id stringlengths 9 13 | submitter stringlengths 4 48 | authors stringlengths 4 9.62k | title stringlengths 4 343 | comments stringlengths 2 480 ⌀ | journal-ref stringlengths 9 309 ⌀ | doi stringlengths 12 138 ⌀ | report-no stringclasses 277 values | categories stringlengths 8 87 | license stringclasses 9 values | orig_abstract stringlengths 27 3.76k | versions listlengths 1 15 | update_date stringlengths 10 10 | authors_parsed listlengths 1 147 | abstract stringlengths 24 3.75k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2007.00975 | Zaixing Yang | ChenChen Wu, Shengtang Liu, Shitong Zhang, Zaixing Yang | Molcontroller: a VMD Graphical User Interface for Manipulating Molecules | 7 pages, 3 figures | null | null | null | q-bio.BM physics.chem-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Visual Molecular Dynamics (VMD) is one of the most widely used molecular
graphics software in the community of theoretical simulations. So far, however,
it still lacks a graphical user interface (GUI) for molecular manipulations
when doing some modeling tasks. For instance, translation or rotation of a
selected molecule(s) or part(s) of a molecule, which are currently only can be
achieved using tcl scripts. Here, we use tcl script develop a user-friendly GUI
for VMD, named Molcontroller, which is featured by allowing users to quickly
and conveniently perform various molecular manipulations. This GUI might be
helpful for improving the modeling efficiency of VMD users.
| [
{
"created": "Thu, 2 Jul 2020 09:20:00 GMT",
"version": "v1"
}
] | 2020-07-03 | [
[
"Wu",
"ChenChen",
""
],
[
"Liu",
"Shengtang",
""
],
[
"Zhang",
"Shitong",
""
],
[
"Yang",
"Zaixing",
""
]
] | Visual Molecular Dynamics (VMD) is one of the most widely used molecular graphics software in the community of theoretical simulations. So far, however, it still lacks a graphical user interface (GUI) for molecular manipulations when doing some modeling tasks. For instance, translation or rotation of a selected molecule(s) or part(s) of a molecule, which are currently only can be achieved using tcl scripts. Here, we use tcl script develop a user-friendly GUI for VMD, named Molcontroller, which is featured by allowing users to quickly and conveniently perform various molecular manipulations. This GUI might be helpful for improving the modeling efficiency of VMD users. |
1203.3966 | Bailu Si | Bailu Si, Emilio Kropff, Alessandro Treves | Grid Alignment in Entorhinal Cortex | null | null | null | null | q-bio.NC cond-mat.dis-nn nlin.AO nlin.PS physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The spatial responses of many of the cells recorded in all layers of rodent
medial entorhinal cortex (mEC) show a triangular grid pattern, and once
established might be based in part on path-integration mechanisms. Grid axes
are tightly aligned across simultaneously recorded units. Recent experimental
findings have shown that grids can often be better described as elliptical
rather than purely circular and that, beyond the mutual alignment of their grid
axes, ellipses tend to also orient their long axis along preferred directions.
Are grid alignment and ellipse orientation the same phenomenon? Does the grid
alignment result from single-unit mechanisms or does it require network
interactions?
We address these issues by refining our model, to describe specifically the
spontaneous emergence of conjunctive grid-by-head-direction cells in layers
III, V and VI of mEC. We find that tight alignment can be produced by recurrent
collateral interactions, but this requires head-direction modulation. Through a
competitive learning process driven by spatial inputs, grid fields then form
already aligned, and with randomly distributed spatial phases. In addition, we
find that the self-organization process is influenced by the behavior of the
simulated rat. The common grid alignment often orients along preferred running
directions. The shape of individual grids is distorted towards an ellipsoid
arrangement when some speed anisotropy is present in exploration behavior.
Speed anisotropy on its own also tends to align grids, even without
collaterals, but the alignment is seen to be loose. Finally, the alignment of
spatial grid fields in multiple environments shows that the network expresses
the same set of grid fields across environments, modulo a coherent rotation and
translation. Thus, an efficient metric encoding of space may emerge through
spontaneous pattern formation at the single-unit level.
| [
{
"created": "Sun, 18 Mar 2012 15:53:01 GMT",
"version": "v1"
}
] | 2012-03-20 | [
[
"Si",
"Bailu",
""
],
[
"Kropff",
"Emilio",
""
],
[
"Treves",
"Alessandro",
""
]
] | The spatial responses of many of the cells recorded in all layers of rodent medial entorhinal cortex (mEC) show a triangular grid pattern, and once established might be based in part on path-integration mechanisms. Grid axes are tightly aligned across simultaneously recorded units. Recent experimental findings have shown that grids can often be better described as elliptical rather than purely circular and that, beyond the mutual alignment of their grid axes, ellipses tend to also orient their long axis along preferred directions. Are grid alignment and ellipse orientation the same phenomenon? Does the grid alignment result from single-unit mechanisms or does it require network interactions? We address these issues by refining our model, to describe specifically the spontaneous emergence of conjunctive grid-by-head-direction cells in layers III, V and VI of mEC. We find that tight alignment can be produced by recurrent collateral interactions, but this requires head-direction modulation. Through a competitive learning process driven by spatial inputs, grid fields then form already aligned, and with randomly distributed spatial phases. In addition, we find that the self-organization process is influenced by the behavior of the simulated rat. The common grid alignment often orients along preferred running directions. The shape of individual grids is distorted towards an ellipsoid arrangement when some speed anisotropy is present in exploration behavior. Speed anisotropy on its own also tends to align grids, even without collaterals, but the alignment is seen to be loose. Finally, the alignment of spatial grid fields in multiple environments shows that the network expresses the same set of grid fields across environments, modulo a coherent rotation and translation. Thus, an efficient metric encoding of space may emerge through spontaneous pattern formation at the single-unit level. |
2110.06144 | Ian von Hegner | Ian von Hegner | Extreme exoworlds and the extremophile paradox | 14 pages | null | 10.1089/ast.2021.0153 | null | q-bio.PE physics.bio-ph | http://creativecommons.org/licenses/by/4.0/ | Extremophiles have gained prominence by providing an experimental approach to
astrobiology. Extremophiles gain equal value by being part of a framework for
high-level characterisation of the evolutionary mechanisms that must
necessarily restrict or promote their emergence and presence on solar system
bodies. Thus, extremophiles exist in extreme environments, and therein lies the
paradox: extremophiles can only live in extreme environments but yet are not
able to originate in such environments. Therefore, even though the range of
extremophile capabilities in extreme environments is wider than that in
mesophiles, the range of their emergence possibilities is still equally
restricted. Therefore, even if one locates an extreme exoworld where
terrestrial extremophiles could live here-and-now, it can be predicted that no
extremophile analogues are present anyway. Furthermore, it is possible for a
world to be uninhabited, yet be habitable, and therein arises the extreme
environment paradox: an extreme environment can sustain chemical evolution as
well as arriving non-native life, yet native life cannot be built up in that
very environment. Thus, life may exist on an extraterrestrial extreme world (if
imported there), and chemical evolution may be present on that world. However,
it can be predicted that there is no native life anyway. This situation can be
predicted to function as a chemosignature and eventually as a biosignature.
However, the fact that a non-native extremopile in principle can exist in
extreme environments may demonstrate that the intermediate step between
chemical evolution and extremophiles can still occur in the form of a
statistical deviation.
| [
{
"created": "Fri, 17 Sep 2021 08:43:02 GMT",
"version": "v1"
},
{
"created": "Wed, 13 Oct 2021 07:11:29 GMT",
"version": "v2"
}
] | 2022-08-17 | [
[
"von Hegner",
"Ian",
""
]
] | Extremophiles have gained prominence by providing an experimental approach to astrobiology. Extremophiles gain equal value by being part of a framework for high-level characterisation of the evolutionary mechanisms that must necessarily restrict or promote their emergence and presence on solar system bodies. Thus, extremophiles exist in extreme environments, and therein lies the paradox: extremophiles can only live in extreme environments but yet are not able to originate in such environments. Therefore, even though the range of extremophile capabilities in extreme environments is wider than that in mesophiles, the range of their emergence possibilities is still equally restricted. Therefore, even if one locates an extreme exoworld where terrestrial extremophiles could live here-and-now, it can be predicted that no extremophile analogues are present anyway. Furthermore, it is possible for a world to be uninhabited, yet be habitable, and therein arises the extreme environment paradox: an extreme environment can sustain chemical evolution as well as arriving non-native life, yet native life cannot be built up in that very environment. Thus, life may exist on an extraterrestrial extreme world (if imported there), and chemical evolution may be present on that world. However, it can be predicted that there is no native life anyway. This situation can be predicted to function as a chemosignature and eventually as a biosignature. However, the fact that a non-native extremopile in principle can exist in extreme environments may demonstrate that the intermediate step between chemical evolution and extremophiles can still occur in the form of a statistical deviation. |
2211.02430 | Cl\'audia Arag\~ao | C. Arag\~ao, M. Cabano, R. Colen, J. Fuentes and J. Dias | Alternative formulations for gilthead seabream diets: towards a more
sustainable production | null | Aquaculture Nutrition 26: 444-455 (2020) | 10.1111/anu.13007 | null | q-bio.TO | http://creativecommons.org/licenses/by-nc-nd/4.0/ | To support the expected increase in aquaculture production during the next
years, a wider range of alternative ingredients to fishmeal is needed, towards
contributing to an increase in production sustainability. This study aimed to
test diets formulated with non-conventional feed ingredients on gilthead
seabream (Sparus aurata) growth performance, feed utilization, apparent
digestibility of nutrients and nutrient outputs to the environment. Four
isonitrogenous and isoenergetic diets were formulated: a control diet (CTRL)
similar to a commercial feed and three experimental diets containing, as main
protein sources, plant by-products, glutens and concentrates (PLANT); processed
animal proteins (PAP); or micro/macroalgae, insect meals and yeast (EMERG).
Diets were tested in triplicate during 80 days. The (EMERG) treatment resulted
in lower fish growth performance, higher FCR and lower nutrient and energy
retentions than the other treatments. The lowest protein digestibility was
found for the EMERG diet, which caused increased nitrogen losses. The PLANT and
PAP treatments resulted in better fish growth performance, higher nutrient and
energy retentions, and lower FCR than the CTRL treatment. The significant
improvement in FCR found for fish fed PLANT and PAP diets and the high protein
digestibility of these diets contribute towards minimizing the environmental
impacts of seabream production
| [
{
"created": "Thu, 3 Nov 2022 17:15:08 GMT",
"version": "v1"
}
] | 2022-11-07 | [
[
"Aragão",
"C.",
""
],
[
"Cabano",
"M.",
""
],
[
"Colen",
"R.",
""
],
[
"Fuentes",
"J.",
""
],
[
"Dias",
"J.",
""
]
] | To support the expected increase in aquaculture production during the next years, a wider range of alternative ingredients to fishmeal is needed, towards contributing to an increase in production sustainability. This study aimed to test diets formulated with non-conventional feed ingredients on gilthead seabream (Sparus aurata) growth performance, feed utilization, apparent digestibility of nutrients and nutrient outputs to the environment. Four isonitrogenous and isoenergetic diets were formulated: a control diet (CTRL) similar to a commercial feed and three experimental diets containing, as main protein sources, plant by-products, glutens and concentrates (PLANT); processed animal proteins (PAP); or micro/macroalgae, insect meals and yeast (EMERG). Diets were tested in triplicate during 80 days. The (EMERG) treatment resulted in lower fish growth performance, higher FCR and lower nutrient and energy retentions than the other treatments. The lowest protein digestibility was found for the EMERG diet, which caused increased nitrogen losses. The PLANT and PAP treatments resulted in better fish growth performance, higher nutrient and energy retentions, and lower FCR than the CTRL treatment. The significant improvement in FCR found for fish fed PLANT and PAP diets and the high protein digestibility of these diets contribute towards minimizing the environmental impacts of seabream production |
0906.3507 | Steven Frank | Steven A. Frank | The common patterns of nature | Published version freely available at DOI listed here | Journal of Evolutionary Biology 22:1563-1585 (2009) | 10.1111/j.1420-9101.2009.01775.x | null | q-bio.QM physics.data-an q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We typically observe large-scale outcomes that arise from the interactions of
many hidden, small-scale processes. Examples include age of disease onset,
rates of amino acid substitutions, and composition of ecological communities.
The macroscopic patterns in each problem often vary around a characteristic
shape that can be generated by neutral processes. A neutral generative model
assumes that each microscopic process follows unbiased stochastic fluctuations:
random connections of network nodes; amino acid substitutions with no effect on
fitness; species that arise or disappear from communities randomly. These
neutral generative models often match common patterns of nature. In this paper,
I present the theoretical background by which we can understand why these
neutral generative models are so successful. I show how the classic patterns
such as Poisson and Gaussian arise. Each classic pattern was often discovered
by a simple neutral generative model. The neutral patterns share a special
characteristic: they describe the patterns of nature that follow from simple
constraints on information. For example, any aggregation of processes that
preserves information only about the mean and variance attracts to the Gaussian
pattern; any aggregation that preserves information only about the mean
attracts to the exponential pattern; any aggregation that preserves information
only about the geometric mean attracts to the power law pattern. I present an
informational framework of the common patterns of nature based on the method of
maximum entropy. This framework shows that each neutral generative model is a
special case that helps to discover a particular set of informational
constraints; those informational constraints define a much wider domain of
non-neutral generative processes that attract to the same neutral pattern.
| [
{
"created": "Thu, 18 Jun 2009 19:10:38 GMT",
"version": "v1"
}
] | 2009-07-19 | [
[
"Frank",
"Steven A.",
""
]
] | We typically observe large-scale outcomes that arise from the interactions of many hidden, small-scale processes. Examples include age of disease onset, rates of amino acid substitutions, and composition of ecological communities. The macroscopic patterns in each problem often vary around a characteristic shape that can be generated by neutral processes. A neutral generative model assumes that each microscopic process follows unbiased stochastic fluctuations: random connections of network nodes; amino acid substitutions with no effect on fitness; species that arise or disappear from communities randomly. These neutral generative models often match common patterns of nature. In this paper, I present the theoretical background by which we can understand why these neutral generative models are so successful. I show how the classic patterns such as Poisson and Gaussian arise. Each classic pattern was often discovered by a simple neutral generative model. The neutral patterns share a special characteristic: they describe the patterns of nature that follow from simple constraints on information. For example, any aggregation of processes that preserves information only about the mean and variance attracts to the Gaussian pattern; any aggregation that preserves information only about the mean attracts to the exponential pattern; any aggregation that preserves information only about the geometric mean attracts to the power law pattern. I present an informational framework of the common patterns of nature based on the method of maximum entropy. This framework shows that each neutral generative model is a special case that helps to discover a particular set of informational constraints; those informational constraints define a much wider domain of non-neutral generative processes that attract to the same neutral pattern. |
1602.05723 | Aristides Moustakas | Aristides Moustakas | The effects of marine protected areas over time and species dispersal
potential: A quantitative conservation conflict attempt | to appear in the journal: Web Ecology | null | null | null | q-bio.PE cs.MA q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Protected areas are an important conservation measure. However, there are
controversial findings regarding whether closed areas are beneficial for
species and habitat conservation as well as landings. Species dispersal is
acknowledged as a key factor for the design and impacts of closed areas. A
series of agent based models using random diffusion to model fish dispersal
were run before and after habitat protection. All results were normalised
without the protected habitat in each scenario to detect the relative
difference after closing an area, all else being equal. Results show that
landings of species with short dispersal ranges will take longer to reach the
levels of pre Marine Protected Areas (MPAs) establishment than landings of
species with long dispersal ranges. Further the establishment of an MPA
generates a higher relative population source within the MPA for species with
low dispersal abilities than for species with high dispersal abilities. Results
derived here show that there exists a win-win feasible scenario that maximises
both fish biomass as well as fish catches.
| [
{
"created": "Thu, 18 Feb 2016 09:02:38 GMT",
"version": "v1"
},
{
"created": "Thu, 28 Jul 2016 08:35:31 GMT",
"version": "v2"
}
] | 2016-07-29 | [
[
"Moustakas",
"Aristides",
""
]
] | Protected areas are an important conservation measure. However, there are controversial findings regarding whether closed areas are beneficial for species and habitat conservation as well as landings. Species dispersal is acknowledged as a key factor for the design and impacts of closed areas. A series of agent based models using random diffusion to model fish dispersal were run before and after habitat protection. All results were normalised without the protected habitat in each scenario to detect the relative difference after closing an area, all else being equal. Results show that landings of species with short dispersal ranges will take longer to reach the levels of pre Marine Protected Areas (MPAs) establishment than landings of species with long dispersal ranges. Further the establishment of an MPA generates a higher relative population source within the MPA for species with low dispersal abilities than for species with high dispersal abilities. Results derived here show that there exists a win-win feasible scenario that maximises both fish biomass as well as fish catches. |
2309.09813 | Paulo Roberto Cabral-Passos | Paulo Roberto Cabral-Passos, Antonio Galves, Jesus Enrique Garcia, and
Claudia Domingues Vargas | What comes next? response times are affected by mispredictions in a
stochastic game | null | null | null | null | q-bio.NC math.PR | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Acting as a goalkeeper in a video-game, a participant is asked to predict the
successive choices of the penalty taker. The sequence of choices of the penalty
taker is generated by a stochastic chain with memory of variable length. It has
been conjectured that the probability distribution of the response times is a
function of the specific sequence of past choices governing the algorithm used
by the penalty taker to make his choice at each step. We found empirical
evidence that besides this dependence, the distribution of the response times
depends also on the success or failure of the previous prediction made by the
participant. Moreover, we found statistical evidence that this dependence
propagates up to two steps forward after the prediction failure.
| [
{
"created": "Mon, 18 Sep 2023 14:35:37 GMT",
"version": "v1"
}
] | 2023-09-19 | [
[
"Cabral-Passos",
"Paulo Roberto",
""
],
[
"Galves",
"Antonio",
""
],
[
"Garcia",
"Jesus Enrique",
""
],
[
"Vargas",
"Claudia Domingues",
""
]
] | Acting as a goalkeeper in a video-game, a participant is asked to predict the successive choices of the penalty taker. The sequence of choices of the penalty taker is generated by a stochastic chain with memory of variable length. It has been conjectured that the probability distribution of the response times is a function of the specific sequence of past choices governing the algorithm used by the penalty taker to make his choice at each step. We found empirical evidence that besides this dependence, the distribution of the response times depends also on the success or failure of the previous prediction made by the participant. Moreover, we found statistical evidence that this dependence propagates up to two steps forward after the prediction failure. |
2105.01933 | Stephan Bialonski | Niklas Grieger, Justus T. C. Schwabedal, Stefanie Wendel, Yvonne
Ritze, Stephan Bialonski | Automated scoring of pre-REM sleep in mice with deep learning | 14 pages, 5 figures | S. Scientific Reports 11, 12245 (2021) | 10.1038/s41598-021-91286-0 | null | q-bio.QM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Reliable automation of the labor-intensive manual task of scoring animal
sleep can facilitate the analysis of long-term sleep studies. In recent years,
deep-learning-based systems, which learn optimal features from the data,
increased scoring accuracies for the classical sleep stages of Wake, REM, and
Non-REM. Meanwhile, it has been recognized that the statistics of transitional
stages such as pre-REM, found between Non-REM and REM, may hold additional
insight into the physiology of sleep and are now under vivid investigation. We
propose a classification system based on a simple neural network architecture
that scores the classical stages as well as pre-REM sleep in mice. When
restricted to the classical stages, the optimized network showed
state-of-the-art classification performance with an out-of-sample F1 score of
0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1
scores on pre-REM (0.5) compared to the classical stages. The result is
comparable to previous attempts to score transitional stages in other species
such as transition sleep in rats or N1 sleep in humans. Nevertheless, we
observed that the sequence of predictions including pre-REM typically
transitioned from Non-REM to REM reflecting sleep dynamics observed by human
scorers. Our findings provide further evidence for the difficulty of scoring
transitional sleep stages, likely because such stages of sleep are
under-represented in typical data sets or show large inter-scorer variability.
We further provide our source code and an online platform to run predictions
with our trained network.
| [
{
"created": "Wed, 5 May 2021 09:03:03 GMT",
"version": "v1"
},
{
"created": "Wed, 16 Jun 2021 10:43:30 GMT",
"version": "v2"
}
] | 2021-06-17 | [
[
"Grieger",
"Niklas",
""
],
[
"Schwabedal",
"Justus T. C.",
""
],
[
"Wendel",
"Stefanie",
""
],
[
"Ritze",
"Yvonne",
""
],
[
"Bialonski",
"Stephan",
""
]
] | Reliable automation of the labor-intensive manual task of scoring animal sleep can facilitate the analysis of long-term sleep studies. In recent years, deep-learning-based systems, which learn optimal features from the data, increased scoring accuracies for the classical sleep stages of Wake, REM, and Non-REM. Meanwhile, it has been recognized that the statistics of transitional stages such as pre-REM, found between Non-REM and REM, may hold additional insight into the physiology of sleep and are now under vivid investigation. We propose a classification system based on a simple neural network architecture that scores the classical stages as well as pre-REM sleep in mice. When restricted to the classical stages, the optimized network showed state-of-the-art classification performance with an out-of-sample F1 score of 0.95 in male C57BL/6J mice. When unrestricted, the network showed lower F1 scores on pre-REM (0.5) compared to the classical stages. The result is comparable to previous attempts to score transitional stages in other species such as transition sleep in rats or N1 sleep in humans. Nevertheless, we observed that the sequence of predictions including pre-REM typically transitioned from Non-REM to REM reflecting sleep dynamics observed by human scorers. Our findings provide further evidence for the difficulty of scoring transitional sleep stages, likely because such stages of sleep are under-represented in typical data sets or show large inter-scorer variability. We further provide our source code and an online platform to run predictions with our trained network. |
2210.03677 | Karna Gowda | Juan Diaz-Colunga, Abigail Skwara, Karna Gowda, Ramon Diaz-Uriarte,
Mikhail Tikhonov, Djordje Bajic, and Alvaro Sanchez | Global epistasis on fitness landscapes | 20 pages, 4 figures | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Epistatic interactions between mutations add substantial complexity to
adaptive landscapes, and are often thought of as detrimental to our ability to
predict evolution. Yet, patterns of global epistasis, in which the fitness
effect of a mutation is well-predicted by the fitness of its genetic
background, may actually be of help in our efforts to reconstruct fitness
landscapes and infer adaptive trajectories. Microscopic interactions between
mutations, or inherent nonlinearities in the fitness landscape, may cause
global epistasis patterns to emerge. In this brief review, we provide a
succinct overview of recent work about global epistasis, with an emphasis on
building intuition about why it is often observed. To this end, we reconcile
simple geometric reasoning with recent mathematical analyses, using these to
explain why different mutations in an empirical landscape may exhibit different
global epistasis patterns - ranging from diminishing to increasing returns.
