic field ($h$)
and the inverse temperature ($\beta$) in the Ising model, for which we have
explicit formulas in terms of SR Ca and release channel opening/closing rates.
The classification of leak regimes takes the shape of a phase $\beta$-$h$
diagram, with the regime boundaries occurring at $h$=0 and a critical value of
$\beta$ ($\beta*$) which we estimate using a classical Ising model and mean
field theory. Our theory predicts that a synchronized Ca leak will occur when
$h$>0 and $\beta>\beta*$ and a disordered leak occurs when $\beta<\beta*$ and
$h$ is not too negative. The disorder leak is distinguished from synchronized
leak (in long-lasting sparks) by larger Peierls contour lengths, an output
parameter reflecting degree of disorder. Thus, in addition to our detailed
numerical model approach we also offer an instantaneous computational tool
using analytical formulas of the Ising model for respective RyR parameters and
SR Ca load that describe and classify phase transitions and leak emergence.
| [
{
"created": "Wed, 4 Jul 2018 20:47:43 GMT",
"version": "v1"
},
{
"created": "Sun, 12 May 2019 17:53:52 GMT",
"version": "v2"
}
] | 2023-07-19 | [
[
"Maltsev",
"Anna",
""
],
[
"Stern",
"Michael",
""
],
[
"Maltsev",
"Victor",
""
]
] | Heart muscle contraction is normally activated by a synchronized Ca release from sarcoplasmic reticulum (SR), a major intracellular Ca store. However, under abnormal conditions Ca leaks from the SR, decreasing heart contraction amplitude and increasing risk of life-threatening arrhythmia. The mechanisms and regimes of SR operation generating the abnormal Ca leak remain unclear. Here we employed both numerical and analytical modeling to get mechanistic insights into the emergent Ca leak phenomenon. Our numerical simulations using a detailed realistic model of Ca release unit (CRU) reveal sharp transitions resulting in Ca leak. The emergence of leak is closely mapped mathematically to the Ising model from statistical mechanics. The system steady-state behavior is determined by two aggregate parameters: the analogues of magnetic field ($h$) and the inverse temperature ($\beta$) in the Ising model, for which we have explicit formulas in terms of SR Ca and release channel opening/closing rates. The classification of leak regimes takes the shape of a phase $\beta$-$h$ diagram, with the regime boundaries occurring at $h$=0 and a critical value of $\beta$ ($\beta*$) which we estimate using a classical Ising model and mean field theory. Our theory predicts that a synchronized Ca leak will occur when $h$>0 and $\beta>\beta*$ and a disordered leak occurs when $\beta<\beta*$ and $h$ is not too negative. The disorder leak is distinguished from synchronized leak (in long-lasting sparks) by larger Peierls contour lengths, an output parameter reflecting degree of disorder. Thus, in addition to our detailed numerical model approach we also offer an instantaneous computational tool using analytical formulas of the Ising model for respective RyR parameters and SR Ca load that describe and classify phase transitions and leak emergence. |
1610.02543 | Richard McMurtrey | Richard J. McMurtrey | Multi-Compartmental Biomaterial Scaffolds for Patterning Neural Tissue
Organoids in Models of Neurodevelopment and Tissue Regeneration | null | J. Tissue Engineering 2016; 7:1-8 | 10.1177/2041731416671926 | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Biomaterials are becoming an essential tool in the study and application of
stem cell research. Various types of biomaterials enable three-dimensional (3D)
culture of stem cells, and, more recently, also enable high-resolution
patterning and organization of multicellular architectures. Biomaterials also
hold potential to provide many additional advantages over cell transplants
alone in regenerative medicine. This paper describes novel designs for
functionalized biomaterial constructs that guide tissue development to targeted
regional identities and structures. Such designs comprise compartmentalized
regions in the biomaterial structure that are functionalized with molecular
factors that form concentration gradients through the construct and guide stem
cell development, axis patterning, and tissue architecture, including
rostral/caudal, ventral/dorsal, or medial/lateral identities of the central
nervous system. The ability to recapitulate innate developmental processes in a
3D environment and under specific controlled conditions has vital application
to advanced models of neurodevelopment and for repair of specific sites of
damaged or diseased neural tissue.
| [
{
"created": "Sat, 8 Oct 2016 15:12:53 GMT",
"version": "v1"
}
] | 2016-10-11 | [
[
"McMurtrey",
"Richard J.",
""
]
] | Biomaterials are becoming an essential tool in the study and application of stem cell research. Various types of biomaterials enable three-dimensional (3D) culture of stem cells, and, more recently, also enable high-resolution patterning and organization of multicellular architectures. Biomaterials also hold potential to provide many additional advantages over cell transplants alone in regenerative medicine. This paper describes novel designs for functionalized biomaterial constructs that guide tissue development to targeted regional identities and structures. Such designs comprise compartmentalized regions in the biomaterial structure that are functionalized with molecular factors that form concentration gradients through the construct and guide stem cell development, axis patterning, and tissue architecture, including rostral/caudal, ventral/dorsal, or medial/lateral identities of the central nervous system. The ability to recapitulate innate developmental processes in a 3D environment and under specific controlled conditions has vital application to advanced models of neurodevelopment and for repair of specific sites of damaged or diseased neural tissue. |
1307.6432 | Casey Dunn | Casey W. Dunn, Mark Howison, and Felipe Zapata | Agalma: an automated phylogenomics workflow | 17 pages, 4 figures | BMC Bioinformatics 14 (2013) 330 | 10.1186/1471-2105-14-330 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In the past decade, transcriptome data have become an important component of
many phylogenetic studies. Phylogenetic studies now regularly include genes
from newly sequenced transcriptomes, as well as publicly available
transcriptomes and genomes. Implementing such a phylogenomic study, however, is
computationally intensive, requires the coordinated use of many complex
software tools, and includes multiple steps for which no published tools exist.
Phylogenomic studies have therefore been manual or semiautomated. In addition
to taking considerable user time, this makes phylogenomic analyses difficult to
reproduce, compare, and extend. In addition, methodological improvements made
in the context of one study often cannot be easily applied and evaluated in the
context of other studies. We present Agalma, an automated tool that conducts
phylogenomic analyses. The user provides raw Illumina transcriptome data, and
Agalma produces annotated assemblies, aligned gene sequence matrices, a
preliminary phylogeny, and detailed diagnostics that allow the investigator to
make extensive assessments of intermediate analysis steps and the final
results. Sequences from other sources, such as externally assembled genomes and
transcriptomes, can also be incorporated in the analyses. Agalma tracks
provenance, profiles processor and memory use, records diagnostics, manages
metadata, and enables rich HTML reports for all stages of the analysis. Agalma
includes a test data set and a built-in test analysis of these data. In
addition to describing Agalma, we here present a sample analysis of a larger
seven-taxon data set. Agalma is available for download at
https://bitbucket.org/caseywdunn/agalma. Agalma allows complex phylogenomic
analyses to be implemented and described unambiguously as a series of
high-level commands. This will enable phylogenomic studies to be readily
reproduced, modified, and extended.
| [
{
"created": "Wed, 24 Jul 2013 14:18:29 GMT",
"version": "v1"
}
] | 2014-01-14 | [
[
"Dunn",
"Casey W.",
""
],
[
"Howison",
"Mark",
""
],
[
"Zapata",
"Felipe",
""
]
] | In the past decade, transcriptome data have become an important component of many phylogenetic studies. Phylogenetic studies now regularly include genes from newly sequenced transcriptomes, as well as publicly available transcriptomes and genomes. Implementing such a phylogenomic study, however, is computationally intensive, requires the coordinated use of many complex software tools, and includes multiple steps for which no published tools exist. Phylogenomic studies have therefore been manual or semiautomated. In addition to taking considerable user time, this makes phylogenomic analyses difficult to reproduce, compare, and extend. In addition, methodological improvements made in the context of one study often cannot be easily applied and evaluated in the context of other studies. We present Agalma, an automated tool that conducts phylogenomic analyses. The user provides raw Illumina transcriptome data, and Agalma produces annotated assemblies, aligned gene sequence matrices, a preliminary phylogeny, and detailed diagnostics that allow the investigator to make extensive assessments of intermediate analysis steps and the final results. Sequences from other sources, such as externally assembled genomes and transcriptomes, can also be incorporated in the analyses. Agalma tracks provenance, profiles processor and memory use, records diagnostics, manages metadata, and enables rich HTML reports for all stages of the analysis. Agalma includes a test data set and a built-in test analysis of these data. In addition to describing Agalma, we here present a sample analysis of a larger seven-taxon data set. Agalma is available for download at https://bitbucket.org/caseywdunn/agalma. Agalma allows complex phylogenomic analyses to be implemented and described unambiguously as a series of high-level commands. This will enable phylogenomic studies to be readily reproduced, modified, and extended. |
1607.00998 | Marco Alberto Javarone | Marco Alberto Javarone | The Host-Pathogen Game: an evolutionary approach to biological
competitions | 17 pages, 7 figures | Front. Phys. 6:94 2018 | 10.3389/fphy.2018.00094 | null | q-bio.PE nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We introduce a model called Host-Pathogen game for studying biological
competitions. Notably, we focus on the invasive dynamics of external agents,
like bacteria, within a host organism. The former are mapped to a population of
defectors that aim to spread in the extracellular medium of the host. In turn,
the latter is composed of cells, mapped to a population of cooperators, that
aim to kill pathogens. The cooperative behavior of cells is fundamental for the
emergence of the living functions of the whole organism, since each one
contributes to a specific set of tasks. So, broadly speaking, their
contribution can be viewed as a form of energy. When bacteria are spatially
close to a cell, the latter can use a fraction of its energy to remove them. On
the other hand, when bacteria survive an attack, they absorb the received
energy, becoming stronger and more resistant to further attacks. In addition,
since bacteria play as defectors, their unique target is to increase their
wealth, without supporting their own kind. As in many living organisms, the
host temperature plays a relevant role in the host-pathogen equilibrium. For
instance, in animals like human beings, a neural mechanism triggers the
increasing of the body temperature in order to activate the immune system.
Here, cooperators succeed once bacteria are completely removed while, in the
opposite scenario, the host undergoes a deep invasive process, like a blood
poisoning. Results of numerical simulations show that the dynamics of the
proposed model allow to reach a variety of states. At a very high level of
abstraction, some of these states seem to be similar to those that can be
observed in some living systems. Therefore, to conclude, we deem that our model
might be exploited for studying further biological phenomena.
| [
{
"created": "Mon, 4 Jul 2016 19:22:03 GMT",
"version": "v1"
},
{
"created": "Fri, 31 Aug 2018 15:48:17 GMT",
"version": "v2"
}
] | 2018-09-03 | [
[
"Javarone",
"Marco Alberto",
""
]
] | We introduce a model called Host-Pathogen game for studying biological competitions. Notably, we focus on the invasive dynamics of external agents, like bacteria, within a host organism. The former are mapped to a population of defectors that aim to spread in the extracellular medium of the host. In turn, the latter is composed of cells, mapped to a population of cooperators, that aim to kill pathogens. The cooperative behavior of cells is fundamental for the emergence of the living functions of the whole organism, since each one contributes to a specific set of tasks. So, broadly speaking, their contribution can be viewed as a form of energy. When bacteria are spatially close to a cell, the latter can use a fraction of its energy to remove them. On the other hand, when bacteria survive an attack, they absorb the received energy, becoming stronger and more resistant to further attacks. In addition, since bacteria play as defectors, their unique target is to increase their wealth, without supporting their own kind. As in many living organisms, the host temperature plays a relevant role in the host-pathogen equilibrium. For instance, in animals like human beings, a neural mechanism triggers the increasing of the body temperature in order to activate the immune system. Here, cooperators succeed once bacteria are completely removed while, in the opposite scenario, the host undergoes a deep invasive process, like a blood poisoning. Results of numerical simulations show that the dynamics of the proposed model allow to reach a variety of states. At a very high level of abstraction, some of these states seem to be similar to those that can be observed in some living systems. Therefore, to conclude, we deem that our model might be exploited for studying further biological phenomena. |
2004.03181 | Leo Bouscarrat | L\'eo Bouscarrat (QARMA, TALEP), Antoine Bonnefoy, C\'ecile Capponi
(LIF, QARMA), Carlos Ramisch (TALEP) | Multilingual enrichment of disease biomedical ontologies | null | 2nd workshop on MultilingualBIO: Multilingual Biomedical Text
Processing, May 2020, Marseille, France | null | null | q-bio.QM cs.CL cs.IR | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Translating biomedical ontologies is an important challenge, but doing it
manually requires much time and money. We study the possibility to use
open-source knowledge bases to translate biomedical ontologies. We focus on two
aspects: coverage and quality. We look at the coverage of two biomedical
ontologies focusing on diseases with respect to Wikidata for 9 European
languages (Czech, Dutch, English, French, German, Italian, Polish, Portuguese
and Spanish) for both ontologies, plus Arabic, Chinese and Russian for the
second one. We first use direct links between Wikidata and the studied
ontologies and then use second-order links by going through other intermediate
ontologies. We then compare the quality of the translations obtained thanks to
Wikidata with a commercial machine translation tool, here Google Cloud
Translation.
| [
{
"created": "Tue, 7 Apr 2020 08:04:21 GMT",
"version": "v1"
}
] | 2020-04-08 | [
[
"Bouscarrat",
"Léo",
"",
"QARMA, TALEP"
],
[
"Bonnefoy",
"Antoine",
"",
"LIF, QARMA"
],
[
"Capponi",
"Cécile",
"",
"LIF, QARMA"
],
[
"Ramisch",
"Carlos",
"",
"TALEP"
]
] | Translating biomedical ontologies is an important challenge, but doing it manually requires much time and money. We study the possibility to use open-source knowledge bases to translate biomedical ontologies. We focus on two aspects: coverage and quality. We look at the coverage of two biomedical ontologies focusing on diseases with respect to Wikidata for 9 European languages (Czech, Dutch, English, French, German, Italian, Polish, Portuguese and Spanish) for both ontologies, plus Arabic, Chinese and Russian for the second one. We first use direct links between Wikidata and the studied ontologies and then use second-order links by going through other intermediate ontologies. We then compare the quality of the translations obtained thanks to Wikidata with a commercial machine translation tool, here Google Cloud Translation. |
2102.00925 | Zichao Yan | Zichao Yan, William L. Hamilton and Mathieu Blanchette | Neural representation and generation for RNA secondary structures | null | null | null | null | q-bio.BM cs.LG | http://creativecommons.org/licenses/by/4.0/ | Our work is concerned with the generation and targeted design of RNA, a type
of genetic macromolecule that can adopt complex structures which influence
their cellular activities and functions. The design of large scale and complex
biological structures spurs dedicated graph-based deep generative modeling
techniques, which represents a key but underappreciated aspect of computational
drug discovery. In this work, we investigate the principles behind representing
and generating different RNA structural modalities, and propose a flexible
framework to jointly embed and generate these molecular structures along with
their sequence in a meaningful latent space. Equipped with a deep understanding
of RNA molecular structures, our most sophisticated encoding and decoding
methods operate on the molecular graph as well as the junction tree hierarchy,
integrating strong inductive bias about RNA structural regularity and folding
mechanism such that high structural validity, stability and diversity of
generated RNAs are achieved. Also, we seek to adequately organize the latent
space of RNA molecular embeddings with regard to the interaction with proteins,
and targeted optimization is used to navigate in this latent space to search
for desired novel RNA molecules.
| [
{
"created": "Mon, 1 Feb 2021 15:49:25 GMT",
"version": "v1"
}
] | 2021-02-02 | [
[
"Yan",
"Zichao",
""
],
[
"Hamilton",
"William L.",
""
],
[
"Blanchette",
"Mathieu",
""
]
] | Our work is concerned with the generation and targeted design of RNA, a type of genetic macromolecule that can adopt complex structures which influence their cellular activities and functions. The design of large scale and complex biological structures spurs dedicated graph-based deep generative modeling techniques, which represents a key but underappreciated aspect of computational drug discovery. In this work, we investigate the principles behind representing and generating different RNA structural modalities, and propose a flexible framework to jointly embed and generate these molecular structures along with their sequence in a meaningful latent space. Equipped with a deep understanding of RNA molecular structures, our most sophisticated encoding and decoding methods operate on the molecular graph as well as the junction tree hierarchy, integrating strong inductive bias about RNA structural regularity and folding mechanism such that high structural validity, stability and diversity of generated RNAs are achieved. Also, we seek to adequately organize the latent space of RNA molecular embeddings with regard to the interaction with proteins, and targeted optimization is used to navigate in this latent space to search for desired novel RNA molecules. |
2001.07396 | William Ireland | William T. Ireland, Suzannah M. Beeler, Emanuel Flores-Bautista,
Nathan M. Belliveau, Michael J. Sweredoski, Annie Moradian, Justin B. Kinney,
and Rob Phillips | Deciphering the regulatory genome of $\textit{Escherichia coli}$, one
hundred promoters at a time | 47 pages, 15 figures | null | null | null | q-bio.GN | http://creativecommons.org/licenses/by/4.0/ | Advances in DNA sequencing have revolutionized our ability to read genomes.
However, even in the most well-studied of organisms, the bacterium ${\it
Escherichia coli}$, for $\approx$ 65$\%$ of the promoters we remain completely
ignorant of their regulation. Until we have cracked this regulatory Rosetta
Stone, efforts to read and write genomes will remain haphazard. We introduce a
new method (Reg-Seq) linking a massively-parallel reporter assay and mass
spectrometry to produce a base pair resolution dissection of more than 100
promoters in ${\it E. coli}$ in 12 different growth conditions. First, we show
that our method recapitulates regulatory information from known sequences.
Then, we examine the regulatory architectures for more than 80 promoters in the
${\it E. coli}$ genome which previously had no known regulation. In many cases,
we also identify which transcription factors mediate their regulation. The
method introduced here clears a path for fully characterizing the regulatory
genome of model organisms, with the potential of moving on to an array of other
microbes of ecological and medical relevance.
| [
{
"created": "Tue, 21 Jan 2020 09:07:10 GMT",
"version": "v1"
}
] | 2020-01-22 | [
[
"Ireland",
"William T.",
""
],
[
"Beeler",
"Suzannah M.",
""
],
[
"Flores-Bautista",
"Emanuel",
""
],
[
"Belliveau",
"Nathan M.",
""
],
[
"Sweredoski",
"Michael J.",
""
],
[
"Moradian",
"Annie",
""
],
[
"Kinney",
"Justin B.",
""
],
[
"Phillips",
"Rob",
""
]
] | Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium ${\it Escherichia coli}$, for $\approx$ 65$\%$ of the promoters we remain completely ignorant of their regulation. Until we have cracked this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method (Reg-Seq) linking a massively-parallel reporter assay and mass spectrometry to produce a base pair resolution dissection of more than 100 promoters in ${\it E. coli}$ in 12 different growth conditions. First, we show that our method recapitulates regulatory information from known sequences. Then, we examine the regulatory architectures for more than 80 promoters in the ${\it E. coli}$ genome which previously had no known regulation. In many cases, we also identify which transcription factors mediate their regulation. The method introduced here clears a path for fully characterizing the regulatory genome of model organisms, with the potential of moving on to an array of other microbes of ecological and medical relevance. |
1908.05370 | Natsuko Rivera Ms | Natsuko Rivera-Yoshida, Alejandra Hernandez-Teran, Ana E. Escalante,
Mariana Benitez | Laboratory biases hinder Eco-Evo-Devo integration: hints from the
microworld | 29 pages, 1 figure | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | How specific environmental contexts contribute to the robustness and
variation of developmental trajectories and evolutionary transitions is a
central point in Eco-Evo-Devo. However, the articulation of ecological,
evolutionary and developmental processes into integrative frameworks has been
elusive, partly because standard experimental designs neglect or oversimplify
ecologically meaningful contexts. Microbial models are useful to expose and
discuss two possible sources of bias associated with gene-centered experimental
designs: the use of laboratory strains and laboratory environmental conditions.
We illustrate our point by showing how contrasting developmental phenotypes in
Myxococcus xanthus depend on the joint variation of temperature and substrate
stiffness. Microorganismal development can provide key information for better
understanding the role of environmental conditions in the evolution of
developmental variation, and to overcome some of the limitations associated
with current experimental approaches.
| [
{
"created": "Wed, 14 Aug 2019 23:05:08 GMT",
"version": "v1"
}
] | 2019-08-16 | [
[
"Rivera-Yoshida",
"Natsuko",
""
],
[
"Hernandez-Teran",
"Alejandra",
""
],
[
"Escalante",
"Ana E.",
""
],
[
"Benitez",
"Mariana",
""
]
] | How specific environmental contexts contribute to the robustness and variation of developmental trajectories and evolutionary transitions is a central point in Eco-Evo-Devo. However, the articulation of ecological, evolutionary and developmental processes into integrative frameworks has been elusive, partly because standard experimental designs neglect or oversimplify ecologically meaningful contexts. Microbial models are useful to expose and discuss two possible sources of bias associated with gene-centered experimental designs: the use of laboratory strains and laboratory environmental conditions. We illustrate our point by showing how contrasting developmental phenotypes in Myxococcus xanthus depend on the joint variation of temperature and substrate stiffness. Microorganismal development can provide key information for better understanding the role of environmental conditions in the evolution of developmental variation, and to overcome some of the limitations associated with current experimental approaches. |
1603.04518 | Matthew Holden | Matthew Holden and Stephen Ellner | Human judgment vs. theoretical models for the management of ecological
resources | Ecological Applications (2016) | Ecological Applications. Volume 26. Issue 5. Pages 1553-1565.
(2016) | 10.1890/15-1295 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Despite major advances in quantitative approaches to natural resource
management, there has been resistance to using these tools in the actual
practice of managing ecological populations. Given a managed system and a set
of assumptions, translated into a model, optimization methods can be used to
solve for the most cost effective management actions. However, when the
underlying assumptions are not met, such methods can potentially lead to poor
decisions. Managers who develop decisions based on past experience and
judgment, without the aid of mathematical models, can potentially learn about
the system and develop flexible management strategies. However, these
strategies are often based on subjective criteria and equally invalid and often
unstated assumptions. Given the drawbacks of both methods, it is unclear
whether simple quantitative models improve environmental decision making over
expert opinion. In this paper, we explore how well students, using their
experience and judgment, manage simulated fishery populations in an online
computer game and compare their management outcomes to the performance of
model-based decisions. We consider harvest decisions generated using four
different quantitative models: 1. the model used to produce the simulated
population dynamics observed in the game, with all underlying parameter values
known [a control], 2. the same model, but with unknown parameter values that
must be estimated during the game from observed data, 3. models that are
structurally different from those used to simulate the population dynamics and
4. a model that ignores age structure. Humans on average performed much worse
than the models in cases 1 - 3. When the models ignored age structure, they
generated poorly performing management decisions, but still outperformed
students using experience and judgment 66 percent of the time.
| [
{
"created": "Tue, 15 Mar 2016 01:04:24 GMT",
"version": "v1"
}
] | 2017-09-05 | [
[
"Holden",
"Matthew",
""
],
[
"Ellner",
"Stephen",
""
]
] | Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to poor decisions. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this paper, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: 1. the model used to produce the simulated population dynamics observed in the game, with all underlying parameter values known [a control], 2. the same model, but with unknown parameter values that must be estimated during the game from observed data, 3. models that are structurally different from those used to simulate the population dynamics and 4. a model that ignores age structure. Humans on average performed much worse than the models in cases 1 - 3. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66 percent of the time. |
2103.04979 | Jitka Polechova | Jitka Polechov\'a, Kory D. Johnson, Pavel Payne, Alex Crozier, Mathias
Beiglb\"ock, Pavel Plevka, Eva Schernhammer | Evidence suggests that SARS-CoV-2 rapid antigen tests provide benefits
for epidemic control -- observations from Austrian schools | We have updated the article with recent data on viral loads in
breakthrough infections and more information about testing efficacy,
especially in children | null | 10.1016/j.jclinepi.2022.01.002 | null | q-bio.PE | http://creativecommons.org/licenses/by-sa/4.0/ | Rapid antigen tests detect proteins at the surface of virus particles,
identifying the disease during its infectious phase. In contrast, PCR tests
detect viral genomes; they can thus diagnose COVID-19 before the infectious
phase but also react to remnants of the virus genome, even weeks after live
virus ceases to be detectable in the respiratory tract. Furthermore, the
logistics for administering the tests are different, with rapid antigen tests
being much easier to administer at-scale. In this article, we discuss the
relative advantages of the different testing procedures and summarise evidence
that shows that using antigen tests 2-3 times per week could become a powerful
tool to suppress the COVID-19 pandemic. We also discuss the results of recent
large-scale rapid antigen testing in Austrian schools. While our report on
testing predates Delta, we have updated the review with recent data on viral
loads in breakthrough infections and more information about testing efficacy,
especially in children.
| [
{
"created": "Mon, 8 Mar 2021 18:57:48 GMT",
"version": "v1"
},
{
"created": "Sat, 20 Mar 2021 14:15:28 GMT",
"version": "v2"
},
{
"created": "Wed, 24 Mar 2021 16:45:18 GMT",
"version": "v3"
},
{
"created": "Mon, 29 Mar 2021 15:50:48 GMT",
"version": "v4"
},
{
"created": "Fri, 6 Aug 2021 10:46:28 GMT",
"version": "v5"
},
{
"created": "Tue, 10 Aug 2021 17:51:53 GMT",
"version": "v6"
},
{
"created": "Sun, 5 Dec 2021 12:16:49 GMT",
"version": "v7"
},
{
"created": "Fri, 17 Dec 2021 14:06:25 GMT",
"version": "v8"
}
] | 2022-01-21 | [
[
"Polechová",
"Jitka",
""
],
[
"Johnson",
"Kory D.",
""
],
[
"Payne",
"Pavel",
""
],
[
"Crozier",
"Alex",
""
],
[
"Beiglböck",
"Mathias",
""
],
[
"Plevka",
"Pavel",
""
],
[
"Schernhammer",
"Eva",
""
]
] | Rapid antigen tests detect proteins at the surface of virus particles, identifying the disease during its infectious phase. In contrast, PCR tests detect viral genomes; they can thus diagnose COVID-19 before the infectious phase but also react to remnants of the virus genome, even weeks after live virus ceases to be detectable in the respiratory tract. Furthermore, the logistics for administering the tests are different, with rapid antigen tests being much easier to administer at-scale. In this article, we discuss the relative advantages of the different testing procedures and summarise evidence that shows that using antigen tests 2-3 times per week could become a powerful tool to suppress the COVID-19 pandemic. We also discuss the results of recent large-scale rapid antigen testing in Austrian schools. While our report on testing predates Delta, we have updated the review with recent data on viral loads in breakthrough infections and more information about testing efficacy, especially in children. |
2003.03232 | Alexei Vazquez | Alexei Vazquez | The colon-pile | 4 pages, 5 figures | null | null | null | q-bio.PE cond-mat.stat-mech physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Bacteria populate the colon where they replicate and migrate in response to
nutrient availability. Here I model the colon bacterial population as a
sandpile model, the colon-pile. Sand addition mimics bacterial replication and
grains toppling represents bacterial migration coupled to high population
density. The numerical simulations reveal a behaviour similar to
non-conservative sandpile models, approaching a critical state with system wide
avalanches when the death rate becomes negligible. The critical exponents
estimation indicates that the colon-pile belongs to a new universality class.
This work suggest that the colon microbiome is in a self-organised critical
state, where small perturbations can trigger large scale rearrangements,
covering an area comparable to the system size and characterised by a 1/f noise
spectra
| [
{
"created": "Fri, 6 Mar 2020 14:18:03 GMT",
"version": "v1"
}
] | 2020-03-09 | [
[
"Vazquez",
"Alexei",
""
]
] | Bacteria populate the colon where they replicate and migrate in response to nutrient availability. Here I model the colon bacterial population as a sandpile model, the colon-pile. Sand addition mimics bacterial replication and grains toppling represents bacterial migration coupled to high population density. The numerical simulations reveal a behaviour similar to non-conservative sandpile models, approaching a critical state with system wide avalanches when the death rate becomes negligible. The critical exponents estimation indicates that the colon-pile belongs to a new universality class. This work suggest that the colon microbiome is in a self-organised critical state, where small perturbations can trigger large scale rearrangements, covering an area comparable to the system size and characterised by a 1/f noise spectra |
0801.0365 | Sanzo Miyazawa | Sanzo Miyazawa and Akira R. Kinjo | Properties of contact matrices induced by pairwise interactions in
proteins | Errata in DOI:10.1103/PhysRevE.77.051910 has been corrected in the
present version | Physical Review E, 77, 051910, 2008 | 10.1103/PhysRevE.77.051910 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The total conformational energy is assumed to consist of pairwise interaction
energies between atoms or residues, each of which is expressed as a product of
a conformation-dependent function (an element of a contact matrix, C-matrix)
and a sequence-dependent energy parameter (an element of a contact energy
matrix, E-matrix). Such pairwise interactions in proteins force native
C-matrices to be in a relationship as if the interactions are a Go-like
potential [N. Go, Annu. Rev. Biophys. Bioeng. 12. 183 (1983)] for the native
C-matrix, because the lowest bound of the total energy function is equal to the
total energy of the native conformation interacting in a Go-like pairwise
potential. This relationship between C- and E-matrices corresponds to (a) a
parallel relationship between the eigenvectors of the C- and E-matrices and a
linear relationship between their eigenvalues, and (b) a parallel relationship
between a contact number vector and the principal eigenvectors of the C- and
E-matrices; the E-matrix is expanded in a series of eigenspaces with an
additional constant term, which corresponds to a threshold of contact energy
that approximately separates native contacts from non-native ones. These
relationships are confirmed in 182 representatives from each family of the SCOP
database by examining inner products between the principal eigenvector of the
C-matrix, that of the E-matrix evaluated with a statistical contact potential,
and a contact number vector. In addition, the spectral representation of C- and
E-matrices reveals that pairwise residue-residue interactions, which depends
only on the types of interacting amino acids but not on other residues in a
protein, are insufficient and other interactions including residue
connectivities and steric hindrance are needed to make native structures the
unique lowest energy conformations.
| [
{
"created": "Wed, 2 Jan 2008 10:37:16 GMT",
"version": "v1"
},
{
"created": "Tue, 22 Jan 2008 06:43:43 GMT",
"version": "v2"
},
{
"created": "Wed, 31 Aug 2011 07:53:25 GMT",
"version": "v3"
}
] | 2011-09-01 | [
[
"Miyazawa",
"Sanzo",
""
],
[
"Kinjo",
"Akira R.",
""
]
] | The total conformational energy is assumed to consist of pairwise interaction energies between atoms or residues, each of which is expressed as a product of a conformation-dependent function (an element of a contact matrix, C-matrix) and a sequence-dependent energy parameter (an element of a contact energy matrix, E-matrix). Such pairwise interactions in proteins force native C-matrices to be in a relationship as if the interactions are a Go-like potential [N. Go, Annu. Rev. Biophys. Bioeng. 12. 183 (1983)] for the native C-matrix, because the lowest bound of the total energy function is equal to the total energy of the native conformation interacting in a Go-like pairwise potential. This relationship between C- and E-matrices corresponds to (a) a parallel relationship between the eigenvectors of the C- and E-matrices and a linear relationship between their eigenvalues, and (b) a parallel relationship between a contact number vector and the principal eigenvectors of the C- and E-matrices; the E-matrix is expanded in a series of eigenspaces with an additional constant term, which corresponds to a threshold of contact energy that approximately separates native contacts from non-native ones. These relationships are confirmed in 182 representatives from each family of the SCOP database by examining inner products between the principal eigenvector of the C-matrix, that of the E-matrix evaluated with a statistical contact potential, and a contact number vector. In addition, the spectral representation of C- and E-matrices reveals that pairwise residue-residue interactions, which depends only on the types of interacting amino acids but not on other residues in a protein, are insufficient and other interactions including residue connectivities and steric hindrance are needed to make native structures the unique lowest energy conformations. |
1101.1892 | Michael Yampolsky | Michael Yampolsky, Carolyn M. Salafia, Oleksandr Shlakhter, Danielle
Haas, Barbara Eucker, John Thorp | Abnormality of the placental vasculature affects placental thickness | null | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Our empirical modeling suggests that deformation of placental vascular growth
is associated with abnormal placental chorionic surface shape. Altered
chorionic surface shape is associated with lowered placental functional
efficiency. We hypothesize that placentas with deformed chorionic surface
vascular trees and reduced functional efficiency also have irregular vascular
arborization that will be reflected in increased variability of placental
thickness and a lower mean thickness.
We find that non-centrality of the umbilical cord insertion is strongly and
significantly correlated with disk thickness (Spearman's rho=0.128, p=0.002).
Deformed shape is strongly and significantly associated with lower overall
thickness and higher variability of thickness with beta between -0.173 and
-0.254 (p<0.001) . Both lower mean thickness and high variability of thickness
are strongly correlated with higher beta (reduced placental efficiency)
(p<0.001 and p=0.038 respectively). Greater thickness variability is correlated
with higher beta independent of the other placental shape variables p=0.004.
| [
{
"created": "Mon, 10 Jan 2011 17:21:26 GMT",
"version": "v1"
}
] | 2011-01-11 | [
[
"Yampolsky",
"Michael",
""
],
[
"Salafia",
"Carolyn M.",
""
],
[
"Shlakhter",
"Oleksandr",
""
],
[
"Haas",
"Danielle",
""
],
[
"Eucker",
"Barbara",
""
],
[
"Thorp",
"John",
""
]
] | Our empirical modeling suggests that deformation of placental vascular growth is associated with abnormal placental chorionic surface shape. Altered chorionic surface shape is associated with lowered placental functional efficiency. We hypothesize that placentas with deformed chorionic surface vascular trees and reduced functional efficiency also have irregular vascular arborization that will be reflected in increased variability of placental thickness and a lower mean thickness. We find that non-centrality of the umbilical cord insertion is strongly and significantly correlated with disk thickness (Spearman's rho=0.128, p=0.002). Deformed shape is strongly and significantly associated with lower overall thickness and higher variability of thickness with beta between -0.173 and -0.254 (p<0.001) . Both lower mean thickness and high variability of thickness are strongly correlated with higher beta (reduced placental efficiency) (p<0.001 and p=0.038 respectively). Greater thickness variability is correlated with higher beta independent of the other placental shape variables p=0.004. |
0906.3489 | Andrieux David | David Andrieux and Takaaki Monnai | Firing Rate of Noisy Integrate-and-fire Neurons with Synaptic Current
Dynamics | null | Physical Review E 80, 021933 (2009) | 10.1103/PhysRevE.80.021933 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We derive analytical formulae for the firing rate of integrate-and-fire
neurons endowed with realistic synaptic dynamics. In particular we include the
possibility of multiple synaptic inputs as well as the effect of an absolute
refractory period into the description.
| [
{
"created": "Thu, 18 Jun 2009 17:49:20 GMT",
"version": "v1"
}
] | 2009-08-27 | [
[
"Andrieux",
"David",
""
],
[
"Monnai",
"Takaaki",
""
]
] | We derive analytical formulae for the firing rate of integrate-and-fire neurons endowed with realistic synaptic dynamics. In particular we include the possibility of multiple synaptic inputs as well as the effect of an absolute refractory period into the description. |
1304.4620 | Russell Dickson | Russell J. Dickson and Gregory B. Gloor | XORRO: Rapid Paired-End Read Overlapper | 6 pages, 2 figures | null | null | null | q-bio.GN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background: Computational analysis of next-generation sequencing data is
outpaced by data generation in many cases. In one such case, paired-end reads
can be produced from the Illumina sequencing method faster than they can be
overlapped by downstream analysis. The advantages in read length and accuracy
provided by overlapping paired-end reads demonstrates the necessity for
software to efficiently solve this problem.
Results: XORRO is an extremely efficient paired-end read overlapping program.
XORRO can overlap millions of short paired-end reads in a few minutes. It uses
64-bit registers with a two bit alphabet to represent sequences and does
comparisons using low-level logical operations like XOR, AND, bitshifting and
popcount.
Conclusions: As of the writing of this manuscript, XORRO provides the fastest
solution to the paired-end read overlap problem. XORRO is available for
download at: sourceforge.net/projects/xorro-overlap/
| [
{
"created": "Tue, 16 Apr 2013 20:54:32 GMT",
"version": "v1"
}
] | 2013-04-18 | [
[
"Dickson",
"Russell J.",
""
],
[
"Gloor",
"Gregory B.",
""
]
] | Background: Computational analysis of next-generation sequencing data is outpaced by data generation in many cases. In one such case, paired-end reads can be produced from the Illumina sequencing method faster than they can be overlapped by downstream analysis. The advantages in read length and accuracy provided by overlapping paired-end reads demonstrates the necessity for software to efficiently solve this problem. Results: XORRO is an extremely efficient paired-end read overlapping program. XORRO can overlap millions of short paired-end reads in a few minutes. It uses 64-bit registers with a two bit alphabet to represent sequences and does comparisons using low-level logical operations like XOR, AND, bitshifting and popcount. Conclusions: As of the writing of this manuscript, XORRO provides the fastest solution to the paired-end read overlap problem. XORRO is available for download at: sourceforge.net/projects/xorro-overlap/ |
1806.05013 | Xiaochang Leng | Xiaochang Leng, Lindsey Davis, Xiaomin Deng, Tarek Shazly, Michael A.