Finally, we highlight open questions and research directions.
| [
{
"created": "Fri, 7 Oct 2022 16:34:43 GMT",
"version": "v1"
}
] | 2022-10-10 | [
[
"Diaz-Colunga",
"Juan",
""
],
[
"Skwara",
"Abigail",
""
],
[
"Gowda",
"Karna",
""
],
[
"Diaz-Uriarte",
"Ramon",
""
],
[
"Tikhonov",
"Mikhail",
""
],
[
"Bajic",
"Djordje",
""
],
[
"Sanchez",
"Alvaro",
""
]
] | Epistatic interactions between mutations add substantial complexity to adaptive landscapes, and are often thought of as detrimental to our ability to predict evolution. Yet, patterns of global epistasis, in which the fitness effect of a mutation is well-predicted by the fitness of its genetic background, may actually be of help in our efforts to reconstruct fitness landscapes and infer adaptive trajectories. Microscopic interactions between mutations, or inherent nonlinearities in the fitness landscape, may cause global epistasis patterns to emerge. In this brief review, we provide a succinct overview of recent work about global epistasis, with an emphasis on building intuition about why it is often observed. To this end, we reconcile simple geometric reasoning with recent mathematical analyses, using these to explain why different mutations in an empirical landscape may exhibit different global epistasis patterns - ranging from diminishing to increasing returns. Finally, we highlight open questions and research directions. |
2203.04848 | Vojtech Spiwok | Vojt\v{e}ch Spiwok, Martin Kure\v{c}ka, Ale\v{s} K\v{r}enek | Collective Variable for Metadynamics Derived from AlphaFold Output | 16 pages, 9 figures | Front. Mol. Biosci. 9, 878133 (2022) | 10.3389/fmolb.2022.878133 | null | q-bio.BM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | AlphaFold is a neural-network-based tool for the prediction of 3D structures
of protein. In CASP14, a blind structure prediction challenge, it performed
significantly better than other competitors, which makes it the best available
structure prediction tool. One of the outputs of AlphaFold is the probability
profile of residue-residue distances. This makes it possible to score any
conformation of the studied protein to express its compliance with the
AlphaFold model. Here we show how this score can be used to drive protein
folding simulation by metadynamics and parallel tempering metadynamics. By
parallel tempering metadynamics, we simulated folding of a mini-protein
Trp-cage beta hairpin and predicted their folding equilibria. We see the
potential of AlphaFold-based collective variable in applications beyond
structure prediction, such as in structure refinement or prediction of the
outcome of a mutation.
| [
{
"created": "Thu, 17 Feb 2022 13:59:12 GMT",
"version": "v1"
},
{
"created": "Fri, 29 Apr 2022 14:25:57 GMT",
"version": "v2"
}
] | 2022-06-22 | [
[
"Spiwok",
"Vojtěch",
""
],
[
"Kurečka",
"Martin",
""
],
[
"Křenek",
"Aleš",
""
]
] | AlphaFold is a neural-network-based tool for the prediction of 3D structures of protein. In CASP14, a blind structure prediction challenge, it performed significantly better than other competitors, which makes it the best available structure prediction tool. One of the outputs of AlphaFold is the probability profile of residue-residue distances. This makes it possible to score any conformation of the studied protein to express its compliance with the AlphaFold model. Here we show how this score can be used to drive protein folding simulation by metadynamics and parallel tempering metadynamics. By parallel tempering metadynamics, we simulated folding of a mini-protein Trp-cage beta hairpin and predicted their folding equilibria. We see the potential of AlphaFold-based collective variable in applications beyond structure prediction, such as in structure refinement or prediction of the outcome of a mutation. |
1412.4034 | Gary Whittaker | Beth N. Licitra, Kelly L. Sams, Donald W. Lee and Gary R.Whittaker | Feline coronaviruses associated with feline infectious peritonitis have
modifications to spike protein activation sites at two discrete positions | 5 pages, 4 tables, 1 figure | null | null | null | q-bio.GN q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Feline infectious peritonitis (FIP) is associated with mutations in the
feline coronavirus (FCoV) genome that are thought to convert the subclinical
feline enteric coronavirus (FECV) into the lethal feline infectious peritonitis
virus (FIPV). A key feature of FIPV, not shared with FECV, is the productive
infection of macrophages. Therefore mutations in proteins that govern cell
tropism, such as the spike glycoprotein, may play an important role in FIP
progression. In a prior study, involving a limited number of samples, we have
shown an association of FIP with mutations in the protease cleavage-activation
site located between the receptor-binding and fusion domains of the FCoV spike
(S1/S2). Here, we extend these studies to investigate a larger sample set and
to obtain a more refined analysis of the mutations at this S1/S2 site. Our
larger data set more clearly shows that the mutations acquired by FIPV at S1/S2
are also accompanied by additional mutations at a second protease
cleavage-activation site located in the fusion domain (S2'), adjacent to the
viral fusion peptide. Overall, our data indicate a pattern of mutations across
the two protease recognition sites that results in substitutions, and/or
altered recognition, of critical basic/polar amino acid residues needed for
virus activation in the enteric tract. Typically, FIPVs have substitutions of
non-polar, aliphatic or aromatic residues in the protease recognition sites.
These changes likely modulate the proteolytic activation of the virus and its
ability to productively infect macrophages in vivo.
| [
{
"created": "Fri, 12 Dec 2014 16:15:49 GMT",
"version": "v1"
}
] | 2014-12-15 | [
[
"Licitra",
"Beth N.",
""
],
[
"Sams",
"Kelly L.",
""
],
[
"Lee",
"Donald W.",
""
],
[
"Whittaker",
"Gary R.",
""
]
] | Feline infectious peritonitis (FIP) is associated with mutations in the feline coronavirus (FCoV) genome that are thought to convert the subclinical feline enteric coronavirus (FECV) into the lethal feline infectious peritonitis virus (FIPV). A key feature of FIPV, not shared with FECV, is the productive infection of macrophages. Therefore mutations in proteins that govern cell tropism, such as the spike glycoprotein, may play an important role in FIP progression. In a prior study, involving a limited number of samples, we have shown an association of FIP with mutations in the protease cleavage-activation site located between the receptor-binding and fusion domains of the FCoV spike (S1/S2). Here, we extend these studies to investigate a larger sample set and to obtain a more refined analysis of the mutations at this S1/S2 site. Our larger data set more clearly shows that the mutations acquired by FIPV at S1/S2 are also accompanied by additional mutations at a second protease cleavage-activation site located in the fusion domain (S2'), adjacent to the viral fusion peptide. Overall, our data indicate a pattern of mutations across the two protease recognition sites that results in substitutions, and/or altered recognition, of critical basic/polar amino acid residues needed for virus activation in the enteric tract. Typically, FIPVs have substitutions of non-polar, aliphatic or aromatic residues in the protease recognition sites. These changes likely modulate the proteolytic activation of the virus and its ability to productively infect macrophages in vivo. |
1407.7999 | Jens Christian Claussen | Hong-Viet V. Ngo, Jens Christian Claussen, Jan Born, and Matthias
M\"olle | Induction of slow oscillations by rhythmic acoustic stimulation | null | J. Sleep Res. 22, 22-31 (2013) | 10.1111/j.1365-2869.2012.01039.x | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Slow oscillations are electrical potential oscillations with a spectral peak
frequency of $\sim$0.8 Hz, and hallmark the electroencephalogram during
slow-wave sleep. Recent studies have indicated a causal contribution of slow
oscillations to the consolidation of memories during slow-wave sleep, raising
the question to what extent such oscillations can be induced by external
stimulation. Here, we examined whether slow oscillations can be effectively
induced by rhythmic acoustic stimulation. Human subjects were examined in three
conditions: (i) with tones presented at a rate of 0.8 Hz (`0.8-Hz
stimulation'); (ii) with tones presented at a random sequence (`random
stimulation'); and (iii) with no tones presented in a control condition
(`sham'). Stimulation started during wakefulness before sleep and continued for
the first $\sim$90 min of sleep. Compared with the other two conditions, 0.8-Hz
stimulation significantly delayed sleep onset. However, once sleep was
established, 0.8-Hz stimulation significantly increased and entrained
endogenous slow oscillation activity. Sleep after the 90-min period of
stimulation did not differ between the conditions. Our data show that rhythmic
acoustic stimulation can be used to effectively enhance slow oscillation
activity. However, the effect depends on the brain state, requiring the
presence of stable non-rapid eye movement sleep.
| [
{
"created": "Wed, 30 Jul 2014 11:08:20 GMT",
"version": "v1"
}
] | 2014-07-31 | [
[
"Ngo",
"Hong-Viet V.",
""
],
[
"Claussen",
"Jens Christian",
""
],
[
"Born",
"Jan",
""
],
[
"Mölle",
"Matthias",
""
]
] | Slow oscillations are electrical potential oscillations with a spectral peak frequency of $\sim$0.8 Hz, and hallmark the electroencephalogram during slow-wave sleep. Recent studies have indicated a causal contribution of slow oscillations to the consolidation of memories during slow-wave sleep, raising the question to what extent such oscillations can be induced by external stimulation. Here, we examined whether slow oscillations can be effectively induced by rhythmic acoustic stimulation. Human subjects were examined in three conditions: (i) with tones presented at a rate of 0.8 Hz (`0.8-Hz stimulation'); (ii) with tones presented at a random sequence (`random stimulation'); and (iii) with no tones presented in a control condition (`sham'). Stimulation started during wakefulness before sleep and continued for the first $\sim$90 min of sleep. Compared with the other two conditions, 0.8-Hz stimulation significantly delayed sleep onset. However, once sleep was established, 0.8-Hz stimulation significantly increased and entrained endogenous slow oscillation activity. Sleep after the 90-min period of stimulation did not differ between the conditions. Our data show that rhythmic acoustic stimulation can be used to effectively enhance slow oscillation activity. However, the effect depends on the brain state, requiring the presence of stable non-rapid eye movement sleep. |
2407.11942 | Leo Klarner | Leo Klarner, Tim G. J. Rudner, Garrett M. Morris, Charlotte M. Deane,
Yee Whye Teh | Context-Guided Diffusion for Out-of-Distribution Molecular and Protein
Design | Published in the Proceedings of the 41st International Conference on
Machine Learning (ICML 2024) | null | null | null | q-bio.BM cs.LG stat.ML | http://creativecommons.org/licenses/by/4.0/ | Generative models have the potential to accelerate key steps in the discovery
of novel molecular therapeutics and materials. Diffusion models have recently
emerged as a powerful approach, excelling at unconditional sample generation
and, with data-driven guidance, conditional generation within their training
domain. Reliably sampling from high-value regions beyond the training data,
however, remains an open challenge -- with current methods predominantly
focusing on modifying the diffusion process itself. In this paper, we develop
context-guided diffusion (CGD), a simple plug-and-play method that leverages
unlabeled data and smoothness constraints to improve the out-of-distribution
generalization of guided diffusion models. We demonstrate that this approach
leads to substantial performance gains across various settings, including
continuous, discrete, and graph-structured diffusion processes with
applications across drug discovery, materials science, and protein design.
| [
{
"created": "Tue, 16 Jul 2024 17:34:00 GMT",
"version": "v1"
}
] | 2024-07-17 | [
[
"Klarner",
"Leo",
""
],
[
"Rudner",
"Tim G. J.",
""
],
[
"Morris",
"Garrett M.",
""
],
[
"Deane",
"Charlotte M.",
""
],
[
"Teh",
"Yee Whye",
""
]
] | Generative models have the potential to accelerate key steps in the discovery of novel molecular therapeutics and materials. Diffusion models have recently emerged as a powerful approach, excelling at unconditional sample generation and, with data-driven guidance, conditional generation within their training domain. Reliably sampling from high-value regions beyond the training data, however, remains an open challenge -- with current methods predominantly focusing on modifying the diffusion process itself. In this paper, we develop context-guided diffusion (CGD), a simple plug-and-play method that leverages unlabeled data and smoothness constraints to improve the out-of-distribution generalization of guided diffusion models. We demonstrate that this approach leads to substantial performance gains across various settings, including continuous, discrete, and graph-structured diffusion processes with applications across drug discovery, materials science, and protein design. |
2304.04775 | Wanting Su None | Wanting Su, Dongwei Liu, Feng Tan, Lun Hu, Pengwei Hu | NutriFD: Proving the medicinal value of food nutrition based on
food-disease association and treatment networks | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | There is rising evidence of the health benefit associated with specific
dietary interventions. Current food-disease databases focus on associations and
treatment relationships but haven't provided a reasonable assessment of the
strength of the relationship, and lack of attention on food nutrition. There is
an unmet need for a large database that can guide dietary therapy. We fill the
gap with NutriFD, a scoring network based on associations and therapeutic
relationships between foods and diseases. NutriFD integrates 9 databases
including foods, nutrients, diseases, genes, miRNAs, compounds, disease
ontology and their relationships. To our best knowledge, this database is the
only one that can score the associations and therapeutic relationships of
everyday foods and diseases by weighting inference scores of food compounds to
diseases. In addition, NutriFD demonstrates the predictive nature of nutrients
on the therapeutic relationships between foods and diseases through machine
learning models, laying the foundation for a mechanistic understanding of food
therapy.
| [
{
"created": "Mon, 10 Apr 2023 13:21:10 GMT",
"version": "v1"
},
{
"created": "Wed, 17 May 2023 11:51:29 GMT",
"version": "v2"
}
] | 2023-05-18 | [
[
"Su",
"Wanting",
""
],
[
"Liu",
"Dongwei",
""
],
[
"Tan",
"Feng",
""
],
[
"Hu",
"Lun",
""
],
[
"Hu",
"Pengwei",
""
]
] | There is rising evidence of the health benefit associated with specific dietary interventions. Current food-disease databases focus on associations and treatment relationships but haven't provided a reasonable assessment of the strength of the relationship, and lack of attention on food nutrition. There is an unmet need for a large database that can guide dietary therapy. We fill the gap with NutriFD, a scoring network based on associations and therapeutic relationships between foods and diseases. NutriFD integrates 9 databases including foods, nutrients, diseases, genes, miRNAs, compounds, disease ontology and their relationships. To our best knowledge, this database is the only one that can score the associations and therapeutic relationships of everyday foods and diseases by weighting inference scores of food compounds to diseases. In addition, NutriFD demonstrates the predictive nature of nutrients on the therapeutic relationships between foods and diseases through machine learning models, laying the foundation for a mechanistic understanding of food therapy. |
2103.10033 | Paolo Castorina | P.Castorina, D.Carco', C.Colarossi, M.Mare, L.Memeo, M.Pace,
I.Puliafito, D.Giuffrida | Quantitative predictions of neoadjuvant chemotherapy effects in breast
cancer by individual patient data assimililation | In press on Annals of Hematology and Oncology | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Neoadjuvant chemotherapy has been used for breast cancer aiming at
downgrading before surgery. In this article we propose a new quantitative
analysis of the effects of the neoadjuvant therapy to obtain numerical,
personalized, predictions on the shrinkage of the tumor size after the drug
doses, by data assimilation of the individual patient. The algorithm has been
validated by a sample of 37 patients with histological diagnosis of locally
advanced primary breast carcinoma. The biopsy specimen, the initial tumor size
and its reduction after each treatment were known for all patients. We find
that: a) the measure of tumor size at the diagnosis and after the first dose
permits to predict the size reduction for the follow up; b) the results are in
agreement with our data sample, within 10-20 %, for about 90% of the patients.
The quantitative indications suggest the best time for surgery. The analysis is
patient oriented, weakly model dependent and can be applied to other cancer
phenotypes.
| [
{
"created": "Thu, 18 Mar 2021 06:09:53 GMT",
"version": "v1"
}
] | 2021-03-19 | [
[
"Castorina",
"P.",
""
],
[
"Carco'",
"D.",
""
],
[
"Colarossi",
"C.",
""
],
[
"Mare",
"M.",
""
],
[
"Memeo",
"L.",
""
],
[
"Pace",
"M.",
""
],
[
"Puliafito",
"I.",
""
],
[
"Giuffrida",
"D.",
""
]
] | Neoadjuvant chemotherapy has been used for breast cancer aiming at downgrading before surgery. In this article we propose a new quantitative analysis of the effects of the neoadjuvant therapy to obtain numerical, personalized, predictions on the shrinkage of the tumor size after the drug doses, by data assimilation of the individual patient. The algorithm has been validated by a sample of 37 patients with histological diagnosis of locally advanced primary breast carcinoma. The biopsy specimen, the initial tumor size and its reduction after each treatment were known for all patients. We find that: a) the measure of tumor size at the diagnosis and after the first dose permits to predict the size reduction for the follow up; b) the results are in agreement with our data sample, within 10-20 %, for about 90% of the patients. The quantitative indications suggest the best time for surgery. The analysis is patient oriented, weakly model dependent and can be applied to other cancer phenotypes. |
2407.11687 | Kartik Ayyer | Abhishek Mall, Anna Munke, Zhou Shen, Parichita Mazumder, Johan
Bielecki, Juncheng E, Armando Estillore, Chan Kim, Romain Letrun, Jannik
L\"ubke, Safi Rafie-Zinedine, Adam Round, Ekaterina Round, Michael R\"utten,
Amit K. Samanta, Abhisakh Sarma, Tokushi Sato, Florian Schulz, Carolin
Seuring, Tamme Wollweber, Lena Worbs, Patrik Vagovic, Richard Bean, Adrian P.
Mancuso, Ne-Te Duane Loh, Tobias Beck, Jochen K\"upper, Filipe R.N.C. Maia,
Henry N. Chapman, and Kartik Ayyer | Observation of Aerosolization-induced Morphological Changes in Viral
Capsids | 10 pages, 4 figures plus 9 pages supplementary information | null | null | null | q-bio.BM eess.IV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Single-stranded RNA viruses co-assemble their capsid with the genome and
variations in capsid structures can have significant functional relevance. In
particular, viruses need to respond to a dehydrating environment to prevent
genomic degradation and remain active upon rehydration. Theoretical work has
predicted low-energy buckling transitions in icosahedral capsids which could
protect the virus from further dehydration. However, there has been no direct
experimental evidence, nor molecular mechanism, for such behaviour. Here we
observe this transition using X-ray single particle imaging of MS2
bacteriophages after aerosolization. Using a combination of machine learning
tools, we classify hundreds of thousands of single particle diffraction
patterns to learn the structural landscape of the capsid morphology as a
function of time spent in the aerosol phase. We found a previously unreported
compact conformation as well as intermediate structures which suggest an
incoherent buckling transition which does not preserve icosahedral symmetry.
Finally, we propose a mechanism of this buckling, where a single 19-residue
loop is destabilised, leading to the large observed morphology change. Our
results provide experimental evidence for a mechanism by which viral capsids
protect themselves from dehydration. In the process, these findings also
demonstrate the power of single particle X-ray imaging and machine learning
methods in studying biomolecular structural dynamics.
| [
{
"created": "Tue, 16 Jul 2024 13:04:14 GMT",
"version": "v1"
}
] | 2024-07-17 | [
[
"Mall",
"Abhishek",
""
],
[
"Munke",
"Anna",
""
],
[
"Shen",
"Zhou",
""
],
[
"Mazumder",
"Parichita",
""
],
[
"Bielecki",
"Johan",
""
],
[
"E",
"Juncheng",
""
],
[
"Estillore",
"Armando",
""
],
[
"Kim",
"Chan",
""
],
[
"Letrun",
"Romain",
""
],
[
"Lübke",
"Jannik",
""
],
[
"Rafie-Zinedine",
"Safi",
""
],
[
"Round",
"Adam",
""
],
[
"Round",
"Ekaterina",
""
],
[
"Rütten",
"Michael",
""
],
[
"Samanta",
"Amit K.",
""
],
[
"Sarma",
"Abhisakh",
""
],
[
"Sato",
"Tokushi",
""
],
[
"Schulz",
"Florian",
""
],
[
"Seuring",
"Carolin",
""
],
[
"Wollweber",
"Tamme",
""
],
[
"Worbs",
"Lena",
""
],
[
"Vagovic",
"Patrik",
""
],
[
"Bean",
"Richard",
""
],
[
"Mancuso",
"Adrian P.",
""
],
[
"Loh",
"Ne-Te Duane",
""
],
[
"Beck",
"Tobias",
""
],
[
"Küpper",
"Jochen",
""
],
[
"Maia",
"Filipe R. N. C.",
""
],
[
"Chapman",
"Henry N.",
""
],
[
"Ayyer",
"Kartik",
""
]
] | Single-stranded RNA viruses co-assemble their capsid with the genome and variations in capsid structures can have significant functional relevance. In particular, viruses need to respond to a dehydrating environment to prevent genomic degradation and remain active upon rehydration. Theoretical work has predicted low-energy buckling transitions in icosahedral capsids which could protect the virus from further dehydration. However, there has been no direct experimental evidence, nor molecular mechanism, for such behaviour. Here we observe this transition using X-ray single particle imaging of MS2 bacteriophages after aerosolization. Using a combination of machine learning tools, we classify hundreds of thousands of single particle diffraction patterns to learn the structural landscape of the capsid morphology as a function of time spent in the aerosol phase. We found a previously unreported compact conformation as well as intermediate structures which suggest an incoherent buckling transition which does not preserve icosahedral symmetry. Finally, we propose a mechanism of this buckling, where a single 19-residue loop is destabilised, leading to the large observed morphology change. Our results provide experimental evidence for a mechanism by which viral capsids protect themselves from dehydration. In the process, these findings also demonstrate the power of single particle X-ray imaging and machine learning methods in studying biomolecular structural dynamics. |
2005.14363 | Aditi Jha | Aditi Jha, Joshua Peterson, Thomas L. Griffiths | Extracting low-dimensional psychological representations from
convolutional neural networks | Accepted to CogSci 2020 | null | null | null | q-bio.NC cs.CV | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deep neural networks are increasingly being used in cognitive modeling as a
means of deriving representations for complex stimuli such as images. While the
predictive power of these networks is high, it is often not clear whether they
also offer useful explanations of the task at hand. Convolutional neural
network representations have been shown to be predictive of human similarity
judgments for images after appropriate adaptation. However, these
high-dimensional representations are difficult to interpret. Here we present a
method for reducing these representations to a low-dimensional space which is
still predictive of similarity judgments. We show that these low-dimensional
representations also provide insightful explanations of factors underlying
human similarity judgments.
| [
{
"created": "Fri, 29 May 2020 01:29:39 GMT",
"version": "v1"
}
] | 2020-06-01 | [
[
"Jha",
"Aditi",
""
],
[
"Peterson",
"Joshua",
""
],
[
"Griffiths",
"Thomas L.",
""
]
] | Deep neural networks are increasingly being used in cognitive modeling as a means of deriving representations for complex stimuli such as images. While the predictive power of these networks is high, it is often not clear whether they also offer useful explanations of the task at hand. Convolutional neural network representations have been shown to be predictive of human similarity judgments for images after appropriate adaptation. However, these high-dimensional representations are difficult to interpret. Here we present a method for reducing these representations to a low-dimensional space which is still predictive of similarity judgments. We show that these low-dimensional representations also provide insightful explanations of factors underlying human similarity judgments. |
1403.2526 | Pascal Buenzli | Pascal R Buenzli | Osteocytes as a record of bone formation dynamics: A mathematical model
of osteocyte generation in bone matrix | 11 pages, 6 figures. V2: substantially augmented version. Addition of
Section 4 (osteocyte apoptosis) | J Theor Biol 364: 418-427 (2015) | 10.1016/j.jtbi.2014.09.028 | null | q-bio.CB physics.bio-ph q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The formation of new bone involves both the deposition of bone matrix, and
the formation of a network of cells embedded within the bone matrix, called
osteocytes. Osteocytes derive from bone-synthesising cells (osteoblasts) that
become buried in bone matrix during bone deposition. The generation of
osteocytes is a complex process that remains incompletely understood. Whilst
osteoblast burial determines the density of osteocytes, the expanding network
of osteocytes regulates in turn osteoblast activity and osteoblast burial. In
this paper, a spatiotemporal continuous model is proposed to investigate the
osteoblast-to-osteocyte transition. The aims of the model are (i) to link
dynamic properties of osteocyte generation with properties of the osteocyte
network imprinted in bone, and (ii) to investigate Marotti's hypothesis that
osteocytes prompt the burial of osteoblasts when they become covered with
sufficient bone matrix. Osteocyte density is assumed in the model to be
generated at the moving bone surface by a combination of osteoblast density,
matrix secretory rate, rate of entrapment, and curvature of the bone substrate,
but is found to be determined solely by the ratio of the instantaneous burial
rate and matrix secretory rate. Osteocyte density does not explicitly depend on
osteoblast density nor curvature. Osteocyte apoptosis is also included to
distinguish between the density of osteocyte lacuna and the density of live
osteocytes. Experimental measurements of osteocyte lacuna densities are used to
estimate the rate of burial of osteoblasts in bone matrix. These results
suggest that: (i) burial rate decreases during osteonal infilling, and (ii) the
control of osteoblast burial by osteocytes is likely to emanate as a collective
signal from a large group of osteocytes, rather than from the osteocytes
closest to the bone deposition front.
| [
{
"created": "Tue, 11 Mar 2014 10:19:18 GMT",
"version": "v1"
},
{
"created": "Thu, 15 May 2014 12:50:34 GMT",
"version": "v2"
}
] | 2014-12-15 | [
[
"Buenzli",
"Pascal R",
""
]
] | The formation of new bone involves both the deposition of bone matrix, and the formation of a network of cells embedded within the bone matrix, called osteocytes. Osteocytes derive from bone-synthesising cells (osteoblasts) that become buried in bone matrix during bone deposition. The generation of osteocytes is a complex process that remains incompletely understood. Whilst osteoblast burial determines the density of osteocytes, the expanding network of osteocytes regulates in turn osteoblast activity and osteoblast burial. In this paper, a spatiotemporal continuous model is proposed to investigate the osteoblast-to-osteocyte transition. The aims of the model are (i) to link dynamic properties of osteocyte generation with properties of the osteocyte network imprinted in bone, and (ii) to investigate Marotti's hypothesis that osteocytes prompt the burial of osteoblasts when they become covered with sufficient bone matrix. Osteocyte density is assumed in the model to be generated at the moving bone surface by a combination of osteoblast density, matrix secretory rate, rate of entrapment, and curvature of the bone substrate, but is found to be determined solely by the ratio of the instantaneous burial rate and matrix secretory rate. Osteocyte density does not explicitly depend on osteoblast density nor curvature. Osteocyte apoptosis is also included to distinguish between the density of osteocyte lacuna and the density of live osteocytes. Experimental measurements of osteocyte lacuna densities are used to estimate the rate of burial of osteoblasts in bone matrix. These results suggest that: (i) burial rate decreases during osteonal infilling, and (ii) the control of osteoblast burial by osteocytes is likely to emanate as a collective signal from a large group of osteocytes, rather than from the osteocytes closest to the bone deposition front. |
1704.02961 | Elisabeth Logak | Elisabeth Logak, Isabelle Passat | A nonlocal model of epidemic network with nonlimited transmission:
Global existence and uniqueness | null | null | null | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Following \cite{ipel1}, we consider a nonlinear SIS-type nonlocal system
describing the spread of epidemics on networks, assuming nonlimited
transmission, We prove local existence of a unique solution for any diffusion
coefficients and global existence in the case of equal diffusion coefficients.
Next we study the asymptotic behaviour of the solution and show that the
disease-free equilibrium (DFE) is linearly and globally asymptotically stable
when the total mean population is small. Finally, we prove that the solution of
the system converge to the $DFE$.
| [
{
"created": "Mon, 10 Apr 2017 17:35:26 GMT",
"version": "v1"
}
] | 2017-04-11 | [
[
"Logak",
"Elisabeth",
""
],
[
"Passat",
"Isabelle",
""
]
] | Following \cite{ipel1}, we consider a nonlinear SIS-type nonlocal system describing the spread of epidemics on networks, assuming nonlimited transmission, We prove local existence of a unique solution for any diffusion coefficients and global existence in the case of equal diffusion coefficients. Next we study the asymptotic behaviour of the solution and show that the disease-free equilibrium (DFE) is linearly and globally asymptotically stable when the total mean population is small. Finally, we prove that the solution of the system converge to the $DFE$. |
2212.04937 | Kit Gallagher | Kit Gallagher, Ioana Bouros, Nicholas Fan, Elizabeth Hayman, Luke
Heirene, Patricia Lamirande, Annabelle Lemenuel-Diot, Ben Lambert, David
Gavaghan, Richard Creswell | Epidemiological Agent-Based Modelling Software (Epiabm) | Submitted to Journal of Open Research Software | Journal of Open Research Software, 12(1), p. 3 | 10.5334/jors.449 | Volume: 12 Issue: 1 | q-bio.PE q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Epiabm is a fully tested, open-source software package for epidemiological
agent-based modelling, re-implementing the well-known CovidSim model from the
MRC Centre for Global Infectious Disease Analysis at Imperial College London.
It has been developed as part of the first-year training programme in the EPSRC
SABS:R3 Centre for Doctoral Training at the University of Oxford. The model
builds an age-stratified, spatially heterogeneous population and offers a
modular approach to configure and run epidemic scenarios, allowing for a broad
scope of investigative and comparative studies. Two simulation backends are
provided: a pedagogical Python backend (with full functionality) and a high
performance C++ backend for use with larger population simulations. Both are
highly modular, with comprehensive testing and documentation for ease of
understanding and extensibility. Epiabm is publicly available through GitHub at
https://github.com/SABS-R3-Epidemiology/epiabm.
| [
{
"created": "Wed, 7 Dec 2022 11:16:38 GMT",
"version": "v1"
}
] | 2024-03-07 | [
[
"Gallagher",
"Kit",
""
],
[
"Bouros",
"Ioana",
""
],
[
"Fan",
"Nicholas",
""
],
[
"Hayman",
"Elizabeth",
""
],
[
"Heirene",
"Luke",
""
],
[
"Lamirande",
"Patricia",
""
],
[
"Lemenuel-Diot",
"Annabelle",
""
],
[
"Lambert",
"Ben",
""
],
[
"Gavaghan",
"David",
""
],
[
"Creswell",
"Richard",
""
]
] | Epiabm is a fully tested, open-source software package for epidemiological agent-based modelling, re-implementing the well-known CovidSim model from the MRC Centre for Global Infectious Disease Analysis at Imperial College London. It has been developed as part of the first-year training programme in the EPSRC SABS:R3 Centre for Doctoral Training at the University of Oxford. The model builds an age-stratified, spatially heterogeneous population and offers a modular approach to configure and run epidemic scenarios, allowing for a broad scope of investigative and comparative studies. Two simulation backends are provided: a pedagogical Python backend (with full functionality) and a high performance C++ backend for use with larger population simulations. Both are highly modular, with comprehensive testing and documentation for ease of understanding and extensibility. Epiabm is publicly available through GitHub at https://github.com/SABS-R3-Epidemiology/epiabm. |
0902.0400 | Filippo Posta | Filippo Posta, Maria R. D'Orsogna, and Tom Chou | Enhancement of cargo processivity by cooperating molecular motors | 11 pages, 8 figures, submitted to PCCP | null | 10.1039/b900760c | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cellular cargo can be bound to cytoskeletal filaments by one or multiple
active or passive molecular motors. Recent experiments have shown that the
presence of auxiliary, nondriving motors, results in an enhanced processivity
of the cargo, compared to the case of a single active motor alone. We model the
observed cooperative transport process using a stochastic model that describes
the dynamics of two molecular motors, an active one that moves cargo
unidirectionally along a filament track and a passive one that acts as a
tether. Analytical expressions obtained from our analysis are fit to
experimental data to estimate the microscopic kinetic parameters of our model.
Our analysis reveals two qualitatively distinct processivity-enhancing
mechanisms: the passive tether can decrease the typical detachment rate of the
active motor from the filament track or it can increase the corresponding
reattachment rate. Our estimates unambiguously show that in the case of
microtubular transport, a higher average run length arises mainly from the
ability of the passive motor to keep the cargo close to the filament, enhancing
the reattachment rate of an active kinesin motor that has recently detached.
Instead, for myosin-driven transport along actin, the passive motor tightly
tethers the cargo to the filament, suppressing the detachment rate of the
active myosin.
| [
{
"created": "Mon, 2 Feb 2009 23:06:34 GMT",
"version": "v1"
}
] | 2019-03-27 | [
[
"Posta",
"Filippo",
""
],
[
"D'Orsogna",
"Maria R.",
""
],
[
"Chou",
"Tom",
""
]
] | Cellular cargo can be bound to cytoskeletal filaments by one or multiple active or passive molecular motors. Recent experiments have shown that the presence of auxiliary, nondriving motors, results in an enhanced processivity of the cargo, compared to the case of a single active motor alone. We model the observed cooperative transport process using a stochastic model that describes the dynamics of two molecular motors, an active one that moves cargo unidirectionally along a filament track and a passive one that acts as a tether. Analytical expressions obtained from our analysis are fit to experimental data to estimate the microscopic kinetic parameters of our model. Our analysis reveals two qualitatively distinct processivity-enhancing mechanisms: the passive tether can decrease the typical detachment rate of the active motor from the filament track or it can increase the corresponding reattachment rate. Our estimates unambiguously show that in the case of microtubular transport, a higher average run length arises mainly from the ability of the passive motor to keep the cargo close to the filament, enhancing the reattachment rate of an active kinesin motor that has recently detached. Instead, for myosin-driven transport along actin, the passive motor tightly tethers the cargo to the filament, suppressing the detachment rate of the active myosin. |
1407.2297 | Johnatan Aljadeff | Johnatan Aljadeff, Merav Stern, Tatyana O. Sharpee | Transition to chaos in random networks with cell-type-specific
connectivity | null | Phys. Rev. Lett. 114, 088101 (2015) | 10.1103/PhysRevLett.114.088101 | null | q-bio.NC cond-mat.dis-nn math.PR nlin.CD | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In neural circuits, statistical connectivity rules strongly depend on
neuronal type. Here we study dynamics of neural networks with cell-type
specific connectivity by extending the dynamic mean field method, and find that
these networks exhibit a phase transition between silent and chaotic activity.
By analyzing the locus of this transition, we derive a new result in random
matrix theory: the spectral radius of a random connectivity matrix with
block-structured variances. We apply our results to show how a small group of
hyper-excitable neurons within the network can significantly increase the
network's computational capacity.
| [
{
"created": "Tue, 8 Jul 2014 23:30:19 GMT",
"version": "v1"
}
] | 2015-02-24 | [
[
"Aljadeff",
"Johnatan",
""
],
[
"Stern",
"Merav",
""
],
[
"Sharpee",
"Tatyana O.",
""
]
] | In neural circuits, statistical connectivity rules strongly depend on neuronal type. Here we study dynamics of neural networks with cell-type specific connectivity by extending the dynamic mean field method, and find that these networks exhibit a phase transition between silent and chaotic activity. By analyzing the locus of this transition, we derive a new result in random matrix theory: the spectral radius of a random connectivity matrix with block-structured variances. We apply our results to show how a small group of hyper-excitable neurons within the network can significantly increase the network's computational capacity. |
1610.00825 | Zhengwei Xie Prof. | Zhengwei Xie, Tianyu Zhang, Qi Ouyang | Predict genome-scale fluxes based solely on enzyme abundance by a novel
Hyper-Cube Shrink Algorithm | null | null | null | null | q-bio.MN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One of the long-expected goals of genome-scale metabolic modeling is to
evaluate the influence of the perturbed enzymes to the flux distribution. Both
ordinary differential equation (ODE) models and the constraint-based models,
like Flux balance analysis (FBA), lack of the room of performing metabolic
control analysis (MCA) for large-scale networks. In this study, we developed a
Hyper-Cube Shrink Algorithm (HCSA) to incorporate the enzymatic properties to
the FBA model by introducing a pseudo reaction constrained by enzymatic
parameters. Our algorithm was able to handle not only prediction of knockout
strains but also strains with quantitative adjustment of expression level or
activity. We first demonstrate the concept by applying HCSA to a simplest
three-node network. Then we validate its prediction by comparing with ODE and
with a synthetic network in Saccharomyces cerevisiae producing voilacein and
analogues. Finally we show its capability of predicting the flux distribution
in genome-scale networks by applying it to the sporulation in yeast.
| [
{
"created": "Tue, 4 Oct 2016 02:27:11 GMT",
"version": "v1"
}
] | 2016-10-05 | [
[
"Xie",
"Zhengwei",
""
],
[
"Zhang",
"Tianyu",
""
],
[
"Ouyang",
"Qi",
""
]
] | One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the flux distribution. Both ordinary differential equation (ODE) models and the constraint-based models, like Flux balance analysis (FBA), lack of the room of performing metabolic control analysis (MCA) for large-scale networks. In this study, we developed a Hyper-Cube Shrink Algorithm (HCSA) to incorporate the enzymatic properties to the FBA model by introducing a pseudo reaction constrained by enzymatic parameters. Our algorithm was able to handle not only prediction of knockout strains but also strains with quantitative adjustment of expression level or activity. We first demonstrate the concept by applying HCSA to a simplest three-node network. Then we validate its prediction by comparing with ODE and with a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues. Finally we show its capability of predicting the flux distribution in genome-scale networks by applying it to the sporulation in yeast. |
2204.12178 | Johannes Falk | Piotr Nyczka, Johannes Falk, Marc-Thorsten H\"utt | Network location and clustering of genetic mutations determine
chronicity in a stylized model of genetic diseases | null | Sci Rep 12, 19906 (2022) | 10.1038/s41598-022-23775-9 | null | q-bio.MN cond-mat.stat-mech | http://creativecommons.org/licenses/by/4.0/ | In a highly simplified view, a disease can be seen as the phenotype emerging
from the interplay of genetic predisposition and fluctuating environmental
stimuli. We formalize this situation in a minimal model, where a network
(representing cellular regulation) serves as an interface between an input
layer (representing environment) and an output layer (representing functional
phenotype). Genetic predisposition for a disease is represented as a loss of
function of some network nodes. Reduced, but non-zero, output indicates
disease. The simplicity of this genetic disease model and its deep relationship
to percolation theory allows us to understand the interplay between disease,
network topology and the location and clusters of affected network nodes. We
find that our model generates two different characteristics of diseases, which
can be interpreted as chronic and acute diseases. In its stylized form, our
model provides a new view on the relationship between genetic mutations and the
type and severity of a disease.
| [
{
"created": "Tue, 26 Apr 2022 09:23:47 GMT",
"version": "v1"
}
] | 2022-12-16 | [
[
"Nyczka",
"Piotr",
""
],
[
"Falk",
"Johannes",
""
],
[
"Hütt",
"Marc-Thorsten",
""
]
] | In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease. |
1712.08180 | Pantea Moghimi | Pantea Moghimi, Kelvin O. Lim, Theoden I. Netoff | Construction and Evaluation of Hierarchical Parcellation of the Brain
using fMRI with Prewhitening | 16 pages, 7 figures | null | null | null | q-bio.QM q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Brain atlases are a ubiquitous tool used for analyzing and interpreting brain
imaging datasets. Traditionally, brain atlases divided the brain into regions
separated by anatomical landmarks. In the last decade, several attempts have
been made to parcellate the brain into regions with distinct functional
activity using fMRI. To construct a brain atlas using fMRI, data driven
algorithms are used to group voxels with similar functional activity together
to form regions. Hierarchical clustering is one parcellation method that has
been used for functional parcellation of the brain, resulting in parcellations
that align well with cytoarchitectonic divisions of the brain. However, few
rigorous data driven evaluations of the method have been performed. Moreover,
the effect of removing autocorrelation trends from fMRI time series
(prewhitening) on the structure of the resultant atlas has not been previously
explored. In this paper, we use hierarchical clustering to produce functional
parcellations of the brain using hierarchical clustering. We use both
prewhitened and raw fMRI time series to construct the atlas. The resultant
atlases were then evaluated for their homogeneity, separation between regions,
reproducibility across subjects, and reproducibility across scans.
| [
{
"created": "Thu, 21 Dec 2017 19:22:57 GMT",
"version": "v1"
},
{
"created": "Wed, 7 Feb 2018 15:32:26 GMT",
"version": "v2"
}
] | 2018-02-08 | [
[
"Moghimi",
"Pantea",
""
],
[
"Lim",
"Kelvin O.",
""
],
[
"Netoff",
"Theoden I.",
""
]
] | Brain atlases are a ubiquitous tool used for analyzing and interpreting brain imaging datasets. Traditionally, brain atlases divided the brain into regions separated by anatomical landmarks. In the last decade, several attempts have been made to parcellate the brain into regions with distinct functional activity using fMRI. To construct a brain atlas using fMRI, data driven algorithms are used to group voxels with similar functional activity together to form regions. Hierarchical clustering is one parcellation method that has been used for functional parcellation of the brain, resulting in parcellations that align well with cytoarchitectonic divisions of the brain. However, few rigorous data driven evaluations of the method have been performed. Moreover, the effect of removing autocorrelation trends from fMRI time series (prewhitening) on the structure of the resultant atlas has not been previously explored. In this paper, we use hierarchical clustering to produce functional parcellations of the brain using hierarchical clustering. We use both prewhitened and raw fMRI time series to construct the atlas. The resultant atlases were then evaluated for their homogeneity, separation between regions, reproducibility across subjects, and reproducibility across scans. |
1702.06831 | Matej Mihel\v{c}i\'c | Matej Mihel\v{c}i\'c, Goran \v{S}imi\'c, Mirjana Babi\'c Leko, Nada
Lavra\v{c}, Sa\v{s}o D\v{z}eroski, Tomislav \v{S}muc | Using Redescription Mining to Relate Clinical and Biological
Characteristics of Cognitively Impaired and Alzheimer's Disease Patients | null | null | 10.1371/journal.pone.0187364 | null | q-bio.QM cs.AI q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We used redescription mining to find interpretable rules revealing
associations between those determinants that provide insights about the
Alzheimer's disease (AD). We extended the CLUS-RM redescription mining
algorithm to a constraint-based redescription mining (CBRM) setting, which
enables several modes of targeted exploration of specific, user-constrained
associations. Redescription mining enabled finding specific constructs of
clinical and biological attributes that describe many groups of subjects of
different size, homogeneity and levels of cognitive impairment. We confirmed
some previously known findings. However, in some instances, as with the
attributes: testosterone, the imaging attribute Spatial Pattern of
Abnormalities for Recognition of Early AD, as well as the levels of leptin and
angiopoietin-2 in plasma, we corroborated previously debatable findings or
provided additional information about these variables and their association
with AD pathogenesis. Applying redescription mining on ADNI data resulted with
the discovery of one largely unknown attribute: the Pregnancy-Associated
Protein-A (PAPP-A), which we found highly associated with cognitive impairment
in AD. Statistically significant correlations (p <= 0.01) were found between
PAPP-A and various different clinical tests. The high importance of this
finding lies in the fact that PAPP-A is a metalloproteinase, known to cleave
insulin-like growth factor binding proteins. Since it also shares similar
substrates with A Disintegrin and the Metalloproteinase family of enzymes that
act as {\alpha}-secretase to physiologically cleave amyloid precursor protein
(APP) in the non-amyloidogenic pathway, it could be directly involved in the
metabolism of APP very early during the disease course. Therefore, further
studies should investigate the role of PAPP-A in the development of AD more
thoroughly.