Sutton, Susan M. Lessner | An inverse analysis of cohesive zone model parameter values for human
fibrous cap mode I tearing | 26 pages, 7 figures | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Atherosclerotic plaque failure results from various pathophysiological
events, with the existence of fibrous cap mode I tearing in the arterial wall,
having the potential to block the aortic lumen and correspondingly induce
serious clinical conditions.The aim of this study was to quantify the
interfacial strength and critical energy release rate of the fibrous tissue
across the thickness. in this study, an inverse analysis method via finite
element modeling and simulation approach was presented. A cohesive zone model
(CZM) was applied to simulate the tearing of the fibrous cap tissue under
uniaxial tensile tests along the circumferential direction. A fiber-reinforced
hyperelastic model (Holzapfel-Gasser-Ogden) was implemented for characterizing
the mechanical properties of bulk material. With the material parameter values
of HGO model from inverse analysis process as the input for the bulk material,
the interfacial strength and critical energy release rate along the tearing
path or failure zones are obtained through the same method as material
identification process of HGO model. Results of this study demonstrate the
fibrous cap tissue tearing failure processes.
| [
{
"created": "Wed, 13 Jun 2018 13:11:26 GMT",
"version": "v1"
}
] | 2018-06-14 | [
[
"Leng",
"Xiaochang",
""
],
[
"Davis",
"Lindsey",
""
],
[
"Deng",
"Xiaomin",
""
],
[
"Shazly",
"Tarek",
""
],
[
"Sutton",
"Michael A.",
""
],
[
"Lessner",
"Susan M.",
""
]
] | Atherosclerotic plaque failure results from various pathophysiological events, with the existence of fibrous cap mode I tearing in the arterial wall, having the potential to block the aortic lumen and correspondingly induce serious clinical conditions.The aim of this study was to quantify the interfacial strength and critical energy release rate of the fibrous tissue across the thickness. in this study, an inverse analysis method via finite element modeling and simulation approach was presented. A cohesive zone model (CZM) was applied to simulate the tearing of the fibrous cap tissue under uniaxial tensile tests along the circumferential direction. A fiber-reinforced hyperelastic model (Holzapfel-Gasser-Ogden) was implemented for characterizing the mechanical properties of bulk material. With the material parameter values of HGO model from inverse analysis process as the input for the bulk material, the interfacial strength and critical energy release rate along the tearing path or failure zones are obtained through the same method as material identification process of HGO model. Results of this study demonstrate the fibrous cap tissue tearing failure processes. |
2110.12622 | Rishabh Rishabh | Rishabh, Hadi Zadeh-Haghighi, Dennis Salahub, Christoph Simon | Radical pairs may explain reactive oxygen species-mediated effects of
hypomagnetic field on neurogenesis | 16 pages, 6 figures, 2 tables | null | null | null | q-bio.NC physics.bio-ph quant-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Exposures to a hypomagnetic field can affect biological processes. Recently,
it has been observed that hypomagnetic field exposure can adversely affect
adult hippocampal neurogenesis and hippocampus-dependent cognition in mice. In
the same study, the role of reactive oxygen species (ROS) in hypomagnetic field
effects has been demonstrated. However, the mechanistic reasons behind this
effect are not clear. This study proposes a radical pair mechanism based on a
flavin-superoxide radical pair to explain the modulation of ROS production and
the attenuation of adult hippocampal neurogenesis in a hypomagnetic field. The
results of our calculations favor a singlet-born radical pair over a
triplet-born radical pair. Our model predicts hypomagnetic field effects on the
triplet/singlet yield of comparable strength as the effects observed in
experimental studies on adult hippocampal neurogenesis. Our predictions are
also in qualitative agreement with experimental results on superoxide
concentration and other observed ROS effects. We also predict the effects of
applied magnetic fields and oxygen isotopic substitution on adult hippocampal
neurogenesis. Our findings strengthen the idea that nature might harness
quantum resources in the context of the brain.
| [
{
"created": "Mon, 25 Oct 2021 03:19:22 GMT",
"version": "v1"
}
] | 2021-10-26 | [
[
"Rishabh",
"",
""
],
[
"Zadeh-Haghighi",
"Hadi",
""
],
[
"Salahub",
"Dennis",
""
],
[
"Simon",
"Christoph",
""
]
] | Exposures to a hypomagnetic field can affect biological processes. Recently, it has been observed that hypomagnetic field exposure can adversely affect adult hippocampal neurogenesis and hippocampus-dependent cognition in mice. In the same study, the role of reactive oxygen species (ROS) in hypomagnetic field effects has been demonstrated. However, the mechanistic reasons behind this effect are not clear. This study proposes a radical pair mechanism based on a flavin-superoxide radical pair to explain the modulation of ROS production and the attenuation of adult hippocampal neurogenesis in a hypomagnetic field. The results of our calculations favor a singlet-born radical pair over a triplet-born radical pair. Our model predicts hypomagnetic field effects on the triplet/singlet yield of comparable strength as the effects observed in experimental studies on adult hippocampal neurogenesis. Our predictions are also in qualitative agreement with experimental results on superoxide concentration and other observed ROS effects. We also predict the effects of applied magnetic fields and oxygen isotopic substitution on adult hippocampal neurogenesis. Our findings strengthen the idea that nature might harness quantum resources in the context of the brain. |
1712.00813 | Simcha Srebnik | Boris Haimov and Simcha Srebnik | The Relation Between {\alpha}-Helical Conformation And Amyloidogenicity | null | null | 10.1016/j.bpj.2018.03.019 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Amyloid fibrils are stable aggregates of misfolded proteins and polypeptides
that are insoluble and resistant to protease activity. Abnormal formation of
amyloid fibrils in vivo may lead to neurodegenerative disorders and other
systemic amyloidosis such as Alzheimer's, Parkinson's, and atherosclerosis.
Because of their clinical importance amyloids are found under intense
scientific research. Amyloidogenic sequences of short polypeptide segments
within proteins are responsible for the transformation of correctly folded
proteins into parts of larger amyloid fibrils. The {\alpha}-helical secondary
structure is believed to host many amyloidogenic sequences and be a key player
in different stages of the amyloidogenesis process. Most of the studies on
amyloids focus on the role of amyloidogenic sequences. The focus of this study
is the relation between amyloidogenicity and the structure of the amyloidogenic
{\alpha}-helical sequence. We have previously shown that the {\alpha}-helical
conformation may be expressed by two parameters ({\theta} and \{rho}) that form
orthogonal coordinates based on the Ramachandran dihedrals ({\phi} and {\psi})
and provide an illuminating interpretation of the {\alpha}-helical
conformation. By performing statistical analysis on {\alpha}-helical
conformations found in the protein data bank, an apparent relation between
{\alpha}-helical conformation, as expressed by {\theta} and \{rho}, and
amyloidogenicity is revealed. Remarkably, random amino acid sequences, whose
helical structure was obtained from the most probably dihedral angles as
obtained from PDB data, revealed the same dependency of amyloidogenicity,
suggesting the importance of {\alpha}-helical structure as opposed to sequence.
| [
{
"created": "Sun, 3 Dec 2017 18:43:15 GMT",
"version": "v1"
}
] | 2018-05-22 | [
[
"Haimov",
"Boris",
""
],
[
"Srebnik",
"Simcha",
""
]
] | Amyloid fibrils are stable aggregates of misfolded proteins and polypeptides that are insoluble and resistant to protease activity. Abnormal formation of amyloid fibrils in vivo may lead to neurodegenerative disorders and other systemic amyloidosis such as Alzheimer's, Parkinson's, and atherosclerosis. Because of their clinical importance amyloids are found under intense scientific research. Amyloidogenic sequences of short polypeptide segments within proteins are responsible for the transformation of correctly folded proteins into parts of larger amyloid fibrils. The {\alpha}-helical secondary structure is believed to host many amyloidogenic sequences and be a key player in different stages of the amyloidogenesis process. Most of the studies on amyloids focus on the role of amyloidogenic sequences. The focus of this study is the relation between amyloidogenicity and the structure of the amyloidogenic {\alpha}-helical sequence. We have previously shown that the {\alpha}-helical conformation may be expressed by two parameters ({\theta} and \{rho}) that form orthogonal coordinates based on the Ramachandran dihedrals ({\phi} and {\psi}) and provide an illuminating interpretation of the {\alpha}-helical conformation. By performing statistical analysis on {\alpha}-helical conformations found in the protein data bank, an apparent relation between {\alpha}-helical conformation, as expressed by {\theta} and \{rho}, and amyloidogenicity is revealed. Remarkably, random amino acid sequences, whose helical structure was obtained from the most probably dihedral angles as obtained from PDB data, revealed the same dependency of amyloidogenicity, suggesting the importance of {\alpha}-helical structure as opposed to sequence. |
2402.07663 | Calina M. Durbac | M.H. Duong, C.M. Durbac, T.A. Han | Cost optimisation of individual-based institutional reward incentives
for promoting cooperation in finite populations | null | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we study the problem of cost optimisation of individual-based
institutional incentives (reward, punishment, and hybrid) for guaranteeing a
certain minimal level of cooperative behaviour in a well-mixed, finite
population. In this scheme, the individuals in the population interact via
cooperation dilemmas (Donation Game or Public Goods Game) in which
institutional reward is carried out only if cooperation is not abundant enough
(i.e., the number of cooperators is below a threshold $1\leq t\leq N-1$, where
$N$ is the population size); and similarly, institutional punishment is carried
out only when defection is too abundant. We study analytically the cases $t=1$
for the reward incentive under the small mutation limit assumption and two
different initial states, showing that the cost function is always
non-decreasing. We derive the neutral drift and strong selection limits when
the intensity of selection tends to zero and infinity, respectively. We
numerically investigate the problem for other values of $t$ and for population
dynamics with arbitrary mutation rates.
| [
{
"created": "Mon, 12 Feb 2024 14:11:28 GMT",
"version": "v1"
},
{
"created": "Sun, 21 Jul 2024 10:29:57 GMT",
"version": "v2"
},
{
"created": "Mon, 29 Jul 2024 10:58:36 GMT",
"version": "v3"
}
] | 2024-07-30 | [
[
"Duong",
"M. H.",
""
],
[
"Durbac",
"C. M.",
""
],
[
"Han",
"T. A.",
""
]
] | In this paper, we study the problem of cost optimisation of individual-based institutional incentives (reward, punishment, and hybrid) for guaranteeing a certain minimal level of cooperative behaviour in a well-mixed, finite population. In this scheme, the individuals in the population interact via cooperation dilemmas (Donation Game or Public Goods Game) in which institutional reward is carried out only if cooperation is not abundant enough (i.e., the number of cooperators is below a threshold $1\leq t\leq N-1$, where $N$ is the population size); and similarly, institutional punishment is carried out only when defection is too abundant. We study analytically the cases $t=1$ for the reward incentive under the small mutation limit assumption and two different initial states, showing that the cost function is always non-decreasing. We derive the neutral drift and strong selection limits when the intensity of selection tends to zero and infinity, respectively. We numerically investigate the problem for other values of $t$ and for population dynamics with arbitrary mutation rates. |
2312.06100 | Zachary Kilpatrick PhD | Sage Shaw and Zachary P Kilpatrick | Representing stimulus motion with waves in adaptive neural fields | 31 pages, 6 figures | null | null | null | q-bio.NC nlin.PS | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Traveling waves of neural activity emerge in cortical networks both
spontaneously and in response to stimuli. The spatiotemporal structure of waves
can indicate the information they encode and the physiological processes that
sustain them. Here, we investigate the stimulus-response relationships of
traveling waves emerging in adaptive neural fields as a model of visual motion
processing. Neural field equations model the activity of cortical tissue as a
continuum excitable medium, and adaptive processes provide negative feedback,
generating localized activity patterns. Synaptic connectivity in our model is
described by an integral kernel that weakens dynamically due to
activity-dependent synaptic depression, leading to marginally stable traveling
fronts (with attenuated backs) or pulses of a fixed speed. Our analysis
quantifies how weak stimuli shift the relative position of these waves over
time, characterized by a wave response function we obtain perturbatively.
Persistent and continuously visible stimuli model moving visual objects.
Intermittent flashes that hop across visual space can produce the experience of
smooth apparent visual motion. Entrainment of waves to both kinds of moving
stimuli are well characterized by our theory and numerical simulations,
providing a mechanistic description of the perception of visual motion.
| [
{
"created": "Mon, 11 Dec 2023 04:06:27 GMT",
"version": "v1"
}
] | 2023-12-12 | [
[
"Shaw",
"Sage",
""
],
[
"Kilpatrick",
"Zachary P",
""
]
] | Traveling waves of neural activity emerge in cortical networks both spontaneously and in response to stimuli. The spatiotemporal structure of waves can indicate the information they encode and the physiological processes that sustain them. Here, we investigate the stimulus-response relationships of traveling waves emerging in adaptive neural fields as a model of visual motion processing. Neural field equations model the activity of cortical tissue as a continuum excitable medium, and adaptive processes provide negative feedback, generating localized activity patterns. Synaptic connectivity in our model is described by an integral kernel that weakens dynamically due to activity-dependent synaptic depression, leading to marginally stable traveling fronts (with attenuated backs) or pulses of a fixed speed. Our analysis quantifies how weak stimuli shift the relative position of these waves over time, characterized by a wave response function we obtain perturbatively. Persistent and continuously visible stimuli model moving visual objects. Intermittent flashes that hop across visual space can produce the experience of smooth apparent visual motion. Entrainment of waves to both kinds of moving stimuli are well characterized by our theory and numerical simulations, providing a mechanistic description of the perception of visual motion. |
2005.03093 | Marcus Kaiser | Marcus Kaiser | Functional compensation after lesions: Predicting site and extent of
recovery | Technical Report | null | null | null | q-bio.NC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In some cases, the function of a lesioned area can be compensated for by
another area. However, it remains unpredictable if and by which other area a
lesion can be compensated. We assume that similar incoming and outgoing
connections are necessary to encode the same function as the damaged region.
The similarity can be measured both locally using the matching index and
looking at a more global scale by non-metric multidimensional scaling (NMDS).
We tested how well both measures can predict the compensating area for the loss
of the visual cortex in kittens. For this case study, the global comparison of
connectivity turns out to be a better method for predicting functional
compensation. In future studies, the extent of the similarity between the
lesioned and compensating regions might be a measure of the extent to which
function can be successfully recovered.
| [
{
"created": "Wed, 6 May 2020 19:29:49 GMT",
"version": "v1"
}
] | 2020-05-08 | [
[
"Kaiser",
"Marcus",
""
]
] | In some cases, the function of a lesioned area can be compensated for by another area. However, it remains unpredictable if and by which other area a lesion can be compensated. We assume that similar incoming and outgoing connections are necessary to encode the same function as the damaged region. The similarity can be measured both locally using the matching index and looking at a more global scale by non-metric multidimensional scaling (NMDS). We tested how well both measures can predict the compensating area for the loss of the visual cortex in kittens. For this case study, the global comparison of connectivity turns out to be a better method for predicting functional compensation. In future studies, the extent of the similarity between the lesioned and compensating regions might be a measure of the extent to which function can be successfully recovered. |
1902.00249 | Mohammed AlQuraishi | Mohammed AlQuraishi | ProteinNet: a standardized data set for machine learning of protein
structure | 8 pages, 6 figures, 1 table | null | null | null | q-bio.BM cs.LG q-bio.QM stat.ML | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Rapid progress in deep learning has spurred its application to bioinformatics
problems including protein structure prediction and design. In classic machine
learning problems like computer vision, progress has been driven by
standardized data sets that facilitate fair assessment of new methods and lower
the barrier to entry for non-domain experts. While data sets of protein
sequence and structure exist, they lack certain components critical for machine
learning, including high-quality multiple sequence alignments and insulated
training / validation splits that account for deep but only weakly detectable
homology across protein space. We have created the ProteinNet series of data
sets to provide a standardized mechanism for training and assessing data-driven
models of protein sequence-structure relationships. ProteinNet integrates
sequence, structure, and evolutionary information in programmatically
accessible file formats tailored for machine learning frameworks. Multiple
sequence alignments of all structurally characterized proteins were created
using substantial high-performance computing resources. Standardized data
splits were also generated to emulate the difficulty of past CASP (Critical
Assessment of protein Structure Prediction) experiments by resetting protein
sequence and structure space to the historical states that preceded six prior
CASPs. Utilizing sensitive evolution-based distance metrics to segregate
distantly related proteins, we have additionally created validation sets
distinct from the official CASP sets that faithfully mimic their difficulty.
ProteinNet thus represents a comprehensive and accessible resource for training
and assessing machine-learned models of protein structure.
| [
{
"created": "Fri, 1 Feb 2019 09:43:50 GMT",
"version": "v1"
}
] | 2019-02-04 | [
[
"AlQuraishi",
"Mohammed",
""
]
] | Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like computer vision, progress has been driven by standardized data sets that facilitate fair assessment of new methods and lower the barrier to entry for non-domain experts. While data sets of protein sequence and structure exist, they lack certain components critical for machine learning, including high-quality multiple sequence alignments and insulated training / validation splits that account for deep but only weakly detectable homology across protein space. We have created the ProteinNet series of data sets to provide a standardized mechanism for training and assessing data-driven models of protein sequence-structure relationships. ProteinNet integrates sequence, structure, and evolutionary information in programmatically accessible file formats tailored for machine learning frameworks. Multiple sequence alignments of all structurally characterized proteins were created using substantial high-performance computing resources. Standardized data splits were also generated to emulate the difficulty of past CASP (Critical Assessment of protein Structure Prediction) experiments by resetting protein sequence and structure space to the historical states that preceded six prior CASPs. Utilizing sensitive evolution-based distance metrics to segregate distantly related proteins, we have additionally created validation sets distinct from the official CASP sets that faithfully mimic their difficulty. ProteinNet thus represents a comprehensive and accessible resource for training and assessing machine-learned models of protein structure. |
1404.1626 | Andrei Zinovyev Dr. | Andrei Zinovyev | Dealing with complexity of biological systems: from data to models | HDR m\'emoire (habilitation thesis) defended on the 04/04/2014 | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Four chapters of the synthesis represent four major areas of my research
interests: 1) data analysis in molecular biology, 2) mathematical modeling of
biological networks, 3) genome evolution, and 4) cancer systems biology. The
first chapter is devoted to my work in developing non-linear methods of
dimension reduction (methods of elastic maps and principal trees) which extends
the classical method of principal components. Also I present application of
matrix factorization techniques to analysis of cancer data. The second chapter
is devoted to the complexity of mathematical models in molecular biology. I
describe the basic ideas of asymptotology of chemical reaction networks aiming
at dissecting and simplifying complex chemical kinetics models. Two
applications of this approach are presented: to modeling NFkB and apoptosis
pathways, and to modeling mechanisms of miRNA action on protein translation.