| [
{
"created": "Mon, 20 Feb 2017 09:56:34 GMT",
"version": "v1"
},
{
"created": "Tue, 14 Nov 2017 18:15:52 GMT",
"version": "v2"
}
] | 2017-11-15 | [
[
"Mihelčić",
"Matej",
""
],
[
"Šimić",
"Goran",
""
],
[
"Leko",
"Mirjana Babić",
""
],
[
"Lavrač",
"Nada",
""
],
[
"Džeroski",
"Sašo",
""
],
[
"Šmuc",
"Tomislav",
""
]
] | We used redescription mining to find interpretable rules revealing associations between those determinants that provide insights about the Alzheimer's disease (AD). We extended the CLUS-RM redescription mining algorithm to a constraint-based redescription mining (CBRM) setting, which enables several modes of targeted exploration of specific, user-constrained associations. Redescription mining enabled finding specific constructs of clinical and biological attributes that describe many groups of subjects of different size, homogeneity and levels of cognitive impairment. We confirmed some previously known findings. However, in some instances, as with the attributes: testosterone, the imaging attribute Spatial Pattern of Abnormalities for Recognition of Early AD, as well as the levels of leptin and angiopoietin-2 in plasma, we corroborated previously debatable findings or provided additional information about these variables and their association with AD pathogenesis. Applying redescription mining on ADNI data resulted with the discovery of one largely unknown attribute: the Pregnancy-Associated Protein-A (PAPP-A), which we found highly associated with cognitive impairment in AD. Statistically significant correlations (p <= 0.01) were found between PAPP-A and various different clinical tests. The high importance of this finding lies in the fact that PAPP-A is a metalloproteinase, known to cleave insulin-like growth factor binding proteins. Since it also shares similar substrates with A Disintegrin and the Metalloproteinase family of enzymes that act as {\alpha}-secretase to physiologically cleave amyloid precursor protein (APP) in the non-amyloidogenic pathway, it could be directly involved in the metabolism of APP very early during the disease course. Therefore, further studies should investigate the role of PAPP-A in the development of AD more thoroughly. |
1904.00919 | Christophe Bastien | C. Bastien, C. Neal-Sturgess, J. Christensen and L. Wen | A Deterministic Method to Calculate the AIS Trauma Score from a Finite
Element Organ Trauma Model (OTM) | null | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Traumatic injuries are measured using the Abbreviated Injury Scale (AIS),
which is a risk to life scale. New human computer models use stresses and
strains to evaluate whether serious or fatal injuries are reached,
unfortunately these tensors bear no direct relation to AIS. This paper proposes
to overcome this deficiency and suggests a unique Organ Trauma Model (OTM) able
to calculate the risk to life based on the severity on any organ injury,
focussing on real-life pedestrian accidents. The OTM uses a power method, named
Peak Virtual Power (PVP), and calculates the risk to life of brain white and
grey matters as a function of impact direction and impact speed. The OTM
firstly calibrates PVP against the medical critical AIS threshold observed in
each part of the head as a function of speed. This base PVP critical trauma
function is then scaled and banded across all AIS levels using the confirmed
property that AIS and the probability of death is statistically and numerically
a cubic one. The OTM model has been tested against four real-life pedestrian
accidents and proven to be able to predict pedestrian head trauma severity. In
some cases, the method did however under-estimate the head trauma by 1 AIS
level, because of post-impact haemorrhage which cannot be captured with the
employed Lagrangian Finite Element (FE) solver. It is also shown that the
location of the injury predictions using PVP coincide with the post mortem
reports and are different to the predictions made using maximum principal
strain.
| [
{
"created": "Mon, 1 Apr 2019 15:49:30 GMT",
"version": "v1"
}
] | 2019-04-02 | [
[
"Bastien",
"C.",
""
],
[
"Neal-Sturgess",
"C.",
""
],
[
"Christensen",
"J.",
""
],
[
"Wen",
"L.",
""
]
] | Traumatic injuries are measured using the Abbreviated Injury Scale (AIS), which is a risk to life scale. New human computer models use stresses and strains to evaluate whether serious or fatal injuries are reached, unfortunately these tensors bear no direct relation to AIS. This paper proposes to overcome this deficiency and suggests a unique Organ Trauma Model (OTM) able to calculate the risk to life based on the severity on any organ injury, focussing on real-life pedestrian accidents. The OTM uses a power method, named Peak Virtual Power (PVP), and calculates the risk to life of brain white and grey matters as a function of impact direction and impact speed. The OTM firstly calibrates PVP against the medical critical AIS threshold observed in each part of the head as a function of speed. This base PVP critical trauma function is then scaled and banded across all AIS levels using the confirmed property that AIS and the probability of death is statistically and numerically a cubic one. The OTM model has been tested against four real-life pedestrian accidents and proven to be able to predict pedestrian head trauma severity. In some cases, the method did however under-estimate the head trauma by 1 AIS level, because of post-impact haemorrhage which cannot be captured with the employed Lagrangian Finite Element (FE) solver. It is also shown that the location of the injury predictions using PVP coincide with the post mortem reports and are different to the predictions made using maximum principal strain. |
q-bio/0611004 | Miloje Rakocevic M. | Miloje M. Rakocevic | The Factors of the Classification of Protein Amino Acids | 14 pages, 6 Tables, 4 Surveys and 1 Figure | This paper is published in GLASNIK of Montenegrin Academy of
Science and arts, 2000, 13, pp. 173-194 | null | null | q-bio.BM q-bio.OT | null | In this work it is shown that three pairs of the factors appear to be the
key, i.e. main factors of a natural classification of protein (canonical) amino
acids within the amino acid (genetic) code. First pair: the factors of the
habit of an amino acid molecule (size and polarity). Second pair: the factors
of the association (type of the amino acid/enzyme reactivity and degree of the
hydrophobicity/hydrophilicity of an amino acid molecule). Third pair: the
factors of the dissociation (degree of the acidity-basicity, over acidic group,
COOH and degree of the basicity/acidity over the basic group, NH2). As a result
of the influence and interdependence of all six factors (measured through
correspondent valid parameters) it appears still one natural classification
into polar and non-polar amino acids, where polar amino acids possess negative
and non-polar, the positive values of hydropathy index.
| [
{
"created": "Wed, 1 Nov 2006 21:43:31 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Rakocevic",
"Miloje M.",
""
]
] | In this work it is shown that three pairs of the factors appear to be the key, i.e. main factors of a natural classification of protein (canonical) amino acids within the amino acid (genetic) code. First pair: the factors of the habit of an amino acid molecule (size and polarity). Second pair: the factors of the association (type of the amino acid/enzyme reactivity and degree of the hydrophobicity/hydrophilicity of an amino acid molecule). Third pair: the factors of the dissociation (degree of the acidity-basicity, over acidic group, COOH and degree of the basicity/acidity over the basic group, NH2). As a result of the influence and interdependence of all six factors (measured through correspondent valid parameters) it appears still one natural classification into polar and non-polar amino acids, where polar amino acids possess negative and non-polar, the positive values of hydropathy index. |
1104.1090 | Juergen Reingruber | Juergen Reingruber and David Holcman | The Narrow Escape problem in a flat cylindrical microdomain with
application to diffusion in the synaptic cleft | 24 pages, 9 figures | null | null | null | q-bio.NC cond-mat.stat-mech physics.bio-ph q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The mean first passage time (MFPT) for a Brownian particle to reach a small
target in cellular microdomains is a key parameter for chemical activation.
Although asymptotic estimations of the MFPT are available for various
geometries, these formula cannot be applied to degenerated structures where one
dimension of is much smaller compared to the others. Here we study the narrow
escape time (NET) problem for a Brownian particle to reach a small target
located on the surface of a flat cylinder, where the cylinder height is
comparable to the target size, and much smaller than the cylinder radius. When
the cylinder is sealed, we estimate the MFPT for a Brownian particle to hit a
small disk located centrally on the lower surface. For a laterally open
cylinder, we estimate the conditional probability and the conditional MFPT to
reach the small disk before exiting through the lateral opening. We apply our
results to diffusion in the narrow synaptic cleft, and compute the fraction and
the mean time for neurotransmitters to find their specific receptors located on
the postsynaptic terminal. Finally, we confirm our formulas with Brownian
simulations.
| [
{
"created": "Wed, 6 Apr 2011 13:20:03 GMT",
"version": "v1"
}
] | 2015-03-19 | [
[
"Reingruber",
"Juergen",
""
],
[
"Holcman",
"David",
""
]
] | The mean first passage time (MFPT) for a Brownian particle to reach a small target in cellular microdomains is a key parameter for chemical activation. Although asymptotic estimations of the MFPT are available for various geometries, these formula cannot be applied to degenerated structures where one dimension of is much smaller compared to the others. Here we study the narrow escape time (NET) problem for a Brownian particle to reach a small target located on the surface of a flat cylinder, where the cylinder height is comparable to the target size, and much smaller than the cylinder radius. When the cylinder is sealed, we estimate the MFPT for a Brownian particle to hit a small disk located centrally on the lower surface. For a laterally open cylinder, we estimate the conditional probability and the conditional MFPT to reach the small disk before exiting through the lateral opening. We apply our results to diffusion in the narrow synaptic cleft, and compute the fraction and the mean time for neurotransmitters to find their specific receptors located on the postsynaptic terminal. Finally, we confirm our formulas with Brownian simulations. |
1212.4678 | Jeffrey Shaman | Jeffrey Shaman, Alicia Karspeck, Marc Lipstich | Week 49 Influenza Forecast for the 2012-2013 U.S. Season | null | null | null | null | q-bio.PE stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present results of a forecast initiated Week 49 (beginning December 9,
2012) of the 2012-2013 influenza season for municipalities in the United
States. The forecast was made on December 14, 2012. Results from forecasts
initiated the two previous weeks (Weeks 47 and 48) are also presented. Also
results from the forecast generated with the SIRS model without AH forcing (no
AH) are shown
| [
{
"created": "Wed, 19 Dec 2012 14:44:06 GMT",
"version": "v1"
}
] | 2012-12-20 | [
[
"Shaman",
"Jeffrey",
""
],
[
"Karspeck",
"Alicia",
""
],
[
"Lipstich",
"Marc",
""
]
] | We present results of a forecast initiated Week 49 (beginning December 9, 2012) of the 2012-2013 influenza season for municipalities in the United States. The forecast was made on December 14, 2012. Results from forecasts initiated the two previous weeks (Weeks 47 and 48) are also presented. Also results from the forecast generated with the SIRS model without AH forcing (no AH) are shown |
2105.02222 | Nicola Vassena | Nicola Vassena | Sign-sensitivity of metabolic networks: which structures determine the
sign of the responses | 29 pages, 5 figures | International Journal of Robust and Nonlinear Control. 2021; 1- 24 | 10.1002/rnc.5896 | null | q-bio.MN math.DS | http://creativecommons.org/licenses/by/4.0/ | Perturbations are ubiquitous in metabolism. A central tool to understand and
control their influence on metabolic networks is sensitivity analysis, which
investigates how the network responds to external perturbations. We follow here
a structural approach: the analysis is based on the network stoichiometry only
and it does not require any quantitative knowledge of the reaction rates. We
consider perturbations of reaction rates and metabolite concentrations, at
equilibrium, and we investigate the responses in the network. For general
metabolic systems, this paper focuses on the sign of the responses, i.e.
whether a response is positive, negative or whether its sign depends on the
parameters of the system. In particular, we identify and describe the
subnetworks that are the main players in the sign description. These
subnetworks are associated to certain kernel vectors of the stoichiometric
matrix and are thus independent from the chosen kinetics.
| [
{
"created": "Wed, 5 May 2021 17:56:46 GMT",
"version": "v1"
},
{
"created": "Thu, 25 Nov 2021 08:33:01 GMT",
"version": "v2"
}
] | 2021-11-29 | [
[
"Vassena",
"Nicola",
""
]
] | Perturbations are ubiquitous in metabolism. A central tool to understand and control their influence on metabolic networks is sensitivity analysis, which investigates how the network responds to external perturbations. We follow here a structural approach: the analysis is based on the network stoichiometry only and it does not require any quantitative knowledge of the reaction rates. We consider perturbations of reaction rates and metabolite concentrations, at equilibrium, and we investigate the responses in the network. For general metabolic systems, this paper focuses on the sign of the responses, i.e. whether a response is positive, negative or whether its sign depends on the parameters of the system. In particular, we identify and describe the subnetworks that are the main players in the sign description. These subnetworks are associated to certain kernel vectors of the stoichiometric matrix and are thus independent from the chosen kinetics. |
2406.13822 | Apoorva Safai PhD | Apoorva Safai, Erin Jonaitis, Rebecca E Langhough, William R
Buckingham, Sterling C. Johnson, W. Ryan Powell, Amy J. H. Kind, Barbara B.
Bendlin, Pallavi Tiwari | Association of neighborhood disadvantage with cognitive function and
cortical disorganization in an unimpaired cohort | null | null | null | null | q-bio.NC stat.AP | http://creativecommons.org/licenses/by/4.0/ | Neighborhood disadvantage is associated with worse health and cognitive
outcomes. Morphological similarity network (MSN) is a promising approach to
elucidate cortical network patterns underlying complex cognitive functions. We
hypothesized that MSNs could capture changes in cortical patterns related to
neighborhood disadvantage and cognitive function. This cross-sectional study
included cognitively unimpaired participants from two large Alzheimers studies
at University of Wisconsin-Madison. Neighborhood disadvantage status was
obtained using the Area Deprivation Index (ADI). Cognitive performance was
assessed on memory, processing speed and executive function. Morphological
Similarity Networks (MSN) were constructed for each participant based on the
similarity in distribution of cortical thickness of brain regions, followed by
computation of local and global network features. Association of ADI with
cognitive scores and MSN features were examined using linear regression and
mediation analysis. ADI showed negative association with category
fluency,implicit learning speed, story recall and modified pre-clinical
Alzheimers cognitive composite scores, indicating worse cognitive function
among those living in more disadvantaged neighborhoods. Local network features
of frontal and temporal regions differed based on ADI status. Centrality of
left lateral orbitofrontal region showed a partial mediating effect between
association of neighborhood disadvantage and story recall performance. Our
preliminary findings suggest differences in local cortical organization by
neighborhood disadvantage, which partially mediated the relationship between
ADI and cognitive performance, providing a possible network-based mechanism to,
in-part, explain the risk for poor cognitive functioning associated with
disadvantaged neighborhoods.
| [
{
"created": "Wed, 19 Jun 2024 20:32:57 GMT",
"version": "v1"
}
] | 2024-06-21 | [
[
"Safai",
"Apoorva",
""
],
[
"Jonaitis",
"Erin",
""
],
[
"Langhough",
"Rebecca E",
""
],
[
"Buckingham",
"William R",
""
],
[
"Johnson",
"Sterling C.",
""
],
[
"Powell",
"W. Ryan",
""
],
[
"Kind",
"Amy J. H.",
""
],
[
"Bendlin",
"Barbara B.",
""
],
[
"Tiwari",
"Pallavi",
""
]
] | Neighborhood disadvantage is associated with worse health and cognitive outcomes. Morphological similarity network (MSN) is a promising approach to elucidate cortical network patterns underlying complex cognitive functions. We hypothesized that MSNs could capture changes in cortical patterns related to neighborhood disadvantage and cognitive function. This cross-sectional study included cognitively unimpaired participants from two large Alzheimers studies at University of Wisconsin-Madison. Neighborhood disadvantage status was obtained using the Area Deprivation Index (ADI). Cognitive performance was assessed on memory, processing speed and executive function. Morphological Similarity Networks (MSN) were constructed for each participant based on the similarity in distribution of cortical thickness of brain regions, followed by computation of local and global network features. Association of ADI with cognitive scores and MSN features were examined using linear regression and mediation analysis. ADI showed negative association with category fluency,implicit learning speed, story recall and modified pre-clinical Alzheimers cognitive composite scores, indicating worse cognitive function among those living in more disadvantaged neighborhoods. Local network features of frontal and temporal regions differed based on ADI status. Centrality of left lateral orbitofrontal region showed a partial mediating effect between association of neighborhood disadvantage and story recall performance. Our preliminary findings suggest differences in local cortical organization by neighborhood disadvantage, which partially mediated the relationship between ADI and cognitive performance, providing a possible network-based mechanism to, in-part, explain the risk for poor cognitive functioning associated with disadvantaged neighborhoods. |
1111.6488 | Taiki Takahashi | Taiki Takahashi | Neuroeconomics of suicide | 14 pages nofigure | Neuro Endocrinol Lett. 2011;32(4):400-404 | null | null | q-bio.NC q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Suicidal behavior is a leading cause of injury and death worldwide. Suicide
has been associated with psychiatric illnesses such as depression and
schizophrenia, as well as economic uncertainty, and social/cultural factors.
This study proposes a neuroeconomic framework of suicide. Neuroeconomic
parameters (e.g., risk-attitude, probability weighting, time discounting in
intertemporal choice, and loss aversion) are predicted to be related to
suicidal behavior. Neurobiological and neuroendocrinological substrates such as
serotonin, dopamine, cortisol (HPA axis), nitric oxide, serum cholesterol,
epinephrine, norepinephrine, gonadal hormones (e.g., estradiol and
progesterone), dehydroepiandrosterone (DHEA) in brain regions such as the
orbitofrontal/dorsolateral prefrontal cortex and limbic regions (e.g., the
amygdala) may supposedly be related to the neuroeconomic parameters modulating
the risk of suicide. The present framework puts foundations for "molecular
neuroeconomics" of decision-making processes underlying suicidal behavior.
| [
{
"created": "Tue, 22 Nov 2011 14:57:16 GMT",
"version": "v1"
}
] | 2012-12-04 | [
[
"Takahashi",
"Taiki",
""
]
] | Suicidal behavior is a leading cause of injury and death worldwide. Suicide has been associated with psychiatric illnesses such as depression and schizophrenia, as well as economic uncertainty, and social/cultural factors. This study proposes a neuroeconomic framework of suicide. Neuroeconomic parameters (e.g., risk-attitude, probability weighting, time discounting in intertemporal choice, and loss aversion) are predicted to be related to suicidal behavior. Neurobiological and neuroendocrinological substrates such as serotonin, dopamine, cortisol (HPA axis), nitric oxide, serum cholesterol, epinephrine, norepinephrine, gonadal hormones (e.g., estradiol and progesterone), dehydroepiandrosterone (DHEA) in brain regions such as the orbitofrontal/dorsolateral prefrontal cortex and limbic regions (e.g., the amygdala) may supposedly be related to the neuroeconomic parameters modulating the risk of suicide. The present framework puts foundations for "molecular neuroeconomics" of decision-making processes underlying suicidal behavior. |
1510.05941 | Jorge Hidalgo | Jorge Hidalgo, Jacopo Grilli, Samir Suweis, Amos Maritan and Miguel A.
Munoz | Cooperation, competition and the emergence of criticality in communities
of adaptive systems | 20 pages, 5 figures. Supplementary Material: 8 pages | J. Stat. Mech. (2016) 033203 | 10.1088/1742-5468/2016/03/033203 | null | q-bio.PE cond-mat.stat-mech physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The hypothesis that living systems can benefit from operating at the vicinity
of critical points has gained momentum in recent years. Criticality may confer
an optimal balance between exceedingly ordered and too noisy states. We here
present a model, based on information theory and statistical mechanics,
illustrating how and why a community of agents aimed at understanding and
communicating with each other converges to a globally coherent state in which
all individuals are close to an internal critical state, i.e. at the borderline
between order and disorder. We study --both analytically and computationally--
the circumstances under which criticality is the best possible outcome of the
dynamical process, confirming the convergence to critical points under very
generic conditions. Finally, we analyze the effect of cooperation (agents try
to enhance not only their fitness, but also that of other individuals) and
competition (agents try to improve their own fitness and to diminish those of
competitors) within our setting. The conclusion is that, while competition
fosters criticality, cooperation hinders it and can lead to more ordered or
more disordered consensual solutions.
| [
{
"created": "Fri, 16 Oct 2015 17:16:07 GMT",
"version": "v1"
},
{
"created": "Wed, 21 Oct 2015 18:14:41 GMT",
"version": "v2"
},
{
"created": "Tue, 22 Mar 2016 10:16:18 GMT",
"version": "v3"
}
] | 2016-03-23 | [
[
"Hidalgo",
"Jorge",
""
],
[
"Grilli",
"Jacopo",
""
],
[
"Suweis",
"Samir",
""
],
[
"Maritan",
"Amos",
""
],
[
"Munoz",
"Miguel A.",
""
]
] | The hypothesis that living systems can benefit from operating at the vicinity of critical points has gained momentum in recent years. Criticality may confer an optimal balance between exceedingly ordered and too noisy states. We here present a model, based on information theory and statistical mechanics, illustrating how and why a community of agents aimed at understanding and communicating with each other converges to a globally coherent state in which all individuals are close to an internal critical state, i.e. at the borderline between order and disorder. We study --both analytically and computationally-- the circumstances under which criticality is the best possible outcome of the dynamical process, confirming the convergence to critical points under very generic conditions. Finally, we analyze the effect of cooperation (agents try to enhance not only their fitness, but also that of other individuals) and competition (agents try to improve their own fitness and to diminish those of competitors) within our setting. The conclusion is that, while competition fosters criticality, cooperation hinders it and can lead to more ordered or more disordered consensual solutions. |
2202.02377 | H Aerts | Zhongyi Zhang, Jakob Weiss, Jana Taron, Roman Zeleznik, Michael T. Lu,
Hugo J.W.L. Aerts | Deep Learning-based Assessment of Hepatic Steatosis on chest CT | null | null | null | null | q-bio.QM | http://creativecommons.org/publicdomain/zero/1.0/ | Purpose: Automatic methods are required for the early detection of hepatic
steatosis to avoid progression to cirrhosis and cancer. Here, we developed a
fully automated deep learning pipeline to quantify hepatic steatosis on
non-contrast enhanced chest computed tomography (CT) scans. Materials and
Methods: We developed and evaluated our pipeline on chest CT images of 1,431
randomly selected National Lung Screening Trial (NLST) participants. A dataset
of 451 CT scans with volumetric liver segmentations of expert readers was used
for training a deep learning model. For testing, in an independent dataset of
980 CT scans hepatic attenuation was manually measured by an expert reader on
three cross-sectional images at different hepatic levels by selecting three
circular regions of interest. Additionally, 100 randomly selected cases of the
test set were volumetrically segmented by expert readers. Hepatic steatosis on
the test set was defined as mean hepatic attenuation of < 40 Hounsfield unit.
Spearman correlation was conducted to analyze liver fat quantification accuracy
and the Cohen's Kappa coefficient was calculated for hepatic steatosis
prediction reliability. Results: Our pipeline demonstrated strong performance
and achieved a mean dice score of 0.970 for the volumetric liver segmentation.
The spearman correlation of the liver fat quantification was 0.954 (P <0.0001)
between the automated and expert reader measurements. The cohen's kappa
coefficient was 0.875 for automatic assessment of hepatic steatosis.
Conclusion: We developed a fully automatic deep learning-based pipeline for the
assessment of hepatic steatosis in chest CT images. With the fast and cheap
screening of hepatic steatosis, our pipeline has the potential to help initiate
preventive measures to avoid progression to cirrhosis and cancer.
| [
{
"created": "Fri, 4 Feb 2022 20:22:16 GMT",
"version": "v1"
}
] | 2022-02-08 | [
[
"Zhang",
"Zhongyi",
""
],
[
"Weiss",
"Jakob",
""
],
[
"Taron",
"Jana",
""
],
[
"Zeleznik",
"Roman",
""
],
[
"Lu",
"Michael T.",
""
],
[
"Aerts",
"Hugo J. W. L.",
""
]
] | Purpose: Automatic methods are required for the early detection of hepatic steatosis to avoid progression to cirrhosis and cancer. Here, we developed a fully automated deep learning pipeline to quantify hepatic steatosis on non-contrast enhanced chest computed tomography (CT) scans. Materials and Methods: We developed and evaluated our pipeline on chest CT images of 1,431 randomly selected National Lung Screening Trial (NLST) participants. A dataset of 451 CT scans with volumetric liver segmentations of expert readers was used for training a deep learning model. For testing, in an independent dataset of 980 CT scans hepatic attenuation was manually measured by an expert reader on three cross-sectional images at different hepatic levels by selecting three circular regions of interest. Additionally, 100 randomly selected cases of the test set were volumetrically segmented by expert readers. Hepatic steatosis on the test set was defined as mean hepatic attenuation of < 40 Hounsfield unit. Spearman correlation was conducted to analyze liver fat quantification accuracy and the Cohen's Kappa coefficient was calculated for hepatic steatosis prediction reliability. Results: Our pipeline demonstrated strong performance and achieved a mean dice score of 0.970 for the volumetric liver segmentation. The spearman correlation of the liver fat quantification was 0.954 (P <0.0001) between the automated and expert reader measurements. The cohen's kappa coefficient was 0.875 for automatic assessment of hepatic steatosis. Conclusion: We developed a fully automatic deep learning-based pipeline for the assessment of hepatic steatosis in chest CT images. With the fast and cheap screening of hepatic steatosis, our pipeline has the potential to help initiate preventive measures to avoid progression to cirrhosis and cancer. |
1802.00718 | Fabian Chersi | Chersi Fabian, Burgess Neil | Hippocampal and striatal involvement in cognitive tasks: a computational
model | null | Proceedings of the 6th International Conference on Memory ICOM16,
2016, p. 24 | null | null | q-bio.NC | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The hippocampus and the striatum support episodic and procedural memory,
respectively, and "place" and "response" learning within spatial navigation.
Recently this dichotomy has been linked to "model-based" and "model-free"
reinforcement learning. Here we present a well-constrained neural model of how
both systems support spatial navigation, and apply the same model to more
abstract problems such as sequential decision making. In particular, we show
that if a task can be transformed into a Markov Decision Process, the machinery
provided by the hippocampus and striatum can be utilized to solve it. These
results show how the hippocampal complex can represent non-spatial problems,
including context, probabilities and action-dependent information, in support
of "model-based" reinforcement learning to complement learning within the
striatum.
| [
{
"created": "Fri, 2 Feb 2018 15:10:05 GMT",
"version": "v1"
}
] | 2018-02-05 | [
[
"Fabian",
"Chersi",
""
],
[
"Neil",
"Burgess",
""
]
] | The hippocampus and the striatum support episodic and procedural memory, respectively, and "place" and "response" learning within spatial navigation. Recently this dichotomy has been linked to "model-based" and "model-free" reinforcement learning. Here we present a well-constrained neural model of how both systems support spatial navigation, and apply the same model to more abstract problems such as sequential decision making. In particular, we show that if a task can be transformed into a Markov Decision Process, the machinery provided by the hippocampus and striatum can be utilized to solve it. These results show how the hippocampal complex can represent non-spatial problems, including context, probabilities and action-dependent information, in support of "model-based" reinforcement learning to complement learning within the striatum. |
1702.02076 | Gao-De Li Dr | Gao-De Li | Cell-Cycle-Associated Amplified Genomic-DNA Fragments (CAGFs) Might Be
Involved in Chloroquine Action and Resistance in Plasmodium falciparum | 11 pages, 1 figure, 1 table | null | null | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | As a cheap and safe antimalarial agent, chloroquine (CQ) has been used in the
battle against malaria for more than half century. However, the mechanism of CQ
action and resistance in Plasmodium falciparum remains elusive. Based on
further analysis of our published experimental results, we propose that the
mechanism of CQ action and resistance might be closely linked with
cell-cycle-associated amplified genomic-DNA fragments (CAGFs, singular form =
CAGF) as CQ induces CAGF production in P. falciparum, which could affect
multiple biological processes of the parasite, and thus might contribute to
parasite death and CQ resistance. Recently, we found that CQ induced one of
CAGFs, UB1- CAGF, might downregulate a probable P. falciparum cystine
transporter (Pfct) gene expression, which could be used to understand the
mechanism of CQ action and resistance in P. falciparum.
| [
{
"created": "Tue, 7 Feb 2017 16:07:49 GMT",
"version": "v1"
},
{
"created": "Tue, 21 Feb 2017 18:37:03 GMT",
"version": "v2"
},
{
"created": "Thu, 2 Mar 2017 16:00:53 GMT",
"version": "v3"
},
{
"created": "Sun, 5 Mar 2017 23:37:29 GMT",
"version": "v4"
},
{
"created": "Wed, 15 Mar 2017 00:43:17 GMT",
"version": "v5"
},
{
"created": "Sun, 16 Jul 2017 20:44:34 GMT",
"version": "v6"
},
{
"created": "Mon, 29 Jan 2018 08:58:58 GMT",
"version": "v7"
}
] | 2018-01-30 | [
[
"Li",
"Gao-De",
""
]
] | As a cheap and safe antimalarial agent, chloroquine (CQ) has been used in the battle against malaria for more than half century. However, the mechanism of CQ action and resistance in Plasmodium falciparum remains elusive. Based on further analysis of our published experimental results, we propose that the mechanism of CQ action and resistance might be closely linked with cell-cycle-associated amplified genomic-DNA fragments (CAGFs, singular form = CAGF) as CQ induces CAGF production in P. falciparum, which could affect multiple biological processes of the parasite, and thus might contribute to parasite death and CQ resistance. Recently, we found that CQ induced one of CAGFs, UB1- CAGF, might downregulate a probable P. falciparum cystine transporter (Pfct) gene expression, which could be used to understand the mechanism of CQ action and resistance in P. falciparum. |
1111.5724 | Guido Tiana | Guido Tiana and Ludovico Sutto | Equilibrium properties of realistic random heteropolymers and their
relevance for globular and naturally unfolded proteins | null | null | 10.1103/PhysRevE.84.061910 | null | q-bio.BM cond-mat.dis-nn | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Random heteropolymers do not display the typical equilibrium properties of
globular proteins, but are the starting point to understand the physics of
proteins and, in particular, to describe their non-native states. So far, they
have been studied only with mean-field models in the thermodynamic limit, or
with computer simulations of very small chains on lattice. After describing a
self-adjusting parallel-tempering technique to sample efficiently the
low-energy states of frustrated systems without the need of tuning the
system-dependent parameters of the algorithm, we apply it to random
heteropolymers moving in continuous space. We show that if the mean interaction
between monomers is negative, the usual description through the random energy
model is nearly correct, provided that it is extended to account for
non-compact conformations. If the mean interaction is positive, such a simple
description breaks out and the system behaves in a way more similar to Ising
spin glasses. The former case is a model for the denatured state of glob- ular
proteins, the latter of naturally-unfolded proteins, whose equilibrium
properties thus result qualitatively different.
| [
{
"created": "Thu, 24 Nov 2011 11:14:23 GMT",
"version": "v1"
}
] | 2015-06-03 | [
[
"Tiana",
"Guido",
""
],
[
"Sutto",
"Ludovico",
""
]
] | Random heteropolymers do not display the typical equilibrium properties of globular proteins, but are the starting point to understand the physics of proteins and, in particular, to describe their non-native states. So far, they have been studied only with mean-field models in the thermodynamic limit, or with computer simulations of very small chains on lattice. After describing a self-adjusting parallel-tempering technique to sample efficiently the low-energy states of frustrated systems without the need of tuning the system-dependent parameters of the algorithm, we apply it to random heteropolymers moving in continuous space. We show that if the mean interaction between monomers is negative, the usual description through the random energy model is nearly correct, provided that it is extended to account for non-compact conformations. If the mean interaction is positive, such a simple description breaks out and the system behaves in a way more similar to Ising spin glasses. The former case is a model for the denatured state of glob- ular proteins, the latter of naturally-unfolded proteins, whose equilibrium properties thus result qualitatively different. |
2209.07508 | Kaidi Shao | Kaidi Shao, Nikos K. Logothetis and Michel Besserve | Information Theoretic Measures of Causal Influences during Transient
Neural Events | null | null | null | null | q-bio.NC stat.ME stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Transient phenomena play a key role in coordinating brain activity at
multiple scales, however,their underlying mechanisms remain largely unknown. A
key challenge for neural data science is thus to characterize the network
interactions at play during these events. Using the formalism of Structural
Causal Models and their graphical representation, we investigate the
theoretical and empirical properties of Information Theory based causal
strength measures in the context of recurring spontaneous transient events.
After showing the limitations of Transfer Entropy and Dynamic Causal Strength
in such a setting, we introduce a novel measure, relative Dynamic Causal
Strength, and provide theoretical and empirical support for its benefits. These
methods are applied to simulated and experimentally recorded neural time
series, and provide results in agreement with our current understanding of the
underlying brain circuits.
| [
{
"created": "Thu, 15 Sep 2022 17:51:46 GMT",
"version": "v1"
}
] | 2022-09-16 | [
[
"Shao",
"Kaidi",
""
],
[
"Logothetis",
"Nikos K.",
""
],
[
"Besserve",
"Michel",
""
]
] | Transient phenomena play a key role in coordinating brain activity at multiple scales, however,their underlying mechanisms remain largely unknown. A key challenge for neural data science is thus to characterize the network interactions at play during these events. Using the formalism of Structural Causal Models and their graphical representation, we investigate the theoretical and empirical properties of Information Theory based causal strength measures in the context of recurring spontaneous transient events. After showing the limitations of Transfer Entropy and Dynamic Causal Strength in such a setting, we introduce a novel measure, relative Dynamic Causal Strength, and provide theoretical and empirical support for its benefits. These methods are applied to simulated and experimentally recorded neural time series, and provide results in agreement with our current understanding of the underlying brain circuits. |
1111.4579 | Trevor Bedford | Trevor Bedford, Andrew Rambaut and Mercedes Pascual | Canalization of the evolutionary trajectory of the human influenza virus | 29 pages, 5 figures, 10 supporting figures | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/3.0/ | Since its emergence in 1968, influenza A (H3N2) has evolved extensively in
genotype and antigenic phenotype. Antigenic evolution occurs in the context of
a two-dimensional 'antigenic map', while genetic evolution shows a
characteristic ladder-like genealogical tree. Here, we use a large-scale
individual-based model to show that evolution in a Euclidean antigenic space
provides a remarkable correspondence between model behavior and the
epidemiological, antigenic, genealogical and geographic patterns observed in
influenza virus. We find that evolution away from existing human immunity
results in rapid population turnover in the influenza virus and that this
population turnover occurs primarily along a single antigenic axis. Thus,
selective dynamics induce a canalized evolutionary trajectory, in which the
evolutionary fate of the influenza population is surprisingly repeatable and
hence, in theory, predictable.
| [
{
"created": "Sat, 19 Nov 2011 19:41:26 GMT",
"version": "v1"
}
] | 2011-11-22 | [
[
"Bedford",
"Trevor",
""
],
[
"Rambaut",
"Andrew",
""
],
[
"Pascual",
"Mercedes",
""
]
] | Since its emergence in 1968, influenza A (H3N2) has evolved extensively in genotype and antigenic phenotype. Antigenic evolution occurs in the context of a two-dimensional 'antigenic map', while genetic evolution shows a characteristic ladder-like genealogical tree. Here, we use a large-scale individual-based model to show that evolution in a Euclidean antigenic space provides a remarkable correspondence between model behavior and the epidemiological, antigenic, genealogical and geographic patterns observed in influenza virus. We find that evolution away from existing human immunity results in rapid population turnover in the influenza virus and that this population turnover occurs primarily along a single antigenic axis. Thus, selective dynamics induce a canalized evolutionary trajectory, in which the evolutionary fate of the influenza population is surprisingly repeatable and hence, in theory, predictable. |
1509.05004 | Brian Seguin | Mariya Ptashnyk and Brian Seguin | The impact of microfibril orientations on the biomechanics of plant cell
walls and tissues: modelling and simulations | 16 pages, 7 figures | null | null | null | q-bio.CB cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It is known that the orientation of cellulose microfibrils within plant cell
walls has an important impact on the morphogenesis of plant cells and tissues.
Viewing the shape of a plant cell as a square prism or cylinder with the axis
aligning with the primary direction of expansion and growth, the orientation of
the microfibrils within the cell wall on the sides of the cell is known.
However, not much is known about their orientation at the ends of the cell.
Here we investigate the impact of the orientation of cellulose microfibrils
within a plant cell wall at the ends of the cell by solving the equations of
linear elasticity numerically. Three different scenarios for the orientation of
the microfibrils are considered. The macroscopic elastic properties of the cell
wall are obtained using homogenization theory from the microscopic description
of the elastic properties of the cell wall microfibrils and wall matrix. It is
found that the orientation of the microfibrils in the upper and lower parts of
cell walls do not affect the expansion of the cell in the direction of its axis
but do affect its expansion in the lateral directions. The arrangement of the
microfibrils in the upper and lower parts of cell walls is especially important
in the case of directed forces acting on plant cell walls and tissues.
| [
{
"created": "Tue, 15 Sep 2015 00:15:46 GMT",
"version": "v1"
}
] | 2015-09-17 | [
[
"Ptashnyk",
"Mariya",
""
],
[
"Seguin",
"Brian",
""
]
] | It is known that the orientation of cellulose microfibrils within plant cell walls has an important impact on the morphogenesis of plant cells and tissues. Viewing the shape of a plant cell as a square prism or cylinder with the axis aligning with the primary direction of expansion and growth, the orientation of the microfibrils within the cell wall on the sides of the cell is known. However, not much is known about their orientation at the ends of the cell. Here we investigate the impact of the orientation of cellulose microfibrils within a plant cell wall at the ends of the cell by solving the equations of linear elasticity numerically. Three different scenarios for the orientation of the microfibrils are considered. The macroscopic elastic properties of the cell wall are obtained using homogenization theory from the microscopic description of the elastic properties of the cell wall microfibrils and wall matrix. It is found that the orientation of the microfibrils in the upper and lower parts of cell walls do not affect the expansion of the cell in the direction of its axis but do affect its expansion in the lateral directions. The arrangement of the microfibrils in the upper and lower parts of cell walls is especially important in the case of directed forces acting on plant cell walls and tissues. |
2302.10163 | Marc Howard | Marc W. Howard and Zahra G. Esfahani and Bao Le and Per B. Sederberg | Foundations of a temporal RL | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Recent advances in neuroscience and psychology show that the brain has access
to timelines of both the past and the future. Spiking across populations of
neurons in many regions of the mammalian brain maintains a robust temporal
memory, a neural timeline of the recent past. Behavioral results demonstrate
that people can estimate an extended temporal model of the future, suggesting
that the neural timeline of the past could extend through the present into the
future. This paper presents a mathematical framework for learning and
expressing relationships between events in continuous time. We assume that the
brain has access to a temporal memory in the form of the real Laplace transform
of the recent past. Hebbian associations with a diversity of synaptic time
scales are formed between the past and the present that record the temporal
relationships between events. Knowing the temporal relationships between the
past and the present allows one to predict relationships between the present
and the future, thus constructing an extended temporal prediction for the
future. Both memory for the past and the predicted future are represented as
the real Laplace transform, expressed as the firing rate over populations of
neurons indexed by different rate constants $s$. The diversity of synaptic
timescales allows for a temporal record over the much larger time scale of
trial history. In this framework, temporal credit assignment can be assessed
via a Laplace temporal difference. The Laplace temporal difference compares the
future that actually follows a stimulus to the future predicted just before the
stimulus was observed. This computational framework makes a number of specific
neurophysiological predictions and, taken together, could provide the basis for
a future iteration of RL that incorporates temporal memory as a fundamental
building block.
| [
{
"created": "Mon, 20 Feb 2023 18:49:34 GMT",
"version": "v1"
}
] | 2023-02-21 | [
[
"Howard",
"Marc W.",
""
],
[
"Esfahani",
"Zahra G.",
""
],
[
"Le",
"Bao",
""
],
[
"Sederberg",
"Per B.",
""
]
] | Recent advances in neuroscience and psychology show that the brain has access to timelines of both the past and the future. Spiking across populations of neurons in many regions of the mammalian brain maintains a robust temporal memory, a neural timeline of the recent past. Behavioral results demonstrate that people can estimate an extended temporal model of the future, suggesting that the neural timeline of the past could extend through the present into the future. This paper presents a mathematical framework for learning and expressing relationships between events in continuous time. We assume that the brain has access to a temporal memory in the form of the real Laplace transform of the recent past. Hebbian associations with a diversity of synaptic time scales are formed between the past and the present that record the temporal relationships between events. Knowing the temporal relationships between the past and the present allows one to predict relationships between the present and the future, thus constructing an extended temporal prediction for the future. Both memory for the past and the predicted future are represented as the real Laplace transform, expressed as the firing rate over populations of neurons indexed by different rate constants $s$. The diversity of synaptic timescales allows for a temporal record over the much larger time scale of trial history. In this framework, temporal credit assignment can be assessed via a Laplace temporal difference. The Laplace temporal difference compares the future that actually follows a stimulus to the future predicted just before the stimulus was observed. This computational framework makes a number of specific neurophysiological predictions and, taken together, could provide the basis for a future iteration of RL that incorporates temporal memory as a fundamental building block. |
1709.10442 | Francisco Herrer\'ias-Azcu\'e Mr. | Francisco Herrer\'ias-Azcu\'e, Vicente P\'erez-Mu\~nuzuri, Tobias
Galla | Fast flowing populations are not well mixed | 19 pages, 8 figures | Scientific Reports, volume 8, Article number: 4068 (2018) | 10.1038/s41598-018-22062-w | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In evolutionary dynamics, well-mixed populations are almost always associated
with all-to-all interactions; mathematical models are based on complete graphs.