The third chapter briefly describes my investigations of the genome structure
in different organisms (from microbes to human cancer genomes). Unsupervised
data analysis approaches are used to investigate the patterns in genomic
sequences shaped by genome evolution and influenced by the basic properties of
the environment. The fourth chapter summarizes my experience in studying cancer
by computational methods (through combining integrative data analysis and
mathematical modeling approaches). In particular, I describe the on-going
research projects such as mathematical modeling of cell fate decisions and
synthetic lethal interactions in DNA repair network. The synthesis is concluded
by listing major challenges in computational systems biology, connected to the
topics of this text, i.e. dealing with complexity of biological systems.
| [
{
"created": "Sun, 6 Apr 2014 21:46:30 GMT",
"version": "v1"
}
] | 2014-04-08 | [
[
"Zinovyev",
"Andrei",
""
]
] | Four chapters of the synthesis represent four major areas of my research interests: 1) data analysis in molecular biology, 2) mathematical modeling of biological networks, 3) genome evolution, and 4) cancer systems biology. The first chapter is devoted to my work in developing non-linear methods of dimension reduction (methods of elastic maps and principal trees) which extends the classical method of principal components. Also I present application of matrix factorization techniques to analysis of cancer data. The second chapter is devoted to the complexity of mathematical models in molecular biology. I describe the basic ideas of asymptotology of chemical reaction networks aiming at dissecting and simplifying complex chemical kinetics models. Two applications of this approach are presented: to modeling NFkB and apoptosis pathways, and to modeling mechanisms of miRNA action on protein translation. The third chapter briefly describes my investigations of the genome structure in different organisms (from microbes to human cancer genomes). Unsupervised data analysis approaches are used to investigate the patterns in genomic sequences shaped by genome evolution and influenced by the basic properties of the environment. The fourth chapter summarizes my experience in studying cancer by computational methods (through combining integrative data analysis and mathematical modeling approaches). In particular, I describe the on-going research projects such as mathematical modeling of cell fate decisions and synthetic lethal interactions in DNA repair network. The synthesis is concluded by listing major challenges in computational systems biology, connected to the topics of this text, i.e. dealing with complexity of biological systems. |
2206.06862 | Jakub Kaczmarzyk | Jakub R. Kaczmarzyk, Tahsin M. Kurc, Shahira Abousamra, Rajarsi Gupta,
Joel H. Saltz, Peter K. Koo | Evaluating histopathology transfer learning with ChampKit | Submitted to NeurIPS 2022 Track on Datasets and Benchmarks. Source
code available at https://github.com/kaczmarj/champkit | null | 10.1016/j.cmpb.2023.107631 | null | q-bio.QM cs.CV cs.LG eess.IV | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Histopathology remains the gold standard for diagnosis of various cancers.
Recent advances in computer vision, specifically deep learning, have
facilitated the analysis of histopathology images for various tasks, including
immune cell detection and microsatellite instability classification. The
state-of-the-art for each task often employs base architectures that have been
pretrained for image classification on ImageNet. The standard approach to
develop classifiers in histopathology tends to focus narrowly on optimizing
models for a single task, not considering the aspects of modeling innovations
that improve generalization across tasks. Here we present ChampKit
(Comprehensive Histopathology Assessment of Model Predictions toolKit): an
extensible, fully reproducible benchmarking toolkit that consists of a broad
collection of patch-level image classification tasks across different cancers.
ChampKit enables a way to systematically document the performance impact of
proposed improvements in models and methodology. ChampKit source code and data
are freely accessible at https://github.com/kaczmarj/champkit .
| [
{
"created": "Tue, 14 Jun 2022 14:00:17 GMT",
"version": "v1"
}
] | 2023-11-02 | [
[
"Kaczmarzyk",
"Jakub R.",
""
],
[
"Kurc",
"Tahsin M.",
""
],
[
"Abousamra",
"Shahira",
""
],
[
"Gupta",
"Rajarsi",
""
],
[
"Saltz",
"Joel H.",
""
],
[
"Koo",
"Peter K.",
""
]
] | Histopathology remains the gold standard for diagnosis of various cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopathology images for various tasks, including immune cell detection and microsatellite instability classification. The state-of-the-art for each task often employs base architectures that have been pretrained for image classification on ImageNet. The standard approach to develop classifiers in histopathology tends to focus narrowly on optimizing models for a single task, not considering the aspects of modeling innovations that improve generalization across tasks. Here we present ChampKit (Comprehensive Histopathology Assessment of Model Predictions toolKit): an extensible, fully reproducible benchmarking toolkit that consists of a broad collection of patch-level image classification tasks across different cancers. ChampKit enables a way to systematically document the performance impact of proposed improvements in models and methodology. ChampKit source code and data are freely accessible at https://github.com/kaczmarj/champkit . |
2401.03390 | Mansooreh Montazerin | Majd Al Aawar, Srikar Mutnuri, Mansooreh Montazerin, Ajitesh
Srivastava | Dynamics-based Feature Augmentation of Graph Neural Networks for Variant
Emergence Prediction | null | null | null | null | q-bio.PE cs.LG physics.soc-ph | http://creativecommons.org/licenses/by/4.0/ | During the COVID-19 pandemic, a major driver of new surges has been the
emergence of new variants. When a new variant emerges in one or more countries,
other nations monitor its spread in preparation for its potential arrival. The
impact of the new variant and the timings of epidemic peaks in a country highly
depend on when the variant arrives. The current methods for predicting the
spread of new variants rely on statistical modeling, however, these methods
work only when the new variant has already arrived in the region of interest
and has a significant prevalence. Can we predict when a variant existing
elsewhere will arrive in a given region? To address this question, we propose a
variant-dynamics-informed Graph Neural Network (GNN) approach. First, we derive
the dynamics of variant prevalence across pairs of regions (countries) that
apply to a large class of epidemic models. The dynamics motivate the
introduction of certain features in the GNN. We demonstrate that our proposed
dynamics-informed GNN outperforms all the baselines, including the currently
pervasive framework of Physics-Informed Neural Networks (PINNs). To advance
research in this area, we introduce a benchmarking tool to assess a
user-defined model's prediction performance across 87 countries and 36
variants.
| [
{
"created": "Sun, 7 Jan 2024 05:03:30 GMT",
"version": "v1"
},
{
"created": "Wed, 29 May 2024 00:10:30 GMT",
"version": "v2"
}
] | 2024-05-30 | [
[
"Aawar",
"Majd Al",
""
],
[
"Mutnuri",
"Srikar",
""
],
[
"Montazerin",
"Mansooreh",
""
],
[
"Srivastava",
"Ajitesh",
""
]
] | During the COVID-19 pandemic, a major driver of new surges has been the emergence of new variants. When a new variant emerges in one or more countries, other nations monitor its spread in preparation for its potential arrival. The impact of the new variant and the timings of epidemic peaks in a country highly depend on when the variant arrives. The current methods for predicting the spread of new variants rely on statistical modeling, however, these methods work only when the new variant has already arrived in the region of interest and has a significant prevalence. Can we predict when a variant existing elsewhere will arrive in a given region? To address this question, we propose a variant-dynamics-informed Graph Neural Network (GNN) approach. First, we derive the dynamics of variant prevalence across pairs of regions (countries) that apply to a large class of epidemic models. The dynamics motivate the introduction of certain features in the GNN. We demonstrate that our proposed dynamics-informed GNN outperforms all the baselines, including the currently pervasive framework of Physics-Informed Neural Networks (PINNs). To advance research in this area, we introduce a benchmarking tool to assess a user-defined model's prediction performance across 87 countries and 36 variants. |
1006.0825 | Alex Bladon | Alex J. Bladon, Tobias Galla, Alan J. McKane | Evolutionary dynamics, intrinsic noise and cycles of co-operation | 14 pages, 12 figures, accepted for publication by Phys. Rev. E | Phys. Rev. E 81, 066122 (2010) | 10.1103/PhysRevE.81.066122 | null | q-bio.PE cond-mat.stat-mech physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We use analytical techniques based on an expansion in the inverse system size
to study the stochastic evolutionary dynamics of finite populations of players
interacting in a repeated prisoner's dilemma game. We show that a mechanism of
amplification of demographic noise can give rise to coherent oscillations in
parameter regimes where deterministic descriptions converge to fixed points
with complex eigenvalues. These quasi-cycles between co-operation and defection
have previously been observed in computer simulations; here we provide a
systematic and comprehensive analytical characterization of their properties.
We are able to predict their power spectra as a function of the mutation rate
and other model parameters, and to compare the relative magnitude of the cycles
induced by different types of underlying microscopic dynamics. We also extend
our analysis to the iterated prisoner's dilemma game with a win-stay lose-shift
strategy, appropriate in situations where players are subject to errors of the
trembling-hand type.
| [
{
"created": "Fri, 4 Jun 2010 09:47:17 GMT",
"version": "v1"
}
] | 2012-04-20 | [
[
"Bladon",
"Alex J.",
""
],
[
"Galla",
"Tobias",
""
],
[
"McKane",
"Alan J.",
""
]
] | We use analytical techniques based on an expansion in the inverse system size to study the stochastic evolutionary dynamics of finite populations of players interacting in a repeated prisoner's dilemma game. We show that a mechanism of amplification of demographic noise can give rise to coherent oscillations in parameter regimes where deterministic descriptions converge to fixed points with complex eigenvalues. These quasi-cycles between co-operation and defection have previously been observed in computer simulations; here we provide a systematic and comprehensive analytical characterization of their properties. We are able to predict their power spectra as a function of the mutation rate and other model parameters, and to compare the relative magnitude of the cycles induced by different types of underlying microscopic dynamics. We also extend our analysis to the iterated prisoner's dilemma game with a win-stay lose-shift strategy, appropriate in situations where players are subject to errors of the trembling-hand type. |
2406.12108 | Alexander Titus | Samuel A. Donkor, Matthew E. Walsh, and Alexander J. Titus | Computing in the Life Sciences: From Early Algorithms to Modern AI | 53 pages, 4 figures, 10 tables | null | null | null | q-bio.OT cs.AI | http://creativecommons.org/licenses/by/4.0/ | Computing in the life sciences has undergone a transformative evolution, from
early computational models in the 1950s to the applications of artificial
intelligence (AI) and machine learning (ML) seen today. This paper highlights
key milestones and technological advancements through the historical
development of computing in the life sciences. The discussion includes the
inception of computational models for biological processes, the advent of
bioinformatics tools, and the integration of AI/ML in modern life sciences
research. Attention is given to AI-enabled tools used in the life sciences,
such as scientific large language models and bio-AI tools, examining their
capabilities, limitations, and impact to biological risk. This paper seeks to
clarify and establish essential terminology and concepts to ensure informed
decision-making and effective communication across disciplines.
| [
{
"created": "Mon, 17 Jun 2024 21:36:52 GMT",
"version": "v1"
},
{
"created": "Wed, 19 Jun 2024 03:54:28 GMT",
"version": "v2"
}
] | 2024-06-21 | [
[
"Donkor",
"Samuel A.",
""
],
[
"Walsh",
"Matthew E.",
""
],
[
"Titus",
"Alexander J.",
""
]
] | Computing in the life sciences has undergone a transformative evolution, from early computational models in the 1950s to the applications of artificial intelligence (AI) and machine learning (ML) seen today. This paper highlights key milestones and technological advancements through the historical development of computing in the life sciences. The discussion includes the inception of computational models for biological processes, the advent of bioinformatics tools, and the integration of AI/ML in modern life sciences research. Attention is given to AI-enabled tools used in the life sciences, such as scientific large language models and bio-AI tools, examining their capabilities, limitations, and impact to biological risk. This paper seeks to clarify and establish essential terminology and concepts to ensure informed decision-making and effective communication across disciplines. |
1608.01473 | Changbong Hyeon | Yoonji Lee, Songmi Kim, Sun Choi, Changbong Hyeon | Ultraslow water-mediated transmembrane interactions regulate the
activation of A$_{\text{2A}}$ adenosine receptor | 21 pages, 14 figures | Biophys. J. (2016) vol. 111, 1180-1191 | 10.1016/j.bpj.2016.08.002 | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Water molecules inside G-protein coupled receptor have recently been
spotlighted in a series of crystal structures. To decipher the dynamics and
functional roles of internal waters in GPCR activity, we studied
A$_{\text{2A}}$ adenosine receptor using $\mu$sec-molecular dynamics
simulations. Our study finds that the amount of water flux across the
transmembrane (TM) domain varies depending on the receptor state, and that the
water molecules of the TM channel in the active state flow three times slower
than those in the inactive state. Depending on the location in solvent-protein
interface as well as the receptor state, the average residence time of water in
each residue varies from $\sim\mathcal{O}(10^2)$ psec to
$\sim\mathcal{O}(10^2)$ nsec. Especially, water molecules, exhibiting ultraslow
relaxation ($\sim\mathcal{O}(10^2)$ nsec) in the active state, are found around
the microswitch residues that are considered activity hotspots for GPCR
function. A continuous allosteric network spanning the TM domain, arising from
water-mediated contacts, is unique in the active state, underscoring the
importance of slow waters in the GPCR activation.
| [
{
"created": "Thu, 4 Aug 2016 09:11:50 GMT",
"version": "v1"
}
] | 2017-01-04 | [
[
"Lee",
"Yoonji",
""
],
[
"Kim",
"Songmi",
""
],
[
"Choi",
"Sun",
""
],
[
"Hyeon",
"Changbong",
""
]
] | Water molecules inside G-protein coupled receptor have recently been spotlighted in a series of crystal structures. To decipher the dynamics and functional roles of internal waters in GPCR activity, we studied A$_{\text{2A}}$ adenosine receptor using $\mu$sec-molecular dynamics simulations. Our study finds that the amount of water flux across the transmembrane (TM) domain varies depending on the receptor state, and that the water molecules of the TM channel in the active state flow three times slower than those in the inactive state. Depending on the location in solvent-protein interface as well as the receptor state, the average residence time of water in each residue varies from $\sim\mathcal{O}(10^2)$ psec to $\sim\mathcal{O}(10^2)$ nsec. Especially, water molecules, exhibiting ultraslow relaxation ($\sim\mathcal{O}(10^2)$ nsec) in the active state, are found around the microswitch residues that are considered activity hotspots for GPCR function. A continuous allosteric network spanning the TM domain, arising from water-mediated contacts, is unique in the active state, underscoring the importance of slow waters in the GPCR activation. |
2005.05295 | Arthur Goldberg | Arthur P. Goldberg (1) and David R. Jefferson (2) and John A. P. Sekar
(1) and Jonathan R. Karr (1) ((1) Icahn Institute for Data Science and
Genomic Technology, and Department of Genetics and Genomic Sciences, Icahn
School of Medicine at Mount Sinai, (2) Lawrence Livermore National
Laboratory) | Exact Parallelization of the Stochastic Simulation Algorithm for
Scalable Simulation of Large Biochemical Networks | 21 pages, 4 figures; 2020-05-20 submission: updated authors,
affiliations, emails, acknowledgments and layout | null | null | null | q-bio.MN cs.DC cs.DS q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Comprehensive simulations of the entire biochemistry of cells have great
potential to help physicians treat disease and help engineers design biological
machines. But such simulations must model networks of millions of molecular
species and reactions.
The Stochastic Simulation Algorithm (SSA) is widely used for simulating
biochemistry, especially systems with species populations small enough that
discreteness and stochasticity play important roles. However, existing serial
SSA methods are prohibitively slow for comprehensive networks, and existing
parallel SSA methods, which use periodic synchronization, sacrifice accuracy.
To enable fast, accurate, and scalable simulations of biochemistry, we
present an exact parallel algorithm for SSA that partitions a biochemical
network into many SSA processes that simulate in parallel. Our parallel SSA
algorithm exactly coordinates the interactions among these SSA processes and
the species state they share by structuring the algorithm as a parallel
discrete event simulation (DES) application and using an optimistic parallel
DES simulator to synchronize the interactions. We anticipate that our method
will enable unprecedented biochemical simulations.
| [
{
"created": "Mon, 11 May 2020 17:56:21 GMT",
"version": "v1"
},
{
"created": "Wed, 20 May 2020 21:27:01 GMT",
"version": "v2"
}
] | 2020-05-22 | [
[
"Goldberg",
"Arthur P.",
""
],
[
"Jefferson",
"David R.",
""
],
[
"Sekar",
"John A. P.",
""
],
[
"Karr",
"Jonathan R.",
""
]
] | Comprehensive simulations of the entire biochemistry of cells have great potential to help physicians treat disease and help engineers design biological machines. But such simulations must model networks of millions of molecular species and reactions. The Stochastic Simulation Algorithm (SSA) is widely used for simulating biochemistry, especially systems with species populations small enough that discreteness and stochasticity play important roles. However, existing serial SSA methods are prohibitively slow for comprehensive networks, and existing parallel SSA methods, which use periodic synchronization, sacrifice accuracy. To enable fast, accurate, and scalable simulations of biochemistry, we present an exact parallel algorithm for SSA that partitions a biochemical network into many SSA processes that simulate in parallel. Our parallel SSA algorithm exactly coordinates the interactions among these SSA processes and the species state they share by structuring the algorithm as a parallel discrete event simulation (DES) application and using an optimistic parallel DES simulator to synchronize the interactions. We anticipate that our method will enable unprecedented biochemical simulations. |
1611.05080 | Hugo Gabriel Eyherabide Dr | Hugo Gabriel Eyherabide | Neural stochastic codes, encoding and decoding | The additional material and some of the theorems have been integrated
within the main results of the manuscript, and few typos have been corrected | null | null | null | q-bio.NC cs.IT math.IT q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Understanding brain function, constructing computational models and
engineering neural prosthetics require assessing two problems, namely encoding
and decoding, but their relation remains controversial. For decades, the
encoding problem has been shown to provide insight into the decoding problem,
for example, by upper bounding the decoded information. However, here we show
that this need not be the case when studying response aspects beyond noise
correlations, and trace back the actual causes of this major departure from
traditional views. To that end, we reformulate the encoding and decoding
problems from the observer or organism perspective. In addition, we study the
role of spike-time precision and response discrimination, among other response
aspects, using stochastic transformations of the neural responses, here called
stochastic codes. Our results show that stochastic codes may cause different
information losses when used to describe neural responses and when employed to
train optimal decoders. Therefore, we conclude that response aspects beyond
noise correlations may play different roles in encoding and decoding. In
practice, our results show for the first time that decoders constructed
low-quality descriptions of response aspects may operate optimally on
high-quality descriptions and vice versa, thereby potentially yielding
experimental and computational savings, as well as new opportunities for
simplifying the design of computational brain models and neural prosthetics.
| [
{
"created": "Tue, 15 Nov 2016 22:26:50 GMT",
"version": "v1"
},
{
"created": "Fri, 13 Jan 2017 11:19:12 GMT",
"version": "v2"
}
] | 2017-01-16 | [
[
"Eyherabide",
"Hugo Gabriel",
""
]
] | Understanding brain function, constructing computational models and engineering neural prosthetics require assessing two problems, namely encoding and decoding, but their relation remains controversial. For decades, the encoding problem has been shown to provide insight into the decoding problem, for example, by upper bounding the decoded information. However, here we show that this need not be the case when studying response aspects beyond noise correlations, and trace back the actual causes of this major departure from traditional views. To that end, we reformulate the encoding and decoding problems from the observer or organism perspective. In addition, we study the role of spike-time precision and response discrimination, among other response aspects, using stochastic transformations of the neural responses, here called stochastic codes. Our results show that stochastic codes may cause different information losses when used to describe neural responses and when employed to train optimal decoders. Therefore, we conclude that response aspects beyond noise correlations may play different roles in encoding and decoding. In practice, our results show for the first time that decoders constructed low-quality descriptions of response aspects may operate optimally on high-quality descriptions and vice versa, thereby potentially yielding experimental and computational savings, as well as new opportunities for simplifying the design of computational brain models and neural prosthetics. |
0709.1874 | Cheong Xin Chan | Cheong Xin Chan, Robert G. Beiko and Mark A. Ragan | A two-phase approach for detecting recombination in nucleotide sequences | 5 pages, 3 figures. Chan CX, Beiko RG and Ragan MA (2007). A
two-phase approach for detecting recombination in nucleotide sequences. In
Hazelhurst S and Ramsay M (Eds) Proceedings of the First Southern African
Bioinformatics Workshop, 28-30 January, Johannesburg, 9-15 | null | null | null | q-bio.PE | null | Genetic recombination can produce heterogeneous phylogenetic histories within
a set of homologous genes. Delineating recombination events is important in the
study of molecular evolution, as inference of such events provides a clearer
picture of the phylogenetic relationships among different gene sequences or
genomes. Nevertheless, detecting recombination events can be a daunting task,
as the performance of different recombinationdetecting approaches can vary,
depending on evolutionary events that take place after recombination. We
recently evaluated the effects of postrecombination events on the prediction
accuracy of recombination-detecting approaches using simulated nucleotide
sequence data. The main conclusion, supported by other studies, is that one
should not depend on a single method when searching for recombination events.