In most cases, these models do not predict fixation probabilities in groups of
individuals mixed by flows. We propose an analytical description in the
fast-flow limit. This approach is valid for processes with global and local
selection, and accurately predicts the suppression of selection as competition
becomes more local. It provides a modelling tool for biological or social
systems with individuals in motion.
| [
{
"created": "Fri, 29 Sep 2017 15:05:39 GMT",
"version": "v1"
}
] | 2024-02-28 | [
[
"Herrerías-Azcué",
"Francisco",
""
],
[
"Pérez-Muñuzuri",
"Vicente",
""
],
[
"Galla",
"Tobias",
""
]
] | In evolutionary dynamics, well-mixed populations are almost always associated with all-to-all interactions; mathematical models are based on complete graphs. In most cases, these models do not predict fixation probabilities in groups of individuals mixed by flows. We propose an analytical description in the fast-flow limit. This approach is valid for processes with global and local selection, and accurately predicts the suppression of selection as competition becomes more local. It provides a modelling tool for biological or social systems with individuals in motion. |
q-bio/0510053 | Jayprokas Chakrabarti | Zhumur Ghosh, Jayprokas Chakrabarti, Bibekanand Mallick, Smarajit Das,
Satyabrata Sahoo and Harmeet Singh Sethi | tRNA-isoleucine-tryptophan Composite Gene | 15 pages, 3 figures | Biochemical and biophysical Research Communications 339 (2005)
37-40 | 10.1016/j.bbrc.2005.10.183 | null | q-bio.GN | null | Transfer-RNA genes in archaea often have introns intervening between exon
sequences. The structural motif at the boundary between exon and intron is the
bulge-helix-bulge. Computational investigations of these boundary structures in
H. marismortui lead us to propose that tRNA-isoleucine and tRNA-tryptophan
genes are co-located. Precise insilico identification of the splice-sites on
the bulges at the exon-intron boundaries conduce us to infer that a single
intron-containing composite tRNA-gene can give rise to more than one gene
produc.
| [
{
"created": "Fri, 28 Oct 2005 07:33:02 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Ghosh",
"Zhumur",
""
],
[
"Chakrabarti",
"Jayprokas",
""
],
[
"Mallick",
"Bibekanand",
""
],
[
"Das",
"Smarajit",
""
],
[
"Sahoo",
"Satyabrata",
""
],
[
"Sethi",
"Harmeet Singh",
""
]
] | Transfer-RNA genes in archaea often have introns intervening between exon sequences. The structural motif at the boundary between exon and intron is the bulge-helix-bulge. Computational investigations of these boundary structures in H. marismortui lead us to propose that tRNA-isoleucine and tRNA-tryptophan genes are co-located. Precise insilico identification of the splice-sites on the bulges at the exon-intron boundaries conduce us to infer that a single intron-containing composite tRNA-gene can give rise to more than one gene produc. |
1901.02386 | Aydar Uatay | Aydar Uatay | A mathematical model of contact inhibition of locomotion: coupling
contractility and focal adhesions | null | null | null | null | q-bio.CB q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Cell migration is often accompanied by collisions with other cells, which can
lead to cessation of movement, repolarization, and migration away from the
contact site - a process termed contact inhibition of locomotion (CIL). During
CIL, the coupling between actomyosin contractilityand cell-substrate adhesions
is modified. However, mathematical models describing stochastic cell migration
and collision outcomes as a result of the coupling remain elusive. Here, we
extend our previously developed stochastic model of single cell migration to
include CIL. Our simulation results explain, in terms of the modified
contractility and adhesion dynamics, several experimentally observed findings
regarding CIL. These include response modulation in the presence of an external
cue and alterations of group migration in the absence of CIL. Together with our
previous findings, our work is able to explain a wide range of observations
about single and collective cell migration.
| [
{
"created": "Tue, 8 Jan 2019 16:07:57 GMT",
"version": "v1"
},
{
"created": "Wed, 20 Mar 2019 17:30:46 GMT",
"version": "v2"
},
{
"created": "Fri, 22 Mar 2019 14:29:29 GMT",
"version": "v3"
}
] | 2019-03-25 | [
[
"Uatay",
"Aydar",
""
]
] | Cell migration is often accompanied by collisions with other cells, which can lead to cessation of movement, repolarization, and migration away from the contact site - a process termed contact inhibition of locomotion (CIL). During CIL, the coupling between actomyosin contractilityand cell-substrate adhesions is modified. However, mathematical models describing stochastic cell migration and collision outcomes as a result of the coupling remain elusive. Here, we extend our previously developed stochastic model of single cell migration to include CIL. Our simulation results explain, in terms of the modified contractility and adhesion dynamics, several experimentally observed findings regarding CIL. These include response modulation in the presence of an external cue and alterations of group migration in the absence of CIL. Together with our previous findings, our work is able to explain a wide range of observations about single and collective cell migration. |
1403.3776 | Yusuke Himeoka | Yusuke Himeoka and Kunihiko Kaneko | Entropy production of a steady-growth cell with catalytic reactions | 17 pages, 6 figures | null | 10.1103/PhysRevE.90.042714 | null | q-bio.SC q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cells generally convert external nutrient resources to support metabolismand
growth. Understanding the thermodynamic efficiency of this conversion is
essential to determine the general characteristics of cellular growth. Using a
simple protocell model with catalytic reaction dynamics to synthesize the
necessary enzyme and membrane components from nutrients, the entropy production
per unit cell-volume growth is calculated analytically and numerically based on
the rate equation for chemical kinetics and linear non-equilibrium
thermodynamics. The minimal entropy production per unit cell growth is found to
be achieved at a non-zero nutrient uptake rate, rather than at a quasi-static
limit as in the standard Carnot engine. This difference appears because the
equilibration mediated by the enzyme exists only within cells that grow through
enzyme and membrane synthesis. Optimal nutrient uptake is also confirmed by
protocell models with many chemical components synthesized through a catalytic
reaction network. The possible relevance of the identified optimal uptake to
optimal yield for cellular growth is also discussed.
| [
{
"created": "Sat, 15 Mar 2014 09:44:01 GMT",
"version": "v1"
}
] | 2015-06-19 | [
[
"Himeoka",
"Yusuke",
""
],
[
"Kaneko",
"Kunihiko",
""
]
] | Cells generally convert external nutrient resources to support metabolismand growth. Understanding the thermodynamic efficiency of this conversion is essential to determine the general characteristics of cellular growth. Using a simple protocell model with catalytic reaction dynamics to synthesize the necessary enzyme and membrane components from nutrients, the entropy production per unit cell-volume growth is calculated analytically and numerically based on the rate equation for chemical kinetics and linear non-equilibrium thermodynamics. The minimal entropy production per unit cell growth is found to be achieved at a non-zero nutrient uptake rate, rather than at a quasi-static limit as in the standard Carnot engine. This difference appears because the equilibration mediated by the enzyme exists only within cells that grow through enzyme and membrane synthesis. Optimal nutrient uptake is also confirmed by protocell models with many chemical components synthesized through a catalytic reaction network. The possible relevance of the identified optimal uptake to optimal yield for cellular growth is also discussed. |
1107.3569 | Charles Li | Yipeng Yang, Y. Charles Li | A Monte Carlo Simulation on Clustering Dynamics of Social Amoebae | null | null | null | null | q-bio.CB nlin.CD q-bio.PE q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A discrete model for computer simulations of the clustering dynamics of
Social Amoebae is presented. This model incorporates the wavelike propagation
of extracellular signaling cAMP, the sporadic firing of cells at early stage of
aggregation, the signal relaying as a response to stimulus, the inertia and
purposeful random walk of the cell movement. A Monte Carlo simulation is run
which shows the existence of potential equilibriums of mean and variance of
aggregation time. The simulation result of this model could well reproduce many
phenomena observed by actual experiments.
| [
{
"created": "Mon, 18 Jul 2011 20:21:50 GMT",
"version": "v1"
},
{
"created": "Mon, 13 May 2013 17:42:03 GMT",
"version": "v2"
}
] | 2013-05-14 | [
[
"Yang",
"Yipeng",
""
],
[
"Li",
"Y. Charles",
""
]
] | A discrete model for computer simulations of the clustering dynamics of Social Amoebae is presented. This model incorporates the wavelike propagation of extracellular signaling cAMP, the sporadic firing of cells at early stage of aggregation, the signal relaying as a response to stimulus, the inertia and purposeful random walk of the cell movement. A Monte Carlo simulation is run which shows the existence of potential equilibriums of mean and variance of aggregation time. The simulation result of this model could well reproduce many phenomena observed by actual experiments. |
1909.05909 | Jahan Schad | Jahan N. Schad | Mental Stress: Source of Neurological Degeneration; Case of MS | null | J Neurol Stroke 2014, 1(4) | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Mental stress is a vague though familiar concept that accounts for an agency
of the good, the bad and the ugly, that operates in the brains of animated
beings, in response to environmental stressors. In this work, we provide
evidence for correlation of stressors with afflictions of MS throughout the
world, and put forward arguments in support of the fact that stressors can
render disruptions in the normal computational processes of the brain, defining
the innards of the mental stress, which in turn may lead to the onset of
physiologic adversities in the biologic systems, possibly rendering various
diseases, even one as MS. While the real cause of the disease is still not
known, major focus is put on the treatment of MS symptoms, aiming to slow down
its progress and to reduce the frequency of attacks. In this effort we
establish the link between MS and mental stress, through analyses of various
aspects of statistics of prevalence and incidence, available in the literature
[3-5], which lends itself to opening up of additional treatment possibilities
that could be used separate of, or conjunctively with, the medical approaches.
On a grander scale, publicizing the adverse workings of the mental stress and
its evils can attain statistical gains, in the incidence reduction.
| [
{
"created": "Mon, 9 Sep 2019 18:12:56 GMT",
"version": "v1"
}
] | 2019-09-16 | [
[
"Schad",
"Jahan N.",
""
]
] | Mental stress is a vague though familiar concept that accounts for an agency of the good, the bad and the ugly, that operates in the brains of animated beings, in response to environmental stressors. In this work, we provide evidence for correlation of stressors with afflictions of MS throughout the world, and put forward arguments in support of the fact that stressors can render disruptions in the normal computational processes of the brain, defining the innards of the mental stress, which in turn may lead to the onset of physiologic adversities in the biologic systems, possibly rendering various diseases, even one as MS. While the real cause of the disease is still not known, major focus is put on the treatment of MS symptoms, aiming to slow down its progress and to reduce the frequency of attacks. In this effort we establish the link between MS and mental stress, through analyses of various aspects of statistics of prevalence and incidence, available in the literature [3-5], which lends itself to opening up of additional treatment possibilities that could be used separate of, or conjunctively with, the medical approaches. On a grander scale, publicizing the adverse workings of the mental stress and its evils can attain statistical gains, in the incidence reduction. |
2004.02817 | Edward Goldstein | Edward Goldstein | Temporal rise in the proportion of younger adults and older adolescents
among COVID-19 cases in Germany: evidence of lesser adherence to social
distancing practices? | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Background: There is uncertainty about the role of different age groups in
propagating the SARS-CoV-2 epidemics in different countries. Methods: We used
the Koch Institute data on COVID-19 cases in Germany. To minimize the effect of
changes in healthcare seeking behavior and testing practices, we included the
following 5-year age groups in the analyses: 10-14y through 45-49y. For each
age group g, we considered the proportion PL(g) of individuals in age group g
among all detected cases aged 10-49y during weeks 13-14, 2020 (later period),
as well as corresponding proportion PE(g) for weeks 10-11, 2020 (early period),
and the relative risk RR(g)=PL(g)/PE(g). For each pair of age groups g1,g2, a
higher value of RR(g1) compared to RR(g2) is interpreted as the relative
increase in the population incidence of SARS-Cov-2 for g1 compared to g2 for
the later vs. early period. Results: The relative risk was highest for
individuals aged 20-24y (RR=1.4(95% CI (1.27,1.55))), followed by individuals
aged 15-19y (RR=1.14(0.99,1.32)), aged 30-34y (RR= 1.07(0.99,1.16)), aged
25-29y (RR= 1.06(0.98,1.15)), aged 35-39y (RR=0.95(0.87,1.03)), aged 40-44y
(RR=0.9(0.83,0.98)), aged 45-49y (RR=0.83(0.77,0.89)) and aged 10-14y
(RR=0.78(0.64,0.95)). Conclusions: The observed relative increase with time in
the prevalence of individuals aged 15-34y (particularly those aged 20-24y)
among COVID-19 cases is unlikely to be explained by increases in the likelihood
of seeking medical care/being tested for individuals in those age groups
compared to individuals aged 35-49y or 10-14y, suggesting an actual increase in
the prevalence of individuals aged 15-34y among SARS-CoV-2 infections in the
German population. That increase likely reflects elevated mixing among
individuals aged 15-34y (particularly those aged 20-24y) compared to other age
groups, possibly due to lesser adherence to social distancing practices.
| [
{
"created": "Mon, 6 Apr 2020 16:59:08 GMT",
"version": "v1"
}
] | 2020-04-07 | [
[
"Goldstein",
"Edward",
""
]
] | Background: There is uncertainty about the role of different age groups in propagating the SARS-CoV-2 epidemics in different countries. Methods: We used the Koch Institute data on COVID-19 cases in Germany. To minimize the effect of changes in healthcare seeking behavior and testing practices, we included the following 5-year age groups in the analyses: 10-14y through 45-49y. For each age group g, we considered the proportion PL(g) of individuals in age group g among all detected cases aged 10-49y during weeks 13-14, 2020 (later period), as well as corresponding proportion PE(g) for weeks 10-11, 2020 (early period), and the relative risk RR(g)=PL(g)/PE(g). For each pair of age groups g1,g2, a higher value of RR(g1) compared to RR(g2) is interpreted as the relative increase in the population incidence of SARS-Cov-2 for g1 compared to g2 for the later vs. early period. Results: The relative risk was highest for individuals aged 20-24y (RR=1.4(95% CI (1.27,1.55))), followed by individuals aged 15-19y (RR=1.14(0.99,1.32)), aged 30-34y (RR= 1.07(0.99,1.16)), aged 25-29y (RR= 1.06(0.98,1.15)), aged 35-39y (RR=0.95(0.87,1.03)), aged 40-44y (RR=0.9(0.83,0.98)), aged 45-49y (RR=0.83(0.77,0.89)) and aged 10-14y (RR=0.78(0.64,0.95)). Conclusions: The observed relative increase with time in the prevalence of individuals aged 15-34y (particularly those aged 20-24y) among COVID-19 cases is unlikely to be explained by increases in the likelihood of seeking medical care/being tested for individuals in those age groups compared to individuals aged 35-49y or 10-14y, suggesting an actual increase in the prevalence of individuals aged 15-34y among SARS-CoV-2 infections in the German population. That increase likely reflects elevated mixing among individuals aged 15-34y (particularly those aged 20-24y) compared to other age groups, possibly due to lesser adherence to social distancing practices. |
2003.11975 | Daniele Fargion | Benjamin Isac Fargion, Daniele Fargion, Pier Giorgio De Sanctis
Lucentini, Emanuele Habib | Purim: a rapid method with reduced cost for massive detection of
CoVid-19 | 7 pages, 7 figures | null | null | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The CoVid-19 is spreading pandemically all over the world. A rapid defeat of
the pandemic requires carrying out on the population a mass screening, able to
separate positive from negative cases. Such a cleaning will free a flow of
productive population. The current rate and cost of testing, performed with the
common PCR (polymerase chain reaction) method and with the available resources,
is forcing a selection of the subjects to be tested. Indeed, each one must be
examined individually at the cost of precious time. Moreover, the exclusion of
potentially positive individuals from screening induces health risks, a broad
slowdown in the effort to curb the viral spread, and the consequent mortality
rates. We present a new procedure, the Purified by Unified Resampling of
Infected Multitudes, in short Purim, able to untangle any massive candidate
sample with inexpensive screening, through the cross-correlated analysis of the
joint speciments. This procedure can reveal and detect most negative patients
and in most cases discover the identity of the few positives already in the
first or few secondary tests. We investigate the the two-dimensional
correlation case in function of the infection probability. The
multi-dimensional topology, the scaled Purim procedure are also considered.
Extensive Purim tests may measure and weight the degree of epidemic: their
outcome may identify focal regions in the early stages. Assuming hundreds or
thousand subjects, the saving both in time and in cost will be remarkable.
Purim may be able to filter scheduled flights, scholar acceptance, popular
international event participants. The optimal extension of Purim outcome is
growing as the inverse of the epidemia expansion. Therefore, the earlier, the
better.
| [
{
"created": "Thu, 26 Mar 2020 15:22:03 GMT",
"version": "v1"
}
] | 2020-03-27 | [
[
"Fargion",
"Benjamin Isac",
""
],
[
"Fargion",
"Daniele",
""
],
[
"Lucentini",
"Pier Giorgio De Sanctis",
""
],
[
"Habib",
"Emanuele",
""
]
] | The CoVid-19 is spreading pandemically all over the world. A rapid defeat of the pandemic requires carrying out on the population a mass screening, able to separate positive from negative cases. Such a cleaning will free a flow of productive population. The current rate and cost of testing, performed with the common PCR (polymerase chain reaction) method and with the available resources, is forcing a selection of the subjects to be tested. Indeed, each one must be examined individually at the cost of precious time. Moreover, the exclusion of potentially positive individuals from screening induces health risks, a broad slowdown in the effort to curb the viral spread, and the consequent mortality rates. We present a new procedure, the Purified by Unified Resampling of Infected Multitudes, in short Purim, able to untangle any massive candidate sample with inexpensive screening, through the cross-correlated analysis of the joint speciments. This procedure can reveal and detect most negative patients and in most cases discover the identity of the few positives already in the first or few secondary tests. We investigate the the two-dimensional correlation case in function of the infection probability. The multi-dimensional topology, the scaled Purim procedure are also considered. Extensive Purim tests may measure and weight the degree of epidemic: their outcome may identify focal regions in the early stages. Assuming hundreds or thousand subjects, the saving both in time and in cost will be remarkable. Purim may be able to filter scheduled flights, scholar acceptance, popular international event participants. The optimal extension of Purim outcome is growing as the inverse of the epidemia expansion. Therefore, the earlier, the better. |
1703.00981 | Daniel Moyer | Daniel Moyer, Boris A Gutman, Neda Jahanshad, Paul M. Thompson | A Restaurant Process Mixture Model for Connectivity Based Parcellation
of the Cortex | In the Proceedings of Information Processing in Medical Imaging 2017 | null | null | null | q-bio.NC cs.CE cs.CV q-bio.QM stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One of the primary objectives of human brain mapping is the division of the
cortical surface into functionally distinct regions, i.e. parcellation. While
it is generally agreed that at macro-scale different regions of the cortex have
different functions, the exact number and configuration of these regions is not
known. Methods for the discovery of these regions are thus important,
particularly as the volume of available information grows. Towards this end, we
present a parcellation method based on a Bayesian non-parametric mixture model
of cortical connectivity.
| [
{
"created": "Thu, 2 Mar 2017 23:03:56 GMT",
"version": "v1"
}
] | 2017-03-06 | [
[
"Moyer",
"Daniel",
""
],
[
"Gutman",
"Boris A",
""
],
[
"Jahanshad",
"Neda",
""
],
[
"Thompson",
"Paul M.",
""
]
] | One of the primary objectives of human brain mapping is the division of the cortical surface into functionally distinct regions, i.e. parcellation. While it is generally agreed that at macro-scale different regions of the cortex have different functions, the exact number and configuration of these regions is not known. Methods for the discovery of these regions are thus important, particularly as the volume of available information grows. Towards this end, we present a parcellation method based on a Bayesian non-parametric mixture model of cortical connectivity. |
1511.01703 | Chris Brackley | Frank S Heldt, Chris A Brackley, Celso Grebogi and Marco Thiel | Community control in cellular protein production: consequences for amino
acid starvation | 11 pages, 5 figures | Phil. Trans. R. Soc. A 373 20150107 (2015) | 10.1098/rsta.2015.0107 | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Deprivation of essential nutrients can have stark consequences for many
processes in a cell. We consider amino acid starvation, which can result in
bottlenecks in mRNA translation when ribosomes stall due to lack of resources,
i.e. tRNAs charged with the missing amino acid. Recent experiments also show
less obvious effects such as increased charging of other (non-starved) tRNA
species and selective charging of isoaccepting tRNAs. We present a mechanism
which accounts for these observations, and shows that production of some
proteins can actually increase under starvation. One might assume that such
responses could only be a result of sophisticated control pathways, but here we
show that these effects can occur naturally due to changes in the supply and
demand for different resources, and that control can be accomplished through
selective use of rare codons. We develop a model for translation which includes
the dynamics of the charging and use of aa-tRNAs, explicitly taking into
account the effect of specific codon sequences. This constitutes a new control
mechanism in gene regulation which emerges at the community level, i.e., via
resources used by all ribosomes.
| [
{
"created": "Thu, 5 Nov 2015 11:39:35 GMT",
"version": "v1"
}
] | 2015-11-06 | [
[
"Heldt",
"Frank S",
""
],
[
"Brackley",
"Chris A",
""
],
[
"Grebogi",
"Celso",
""
],
[
"Thiel",
"Marco",
""
]
] | Deprivation of essential nutrients can have stark consequences for many processes in a cell. We consider amino acid starvation, which can result in bottlenecks in mRNA translation when ribosomes stall due to lack of resources, i.e. tRNAs charged with the missing amino acid. Recent experiments also show less obvious effects such as increased charging of other (non-starved) tRNA species and selective charging of isoaccepting tRNAs. We present a mechanism which accounts for these observations, and shows that production of some proteins can actually increase under starvation. One might assume that such responses could only be a result of sophisticated control pathways, but here we show that these effects can occur naturally due to changes in the supply and demand for different resources, and that control can be accomplished through selective use of rare codons. We develop a model for translation which includes the dynamics of the charging and use of aa-tRNAs, explicitly taking into account the effect of specific codon sequences. This constitutes a new control mechanism in gene regulation which emerges at the community level, i.e., via resources used by all ribosomes. |
1401.2682 | Chinmaya Gupta | Chinmaya Gupta, Jos\'e Manuel L\'opez, Robert Azencott, Matthew R
Bennett, Kre\v{s}imir Josi\'c and William Ott | Modeling delay in genetic networks: From delay birth-death processes to
delay stochastic differential equations | null | null | 10.1063/1.4878662 | null | q-bio.MN math-ph math.MP q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Delay is an important and ubiquitous aspect of many biochemical processes.
For example, delay plays a central role in the dynamics of genetic regulatory
networks as it stems from the sequential assembly of first mRNA and then
protein. Genetic regulatory networks are therefore frequently modeled as
stochastic birth-death processes with delay. Here we examine the relationship
between delay birth-death processes and their appropriate approximating delay
chemical Langevin equations. We prove that the distance between these two
descriptions, as measured by expectations of functionals of the processes,
converges to zero with increasing system size. Further, we prove that the delay
birth-death process converges to the thermodynamic limit as system size tends
to infinity. Our results hold for both fixed delay and distributed delay.
Simulations demonstrate that the delay chemical Langevin approximation is
accurate even at moderate system sizes. It captures dynamical features such as
the spatial and temporal distributions of transition pathways in metastable
systems, oscillatory behavior in negative feedback circuits, and
cross-correlations between nodes in a network. Overall, these results provide a
foundation for using delay stochastic differential equations to approximate the
dynamics of birth-death processes with delay.
| [
{
"created": "Sun, 12 Jan 2014 23:42:44 GMT",
"version": "v1"
}
] | 2015-06-18 | [
[
"Gupta",
"Chinmaya",
""
],
[
"López",
"José Manuel",
""
],
[
"Azencott",
"Robert",
""
],
[
"Bennett",
"Matthew R",
""
],
[
"Josić",
"Krešimir",
""
],
[
"Ott",
"William",
""
]
] | Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove that the distance between these two descriptions, as measured by expectations of functionals of the processes, converges to zero with increasing system size. Further, we prove that the delay birth-death process converges to the thermodynamic limit as system size tends to infinity. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the spatial and temporal distributions of transition pathways in metastable systems, oscillatory behavior in negative feedback circuits, and cross-correlations between nodes in a network. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay. |
1806.10409 | Gianluca Susi PhD | Gianluca Susi, Luis Anton Toro, Leonides Canuet, Maria Eugenia Lopez,
Fernando Maestu, Claudio R. Mirasso, Ernesto Pereda | A neuro-inspired system for online learning and recognition of parallel
spike trains, based on spike latency and heterosynaptic STDP | Submitted to Frontiers in Neuroscience | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Humans perform remarkably well in many cognitive tasks including pattern
recognition. However, the neuronal mechanisms underlying this process are not
well understood. Nevertheless, artificial neural networks, inspired in brain
circuits, have been designed and used to tackle spatio-temporal pattern
recognition tasks. In this paper we present a multineuronal spike pattern
detection structure able to autonomously implement online learning and
recognition of parallel spike sequences (i.e., sequences of pulses belonging to
different neurons/neural ensembles). The operating principle of this structure
is based on two spiking/synaptic neurocomputational characteristics: spike
latency, that enables neurons to fire spikes with a certain delay and
heterosynaptic plasticity, that allows the own regulation of synaptic weights.
From the perspective of the information representation, the structure allows
mapping a spatio-temporal stimulus into a multidimensional, temporal, feature
space. In this space, the parameter coordinate and the time at which a neuron
fires represent one specific feature. In this sense, each feature can be
considered to span a single temporal axis. We applied our proposed scheme to
experimental data obtained from a motor inhibitory cognitive task. The test
exhibits good classification performance, indicating the adequateness of our
approach. In addition to its effectiveness, its simplicity and low
computational cost suggest a large scale implementation for real time
recognition applications in several areas, such as brain computer interface,
personal biometrics authentication or early detection of diseases.
| [
{
"created": "Wed, 27 Jun 2018 10:56:55 GMT",
"version": "v1"
}
] | 2018-06-28 | [
[
"Susi",
"Gianluca",
""
],
[
"Toro",
"Luis Anton",
""
],
[
"Canuet",
"Leonides",
""
],
[
"Lopez",
"Maria Eugenia",
""
],
[
"Maestu",
"Fernando",
""
],
[
"Mirasso",
"Claudio R.",
""
],
[
"Pereda",
"Ernesto",
""
]
] | Humans perform remarkably well in many cognitive tasks including pattern recognition. However, the neuronal mechanisms underlying this process are not well understood. Nevertheless, artificial neural networks, inspired in brain circuits, have been designed and used to tackle spatio-temporal pattern recognition tasks. In this paper we present a multineuronal spike pattern detection structure able to autonomously implement online learning and recognition of parallel spike sequences (i.e., sequences of pulses belonging to different neurons/neural ensembles). The operating principle of this structure is based on two spiking/synaptic neurocomputational characteristics: spike latency, that enables neurons to fire spikes with a certain delay and heterosynaptic plasticity, that allows the own regulation of synaptic weights. From the perspective of the information representation, the structure allows mapping a spatio-temporal stimulus into a multidimensional, temporal, feature space. In this space, the parameter coordinate and the time at which a neuron fires represent one specific feature. In this sense, each feature can be considered to span a single temporal axis. We applied our proposed scheme to experimental data obtained from a motor inhibitory cognitive task. The test exhibits good classification performance, indicating the adequateness of our approach. In addition to its effectiveness, its simplicity and low computational cost suggest a large scale implementation for real time recognition applications in several areas, such as brain computer interface, personal biometrics authentication or early detection of diseases. |
1602.05328 | David Koslicki | David Koslicki, Daniel Falush | MetaPalette: A $k$-mer painting approach for metagenomic taxonomic
profiling and quantification of novel strain variation | 20 pages, 19 figures | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Metagenomic profiling is challenging in part because of the highly uneven
sampling of the tree of life by genome sequencing projects and the limitations
imposed by performing phylogenetic inference at fixed taxonomic ranks. We
present the algorithm MetaPalette which uses long $k$-mer sizes ($k=30, 50$) to
fit a $k$-mer "palette" of a given sample to the $k$-mer palette of reference
organisms. By modeling the $k$-mer palettes of unknown organisms, the method
also gives an indication of the presence, abundance, and evolutionary
relatedness of novel organisms present in the sample. The method returns a
traditional, fixed-rank taxonomic profile which is shown on independently
simulated data to be one of the most accurate to date. Tree figures are also
returned that quantify the relatedness of novel organisms to reference
sequences and the accuracy of such figures is demonstrated on simulated
spike-ins and a metagenomic soil sample. The software implementing MetaPalette
is available at: https://github.com/dkoslicki/MetaPalette. Pre-trained
databases are included for Archaea, Bacteria, Eukaryota, and viruses.
| [
{
"created": "Wed, 17 Feb 2016 07:38:56 GMT",
"version": "v1"
}
] | 2016-02-18 | [
[
"Koslicki",
"David",
""
],
[
"Falush",
"Daniel",
""
]
] | Metagenomic profiling is challenging in part because of the highly uneven sampling of the tree of life by genome sequencing projects and the limitations imposed by performing phylogenetic inference at fixed taxonomic ranks. We present the algorithm MetaPalette which uses long $k$-mer sizes ($k=30, 50$) to fit a $k$-mer "palette" of a given sample to the $k$-mer palette of reference organisms. By modeling the $k$-mer palettes of unknown organisms, the method also gives an indication of the presence, abundance, and evolutionary relatedness of novel organisms present in the sample. The method returns a traditional, fixed-rank taxonomic profile which is shown on independently simulated data to be one of the most accurate to date. Tree figures are also returned that quantify the relatedness of novel organisms to reference sequences and the accuracy of such figures is demonstrated on simulated spike-ins and a metagenomic soil sample. The software implementing MetaPalette is available at: https://github.com/dkoslicki/MetaPalette. Pre-trained databases are included for Archaea, Bacteria, Eukaryota, and viruses. |
1904.06183 | Qinbing Fu | Huatian Wang, Qinbing Fu, Hongxin Wang, Jigen Peng, Paul Baxter, Cheng
Hu, Shigang Yue | Angular Velocity Estimation of Image Motion Mimicking the Honeybee
Tunnel Centring Behaviour | 7 pages, 8 figures, conference, IEEE format. arXiv admin note: text
overlap with arXiv:1904.02356 | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Insects use visual information to estimate angular velocity of retinal image
motion, which determines a variety of flight behaviours including speed
regulation, tunnel centring and visual navigation. For angular velocity
estimation, honeybees show large spatial-independence against visual stimuli,
whereas the previous models have not fulfilled such an ability. To address this
issue, we propose a bio-plausible model for estimating the image motion
velocity based on behavioural experiments of the honeybee flying through
patterned tunnels. The proposed model contains mainly three parts, the texture
estimation layer for spatial information extraction, the delay-and-correlate
layer for temporal information extraction and the decoding layer for angular
velocity estimation. This model produces responses that are largely independent
of the spatial frequency in grating experiments. And the model has been
implemented in a virtual bee for tunnel centring simulations. The results
coincide with both electro-physiological neuron spike and behavioural path
recordings, which indicates our proposed method provides a better explanation
of the honeybee's image motion detection mechanism guiding the tunnel centring
behaviour.
| [
{
"created": "Wed, 3 Apr 2019 16:50:29 GMT",
"version": "v1"
}
] | 2019-04-15 | [
[
"Wang",
"Huatian",
""
],
[
"Fu",
"Qinbing",
""
],
[
"Wang",
"Hongxin",
""
],
[
"Peng",
"Jigen",
""
],
[
"Baxter",
"Paul",
""
],
[
"Hu",
"Cheng",
""
],
[
"Yue",
"Shigang",
""
]
] | Insects use visual information to estimate angular velocity of retinal image motion, which determines a variety of flight behaviours including speed regulation, tunnel centring and visual navigation. For angular velocity estimation, honeybees show large spatial-independence against visual stimuli, whereas the previous models have not fulfilled such an ability. To address this issue, we propose a bio-plausible model for estimating the image motion velocity based on behavioural experiments of the honeybee flying through patterned tunnels. The proposed model contains mainly three parts, the texture estimation layer for spatial information extraction, the delay-and-correlate layer for temporal information extraction and the decoding layer for angular velocity estimation. This model produces responses that are largely independent of the spatial frequency in grating experiments. And the model has been implemented in a virtual bee for tunnel centring simulations. The results coincide with both electro-physiological neuron spike and behavioural path recordings, which indicates our proposed method provides a better explanation of the honeybee's image motion detection mechanism guiding the tunnel centring behaviour. |
2402.19388 | Wenping Cui | Wenping Cui, Jemma M. Fendley, Sriram Srikant, Boris Shraiman | A model of pan-immunity maintenance by horizontal gene transfer in the
ecological dynamics of bacteria and phages | null | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Phages and their bacterial hosts are locked in an evolutionary competition
which in small and closed systems typically results in the extinction of one or
the other. To resist phages bacteria have evolved numerous defense systems,
which nevertheless are still overcome by specific phage counter-defense
mechanisms. These defense/counter-defense systems are a major element of
microbial genetic diversity and have been demonstrated to propagate between
strains by horizontal gene transfer (HGT). It has been proposed that the
totality of defense systems found in microbial communities collectively form a
distributed "pan-immune" system with individual elements moving between strains
via ubiquitous HGT. Here, we formulate a Lotka-Volterra type model of a
host/phage system interacting via a combinatorial variety of
defense/counter-defense systems and show that HGT enables stable maintenance of
diverse defense/counter-defense genes in the microbial pan-genome even when
individual microbial strains inevitably undergo extinction. This stability
requires the HGT rate to be sufficiently high to ensure that some descendant of
a "dying" strain survives thanks to the immunity acquired through HGT from the
community at large, thus establishing a new strain. This mechanism of
persistence for the pan-immune gene pool is fundamentally similar to the
"island migration" model of ecological diversity, with genes moving between
genomes instead of species migrating between islands.
| [
{
"created": "Thu, 29 Feb 2024 17:43:14 GMT",
"version": "v1"
}
] | 2024-03-01 | [
[
"Cui",
"Wenping",
""
],
[
"Fendley",
"Jemma M.",
""
],
[
"Srikant",
"Sriram",
""
],
[
"Shraiman",
"Boris",
""
]
] | Phages and their bacterial hosts are locked in an evolutionary competition which in small and closed systems typically results in the extinction of one or the other. To resist phages bacteria have evolved numerous defense systems, which nevertheless are still overcome by specific phage counter-defense mechanisms. These defense/counter-defense systems are a major element of microbial genetic diversity and have been demonstrated to propagate between strains by horizontal gene transfer (HGT). It has been proposed that the totality of defense systems found in microbial communities collectively form a distributed "pan-immune" system with individual elements moving between strains via ubiquitous HGT. Here, we formulate a Lotka-Volterra type model of a host/phage system interacting via a combinatorial variety of defense/counter-defense systems and show that HGT enables stable maintenance of diverse defense/counter-defense genes in the microbial pan-genome even when individual microbial strains inevitably undergo extinction. This stability requires the HGT rate to be sufficiently high to ensure that some descendant of a "dying" strain survives thanks to the immunity acquired through HGT from the community at large, thus establishing a new strain. This mechanism of persistence for the pan-immune gene pool is fundamentally similar to the "island migration" model of ecological diversity, with genes moving between genomes instead of species migrating between islands. |
1011.3278 | Xiao-Lun Wu | Tuba Altindal, Li Xie, Xiao-Lun Wu | Implications of 3-step swimming patterns in bacterial chemotaxis | 18 pages, 4 figures, submitted to biophysical journal | null | 10.1016/j.bpj.2010.11.029 | null | q-bio.CB | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We recently found that marine bacteria Vibrio alginolyticus execute a cyclic
3-step (run- reverse-flick) motility pattern that is distinctively different
from the 2-step (run-tumble) pattern of Escherichia coli. How this novel
swimming pattern is regulated by cells of V. alginolyticus is not currently
known, but its significance for bacterial chemotaxis is self- evident and will
be delineated herein. Using an approach introduced by de Gennes, we calculated
the migration speed of a cell executing the 3-step pattern in a linear chemical
gradient, and found that a biphasic chemotactic response arises naturally. The
implication of such a response for the cells to adapt to ocean environments and
its possible connection to E. coli 's response are also discussed.
| [
{
"created": "Mon, 15 Nov 2010 01:42:38 GMT",
"version": "v1"
}
] | 2017-07-26 | [
[
"Altindal",
"Tuba",
""
],
[
"Xie",
"Li",
""
],
[
"Wu",
"Xiao-Lun",
""
]
] | We recently found that marine bacteria Vibrio alginolyticus execute a cyclic 3-step (run- reverse-flick) motility pattern that is distinctively different from the 2-step (run-tumble) pattern of Escherichia coli. How this novel swimming pattern is regulated by cells of V. alginolyticus is not currently known, but its significance for bacterial chemotaxis is self- evident and will be delineated herein. Using an approach introduced by de Gennes, we calculated the migration speed of a cell executing the 3-step pattern in a linear chemical gradient, and found that a biphasic chemotactic response arises naturally. The implication of such a response for the cells to adapt to ocean environments and its possible connection to E. coli 's response are also discussed. |
1807.05189 | Enrica Uggetti | Joan Garcia, Antonio Ortiz, Eduardo Alvarez, Vojtech Belohlav, Maria
Jesus Garcia-Galan, Ruben Diez-Montero, Juan Antonio Alvarez and Enrica
Uggetti | Nutrient removal from agricultural run-off in demonstrative full scale
tubular photobioreactors for microalgae growth | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The objective of this paper is to present the design, construction and
operation of 3 full scale semi-closed, horizontal tubular photobioreactors
(PBR) used to remove nutrients of a mixture of agricultural run-off (90%) and
treated domestic wastewater (10%). The microalgal biomass produced in the PBRs
was harvested in a static lamella settling tank. Each PBR treated in average
2.3 m3/d. PBRs were submitted to strong seasonal changes regarding solar
radiation and temperature, which had a direct impact in the activity of
microalgae and the efficiency of the system. Higher mixed liquor pH values were
registered in summer (daily average> 10). Most of the influent and effluent
nitrogen content was inorganic (average of 9.0 mg N/L and 3.17 mg N/L,
respectively), and in the form of nitrate (62% and 50%, respectively). Average
nitrogen removal efficiency was 65%, with values of around 90% in summer, 80%
in autumn, 50 % in winter and 60% in spring. Most of the influent and effluent
phosphorus content was in the form of ortophosphate. Influent average was 0.62
mg P/L, but with great variations and in a considerable number of samples not
detected. Removal efficiency (when influent values were detected) was very high
during all the study, usually greater than 95%, and there were not clear
seasonal trends for efficiency as observed for TIN. Volumetric biomass
production greatly changed between seasons with much lower values in winter (7
g VSS/m3d) than in summer (43 g VSS/m3d). Biomass separation efficiency of the
settler was very good in either terms of turbidity and total suspended solids,
being most of the time lower than 5 UNT and 15 mg/L, respectively. Overall this
study demonstrated the reliable and good effectiveness of microalgae based
technologies such as the PBR to remove nutrients at a full scale size.
| [
{
"created": "Thu, 12 Jul 2018 11:52:36 GMT",
"version": "v1"
}
] | 2018-07-16 | [
[
"Garcia",
"Joan",
""
],
[
"Ortiz",
"Antonio",
""
],
[
"Alvarez",
"Eduardo",
""
],
[
"Belohlav",
"Vojtech",
""
],
[
"Garcia-Galan",
"Maria Jesus",
""
],
[
"Diez-Montero",
"Ruben",
""
],
[
"Alvarez",
"Juan Antonio",
""
],
[
"Uggetti",
"Enrica",
""
]
] | The objective of this paper is to present the design, construction and operation of 3 full scale semi-closed, horizontal tubular photobioreactors (PBR) used to remove nutrients of a mixture of agricultural run-off (90%) and treated domestic wastewater (10%). The microalgal biomass produced in the PBRs was harvested in a static lamella settling tank. Each PBR treated in average 2.3 m3/d. PBRs were submitted to strong seasonal changes regarding solar radiation and temperature, which had a direct impact in the activity of microalgae and the efficiency of the system. Higher mixed liquor pH values were registered in summer (daily average> 10). Most of the influent and effluent nitrogen content was inorganic (average of 9.0 mg N/L and 3.17 mg N/L, respectively), and in the form of nitrate (62% and 50%, respectively). Average nitrogen removal efficiency was 65%, with values of around 90% in summer, 80% in autumn, 50 % in winter and 60% in spring. Most of the influent and effluent phosphorus content was in the form of ortophosphate. Influent average was 0.62 mg P/L, but with great variations and in a considerable number of samples not detected. Removal efficiency (when influent values were detected) was very high during all the study, usually greater than 95%, and there were not clear seasonal trends for efficiency as observed for TIN. Volumetric biomass production greatly changed between seasons with much lower values in winter (7 g VSS/m3d) than in summer (43 g VSS/m3d). Biomass separation efficiency of the settler was very good in either terms of turbidity and total suspended solids, being most of the time lower than 5 UNT and 15 mg/L, respectively. Overall this study demonstrated the reliable and good effectiveness of microalgae based technologies such as the PBR to remove nutrients at a full scale size. |
1606.01684 | Daqing Guo | Daqing Guo, Shengdun Wu, Mingming Chen, Matjaz Perc, Yangsong Zhang,
Jingling Ma, Yan Cui, Peng Xu, Yang Xia, and Dezhong Yao | Regulation of Irregular Neuronal Firing by Autaptic Transmission | 27 pages, 8 figures | Sci. Rep. 6 (2016) 26096 | 10.1038/srep26096 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The importance of self-feedback autaptic transmission in modulating
spike-time irregularity is still poorly understood. By using a biophysical
model that incorporates autaptic coupling, we here show that self-innervation
of neurons participates in the modulation of irregular neuronal firing,
primarily by regulating the occurrence frequency of burst firing. In
particular, we find that both excitatory and electrical autapses increase the
occurrence of burst firing, thus reducing neuronal firing regularity. In
contrast, inhibitory autapses suppress burst firing and therefore tend to
improve the regularity of neuronal firing. Importantly, we show that these
findings are independent of the firing properties of individual neurons, and as
such can be observed for neurons operating in different modes. Our results
provide an insightful mechanistic understanding of how different types of
autapses shape irregular firing at the single-neuron level, and they highlight
the functional importance of autaptic self-innervation in taming and modulating
neurodynamics.
| [
{
"created": "Mon, 6 Jun 2016 10:40:41 GMT",
"version": "v1"
}
] | 2016-07-04 | [
[
"Guo",
"Daqing",
""
],
[
"Wu",
"Shengdun",
""
],
[
"Chen",
"Mingming",
""
],
[
"Perc",
"Matjaz",
""
],
[
"Zhang",
"Yangsong",
""
],
[
"Ma",
"Jingling",
""
],
[
"Cui",
"Yan",
""
],
[
"Xu",
"Peng",
""
],
[
"Xia",
"Yang",
""
],
[
"Yao",
"Dezhong",
""
]
] | The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates autaptic coupling, we here show that self-innervation of neurons participates in the modulation of irregular neuronal firing, primarily by regulating the occurrence frequency of burst firing. In particular, we find that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. In contrast, inhibitory autapses suppress burst firing and therefore tend to improve the regularity of neuronal firing. Importantly, we show that these findings are independent of the firing properties of individual neurons, and as such can be observed for neurons operating in different modes. Our results provide an insightful mechanistic understanding of how different types of autapses shape irregular firing at the single-neuron level, and they highlight the functional importance of autaptic self-innervation in taming and modulating neurodynamics. |
q-bio/0403042 | Volkan Sevim Mr. | Volkan Sevim, Per Arne Rikvold | A Biological Coevolution Model with Correlated Individual-Based Dynamics | 4 pages, 3 figures. To be published in Computer Simulation Studies in
Condensed-Matter Physics XVII. Ed. by D.P. Landau, S. P. Lewis, H.-B.
Schuttler (Springer-Verlag, Berlin Heidelberg New York). Changes: An error in
results corrected. Fig. 1b and 2 replaced | Computer Simulation Studies in Condensed-Matter Physics
XVII,edited by D.P. Landau, S.P. Lewis, and H.-B. Schuttler, Springer
Proceedings in Physics Vol. 103 (Springer-Verlag, Berlin Heidelberg, 2005) | null | null | q-bio.PE cond-mat.stat-mech | null | We study the effects of interspecific correlations in a biological
coevolution model in which organisms are represented by genomes of bitstrings.