In this paper, we introduce a two-phase strategy, applying three statistical
measures to detect the occurrence of recombination events, and a Bayesian
phylogenetic approach in delineating breakpoints of such events in nucleotide
sequences. We evaluate the performance of these approaches using simulated
data, and demonstrate the applicability of this strategy to empirical data. The
two-phase strategy proves to be time-efficient when applied to large datasets,
and yields high-confidence results.
| [
{
"created": "Wed, 12 Sep 2007 14:02:18 GMT",
"version": "v1"
}
] | 2007-09-13 | [
[
"Chan",
"Cheong Xin",
""
],
[
"Beiko",
"Robert G.",
""
],
[
"Ragan",
"Mark A.",
""
]
] | Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. Delineating recombination events is important in the study of molecular evolution, as inference of such events provides a clearer picture of the phylogenetic relationships among different gene sequences or genomes. Nevertheless, detecting recombination events can be a daunting task, as the performance of different recombinationdetecting approaches can vary, depending on evolutionary events that take place after recombination. We recently evaluated the effects of postrecombination events on the prediction accuracy of recombination-detecting approaches using simulated nucleotide sequence data. The main conclusion, supported by other studies, is that one should not depend on a single method when searching for recombination events. In this paper, we introduce a two-phase strategy, applying three statistical measures to detect the occurrence of recombination events, and a Bayesian phylogenetic approach in delineating breakpoints of such events in nucleotide sequences. We evaluate the performance of these approaches using simulated data, and demonstrate the applicability of this strategy to empirical data. The two-phase strategy proves to be time-efficient when applied to large datasets, and yields high-confidence results. |
2212.02402 | Anwaar Ulhaq Dr | Sadi Md. Redwan, Md Palash Uddin, Muhammad Imran Sharif, and Anwaar
Ulhaq | A Network Theory Investigation into the Altered Resting State Functional
Connectivity in Attention-Deficit Hyperactivity Disorder | 8 Figures, 14 Pages | null | null | null | q-bio.NC cs.LG eess.SP | http://creativecommons.org/licenses/by/4.0/ | In the last two decades, functional magnetic resonance imaging (fMRI) has
emerged as one of the most effective technologies in clinical research of the
human brain. fMRI allows researchers to study healthy and pathological brains
while they perform various neuropsychological functions. Beyond task-related
activations, the human brain has some intrinsic activity at a task-negative
(resting) state that surprisingly consumes a lot of energy to support
communication among neurons. Recent neuroimaging research has also seen an
increase in modeling and analyzing brain activity in terms of a graph or
network. Since graph models facilitate a systems-theoretic explanation of the
brain, they have become increasingly relevant with advances in network science
and the popularization of complex systems theory. The purpose of this study is
to look into the abnormalities in resting brain functions in adults with
Attention Deficit Hyperactivity Disorder (ADHD). The primary goal is to
investigate resting-state functional connectivity (FC), which can be construed
as a significant temporal coincidence in blood-oxygen-level dependent (BOLD)
signals between functionally related brain regions in the absence of any
stimulus or task. When compared to healthy controls, ADHD patients have lower
average connectivity in the Supramarginal Gyrus and Superior Parietal Lobule,
but higher connectivity in the Lateral Occipital Cortex and Inferior Temporal
Gyrus. We also hypothesize that the network organization of default mode and
dorsal attention regions is abnormal in ADHD patients.
| [
{
"created": "Wed, 23 Nov 2022 00:35:16 GMT",
"version": "v1"
}
] | 2022-12-06 | [
[
"Redwan",
"Sadi Md.",
""
],
[
"Uddin",
"Md Palash",
""
],
[
"Sharif",
"Muhammad Imran",
""
],
[
"Ulhaq",
"Anwaar",
""
]
] | In the last two decades, functional magnetic resonance imaging (fMRI) has emerged as one of the most effective technologies in clinical research of the human brain. fMRI allows researchers to study healthy and pathological brains while they perform various neuropsychological functions. Beyond task-related activations, the human brain has some intrinsic activity at a task-negative (resting) state that surprisingly consumes a lot of energy to support communication among neurons. Recent neuroimaging research has also seen an increase in modeling and analyzing brain activity in terms of a graph or network. Since graph models facilitate a systems-theoretic explanation of the brain, they have become increasingly relevant with advances in network science and the popularization of complex systems theory. The purpose of this study is to look into the abnormalities in resting brain functions in adults with Attention Deficit Hyperactivity Disorder (ADHD). The primary goal is to investigate resting-state functional connectivity (FC), which can be construed as a significant temporal coincidence in blood-oxygen-level dependent (BOLD) signals between functionally related brain regions in the absence of any stimulus or task. When compared to healthy controls, ADHD patients have lower average connectivity in the Supramarginal Gyrus and Superior Parietal Lobule, but higher connectivity in the Lateral Occipital Cortex and Inferior Temporal Gyrus. We also hypothesize that the network organization of default mode and dorsal attention regions is abnormal in ADHD patients. |
q-bio/0512012 | Max Shpak | Max Shpak and Stephen Proulx | The Role of Life Cycle and Migration in Selection for Offspring Variance | null | null | null | null | q-bio.PE | null | For two genotypes that have the same mean number of offspring but differ in
the variance in offspring number, natural selection will favor the genotype
with lower variance. The concept of fitness becomes cloudy under these
conditions because the outcome of evolution is not deterministic. However, the
effect of variance in offspring number on the fixation probability of mutant
strategies has been calculated under several scenarios with the general
conclusion that variance in offspring number reduces fitness but only in
proportion to the inverse of the population size (Gillespie 1974, Proulx 2000).
This relationship becomes more complicated under a metapopulation scenario
where the "effective" population size depends on migration rate, population
structure, and life cycle. We show that under hard selection and weak migration
fitness in a metapopulation composed of equal sized demes is determined by deme
size. Conversely, for high migration rates and hard selection the effective
fitness depends on the total size of the metapopulation. Interestingly, under
soft selection there is no effect of migration or neighboring population
structure on effective fitness, and fitness depends only on deme size. We use
individual based simulations in developed in Shpak (2005) to validate our
analytical approximations and investigate deviations of our assumption of equal
deme size.
| [
{
"created": "Mon, 5 Dec 2005 20:54:55 GMT",
"version": "v1"
},
{
"created": "Mon, 5 Dec 2005 21:06:00 GMT",
"version": "v2"
},
{
"created": "Mon, 19 Dec 2005 21:12:24 GMT",
"version": "v3"
}
] | 2007-05-23 | [
[
"Shpak",
"Max",
""
],
[
"Proulx",
"Stephen",
""
]
] | For two genotypes that have the same mean number of offspring but differ in the variance in offspring number, natural selection will favor the genotype with lower variance. The concept of fitness becomes cloudy under these conditions because the outcome of evolution is not deterministic. However, the effect of variance in offspring number on the fixation probability of mutant strategies has been calculated under several scenarios with the general conclusion that variance in offspring number reduces fitness but only in proportion to the inverse of the population size (Gillespie 1974, Proulx 2000). This relationship becomes more complicated under a metapopulation scenario where the "effective" population size depends on migration rate, population structure, and life cycle. We show that under hard selection and weak migration fitness in a metapopulation composed of equal sized demes is determined by deme size. Conversely, for high migration rates and hard selection the effective fitness depends on the total size of the metapopulation. Interestingly, under soft selection there is no effect of migration or neighboring population structure on effective fitness, and fitness depends only on deme size. We use individual based simulations in developed in Shpak (2005) to validate our analytical approximations and investigate deviations of our assumption of equal deme size. |
1311.0778 | Urs K\"oster | Urs K\"oster, Bruno Olshausen | Testing our conceptual understanding of V1 function | 10 pages, 5 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Here we test our conceptual understanding of V1 function by asking two
experimental questions: 1) How do neurons respond to the spatiotemporal
structure contained in dynamic, natural scenes? and 2) What is the true range
of visual responsiveness and predictability of neural responses obtained in an
unbiased sample of neurons across all layers of cortex? We address these
questions by recording responses to natural movie stimuli with 32 channel
silicon probes. By simultaneously recording from cells in all layers, and
taking all recorded cells, we reduce recording bias that results from "hunting"
for neural responses evoked from drifting bars and gratings. A nonparametric
model reveals that many cells that are visually responsive do not appear to be
captured by standard receptive field models. Using nonlinear Radial Basis
Function kernels in a support vector machine, we can explain the responses of
some of these cells better than standard linear and phase-invariant complex
cell models. This suggests that V1 neurons exhibit more complex and diverse
responses than standard models can capture, ranging from simple and complex
cells strongly driven by their classical receptive fields, to cells with more
nonlinear receptive fields inferred from the nonparametric and RFB model, and
cells that are not visually responsive despite robust firing.
| [
{
"created": "Mon, 4 Nov 2013 17:25:54 GMT",
"version": "v1"
}
] | 2013-11-05 | [
[
"Köster",
"Urs",
""
],
[
"Olshausen",
"Bruno",
""
]
] | Here we test our conceptual understanding of V1 function by asking two experimental questions: 1) How do neurons respond to the spatiotemporal structure contained in dynamic, natural scenes? and 2) What is the true range of visual responsiveness and predictability of neural responses obtained in an unbiased sample of neurons across all layers of cortex? We address these questions by recording responses to natural movie stimuli with 32 channel silicon probes. By simultaneously recording from cells in all layers, and taking all recorded cells, we reduce recording bias that results from "hunting" for neural responses evoked from drifting bars and gratings. A nonparametric model reveals that many cells that are visually responsive do not appear to be captured by standard receptive field models. Using nonlinear Radial Basis Function kernels in a support vector machine, we can explain the responses of some of these cells better than standard linear and phase-invariant complex cell models. This suggests that V1 neurons exhibit more complex and diverse responses than standard models can capture, ranging from simple and complex cells strongly driven by their classical receptive fields, to cells with more nonlinear receptive fields inferred from the nonparametric and RFB model, and cells that are not visually responsive despite robust firing. |
1312.1206 | Andrey Olypher | Andrey Olypher, Jean Vaillant | On the properties of input-to-output transformations in networks of
perceptrons | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Information processing in certain neuronal networks in the brain can be
considered as a map of binary vectors, where ones (spikes) and zeros (no
spikes) of input neurons are transformed into spikes and no spikes of output
neurons. A simple but fundamental characteristic of such a map is how it
transforms distances between input vectors. In particular what is the mean
distance between output vectors given certain distance between input vectors?
Using combinatorial approach we found an exact solution to this problem for
networks of perceptrons with binary weights. he resulting formulas allow for
precise analysis how network connectivity and neuronal excitability affect the
transformation of distances between the vectors of neuronal spiking. As an
application, we considered a simple network model of information processing in
the hippocampus, a brain area critically implicated in learning and memory, and
found a combination of parameters for which the output neurons discriminated
similar and distinct inputs most effectively. A decrease of threshold values of
the output neurons, which in biological networks may be associated with
decreased inhibition, impaired optimality of discrimination.
| [
{
"created": "Wed, 4 Dec 2013 15:25:37 GMT",
"version": "v1"
}
] | 2013-12-05 | [
[
"Olypher",
"Andrey",
""
],
[
"Vaillant",
"Jean",
""
]
] | Information processing in certain neuronal networks in the brain can be considered as a map of binary vectors, where ones (spikes) and zeros (no spikes) of input neurons are transformed into spikes and no spikes of output neurons. A simple but fundamental characteristic of such a map is how it transforms distances between input vectors. In particular what is the mean distance between output vectors given certain distance between input vectors? Using combinatorial approach we found an exact solution to this problem for networks of perceptrons with binary weights. he resulting formulas allow for precise analysis how network connectivity and neuronal excitability affect the transformation of distances between the vectors of neuronal spiking. As an application, we considered a simple network model of information processing in the hippocampus, a brain area critically implicated in learning and memory, and found a combination of parameters for which the output neurons discriminated similar and distinct inputs most effectively. A decrease of threshold values of the output neurons, which in biological networks may be associated with decreased inhibition, impaired optimality of discrimination. |
2012.12583 | Pedro Cardoso-Leite | Aur\'elien Defossez, Morteza Ansarinia, Brice Clocher, Emmanuel
Schm\"uck, Paul Schrater and Pedro Cardoso-Leite | The structure of behavioral data | 12 pages, 1 table, 2 figures | null | null | null | q-bio.NC stat.ME | http://creativecommons.org/licenses/by/4.0/ | For more than a century, scientists have been collecting behavioral data--an
increasing fraction of which is now being publicly shared so other researchers
can reuse them to replicate, integrate or extend past results. Although
behavioral data is fundamental to many scientific fields, there is currently no
widely adopted standard for formatting, naming, organizing, describing or
sharing such data. This lack of standardization is a major bottleneck for
scientific progress. Not only does it prevent the effective reuse of data, it
also affects how behavioral data in general are processed, as non-standard data
calls for custom-made data analysis code and prevents the development of
efficient tools. To address this problem, we develop the Behaverse Data Model
(BDM), a standard for structuring behavioral data. Here we focus on major
concepts in behavioral data, leaving further details and developments to the
project's website (https://behaverse.github.io/data-model/).
| [
{
"created": "Wed, 23 Dec 2020 10:22:00 GMT",
"version": "v1"
}
] | 2020-12-24 | [
[
"Defossez",
"Aurélien",
""
],
[
"Ansarinia",
"Morteza",
""
],
[
"Clocher",
"Brice",
""
],
[
"Schmück",
"Emmanuel",
""
],
[
"Schrater",
"Paul",
""
],
[
"Cardoso-Leite",
"Pedro",
""
]
] | For more than a century, scientists have been collecting behavioral data--an increasing fraction of which is now being publicly shared so other researchers can reuse them to replicate, integrate or extend past results. Although behavioral data is fundamental to many scientific fields, there is currently no widely adopted standard for formatting, naming, organizing, describing or sharing such data. This lack of standardization is a major bottleneck for scientific progress. Not only does it prevent the effective reuse of data, it also affects how behavioral data in general are processed, as non-standard data calls for custom-made data analysis code and prevents the development of efficient tools. To address this problem, we develop the Behaverse Data Model (BDM), a standard for structuring behavioral data. Here we focus on major concepts in behavioral data, leaving further details and developments to the project's website (https://behaverse.github.io/data-model/). |
2310.00947 | Quratul Ain Dr. | Qurat-ul-Ain Sidra Rafi, Khairullah, Saeedullah, Arshia Arshia, Reaz
Uddin, Atia-ul-Wahab, Khalid Mohammed Khan, and M. Iqbal Choudhary | Benzophenone Semicarbazones as Potential alpha-glucosidase and Prolyl
Endopeptidase Inhibitor: In-vitro free radical scavenging, enzyme inhibition,
mechanistic, and molecular docking studies | 1 schematic,3 tables,7 figures | null | null | null | q-bio.BM | http://creativecommons.org/licenses/by/4.0/ | $\alpha$-glucosidase and prolylendopeptidase has altered expression and
activity patterns in neurological disease, type 2diabetes respectively and
several cancers. Here we screened a series 1-29 benzophenone semicarbazone
derivatives for in vitro free radical scavenging, alpha-glucosidase and
prolylendopeptidase inhibition activities. Seven derivatives were identified as
potential free radical scavengers, 14 as alpha-glucosidase, and 9 as
prolylendopeptidase inhibitors. Kinetic studies on the most promising
inhibitors were performed. Compounds 23, 27, 25 and 28 were found as inhibitor
of alpha-glucosidase, while compound 26 inhibited both prolylendopeptidase and
alpha-glucosidase. The binding modes and binding free energy of the multi
targeted inhibitor 26 were predicted by molecular docking studies. These
results provide insights on prolylendopeptidase and alpha-glucosidase
inhibition of compound 26 for further development as therapeutic agents for
neoplastic, neurological, and endocrine disorders.
| [
{
"created": "Mon, 2 Oct 2023 07:37:38 GMT",
"version": "v1"
}
] | 2023-10-03 | [
[
"Rafi",
"Qurat-ul-Ain Sidra",
""
],
[
"Khairullah",
"",
""
],
[
"Saeedullah",
"",
""
],
[
"Arshia",
"Arshia",
""
],
[
"Uddin",
"Reaz",
""
],
[
"Atia-ul-Wahab",
"",
""
],
[
"Khan",
"Khalid Mohammed",
""
],
[
"Choudhary",
"M. Iqbal",
""
]
] | $\alpha$-glucosidase and prolylendopeptidase has altered expression and activity patterns in neurological disease, type 2diabetes respectively and several cancers. Here we screened a series 1-29 benzophenone semicarbazone derivatives for in vitro free radical scavenging, alpha-glucosidase and prolylendopeptidase inhibition activities. Seven derivatives were identified as potential free radical scavengers, 14 as alpha-glucosidase, and 9 as prolylendopeptidase inhibitors. Kinetic studies on the most promising inhibitors were performed. Compounds 23, 27, 25 and 28 were found as inhibitor of alpha-glucosidase, while compound 26 inhibited both prolylendopeptidase and alpha-glucosidase. The binding modes and binding free energy of the multi targeted inhibitor 26 were predicted by molecular docking studies. These results provide insights on prolylendopeptidase and alpha-glucosidase inhibition of compound 26 for further development as therapeutic agents for neoplastic, neurological, and endocrine disorders. |
1309.7072 | Christopher Ellison | Qi Zhou, Christopher E. Ellison, Vera B. Kaiser, Artyom A.
Alekseyenko, Andrey A. Gorchakov, Doris Bachtrog | The epigenome of evolving Drosophila neo-sex chromosomes: dosage
compensation and heterochromatin formation | null | null | null | null | q-bio.GN q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Drosophila Y chromosomes are composed entirely of silent heterochromatin,
while male X chromosomes have highly accessible chromatin and are
hypertranscribed due to dosage compensation. Here, we dissect the molecular
mechanisms and functional pressures driving heterochromatin formation and
dosage compensation of the recently formed neo-sex chromosomes of Drosophila
miranda. We show that the onset of heterochromatin formation on the neo-Y is
triggered by an accumulation of repetitive DNA. The neo-X has evolved partial
dosage compensation and we find that diverse mutational paths have been
utilized to establish several dozen novel binding consensus motifs for the
dosage compensation complex on the neo-X, including simple point mutations at
pre-binding sites, insertion and deletion mutations, microsatellite expansions,
or tandem amplification of weak binding sites. Spreading of these silencing or
activating chromatin modifications to adjacent regions results in massive
mis-expression of neo-sex linked genes, and little correspondence between
functionality of genes and their silencing on the neo-Y or dosage compensation
on the neo-X. Intriguingly, the genomic regions being targeted by the dosage
compensation complex on the neo-X and those becoming heterochromatic on the
neo-Y show little overlap, possibly reflecting different propensities along the
ancestral chromosome to adopt active or repressive chromatin configurations.
Our findings have broad implications for current models of sex chromosome
evolution, and demonstrate how mechanistic constraints can limit evolutionary
adaptations. Our study also highlights how evolution can follow predictable
genetic trajectories, by repeatedly acquiring the same 21-bp consensus motif
for recruitment of the dosage compensation complex, yet utilizing a diverse
array of random mutational changes to attain the same phenotypic outcome.
| [
{
"created": "Thu, 26 Sep 2013 20:58:26 GMT",
"version": "v1"
}
] | 2013-09-30 | [
[
"Zhou",
"Qi",
""
],
[
"Ellison",
"Christopher E.",
""
],
[
"Kaiser",
"Vera B.",
""
],
[
"Alekseyenko",
"Artyom A.",
""
],
[
"Gorchakov",
"Andrey A.",
""
],
[
"Bachtrog",
"Doris",
""
]
] | Drosophila Y chromosomes are composed entirely of silent heterochromatin, while male X chromosomes have highly accessible chromatin and are hypertranscribed due to dosage compensation. Here, we dissect the molecular mechanisms and functional pressures driving heterochromatin formation and dosage compensation of the recently formed neo-sex chromosomes of Drosophila miranda. We show that the onset of heterochromatin formation on the neo-Y is triggered by an accumulation of repetitive DNA. The neo-X has evolved partial dosage compensation and we find that diverse mutational paths have been utilized to establish several dozen novel binding consensus motifs for the dosage compensation complex on the neo-X, including simple point mutations at pre-binding sites, insertion and deletion mutations, microsatellite expansions, or tandem amplification of weak binding sites. Spreading of these silencing or activating chromatin modifications to adjacent regions results in massive mis-expression of neo-sex linked genes, and little correspondence between functionality of genes and their silencing on the neo-Y or dosage compensation on the neo-X. Intriguingly, the genomic regions being targeted by the dosage compensation complex on the neo-X and those becoming heterochromatic on the neo-Y show little overlap, possibly reflecting different propensities along the ancestral chromosome to adopt active or repressive chromatin configurations. Our findings have broad implications for current models of sex chromosome evolution, and demonstrate how mechanistic constraints can limit evolutionary adaptations. Our study also highlights how evolution can follow predictable genetic trajectories, by repeatedly acquiring the same 21-bp consensus motif for recruitment of the dosage compensation complex, yet utilizing a diverse array of random mutational changes to attain the same phenotypic outcome. |
1704.01039 | Naho Ichikawa | Naho Ichikawa, Giuseppe Lisi, Noriaki Yahata, Go Okada, Masahiro
Takamura, Makiko Yamada, Tetsuya Suhara, Ryu-ichiro Hashimoto, Takashi
Yamada, Yujiro Yoshihara, Hidehiko Takahashi, Kiyoto Kasai, Nobumasa Kato,
Shigeto Yamawaki, Mitsuo Kawato, Jun Morimoto, Yasumasa Okamoto | Identifying melancholic depression biomarker using whole-brain
functional connectivity | null | null | null | null | q-bio.NC physics.med-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | By focusing on melancholic features with biological homogeneity, this study
aimed to identify a small number of critical functional connections (FCs) that
were specific only to the melancholic type of MDD. On the resting-state fMRI
data, classifiers were developed to differentiate MDD patients from healthy
controls (HCs). The classification accuracy was improved from 50 % (93 MDD and
93 HCs) to 70% (66 melancholic MDD and 66 HCs), when we specifically focused on
the melancholic MDD with moderate or severer level of depressive symptoms. It
showed 65% accuracy for the independent validation cohort. The biomarker score
distribution showed improvements with escitalopram treatments, and also showed
significant correlations with depression symptom scores. This classifier was
specific to melancholic MDD, and it did not generalize in other mental
disorders including autism spectrum disorder (ASD, 54% accuracy) and
schizophrenia spectrum disorder (SSD, 45% accuracy). Among the identified 12
FCs from 9,316 FCs between whole brain anatomical node pairs, the left DLPFC /
IFG region, which has most commonly been targeted for depression treatments,
and its functional connections between Precuneus / PCC, and between right DLPFC
/ SMA areas had the highest contributions. Given the heterogeneity of the MDD,
focusing on the melancholic features is the key to achieve high classification
accuracy. The identified FCs specifically predicted the melancholic MDD and
associated with subjective depressive symptoms. These results suggested key FCs
of melancholic depression, and open doors to novel treatments targeting these
regions in the future.
| [
{
"created": "Mon, 3 Apr 2017 15:05:59 GMT",
"version": "v1"
},
{
"created": "Tue, 18 Apr 2017 05:50:40 GMT",
"version": "v2"
},
{
"created": "Sun, 14 May 2017 20:09:58 GMT",
"version": "v3"
}
] | 2017-05-16 | [
[
"Ichikawa",
"Naho",
""
],
[
"Lisi",
"Giuseppe",
""
],
[
"Yahata",
"Noriaki",
""
],
[
"Okada",
"Go",
""
],
[
"Takamura",
"Masahiro",
""
],
[
"Yamada",
"Makiko",
""
],
[
"Suhara",
"Tetsuya",
""
],
[
"Hashimoto",
"Ryu-ichiro",
""
],
[
"Yamada",
"Takashi",
""
],
[
"Yoshihara",
"Yujiro",
""
],
[
"Takahashi",
"Hidehiko",
""
],
[
"Kasai",
"Kiyoto",
""
],
[
"Kato",
"Nobumasa",
""
],
[
"Yamawaki",
"Shigeto",
""
],
[
"Kawato",
"Mitsuo",
""
],
[
"Morimoto",
"Jun",
""
],
[
"Okamoto",
"Yasumasa",
""
]
] | By focusing on melancholic features with biological homogeneity, this study aimed to identify a small number of critical functional connections (FCs) that were specific only to the melancholic type of MDD. On the resting-state fMRI data, classifiers were developed to differentiate MDD patients from healthy controls (HCs). The classification accuracy was improved from 50 % (93 MDD and 93 HCs) to 70% (66 melancholic MDD and 66 HCs), when we specifically focused on the melancholic MDD with moderate or severer level of depressive symptoms. It showed 65% accuracy for the independent validation cohort. The biomarker score distribution showed improvements with escitalopram treatments, and also showed significant correlations with depression symptom scores. This classifier was specific to melancholic MDD, and it did not generalize in other mental disorders including autism spectrum disorder (ASD, 54% accuracy) and schizophrenia spectrum disorder (SSD, 45% accuracy). Among the identified 12 FCs from 9,316 FCs between whole brain anatomical node pairs, the left DLPFC / IFG region, which has most commonly been targeted for depression treatments, and its functional connections between Precuneus / PCC, and between right DLPFC / SMA areas had the highest contributions. Given the heterogeneity of the MDD, focusing on the melancholic features is the key to achieve high classification accuracy. The identified FCs specifically predicted the melancholic MDD and associated with subjective depressive symptoms. These results suggested key FCs of melancholic depression, and open doors to novel treatments targeting these regions in the future. |
q-bio/0702011 | Steffen Waldherr | Steffen Waldherr, Thomas Eissing, Madalena Chaves, Frank Allgower | Bistability preserving model reduction in apoptosis | 6 pages, 5 figures | null | null | null | q-bio.MN | null | Biological systems are typically very complex and need to be reduced before
they are amenable to a thorough analysis. Also, they often possess functionally
important dynamic features like bistability. In model reduction, it is
sometimes more desirable to preserve the dynamic features only than to recover
a good quantitative approximation. We present an approach to reduce the order
of a bistable dynamical system significantly while preserving bistability and
the switching threshold. These properties are important for the operation of
the system in the context of a larger network. As an application example, a
bistable model for caspase activation in apoptosis is considered.
| [
{
"created": "Wed, 7 Feb 2007 14:19:25 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Waldherr",
"Steffen",
""
],
[
"Eissing",
"Thomas",
""
],
[
"Chaves",
"Madalena",
""
],
[
"Allgower",
"Frank",
""
]
] | Biological systems are typically very complex and need to be reduced before they are amenable to a thorough analysis. Also, they often possess functionally important dynamic features like bistability. In model reduction, it is sometimes more desirable to preserve the dynamic features only than to recover a good quantitative approximation. We present an approach to reduce the order of a bistable dynamical system significantly while preserving bistability and the switching threshold. These properties are important for the operation of the system in the context of a larger network. As an application example, a bistable model for caspase activation in apoptosis is considered. |
2303.09351 | Guy Katriel | Guy Katriel | Optimizing antimicrobial treatment schedules: some fundamental
analytical results | null | Bulletin of Mathematical Biology 86 (1), 2024 | 10.1007/s11538-023-01230-8 | null | q-bio.PE math.OC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This work studies fundamental questions regarding the optimal design of
antimicrobial treatment protocols, using standard pharmacodynamic and
pharmacokinetic mathematical models. We consider the problem of designing an
antimicrobial treatment schedule to achieve eradication of a microbial
infection, while minimizing the area under the time-concentration curve (AUC).
We first solve this problem under the assumption that an arbitrary
antimicrobial concentration profile may be chosen, and prove that the 'ideal'
concentration profile consists of a constant concentration over a finite time
duration, where explicit expressions for the optimal concentration and the time
duration are given in terms of the pharmacodynamic parameters. Since
antimicrobial concentration profiles are induced by a dosing schedule and the
antimicrobial pharmacokinetics, the ideal concentration profile is not strictly
feasible. We therefore also investigate the possibility of achieving outcomes
which are close to those provided by the ideal concentration profile,using a
bolus+continuous dosing schedule, which consists of a loading dose followed by
infusion of the antimicrobial at a constant rate. We explicitly find the
optimal bolus+continuous dosing schedule, and show that, for realistic
parameter ranges, this schedule achieves results which are nearly as efficient
as those attained by the ideal concentration profile. The optimality results
obtained here provide a baseline and reference point for comparison and
evaluation of antimicrobial treatment plans.
| [
{
"created": "Thu, 16 Mar 2023 14:32:18 GMT",
"version": "v1"
},
{
"created": "Sat, 23 Sep 2023 18:04:48 GMT",
"version": "v2"
}
] | 2023-11-27 | [
[
"Katriel",
"Guy",
""
]
] | This work studies fundamental questions regarding the optimal design of antimicrobial treatment protocols, using standard pharmacodynamic and pharmacokinetic mathematical models. We consider the problem of designing an antimicrobial treatment schedule to achieve eradication of a microbial infection, while minimizing the area under the time-concentration curve (AUC). We first solve this problem under the assumption that an arbitrary antimicrobial concentration profile may be chosen, and prove that the 'ideal' concentration profile consists of a constant concentration over a finite time duration, where explicit expressions for the optimal concentration and the time duration are given in terms of the pharmacodynamic parameters. Since antimicrobial concentration profiles are induced by a dosing schedule and the antimicrobial pharmacokinetics, the ideal concentration profile is not strictly feasible. We therefore also investigate the possibility of achieving outcomes which are close to those provided by the ideal concentration profile,using a bolus+continuous dosing schedule, which consists of a loading dose followed by infusion of the antimicrobial at a constant rate. We explicitly find the optimal bolus+continuous dosing schedule, and show that, for realistic parameter ranges, this schedule achieves results which are nearly as efficient as those attained by the ideal concentration profile. The optimality results obtained here provide a baseline and reference point for comparison and evaluation of antimicrobial treatment plans. |
q-bio/0506015 | Matthew Berryman | Matthew J. Berryman, Scott W. Coussens, Yvonne Pamula, Declan Kennedy,
Kurt Lushington, Cosma Shalizi, Andrew Allison, A. James Martin, David Saint
and Derek Abbott | Nonlinear aspects of the EEG during sleep in children | 9 pages, 2 figures, 4 tables | Proc. SPIE: Fluctuations and Noise in Biological, Biophysical, and
Biomedical Systems, Austin, Texas, USA, May 24-26, 2005, vol. 5841, pp. 40-48 | 10.1117/12.622380 | null | q-bio.NC | null | Electroencephalograph (EEG) analysis enables the neuronal behavior of a
section of the brain to be examined. If the behavior is nonlinear then
nonlinear tools can be used to glean information on brain behavior, and aid in
the diagnosis of sleep abnormalities such as obstructive sleep apnea syndrome
(OSAS). In this paper the sleep EEGs of a set of normal and mild OSAS children
are evaluated for nonlinear behaviour. We consider how the behaviour of the
brain changes with sleep stage and between normal and OSAS children.
| [
{
"created": "Tue, 14 Jun 2005 01:49:59 GMT",
"version": "v1"
}
] | 2009-11-11 | [
[
"Berryman",
"Matthew J.",
""
],
[
"Coussens",
"Scott W.",
""
],
[
"Pamula",
"Yvonne",
""
],
[
"Kennedy",
"Declan",
""
],
[
"Lushington",
"Kurt",
""
],
[
"Shalizi",
"Cosma",
""
],
[
"Allison",
"Andrew",
""
],
[
"Martin",
"A. James",
""
],
[
"Saint",
"David",
""
],
[
"Abbott",
"Derek",
""
]
] | Electroencephalograph (EEG) analysis enables the neuronal behavior of a section of the brain to be examined. If the behavior is nonlinear then nonlinear tools can be used to glean information on brain behavior, and aid in the diagnosis of sleep abnormalities such as obstructive sleep apnea syndrome (OSAS). In this paper the sleep EEGs of a set of normal and mild OSAS children are evaluated for nonlinear behaviour. We consider how the behaviour of the brain changes with sleep stage and between normal and OSAS children. |
2001.00091 | Domenico Gatti | Rosella Scrima, Sabino Fugetto, Nazzareno Capitanio, Domenico L. Gatti | Hemoglobin Non-equilibrium Oxygen Dissociation Curve | null | null | null | null | q-bio.BM q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Abnormal hemoglobins can have major consequences for tissue delivery of
oxygen. Correct diagnosis of hemoglobinopathies with altered oxygen affinity
requires a determination of hemoglobin oxygen dissociation curve (ODC), which
relates the hemoglobin oxygen saturation to the partial pressure of oxygen in
the blood. Determination of the ODC of human hemoglobin is typically carried
out under conditions in which hemoglobin is in equilibrium with O2 at each
partial pressure. However, in the human body due to the fast transit of RBCs
through tissues hemoglobin oxygen exchanges occur under non-equilibrium
conditions. We describe the determination of non-equilibrium ODC, and show that
under these conditions Hb cooperativity has two apparent components in the
Adair, Perutz, and MWC models of Hb. The first component, which we call
sequential cooperativity, accounts for ~70% of Hb cooperativity, and emerges
from the constraint of sequential binding that is shared by the three models.
The second component, which we call conformational cooperativity, accounts for
~30% of Hb cooperativity, and is due either to a conformational equilibrium
between low affinity and high affinity tetramers (as in the MWC model), or to a
conformational change from low to high affinity once two of the tetramer sites
are occupied (Perutz model).
| [
{
"created": "Tue, 31 Dec 2019 22:03:51 GMT",
"version": "v1"
}
] | 2020-01-03 | [
[
"Scrima",
"Rosella",
""
],
[
"Fugetto",
"Sabino",
""
],
[
"Capitanio",
"Nazzareno",
""
],
[
"Gatti",
"Domenico L.",
""
]
] | Abnormal hemoglobins can have major consequences for tissue delivery of oxygen. Correct diagnosis of hemoglobinopathies with altered oxygen affinity requires a determination of hemoglobin oxygen dissociation curve (ODC), which relates the hemoglobin oxygen saturation to the partial pressure of oxygen in the blood. Determination of the ODC of human hemoglobin is typically carried out under conditions in which hemoglobin is in equilibrium with O2 at each partial pressure. However, in the human body due to the fast transit of RBCs through tissues hemoglobin oxygen exchanges occur under non-equilibrium conditions. We describe the determination of non-equilibrium ODC, and show that under these conditions Hb cooperativity has two apparent components in the Adair, Perutz, and MWC models of Hb. The first component, which we call sequential cooperativity, accounts for ~70% of Hb cooperativity, and emerges from the constraint of sequential binding that is shared by the three models. The second component, which we call conformational cooperativity, accounts for ~30% of Hb cooperativity, and is due either to a conformational equilibrium between low affinity and high affinity tetramers (as in the MWC model), or to a conformational change from low to high affinity once two of the tetramer sites are occupied (Perutz model). |
2403.00842 | Hong Zhou | Jianfeng Chen, Jize Xiong, Yixu Wang, Qi Xin, Hong Zhou | Implementation of an AI-based MRD evaluation and prediction model for
multiple myeloma | 7 pages, 6 figures | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | With the application of hematopoietic stem cell transplantation and new
drugs, the progression-free survival rate and overall survival rate of multiple
myeloma have been greatly improved, but it is still considered as a kind of
disease that cannot be completely cured. Many patients have disease recurrence
after complete remission, which is rooted in the presence of minimal residual
disease MRD in patients. Studies have shown that positive MRD is an independent
adverse prognostic factor affecting survival, so MRD detection is an important
indicator to judge the prognosis of patients and guide clinical treatment. At
present, multipa-rameter flow cytometry (MFC), polymerase chain reaction (PCR),
positron emission tomography (positron emission) Several techniques, such as
PET/computer tomography (CT), have been used for MRD detection of multiple
myeloma.However, there is still no cure for the disease. "IFM2013-04" four
clinical studies confirmed for the first time that proteasome inhibitors (PIs)
and immunomodulatory drugs, The synergism and importance of the combination of
IMiDs in the treatment of MM, the large Phase 3 clinical study SWOG SO777
compared the combination of bortezomib plus lenalidomide and dexamethasone. The
efficacy of VRD and D established the status of VRD first-line treatment of MM,
and due to the good efficacy of CD38 monoclonal antibody in large clinical
studies, combination therapy with VRD has been recommended as the first-line
treatment of MM. However, to explore the clinical value and problems of
applying artificial intelligence bone marrow cell recognition system Morphogo
in the detection of multiple myeloma minimal residual disease (MRD)
| [
{
"created": "Thu, 29 Feb 2024 12:10:53 GMT",
"version": "v1"
}
] | 2024-03-05 | [
[
"Chen",
"Jianfeng",
""
],
[
"Xiong",
"Jize",
""
],
[
"Wang",
"Yixu",
""
],
[
"Xin",
"Qi",
""
],
[
"Zhou",
"Hong",
""
]
] | With the application of hematopoietic stem cell transplantation and new drugs, the progression-free survival rate and overall survival rate of multiple myeloma have been greatly improved, but it is still considered as a kind of disease that cannot be completely cured. Many patients have disease recurrence after complete remission, which is rooted in the presence of minimal residual disease MRD in patients. Studies have shown that positive MRD is an independent adverse prognostic factor affecting survival, so MRD detection is an important indicator to judge the prognosis of patients and guide clinical treatment. At present, multipa-rameter flow cytometry (MFC), polymerase chain reaction (PCR), positron emission tomography (positron emission) Several techniques, such as PET/computer tomography (CT), have been used for MRD detection of multiple myeloma.However, there is still no cure for the disease. "IFM2013-04" four clinical studies confirmed for the first time that proteasome inhibitors (PIs) and immunomodulatory drugs, The synergism and importance of the combination of IMiDs in the treatment of MM, the large Phase 3 clinical study SWOG SO777 compared the combination of bortezomib plus lenalidomide and dexamethasone. The efficacy of VRD and D established the status of VRD first-line treatment of MM, and due to the good efficacy of CD38 monoclonal antibody in large clinical studies, combination therapy with VRD has been recommended as the first-line treatment of MM. However, to explore the clinical value and problems of applying artificial intelligence bone marrow cell recognition system Morphogo in the detection of multiple myeloma minimal residual disease (MRD) |
1310.0213 | Valentina Agoni | Valentina Agoni | G-quadruplexes and mRNA localization | null | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | G-quadruplexes represent a novelty for molecular biology. Their role inside
the cell remains mysterious. We investigate a possible correlation with mRNA
localization. In particular, we hypothesize that Gquadruplexes influence fluid
dynamics.
| [
{
"created": "Tue, 1 Oct 2013 09:43:40 GMT",
"version": "v1"
}
] | 2013-10-02 | [
[
"Agoni",
"Valentina",
""
]
] | G-quadruplexes represent a novelty for molecular biology. Their role inside the cell remains mysterious. We investigate a possible correlation with mRNA localization. In particular, we hypothesize that Gquadruplexes influence fluid dynamics. |
0912.3513 | Kanaka Rajan | Kanaka Rajan, L F Abbott and Haim Sompolinsky | Stimulus-Dependent Suppression of Chaos in Recurrent Neural Networks | 12 pages, 3 figures | Physical Review E 82, 011903 (2010) | 10.1103/PhysRevE.82.011903 | null | q-bio.NC cond-mat.dis-nn nlin.CD physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Neuronal activity arises from an interaction between ongoing firing generated
spontaneously by neural circuits and responses driven by external stimuli.
Using mean-field analysis, we ask how a neural network that intrinsically
generates chaotic patterns of activity can remain sensitive to extrinsic input.
We find that inputs not only drive network responses, they also actively
suppress ongoing activity, ultimately leading to a phase transition in which
chaos is completely eliminated. The critical input intensity at the phase
transition is a non-monotonic function of stimulus frequency, revealing a
"resonant" frequency at which the input is most effective at suppressing chaos
even though the power spectrum of the spontaneous activity peaks at zero and
falls exponentially. A prediction of our analysis is that the variance of
neural responses should be most strongly suppressed at frequencies matching the
range over which many sensory systems operate.
| [
{
"created": "Thu, 17 Dec 2009 20:39:04 GMT",
"version": "v1"
},
{
"created": "Mon, 2 Aug 2010 20:46:19 GMT",
"version": "v2"
}
] | 2010-08-04 | [
[
"Rajan",
"Kanaka",
""
],
[
"Abbott",
"L F",
""
],
[
"Sompolinsky",
"Haim",
""
]
] | Neuronal activity arises from an interaction between ongoing firing generated spontaneously by neural circuits and responses driven by external stimuli. Using mean-field analysis, we ask how a neural network that intrinsically generates chaotic patterns of activity can remain sensitive to extrinsic input. We find that inputs not only drive network responses, they also actively suppress ongoing activity, ultimately leading to a phase transition in which chaos is completely eliminated. The critical input intensity at the phase transition is a non-monotonic function of stimulus frequency, revealing a "resonant" frequency at which the input is most effective at suppressing chaos even though the power spectrum of the spontaneous activity peaks at zero and falls exponentially. A prediction of our analysis is that the variance of neural responses should be most strongly suppressed at frequencies matching the range over which many sensory systems operate. |
2301.02916 | Rodrigo Bonazzola | Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar, Yan Xia, Bernard
Keavney, Sven Plein, Tanveer Syeda-Mahmood, and Alejandro F Frangi | Unsupervised ensemble-based phenotyping helps enhance the
discoverability of genes related to heart morphology | 14 pages of main text, 22 pages of supplemental information | null | null | null | q-bio.GN cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Recent genome-wide association studies (GWAS) have been successful in
identifying associations between genetic variants and simple cardiac parameters
derived from cardiac magnetic resonance (CMR) images. However, the emergence of
big databases including genetic data linked to CMR, facilitates investigation
of more nuanced patterns of shape variability. Here, we propose a new framework
for gene discovery entitled Unsupervised Phenotype Ensembles (UPE). UPE builds
a redundant yet highly expressive representation by pooling a set of phenotypes
learned in an unsupervised manner, using deep learning models trained with
different hyperparameters. These phenotypes are then analyzed via (GWAS),
retaining only highly confident and stable associations across the ensemble. We
apply our approach to the UK Biobank database to extract left-ventricular (LV)
geometric features from image-derived three-dimensional meshes. We demonstrate
that our approach greatly improves the discoverability of genes influencing LV
shape, identifying 11 loci with study-wide significance and 8 with suggestive
significance. We argue that our approach would enable more extensive discovery
of gene associations with image-derived phenotypes for other organs or image
modalities.
| [
{
"created": "Sat, 7 Jan 2023 18:36:44 GMT",
"version": "v1"
}
] | 2023-01-10 | [
[
"Bonazzola",
"Rodrigo",
""
],
[
"Ferrante",
"Enzo",
""
],
[
"Ravikumar",
"Nishant",
""
],
[
"Xia",
"Yan",
""
],
[
"Keavney",
"Bernard",
""
],
[
"Plein",
"Sven",
""
],
[
"Syeda-Mahmood",
"Tanveer",
""
],
[
"Frangi",
"Alejandro F",
""
]
] | Recent genome-wide association studies (GWAS) have been successful in identifying associations between genetic variants and simple cardiac parameters derived from cardiac magnetic resonance (CMR) images. However, the emergence of big databases including genetic data linked to CMR, facilitates investigation of more nuanced patterns of shape variability. Here, we propose a new framework for gene discovery entitled Unsupervised Phenotype Ensembles (UPE). UPE builds a redundant yet highly expressive representation by pooling a set of phenotypes learned in an unsupervised manner, using deep learning models trained with different hyperparameters. These phenotypes are then analyzed via (GWAS), retaining only highly confident and stable associations across the ensemble. We apply our approach to the UK Biobank database to extract left-ventricular (LV) geometric features from image-derived three-dimensional meshes. We demonstrate that our approach greatly improves the discoverability of genes influencing LV shape, identifying 11 loci with study-wide significance and 8 with suggestive significance. We argue that our approach would enable more extensive discovery of gene associations with image-derived phenotypes for other organs or image modalities. |
1801.07093 | Genki Ichinose | Genki Ichinose, Yoshiki Satotani, Takashi Nagatani | Network flow of mobile agents enhances the evolution of cooperation | 7 pages, 5 figures | EPL 121, 28001, 2018 | 10.1209/0295-5075/121/28001 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study the effect of contingent movement on the persistence of cooperation
on complex networks with empty nodes. Each agent plays Prisoner's Dilemma game
with its neighbors and then it either updates the strategy depending on the
payoff difference with neighbors or it moves to another empty node if not
satisfied with its own payoff. If no neighboring node is empty, each agent
stays at the same site. By extensive evolutionary simulations, we show that the
medium density of agents enhances cooperation where the network flow of mobile
agents is also medium. Moreover, if the movements of agents are more frequent
than the strategy updating, cooperation is further promoted. In scale-free
networks, the optimal density for cooperation is lower than other networks
because agents get stuck at hubs. Our study suggests that keeping a smooth
network flow is significant for the persistence of cooperation in ever-changing
societies.
| [
{
"created": "Mon, 22 Jan 2018 13:47:39 GMT",
"version": "v1"
},
{
"created": "Tue, 20 Mar 2018 02:10:07 GMT",
"version": "v2"
}
] | 2018-04-18 | [
[
"Ichinose",
"Genki",
""
],
[
"Satotani",
"Yoshiki",
""
],
[
"Nagatani",
"Takashi",
""
]
] | We study the effect of contingent movement on the persistence of cooperation on complex networks with empty nodes. Each agent plays Prisoner's Dilemma game with its neighbors and then it either updates the strategy depending on the payoff difference with neighbors or it moves to another empty node if not satisfied with its own payoff. If no neighboring node is empty, each agent stays at the same site. By extensive evolutionary simulations, we show that the medium density of agents enhances cooperation where the network flow of mobile agents is also medium. Moreover, if the movements of agents are more frequent than the strategy updating, cooperation is further promoted. In scale-free networks, the optimal density for cooperation is lower than other networks because agents get stuck at hubs. Our study suggests that keeping a smooth network flow is significant for the persistence of cooperation in ever-changing societies. |
2205.04670 | Mingyu Song | Mingyu Song, Carolyn E. Jones, Marie-H. Monfils, Yael Niv | Explaining the effectiveness of fear extinction through latent-cause
inference | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Acquiring fear responses to predictors of aversive outcomes is crucial for
survival. At the same time, it is important to be able to modify such
associations when they are maladaptive, for instance in treating anxiety and
trauma-related disorders. Standard extinction procedures can reduce fear
temporarily, but with sufficient delay or with reminders of the aversive
experience, fear often returns. The latent-cause inference framework explains
the return of fear by presuming that animals learn a rich model of the
environment, in which the standard extinction procedure triggers the inference
of a new latent cause, preventing the unlearning of the original aversive
associations. This computational framework had previously inspired an
alternative extinction paradigm -- gradual extinction -- which indeed was shown
to be more effective in reducing the return of fear. However, the original
framework was not sufficient to explain the pattern of results seen in the
experiments. Here, we propose a formal model to explain the effectiveness of
gradual extinction in reducing spontaneous recovery and reinstatement effects,
in contrast to the ineffectiveness of standard extinction and a gradual reverse
control procedure. We demonstrate through quantitative simulation that our
model can explain qualitative behavioral differences across different
extinction procedures as seen in the empirical study. We verify the necessity
of several key assumptions added to the latent-cause framework, which suggest
potential general principles of animal learning and provide novel predictions
for future experiments.
| [
{
"created": "Tue, 10 May 2022 04:51:37 GMT",
"version": "v1"
}
] | 2022-05-11 | [
[
"Song",
"Mingyu",
""
],
[
"Jones",
"Carolyn E.",
""
],
[
"Monfils",
"Marie-H.",
""
],
[
"Niv",
"Yael",
""
]
] | Acquiring fear responses to predictors of aversive outcomes is crucial for survival. At the same time, it is important to be able to modify such associations when they are maladaptive, for instance in treating anxiety and trauma-related disorders. Standard extinction procedures can reduce fear temporarily, but with sufficient delay or with reminders of the aversive experience, fear often returns. The latent-cause inference framework explains the return of fear by presuming that animals learn a rich model of the environment, in which the standard extinction procedure triggers the inference of a new latent cause, preventing the unlearning of the original aversive associations. This computational framework had previously inspired an alternative extinction paradigm -- gradual extinction -- which indeed was shown to be more effective in reducing the return of fear. However, the original framework was not sufficient to explain the pattern of results seen in the experiments. Here, we propose a formal model to explain the effectiveness of gradual extinction in reducing spontaneous recovery and reinstatement effects, in contrast to the ineffectiveness of standard extinction and a gradual reverse control procedure. We demonstrate through quantitative simulation that our model can explain qualitative behavioral differences across different extinction procedures as seen in the empirical study. We verify the necessity of several key assumptions added to the latent-cause framework, which suggest potential general principles of animal learning and provide novel predictions for future experiments. |
2203.13650 | Eddy Kwessi | Eddy Kwessi | Strong Allee effect synaptic plasticity rule in an unsupervised learning
environment | null | null | null | null | q-bio.NC math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Synaptic plasticity or the ability of a brain to changes one or more of its
functions or structures has generated and is sill generating a lot of interest
from the scientific community especially neuroscientists. These interests
especially went into high gear after empirical evidences were collected that
challenged the established paradigm that human brain structures and functions
are set from childhood and only modest changes were expected beyond. Early
synaptic plasticity rules or laws to that regard include the basic Hebbian rule
that proposed a mechanism for strengthening or weakening of synapses (weights)
during learning and memory. This rule however did not account from the fact
that weights must have bounded growth overtime. Thereafter, many other rules
were proposed to complement the basic Hebbian rule and they also possess other
desirable properties. In particular, a desirable property in synaptic
plasticity rule is that the ambient system must account for inhibition which is
often achieved if the rule used allows for a lower bound in synaptic weights.
In this paper, we propose a synaptic plasticity rule inspired from the Allee
effect, a phenomenon often observed in population dynamics. We show properties
such such as synaptic normalization, competition between weights,
de-correlation potential, and dynamic stability are satisfied. We show that in
fact, an Allee effect in synaptic plasticity can be construed as an absence of
plasticity.
| [
{
"created": "Fri, 25 Mar 2022 13:57:19 GMT",
"version": "v1"
}
] | 2022-03-28 | [
[
"Kwessi",
"Eddy",
""
]
] | Synaptic plasticity or the ability of a brain to changes one or more of its functions or structures has generated and is sill generating a lot of interest from the scientific community especially neuroscientists. These interests especially went into high gear after empirical evidences were collected that challenged the established paradigm that human brain structures and functions are set from childhood and only modest changes were expected beyond. Early synaptic plasticity rules or laws to that regard include the basic Hebbian rule that proposed a mechanism for strengthening or weakening of synapses (weights) during learning and memory. This rule however did not account from the fact that weights must have bounded growth overtime. Thereafter, many other rules were proposed to complement the basic Hebbian rule and they also possess other desirable properties. In particular, a desirable property in synaptic plasticity rule is that the ambient system must account for inhibition which is often achieved if the rule used allows for a lower bound in synaptic weights. In this paper, we propose a synaptic plasticity rule inspired from the Allee effect, a phenomenon often observed in population dynamics. We show properties such such as synaptic normalization, competition between weights, de-correlation potential, and dynamic stability are satisfied. We show that in fact, an Allee effect in synaptic plasticity can be construed as an absence of plasticity. |
1510.00471 | Ron Nielsen | Ron W. Nielsen | Demographic Transition Theory Contradicted Repeatedly by Data | 21 pages, 6 figures, 8796 words | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In the absence of convincing evidence, data for Sweden and Mauritius are used
in academic publications to illustrate the Demographic Transition Theory. These
data are closely examined and found to be in clear contradiction of this
theory. Demographic Transition Theory is also contradicted by the best
available data for England. Other examples of contradicting evidence are also
discussed.
| [
{
"created": "Fri, 2 Oct 2015 02:21:05 GMT",
"version": "v1"
},
{
"created": "Wed, 20 Jan 2016 10:21:15 GMT",
"version": "v2"
}
] | 2016-01-21 | [
[
"Nielsen",
"Ron W.",
""
]
] | In the absence of convincing evidence, data for Sweden and Mauritius are used in academic publications to illustrate the Demographic Transition Theory. These data are closely examined and found to be in clear contradiction of this theory. Demographic Transition Theory is also contradicted by the best available data for England. Other examples of contradicting evidence are also discussed. |
q-bio/0609016 | Sung Min Park | Sung Min Park and Beom Jun Kim | Dynamic behaviors in directed networks | null | Phys. Rev. E 74, 026114 (2006) | 10.1103/PhysRevE.74.026114 | null | q-bio.QM | null | Motivated by the abundance of directed synaptic couplings in a real
biological neuronal network, we investigate the synchronization behavior of the
Hodgkin-Huxley model in a directed network. We start from the standard model of
the Watts-Strogatz undirected network and then change undirected edges to
directed arcs with a given probability, still preserving the connectivity of
the network. A generalized clustering coefficient for directed networks is
defined and used to investigate the interplay between the synchronization
behavior and underlying structural properties of directed networks. We observe
that the directedness of complex networks plays an important role in emerging
dynamical behaviors, which is also confirmed by a numerical study of the
sociological game theoretic voter model on directed networks.
| [
{
"created": "Mon, 11 Sep 2006 10:52:41 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Park",
"Sung Min",
""
],
[
"Kim",
"Beom Jun",
""
]
] | Motivated by the abundance of directed synaptic couplings in a real biological neuronal network, we investigate the synchronization behavior of the Hodgkin-Huxley model in a directed network. We start from the standard model of the Watts-Strogatz undirected network and then change undirected edges to directed arcs with a given probability, still preserving the connectivity of the network. A generalized clustering coefficient for directed networks is defined and used to investigate the interplay between the synchronization behavior and underlying structural properties of directed networks. We observe that the directedness of complex networks plays an important role in emerging dynamical behaviors, which is also confirmed by a numerical study of the sociological game theoretic voter model on directed networks. |
1511.01426 | Kevin Emmett | Kevin Emmett, Benjamin Schweinhart, Raul Rabadan | Multiscale Topology of Chromatin Folding | 4 pages, 7 figures. Accepted for presentation at BICT 2015 Special
Track on Topology-driven bio-inspired methods and models for complex systems
(TOPDRIM4bio) | null | null | null | q-bio.GN q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The three dimensional structure of DNA in the nucleus (chromatin) plays an
important role in many cellular processes. Recent experimental advances have
led to high-throughput methods of capturing information about chromatin
conformation on genome-wide scales. New models are needed to quantitatively
interpret this data at a global scale. Here we introduce the use of tools from
topological data analysis to study chromatin conformation. We use persistent
homology to identify and characterize conserved loops and voids in contact map
data and identify scales of interaction. We demonstrate the utility of the
approach on simulated data and then look data from both a bacterial genome and
a human cell line. We identify substantial multiscale topology in these
datasets.
| [
{
"created": "Wed, 4 Nov 2015 18:34:43 GMT",
"version": "v1"
}
] | 2015-11-05 | [
[
"Emmett",
"Kevin",
""
],
[
"Schweinhart",
"Benjamin",
""
],
[
"Rabadan",
"Raul",
""
]
] | The three dimensional structure of DNA in the nucleus (chromatin) plays an important role in many cellular processes. Recent experimental advances have led to high-throughput methods of capturing information about chromatin conformation on genome-wide scales. New models are needed to quantitatively interpret this data at a global scale. Here we introduce the use of tools from topological data analysis to study chromatin conformation. We use persistent homology to identify and characterize conserved loops and voids in contact map data and identify scales of interaction. We demonstrate the utility of the approach on simulated data and then look data from both a bacterial genome and a human cell line. We identify substantial multiscale topology in these datasets. |
1903.02026 | Pingkun Yan | Grant Haskins, Uwe Kruger, Pingkun Yan | Deep Learning in Medical Image Registration: A Survey | Accepted for publication by Machine Vision and Applications on
January 8, 2020 | null | 10.1007/s00138-020-01060-x | null | q-bio.QM cs.CV eess.IV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The establishment of image correspondence through robust image registration
is critical to many clinical tasks such as image fusion, organ atlas creation,
and tumor growth monitoring, and is a very challenging problem. Since the
beginning of the recent deep learning renaissance, the medical imaging research
community has developed deep learning based approaches and achieved the
state-of-the-art in many applications, including image registration. The rapid
adoption of deep learning for image registration applications over the past few
years necessitates a comprehensive summary and outlook, which is the main scope
of this survey. This requires placing a focus on the different research areas
as well as highlighting challenges that practitioners face. This survey,
therefore, outlines the evolution of deep learning based medical image
registration in the context of both research challenges and relevant
innovations in the past few years. Further, this survey highlights future
research directions to show how this field may be possibly moved forward to the
next level.
| [
{
"created": "Tue, 5 Mar 2019 19:37:51 GMT",
"version": "v1"
},
{
"created": "Tue, 21 Jan 2020 14:58:06 GMT",
"version": "v2"
}
] | 2020-01-22 | [
[
"Haskins",
"Grant",
""
],
[
"Kruger",
"Uwe",
""
],
[
"Yan",
"Pingkun",
""
]
] | The establishment of image correspondence through robust image registration is critical to many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring, and is a very challenging problem. Since the beginning of the recent deep learning renaissance, the medical imaging research community has developed deep learning based approaches and achieved the state-of-the-art in many applications, including image registration. The rapid adoption of deep learning for image registration applications over the past few years necessitates a comprehensive summary and outlook, which is the main scope of this survey. This requires placing a focus on the different research areas as well as highlighting challenges that practitioners face. This survey, therefore, outlines the evolution of deep learning based medical image registration in the context of both research challenges and relevant innovations in the past few years. Further, this survey highlights future research directions to show how this field may be possibly moved forward to the next level. |
1407.7518 | Ziyue Gao | Ziyue Gao, Darrel Waggoner, Matthew Stephens, Carole Ober and Molly
Przeworski | An estimate of the average number of recessive lethal mutations carried
by humans | 37 pages, 1 figure | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The effects of inbreeding on human health depend critically on the number and
severity of recessive, deleterious mutations carried by individuals. In humans,
existing estimates of these quantities are based on comparisons between
consanguineous and non-consanguineous couples, an approach that confounds
socioeconomic and genetic effects of inbreeding. To circumvent this limitation,
we focused on a founder population with almost complete Mendelian disease
ascertainment and a known pedigree. By considering all recessive lethal
diseases reported in the pedigree and simulating allele transmissions, we
estimated that each haploid set of human autosomes carries on average 0.29 (95%
credible interval [0.10, 0.83]) autosomal, recessive alleles that lead to
complete sterility or severe disorders at birth or before reproductive age when
homozygous. Comparison to existing estimates of the deleterious effects of all
recessive alleles suggests that a substantial fraction of the burden of
autosomal, recessive variants is due to single mutations that lead to death
between birth and reproductive age. In turn, the comparison to estimates from
other eukaryotes points to a surprising constancy of the average number of
recessive lethal mutations across organisms with markedly different genome
sizes.
| [
{
"created": "Mon, 28 Jul 2014 19:53:29 GMT",
"version": "v1"
}
] | 2014-07-29 | [
[
"Gao",
"Ziyue",
""
],
[
"Waggoner",
"Darrel",
""
],
[
"Stephens",
"Matthew",
""
],
[
"Ober",
"Carole",
""
],
[
"Przeworski",
"Molly",
""
]
] | The effects of inbreeding on human health depend critically on the number and severity of recessive, deleterious mutations carried by individuals. In humans, existing estimates of these quantities are based on comparisons between consanguineous and non-consanguineous couples, an approach that confounds socioeconomic and genetic effects of inbreeding. To circumvent this limitation, we focused on a founder population with almost complete Mendelian disease ascertainment and a known pedigree. By considering all recessive lethal diseases reported in the pedigree and simulating allele transmissions, we estimated that each haploid set of human autosomes carries on average 0.29 (95% credible interval [0.10, 0.83]) autosomal, recessive alleles that lead to complete sterility or severe disorders at birth or before reproductive age when homozygous. Comparison to existing estimates of the deleterious effects of all recessive alleles suggests that a substantial fraction of the burden of autosomal, recessive variants is due to single mutations that lead to death between birth and reproductive age. In turn, the comparison to estimates from other eukaryotes points to a surprising constancy of the average number of recessive lethal mutations across organisms with markedly different genome sizes. |
2010.06063 | Laura Kubatko | Andrew Richards and Laura Kubatko | Bayesian Weighted Triplet and Quartet Methods for Species Tree Inference | null | null | null | null | q-bio.PE stat.ME | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Inference of the evolutionary histories of species, commonly represented by a
species tree, is complicated by the divergent evolutionary history of different
parts of the genome. Different loci on the genome can have different histories
from the underlying species tree (and each other) due to processes such as
incomplete lineage sorting (ILS), gene duplication and loss, and horizontal
gene transfer. The multispecies coalescent is a commonly used model for
performing inference on species and gene trees in the presence of ILS. This
paper introduces Lily-T and Lily-Q, two new methods for species tree inference
under the multispecies coalescent. We then compare them to two frequently used
methods, SVDQuartets and ASTRAL, using simulated and empirical data. Both
methods generally showed improvement over SVDQuartets, and Lily-Q was superior
to Lily-T for most simulation settings. The comparison to ASTRAL was more mixed
- Lily-Q tended to be better than ASTRAL when the length of recombination-free
loci was short, when the coalescent population parameter {\theta} was small, or
when the internal branch lengths were longer.
| [
{
"created": "Mon, 12 Oct 2020 22:54:59 GMT",
"version": "v1"
}
] | 2020-10-14 | [
[
"Richards",
"Andrew",
""
],
[
"Kubatko",
"Laura",
""
]
] | Inference of the evolutionary histories of species, commonly represented by a species tree, is complicated by the divergent evolutionary history of different parts of the genome. Different loci on the genome can have different histories from the underlying species tree (and each other) due to processes such as incomplete lineage sorting (ILS), gene duplication and loss, and horizontal gene transfer. The multispecies coalescent is a commonly used model for performing inference on species and gene trees in the presence of ILS. This paper introduces Lily-T and Lily-Q, two new methods for species tree inference under the multispecies coalescent. We then compare them to two frequently used methods, SVDQuartets and ASTRAL, using simulated and empirical data. Both methods generally showed improvement over SVDQuartets, and Lily-Q was superior to Lily-T for most simulation settings. The comparison to ASTRAL was more mixed - Lily-Q tended to be better than ASTRAL when the length of recombination-free loci was short, when the coalescent population parameter {\theta} was small, or when the internal branch lengths were longer. |
2310.13468 | Lara Herriott | Lara Herriott, Henriette L. Capel, Isaac Ellmen, Nathan Schofield,
Jiayuan Zhu, Ben Lambert, David Gavaghan, Ioana Bouros, Richard Creswell and
Kit Gallagher | EpiGeoPop: A Tool for Developing Spatially Accurate Country-level
Epidemiological Models | 16 pages, 6 figures, 3 supplementary figures | null | null | null | q-bio.PE physics.soc-ph q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mathematical models play a crucial role in understanding the spread of
infectious disease outbreaks and influencing policy decisions. These models aid
pandemic preparedness by predicting outcomes under hypothetical scenarios and
identifying weaknesses in existing frameworks. However, their accuracy,
utility, and comparability are being scrutinized. Agent-based models (ABMs)
have emerged as a valuable tool, capturing population heterogeneity and spatial
effects, particularly when assessing intervention strategies. Here we present
EpiGeoPop, a user-friendly tool for rapidly preparing spatially accurate
population configurations of entire countries. EpiGeoPop helps to address the
problem of complex and time-consuming model set up in ABMs, specifically
improving the integration of spatial detail. We subsequently demonstrate the
importance of accurate spatial detail in ABM simulations of disease outbreaks
using Epiabm, an ABM based on Imperial College London's CovidSim with improved
modularity, documentation and testing. Our investigation involves the interplay
between population density, the implementation of spatial transmission, and
realistic interventions implemented in Epiabm.
| [
{
"created": "Fri, 20 Oct 2023 13:05:03 GMT",
"version": "v1"
}
] | 2023-10-23 | [
[
"Herriott",
"Lara",
""
],
[
"Capel",
"Henriette L.",
""
],
[
"Ellmen",
"Isaac",
""
],
[
"Schofield",
"Nathan",
""
],
[
"Zhu",
"Jiayuan",
""
],
[
"Lambert",
"Ben",
""
],
[
"Gavaghan",
"David",
""
],
[
"Bouros",
"Ioana",
""
],
[
"Creswell",
"Richard",
""
],
[
"Gallagher",
"Kit",
""
]
] | Mathematical models play a crucial role in understanding the spread of infectious disease outbreaks and influencing policy decisions. These models aid pandemic preparedness by predicting outcomes under hypothetical scenarios and identifying weaknesses in existing frameworks. However, their accuracy, utility, and comparability are being scrutinized. Agent-based models (ABMs) have emerged as a valuable tool, capturing population heterogeneity and spatial effects, particularly when assessing intervention strategies. Here we present EpiGeoPop, a user-friendly tool for rapidly preparing spatially accurate population configurations of entire countries. EpiGeoPop helps to address the problem of complex and time-consuming model set up in ABMs, specifically improving the integration of spatial detail. We subsequently demonstrate the importance of accurate spatial detail in ABM simulations of disease outbreaks using Epiabm, an ABM based on Imperial College London's CovidSim with improved modularity, documentation and testing. Our investigation involves the interplay between population density, the implementation of spatial transmission, and realistic interventions implemented in Epiabm. |
2106.03713 | Jan Vandenbroucke | Jan P Vandenbroucke, Elizabeth B Brickley, Christina M.J.E.
Vandenbroucke-Grauls, Neil Pearce | The evolving usefulness of the Test-Negative Design in studying risk
factors for COVID-19 due to changes in testing policy | 3 pages | null | null | null | q-bio.PE stat.ME | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | This paper is a short extension of our previous paper [arXiv:2004.06033]
about the use of the Test-Negative design to study risk factors for COVID-19
[See: PubMed and ArXiv reference below] Reason for the extension is that the
conditions under which people refer themselves for testing have greatly
changed: originally, in most countries priority was given to people with
symptoms, but nowadays people without symptoms are also tested for different
reasons, e.g., during contact tracing, or to be allowed on an (international)
flight. Interestingly, this opens new possibilities to separately investigate
risk factors for infection and risk factors for becoming diseased. To use this
new situation to best effect, one has to think carefully about how to elucidate
the different reasons for testing and what analyses one might do with the
different groups.
| [
{
"created": "Mon, 7 Jun 2021 15:24:17 GMT",
"version": "v1"
}
] | 2021-06-08 | [
[
"Vandenbroucke",
"Jan P",
""
],
[
"Brickley",
"Elizabeth B",
""
],
[
"Vandenbroucke-Grauls",
"Christina M. J. E.",
""
],
[
"Pearce",
"Neil",
""
]
] | This paper is a short extension of our previous paper [arXiv:2004.06033] about the use of the Test-Negative design to study risk factors for COVID-19 [See: PubMed and ArXiv reference below] Reason for the extension is that the conditions under which people refer themselves for testing have greatly changed: originally, in most countries priority was given to people with symptoms, but nowadays people without symptoms are also tested for different reasons, e.g., during contact tracing, or to be allowed on an (international) flight. Interestingly, this opens new possibilities to separately investigate risk factors for infection and risk factors for becoming diseased. To use this new situation to best effect, one has to think carefully about how to elucidate the different reasons for testing and what analyses one might do with the different groups. |
2312.12888 | Alain Nogaret | Stephen A. Wells, Joseph D. Taylor, Paul G. Morris and Alain Nogaret | Inferring the dynamics of ionic currents from recursive piecewise data
assimilation of approximate neuron models | null | null | null | null | q-bio.QM math-ph math.MP | http://creativecommons.org/licenses/by/4.0/ | We construct neuron models from data by transferring information from an
observed time series to the state variables and parameters of Hodgkin-Huxley
models. When the learning period completes, the model will predict additional
observations and its parameters uniquely characterise the complement of ion
channels. However, the assimilation of biological data, as opposed to model
data, is complicated by the lack of knowledge of the true neuron equations.
Reliance on guessed conductance models is plagued with multi-valued parameter
solutions. Here, we report on the distributions of parameters and currents
predicted with intentionally erroneous models, over-specified models, and an
approximate model fitting hippocampal neuron data. We introduce a recursive
piecewise data assimilation (RPDA) algorithm that converges with near-perfect
reliability when the model is known. When the model is unknown, we show model
error introduces correlations between certain parameters. The ionic currents
reconstructed from these parameters are excellent predictors of true currents
and carry a higher degree of confidence, >95.5%, than underlying parameters,
>53%. Unexpressed ionic currents are correctly filtered out even in the
presence of mild model error. When the model is unknown, the covariance
eigenvalues of parameter estimates are found to be a good gauge of model error.
Our results suggest that biological information may be retrieved from data by
focussing on current estimates rather than parameters.
| [
{
"created": "Wed, 20 Dec 2023 09:56:54 GMT",
"version": "v1"
}
] | 2023-12-21 | [
[
"Wells",
"Stephen A.",
""
],
[
"Taylor",
"Joseph D.",
""
],
[
"Morris",
"Paul G.",
""
],
[
"Nogaret",
"Alain",
""
]
] | We construct neuron models from data by transferring information from an observed time series to the state variables and parameters of Hodgkin-Huxley models. When the learning period completes, the model will predict additional observations and its parameters uniquely characterise the complement of ion channels. However, the assimilation of biological data, as opposed to model data, is complicated by the lack of knowledge of the true neuron equations. Reliance on guessed conductance models is plagued with multi-valued parameter solutions. Here, we report on the distributions of parameters and currents predicted with intentionally erroneous models, over-specified models, and an approximate model fitting hippocampal neuron data. We introduce a recursive piecewise data assimilation (RPDA) algorithm that converges with near-perfect reliability when the model is known. When the model is unknown, we show model error introduces correlations between certain parameters. The ionic currents reconstructed from these parameters are excellent predictors of true currents and carry a higher degree of confidence, >95.5%, than underlying parameters, >53%. Unexpressed ionic currents are correctly filtered out even in the presence of mild model error. When the model is unknown, the covariance eigenvalues of parameter estimates are found to be a good gauge of model error. Our results suggest that biological information may be retrieved from data by focussing on current estimates rather than parameters. |
2205.09122 | Markus Daniel Herrmann | Chris Gorman, Davide Punzo, Igor Octaviano, Steve Pieper, William J.R.
Longabaugh, David A. Clunie, Ron Kikinis, Andrey Y. Fedorov, Markus D.
Herrmann | Slim: interoperable slide microscopy viewer and annotation tool for
imaging data science and computational pathology | null | null | 10.1038/s41467-023-37224-2 | null | q-bio.QM | http://creativecommons.org/licenses/by-sa/4.0/ | The exchange of large and complex slide microscopy imaging data in biomedical
research and pathology practice is impeded by a lack of data standardization
and interoperability, which is detrimental to the reproducibility of scientific
findings and clinical integration of technological innovations. Slim is an
open-source, web-based slide microscopy viewer that implements the
internationally accepted Digital Imaging and Communications in Medicine (DICOM)
standard to achieve interoperability with a multitude of existing medical
imaging systems. We showcase the capabilities of Slim as the slide microscopy
viewer of the NCI Imaging Data Commons and demonstrate how the viewer enables
interactive visualization of traditional brightfield microscopy and
highly-multiplexed immunofluorescence microscopy images from The Cancer Genome
Atlas and Human Tissue Atlas Network, respectively, using standard DICOMweb
services. We further show how Slim enables the collection of standardized image
annotations for the development or validation of machine learning models and
the visual interpretation of model inference results in the form of
segmentation masks, spatial heat maps, or image-derived measurements.
| [
{
"created": "Wed, 18 May 2022 17:06:07 GMT",
"version": "v1"
},
{
"created": "Mon, 5 Dec 2022 23:27:00 GMT",
"version": "v2"
}
] | 2023-04-26 | [
[
"Gorman",
"Chris",
""
],
[
"Punzo",
"Davide",
""
],
[
"Octaviano",
"Igor",
""
],
[
"Pieper",
"Steve",
""
],
[
"Longabaugh",
"William J. R.",
""
],
[
"Clunie",
"David A.",
""
],
[
"Kikinis",
"Ron",
""
],
[
"Fedorov",
"Andrey Y.",
""
],
[
"Herrmann",
"Markus D.",
""
]
] | The exchange of large and complex slide microscopy imaging data in biomedical research and pathology practice is impeded by a lack of data standardization and interoperability, which is detrimental to the reproducibility of scientific findings and clinical integration of technological innovations. Slim is an open-source, web-based slide microscopy viewer that implements the internationally accepted Digital Imaging and Communications in Medicine (DICOM) standard to achieve interoperability with a multitude of existing medical imaging systems. We showcase the capabilities of Slim as the slide microscopy viewer of the NCI Imaging Data Commons and demonstrate how the viewer enables interactive visualization of traditional brightfield microscopy and highly-multiplexed immunofluorescence microscopy images from The Cancer Genome Atlas and Human Tissue Atlas Network, respectively, using standard DICOMweb services. We further show how Slim enables the collection of standardized image annotations for the development or validation of machine learning models and the visual interpretation of model inference results in the form of segmentation masks, spatial heat maps, or image-derived measurements. |
0807.3287 | Johannes Wollbold | Johannes Wollbold, Reinhard Guthke, Bernhard Ganter | Constructing a Knowledge Base for Gene Regulatory Dynamics by Formal
Concept Analysis Methods | 15 pages, 1 figure, LaTeX style llncsdoc.sty | K. Horimoto et al. (Eds.): AB 2008, LNCS 5147. Springer,
Heidelberg 2008, pp. 230-244 | null | null | q-bio.MN cs.AI math.LO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Our aim is to build a set of rules, such that reasoning over temporal
dependencies within gene regulatory networks is possible. The underlying
transitions may be obtained by discretizing observed time series, or they are
generated based on existing knowledge, e.g. by Boolean networks or their
nondeterministic generalization. We use the mathematical discipline of formal
concept analysis (FCA), which has been applied successfully in domains as
knowledge representation, data mining or software engineering. By the attribute
exploration algorithm, an expert or a supporting computer program is enabled to
decide about the validity of a minimal set of implications and thus to
construct a sound and complete knowledge base. From this all valid implications
are derivable that relate to the selected properties of a set of genes. We
present results of our method for the initiation of sporulation in Bacillus
subtilis. However the formal structures are exhibited in a most general manner.
Therefore the approach may be adapted to signal transduction or metabolic
networks, as well as to discrete temporal transitions in many biological and
nonbiological areas.
| [
{
"created": "Mon, 21 Jul 2008 15:46:22 GMT",
"version": "v1"
}
] | 2008-07-22 | [
[
"Wollbold",
"Johannes",
""
],
[
"Guthke",
"Reinhard",
""
],
[
"Ganter",
"Bernhard",
""
]
] | Our aim is to build a set of rules, such that reasoning over temporal dependencies within gene regulatory networks is possible. The underlying transitions may be obtained by discretizing observed time series, or they are generated based on existing knowledge, e.g. by Boolean networks or their nondeterministic generalization. We use the mathematical discipline of formal concept analysis (FCA), which has been applied successfully in domains as knowledge representation, data mining or software engineering. By the attribute exploration algorithm, an expert or a supporting computer program is enabled to decide about the validity of a minimal set of implications and thus to construct a sound and complete knowledge base. From this all valid implications are derivable that relate to the selected properties of a set of genes. We present results of our method for the initiation of sporulation in Bacillus subtilis. However the formal structures are exhibited in a most general manner. Therefore the approach may be adapted to signal transduction or metabolic networks, as well as to discrete temporal transitions in many biological and nonbiological areas. |
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