We present preliminary results for this model, indicating that these
correlations do not significantly affect the statistical behavior of the
system.
| [
{
"created": "Tue, 30 Mar 2004 14:32:14 GMT",
"version": "v1"
},
{
"created": "Tue, 11 May 2004 16:49:58 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Sevim",
"Volkan",
""
],
[
"Rikvold",
"Per Arne",
""
]
] | We study the effects of interspecific correlations in a biological coevolution model in which organisms are represented by genomes of bitstrings. We present preliminary results for this model, indicating that these correlations do not significantly affect the statistical behavior of the system. |
2107.12026 | Eneko Uru\~nuela | Eneko Uru\~nuela, Thomas A.W. Bolton, Dimitri Van De Ville, C\'esar
Caballero-Gaudes | Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at
Work | 19 pages, 6 figures, submitted to Aperture | null | 10.52294/001c.87574 | null | q-bio.NC | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Deconvolution of the hemodynamic response is an important step to access
short timescales of brain activity recorded by functional magnetic resonance
imaging (fMRI). Albeit conventional deconvolution algorithms have been around
for a long time (e.g., Wiener deconvolution), recent state-of-the-art methods
based on sparsity-pursuing regularization are attracting increasing interest to
investigate brain dynamics and connectivity with fMRI. This technical note
revisits the main concepts underlying two main methods, Paradigm Free Mapping
and Total Activation, in the most accessible way. Despite their apparent
differences in the formulation, these methods are theoretically equivalent as
they represent the synthesis and analysis sides of the same problem,
respectively. We demonstrate this equivalence in practice with their
best-available implementations using both simulations, with different
signal-to-noise ratios, and experimental fMRI data acquired during a motor task
and resting-state. We evaluate the parameter settings that lead to equivalent
results, and showcase the potential of these algorithms compared to other
common approaches. This note is useful for practitioners interested in gaining
a better understanding of state-of-the-art hemodynamic deconvolution, and aims
to answer questions that practitioners often have regarding the differences
between the two methods.
| [
{
"created": "Mon, 26 Jul 2021 08:30:18 GMT",
"version": "v1"
},
{
"created": "Mon, 6 Dec 2021 11:53:22 GMT",
"version": "v2"
},
{
"created": "Tue, 31 May 2022 17:08:35 GMT",
"version": "v3"
},
{
"created": "Mon, 8 Aug 2022 14:40:42 GMT",
"version": "v4"
}
] | 2023-10-19 | [
[
"Uruñuela",
"Eneko",
""
],
[
"Bolton",
"Thomas A. W.",
""
],
[
"Van De Ville",
"Dimitri",
""
],
[
"Caballero-Gaudes",
"César",
""
]
] | Deconvolution of the hemodynamic response is an important step to access short timescales of brain activity recorded by functional magnetic resonance imaging (fMRI). Albeit conventional deconvolution algorithms have been around for a long time (e.g., Wiener deconvolution), recent state-of-the-art methods based on sparsity-pursuing regularization are attracting increasing interest to investigate brain dynamics and connectivity with fMRI. This technical note revisits the main concepts underlying two main methods, Paradigm Free Mapping and Total Activation, in the most accessible way. Despite their apparent differences in the formulation, these methods are theoretically equivalent as they represent the synthesis and analysis sides of the same problem, respectively. We demonstrate this equivalence in practice with their best-available implementations using both simulations, with different signal-to-noise ratios, and experimental fMRI data acquired during a motor task and resting-state. We evaluate the parameter settings that lead to equivalent results, and showcase the potential of these algorithms compared to other common approaches. This note is useful for practitioners interested in gaining a better understanding of state-of-the-art hemodynamic deconvolution, and aims to answer questions that practitioners often have regarding the differences between the two methods. |
1805.10371 | Polly Y. Yu | Polly Y. Yu, Gheorghe Craciun | Mathematical Analysis of Chemical Reaction Systems | 17 pages, 7 figures, review | null | null | null | q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The use of mathematical methods for the analysis of chemical reaction systems
has a very long history, and involves many types of models: deterministic
versus stochastic, continuous versus discrete, and homogeneous versus spatially
distributed. Here we focus on mathematical models based on deterministic
mass-action kinetics. These models are systems of coupled nonlinear
differential equations on the positive orthant. We explain how mathematical
properties of the solutions of mass-action systems are strongly related to key
properties of the networks of chemical reactions that generate them, such as
specific versions of reversibility and feedback interactions.
| [
{
"created": "Fri, 25 May 2018 21:45:08 GMT",
"version": "v1"
}
] | 2018-05-29 | [
[
"Yu",
"Polly Y.",
""
],
[
"Craciun",
"Gheorghe",
""
]
] | The use of mathematical methods for the analysis of chemical reaction systems has a very long history, and involves many types of models: deterministic versus stochastic, continuous versus discrete, and homogeneous versus spatially distributed. Here we focus on mathematical models based on deterministic mass-action kinetics. These models are systems of coupled nonlinear differential equations on the positive orthant. We explain how mathematical properties of the solutions of mass-action systems are strongly related to key properties of the networks of chemical reactions that generate them, such as specific versions of reversibility and feedback interactions. |
2309.00627 | Matteo Ferrante | Matteo Ferrante, Tommaso Boccato, Nicola Toschi | Through their eyes: multi-subject Brain Decoding with simple alignment
techniques | null | null | null | null | q-bio.NC cs.AI | http://creativecommons.org/licenses/by/4.0/ | Previous brain decoding research primarily involves single-subject studies,
reconstructing stimuli via fMRI activity from the same subject. Our study aims
to introduce a generalization technique for cross-subject brain decoding,
facilitated by exploring data alignment methods. We utilized the NSD dataset, a
comprehensive 7T fMRI vision experiment involving multiple subjects exposed to
9841 images, 982 of which were viewed by all. Our approach involved training a
decoding model on one subject, aligning others' data to this space, and testing
the decoding on the second subject. We compared ridge regression, hyper
alignment, and anatomical alignment techniques for fMRI data alignment. We
established that cross-subject brain decoding is feasible, even using around
10% of the total data, or 982 common images, with comparable performance to
single-subject decoding. Ridge regression was the best method for functional
alignment. Through subject alignment, we achieved superior brain decoding and a
potential 90% reduction in scan time. This could pave the way for more
efficient experiments and further advancements in the field, typically
requiring an exorbitant 20-hour scan time per subject.
| [
{
"created": "Tue, 1 Aug 2023 16:07:22 GMT",
"version": "v1"
}
] | 2023-09-06 | [
[
"Ferrante",
"Matteo",
""
],
[
"Boccato",
"Tommaso",
""
],
[
"Toschi",
"Nicola",
""
]
] | Previous brain decoding research primarily involves single-subject studies, reconstructing stimuli via fMRI activity from the same subject. Our study aims to introduce a generalization technique for cross-subject brain decoding, facilitated by exploring data alignment methods. We utilized the NSD dataset, a comprehensive 7T fMRI vision experiment involving multiple subjects exposed to 9841 images, 982 of which were viewed by all. Our approach involved training a decoding model on one subject, aligning others' data to this space, and testing the decoding on the second subject. We compared ridge regression, hyper alignment, and anatomical alignment techniques for fMRI data alignment. We established that cross-subject brain decoding is feasible, even using around 10% of the total data, or 982 common images, with comparable performance to single-subject decoding. Ridge regression was the best method for functional alignment. Through subject alignment, we achieved superior brain decoding and a potential 90% reduction in scan time. This could pave the way for more efficient experiments and further advancements in the field, typically requiring an exorbitant 20-hour scan time per subject. |
2012.04761 | Justin Faber | Justin Faber, Hancheng Li, Dolores Bozovic | Chaos stabilizes synchronization in systems of coupled inner-ear hair
cells | null | Phys. Rev. Research 3, 013266 (2021) | 10.1103/PhysRevResearch.3.013266 | null | q-bio.NC physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Hair cells of the auditory and vestibular systems display astonishing
sensitivity, frequency selectivity, and temporal resolution to external
signals. These specialized cells utilize an internal active amplifier to
achieve highly sensitive mechanical detection. One of the manifestations of
this active process is the occurrence of spontaneous limit-cycle motion of the
hair cell bundle. As hair bundles under in vivo conditions are typically
coupled to each other by overlying structures, we explore the role of this
coupling on the dynamics of the system, using a combination of theoretical and
experimental approaches. Our numerical model suggests that the presence of
chaotic dynamics in the response of individual bundles enhances their ability
to synchronize when coupled, resulting in significant improvement in the
system's ability to detect weak signals. This synchronization persists even for
a large frequency dispersion and a large number of oscillators comprising the
system. Further, the amplitude and coherence of the active motion is not
reduced upon increasing the number of oscillators. Using artificial membranes,
we impose mechanical coupling on groups of live and functional hair bundles,
selected from in vitro preparations of the sensory epithelium, allowing us to
explore the role of coupling experimentally. Consistent with the numerical
simulations of the chaotic system, synchronization occurs even for large
frequency dispersion and a large number of hair cells. Further, the amplitude
and coherence of the spontaneous oscillations are independent of the number of
hair cells in the network. We therefore propose that hair cells utilize their
chaotic dynamics to stabilize the synchronized state and avoid the amplitude
death regime, resulting in collective coherent motion that could play a role in
generating spontaneous otoacoustic emissions and an enhanced ability to detect
weak signals.
| [
{
"created": "Tue, 8 Dec 2020 21:59:51 GMT",
"version": "v1"
}
] | 2021-03-31 | [
[
"Faber",
"Justin",
""
],
[
"Li",
"Hancheng",
""
],
[
"Bozovic",
"Dolores",
""
]
] | Hair cells of the auditory and vestibular systems display astonishing sensitivity, frequency selectivity, and temporal resolution to external signals. These specialized cells utilize an internal active amplifier to achieve highly sensitive mechanical detection. One of the manifestations of this active process is the occurrence of spontaneous limit-cycle motion of the hair cell bundle. As hair bundles under in vivo conditions are typically coupled to each other by overlying structures, we explore the role of this coupling on the dynamics of the system, using a combination of theoretical and experimental approaches. Our numerical model suggests that the presence of chaotic dynamics in the response of individual bundles enhances their ability to synchronize when coupled, resulting in significant improvement in the system's ability to detect weak signals. This synchronization persists even for a large frequency dispersion and a large number of oscillators comprising the system. Further, the amplitude and coherence of the active motion is not reduced upon increasing the number of oscillators. Using artificial membranes, we impose mechanical coupling on groups of live and functional hair bundles, selected from in vitro preparations of the sensory epithelium, allowing us to explore the role of coupling experimentally. Consistent with the numerical simulations of the chaotic system, synchronization occurs even for large frequency dispersion and a large number of hair cells. Further, the amplitude and coherence of the spontaneous oscillations are independent of the number of hair cells in the network. We therefore propose that hair cells utilize their chaotic dynamics to stabilize the synchronized state and avoid the amplitude death regime, resulting in collective coherent motion that could play a role in generating spontaneous otoacoustic emissions and an enhanced ability to detect weak signals. |
1501.07158 | Michael Courtney | Joshua Courtney, Ya'el Courtney, Michael Courtney | Review of Magnetic Shark Deterrents: Hypothetical Mechanisms and
Evidence for Selectivity | 11 pages | Aquatic Science and Technology, ISSN 2168-9148, 2015, Vol. 3, No.
1 | 10.5296/ast.v3i1.6670 | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Several papers published since 2006 describe effects of magnetic fields on
elasmobranchs and assess their utility in reducing negative interactions
between sharks and humans, including bycatch reduction. Most of these repeat a
single untested hypothesis regarding physical mechanisms by which elasmobranchs
detect magnetic fields and also neglect careful consideration of
magnetoreception in teleosts. Several species of teleosts are known to have
magnetoreception based in biogenic magnetite, and direct magnetic field
detection also has support in several species of elasmobranchs. The overly
narrow focus of earlier papers on the unsupported hypothesis that
magnetoreception in elasmobranchs is based in the ampullae of Lorenzini creates
the impression that all teleosts will be insensitive to magnetic deterrents.
However, magnetite based magnetoreception has been demonstrated in several
teleosts, and is supported in others. Furthermore, electroreception is present
in many teleost species; therefore, the possibility of induction based indirect
magnetoreception should be considered. Finally, experiments reported as
demonstrating insensitivity in teleost species to magnetic deterrents suffer
from inadequate design and sample sizes to reject the hypothesis of magnetic
detection in any given species. Since adoption of deterrent hook technologies
depends on both deterrent effects in sharks and the absence of effects in
target teleosts, the hypothesis of detection in teleost species must be
independently tested with adequate sample sizes.
| [
{
"created": "Mon, 24 Nov 2014 15:52:32 GMT",
"version": "v1"
}
] | 2015-01-29 | [
[
"Courtney",
"Joshua",
""
],
[
"Courtney",
"Ya'el",
""
],
[
"Courtney",
"Michael",
""
]
] | Several papers published since 2006 describe effects of magnetic fields on elasmobranchs and assess their utility in reducing negative interactions between sharks and humans, including bycatch reduction. Most of these repeat a single untested hypothesis regarding physical mechanisms by which elasmobranchs detect magnetic fields and also neglect careful consideration of magnetoreception in teleosts. Several species of teleosts are known to have magnetoreception based in biogenic magnetite, and direct magnetic field detection also has support in several species of elasmobranchs. The overly narrow focus of earlier papers on the unsupported hypothesis that magnetoreception in elasmobranchs is based in the ampullae of Lorenzini creates the impression that all teleosts will be insensitive to magnetic deterrents. However, magnetite based magnetoreception has been demonstrated in several teleosts, and is supported in others. Furthermore, electroreception is present in many teleost species; therefore, the possibility of induction based indirect magnetoreception should be considered. Finally, experiments reported as demonstrating insensitivity in teleost species to magnetic deterrents suffer from inadequate design and sample sizes to reject the hypothesis of magnetic detection in any given species. Since adoption of deterrent hook technologies depends on both deterrent effects in sharks and the absence of effects in target teleosts, the hypothesis of detection in teleost species must be independently tested with adequate sample sizes. |
1310.7981 | Liane Gabora | Tomas Veloz, Liane Gabora, Mark Eyjolfson, and Diederik Aerts | Toward a Formal Model of the Shifting Relationship between Concepts and
Contexts during Associative Thought | 11 pages; 2 figures | (2011). Lecture Notes in Computer Science 7052: Proceedings Fifth
International Symposium on Quantum Interaction. June 27-29, Aberdeen, UK.
Berlin: Springer | null | null | q-bio.NC cs.AI | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The quantum inspired State Context Property (SCOP) theory of concepts is
unique amongst theories of concepts in offering a means of incorporating that
for each concept in each different context there are an unlimited number of
exemplars, or states, of varying degrees of typicality. Working with data from
a study in which participants were asked to rate the typicality of exemplars of
a concept for different contexts, and introducing an exemplar typicality
threshold, we built a SCOP model of how states of a concept arise differently
in associative versus analytic (or divergent and convergent) modes of thought.
Introducing measures of state robustness and context relevance, we show that by
varying the threshold, the relevance of different contexts changes, and
seemingly atypical states can become typical. The formalism provides a pivotal
step toward a formal explanation of creative thought proesses.
| [
{
"created": "Tue, 29 Oct 2013 22:57:54 GMT",
"version": "v1"
}
] | 2013-10-31 | [
[
"Veloz",
"Tomas",
""
],
[
"Gabora",
"Liane",
""
],
[
"Eyjolfson",
"Mark",
""
],
[
"Aerts",
"Diederik",
""
]
] | The quantum inspired State Context Property (SCOP) theory of concepts is unique amongst theories of concepts in offering a means of incorporating that for each concept in each different context there are an unlimited number of exemplars, or states, of varying degrees of typicality. Working with data from a study in which participants were asked to rate the typicality of exemplars of a concept for different contexts, and introducing an exemplar typicality threshold, we built a SCOP model of how states of a concept arise differently in associative versus analytic (or divergent and convergent) modes of thought. Introducing measures of state robustness and context relevance, we show that by varying the threshold, the relevance of different contexts changes, and seemingly atypical states can become typical. The formalism provides a pivotal step toward a formal explanation of creative thought proesses. |
2003.09065 | Tom Chou | Jonathan Wylie and Tom Chou | Uniformly accurate effective equations for disease transmission mediated
by pair formation dynamics | 13pp, 2 figures | null | null | null | q-bio.PE q-bio.QM | http://creativecommons.org/licenses/by-nc-sa/4.0/ | We derive and asymptotically analyze mass-action models for disease spread
that include transient pair formation and dissociation. Populations of unpaired
susceptibles and infecteds are distinguished from the population of three types
of pairs of individuals; both susceptible, one susceptible and one infected,
and both infected. Disease transmission can occur only within a pair consisting
of one susceptible individual and one infected individual. By considering the
fast pair formation and fast pair dissociation limits, we use a perturbation
expansion to formally derive a uniformly valid approximation for the dynamics
of the total infected and susceptible populations. Under different parameter
regimes, we derive uniformly valid effective equations for the total infected
population and compare their results to those of the full mass-action model.
Our results are derived from the fundamental mass-action system without
implicitly imposing transmission mechanisms such as that used in
frequency-dependent models. They provide a new formulation for effective
pairing models and are compared with previous models.
| [
{
"created": "Fri, 20 Mar 2020 01:38:36 GMT",
"version": "v1"
}
] | 2020-03-23 | [
[
"Wylie",
"Jonathan",
""
],
[
"Chou",
"Tom",
""
]
] | We derive and asymptotically analyze mass-action models for disease spread that include transient pair formation and dissociation. Populations of unpaired susceptibles and infecteds are distinguished from the population of three types of pairs of individuals; both susceptible, one susceptible and one infected, and both infected. Disease transmission can occur only within a pair consisting of one susceptible individual and one infected individual. By considering the fast pair formation and fast pair dissociation limits, we use a perturbation expansion to formally derive a uniformly valid approximation for the dynamics of the total infected and susceptible populations. Under different parameter regimes, we derive uniformly valid effective equations for the total infected population and compare their results to those of the full mass-action model. Our results are derived from the fundamental mass-action system without implicitly imposing transmission mechanisms such as that used in frequency-dependent models. They provide a new formulation for effective pairing models and are compared with previous models. |
q-bio/0401015 | Michael Schindler | Michael Schindler, Peter Talkner and Peter H\"anggi | Switching Time Statistics for Driven Neuron Models: Analytic Expressions
versus Numerics | 4 pages, 4 figures, RevTeX4 used, final version | Phys. Rev. Lett 93 (2004) 048102 | 10.1103/PhysRevLett.93.048102 | null | q-bio.NC cond-mat.dis-nn cond-mat.stat-mech nlin.AO | null | Analytical expressions are put forward to investigate the forced spiking
activity of abstract neuron models such as the driven leaky integrate-and-fire
(LIF) model. The method is valid in a wide parameter regime beyond the
restraining limits of weak driving (linear response) and/or weak noise. The
novel approximation is based on a discrete state Markovian modeling of the full
dynamics with time-dependent rates. The scheme yields very good agreement with
numerical Langevin and Fokker-Planck simulations of the full non-stationary
dynamics for both, the first-passage time statistics and the interspike
interval (residence time) distributions.
| [
{
"created": "Sat, 10 Jan 2004 00:47:11 GMT",
"version": "v1"
},
{
"created": "Mon, 9 Jan 2006 11:12:03 GMT",
"version": "v2"
}
] | 2007-05-23 | [
[
"Schindler",
"Michael",
""
],
[
"Talkner",
"Peter",
""
],
[
"Hänggi",
"Peter",
""
]
] | Analytical expressions are put forward to investigate the forced spiking activity of abstract neuron models such as the driven leaky integrate-and-fire (LIF) model. The method is valid in a wide parameter regime beyond the restraining limits of weak driving (linear response) and/or weak noise. The novel approximation is based on a discrete state Markovian modeling of the full dynamics with time-dependent rates. The scheme yields very good agreement with numerical Langevin and Fokker-Planck simulations of the full non-stationary dynamics for both, the first-passage time statistics and the interspike interval (residence time) distributions. |
1412.2153 | Yannis Pantazis | Georgios Arampatzis and Markos A. Katsoulakis and Yannis Pantazis | Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction
Networks | null | null | 10.1371/journal.pone.0130825 | null | q-bio.MN q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, a two-step strategy for parametric sensitivity analysis for
such systems is proposed, exploiting advantages and synergies between two
recently proposed sensitivity analysis methodologies for stochastic dynamics.
The first method performs sensitivity analysis of the stochastic dynamics by
means of the Fisher Information Matrix on the underlying distribution of the
trajectories; the second method is a reduced-variance, finite-difference,
gradient-type sensitivity approach relying on stochastic coupling techniques
for variance reduction. Here we demonstrate that these two methods can be
combined and deployed together by means of a new sensitivity bound which
incorporates the variance of the quantity of interest as well as the Fisher
Information Matrix estimated from the first method. The first step of the
proposed strategy labels sensitivities using the bound and screens out the
insensitive parameters in a controlled manner based also on the new sensitivity
bound. In the second step of the proposed strategy, the finite-difference
method is applied only for the sensitivity estimation of the (potentially)
sensitive parameters that have not been screened out in the first step. Results
on an epidermal growth factor network with fifty parameters and on a protein
homeostasis with eighty parameters demonstrate that the proposed strategy is
able to quickly discover and discard the insensitive parameters and in the
remaining potentially sensitive parameters it accurately estimates the
sensitivities. The new sensitivity strategy can be several times faster than
current state-of-the-art approaches that test all parameters, especially in
"sloppy" systems. In particular, the computational acceleration is quantified
by the ratio between the total number of parameters over the number of the
sensitive parameters.
| [
{
"created": "Thu, 4 Dec 2014 15:40:06 GMT",
"version": "v1"
}
] | 2016-02-17 | [
[
"Arampatzis",
"Georgios",
""
],
[
"Katsoulakis",
"Markos A.",
""
],
[
"Pantazis",
"Yannis",
""
]
] | In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner based also on the new sensitivity bound. In the second step of the proposed strategy, the finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the number of the sensitive parameters. |
2207.04736 | Yin Xian | Y. Xian, H. Liu, X. Tai and Y. Wang | Randomized Kaczmarz Method for Single Particle X-ray Image Phase
Retrieval | null | null | null | null | q-bio.QM cs.NA eess.IV math.NA | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | In this paper, we investigate phase retrieval algorithm for the single
particle X-ray imaging data. We present a variance-reduced randomized Kaczmarz
(VR-RK) algorithm for phase retrieval. The VR-RK algorithm is inspired by the
randomized Kaczmarz method and the Stochastic Variance Reduce Gradient Descent
(SVRG) algorithm. Numerical experiments show that the VR-RK algorithm has a
faster convergence rate than randomized Kaczmarz algorithm and the iterative
projection phase retrieval methods, such as the hybrid input output (HIO) and
the relaxed averaged alternating reflections (RAAR) methods. The VR-RK
algorithm can recover the phases with higher accuracy, and is robust at the
presence of noise. Experimental results on the scattering data from individual
particles show that the VR-RK algorithm can recover phases and improve the
single particle image identification.
| [
{
"created": "Mon, 11 Jul 2022 09:42:15 GMT",
"version": "v1"
}
] | 2022-07-12 | [
[
"Xian",
"Y.",
""
],
[
"Liu",
"H.",
""
],
[
"Tai",
"X.",
""
],
[
"Wang",
"Y.",
""
]
] | In this paper, we investigate phase retrieval algorithm for the single particle X-ray imaging data. We present a variance-reduced randomized Kaczmarz (VR-RK) algorithm for phase retrieval. The VR-RK algorithm is inspired by the randomized Kaczmarz method and the Stochastic Variance Reduce Gradient Descent (SVRG) algorithm. Numerical experiments show that the VR-RK algorithm has a faster convergence rate than randomized Kaczmarz algorithm and the iterative projection phase retrieval methods, such as the hybrid input output (HIO) and the relaxed averaged alternating reflections (RAAR) methods. The VR-RK algorithm can recover the phases with higher accuracy, and is robust at the presence of noise. Experimental results on the scattering data from individual particles show that the VR-RK algorithm can recover phases and improve the single particle image identification. |
2008.07574 | David Franklin | Sae Franklin and David W. Franklin | Feedback Gains modulate with Motor Memory Uncertainty | null | null | 10.51628/001c.22336 | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | A sudden change in dynamics produces large errors leading to increases in
muscle co-contraction and feedback gains during early adaptation. We previously
proposed that internal model uncertainty drives these changes, whereby the
sensorimotor system reacts to the change in dynamics by up regulating stiffness
and feedback gains to reduce the effect of model errors. However, these
feedback gain increases have also been suggested to represent part of the
adaptation mechanism. Here, we investigate this by examining changes in
visuomotor feedback gains during gradual or abrupt force field adaptation.
Participants grasped a robotic manipulandum and reached while a curl force
field was introduced gradually or abruptly. Abrupt introduction of dynamics
elicited large initial increases in kinematic error, muscle co-contraction and
visuomotor feedback gains, while gradual introduction showed little initial
change in these measures despite evidence of adaptation. After adaptation had
plateaued,there was a change in the co-contraction and visuomotor feedback
gains relative to null field movements, but no differences (apart from the
final muscle activation pattern) between the abrupt and gradual introduction of
dynamics. This suggests that the initial increase in feedback gains is not part
of the adaptation process, but instead an automatic reactive response to
internal model uncertainty. In contrast, the final level of feedback gains is a
predictive tuning of the feedback gains to the external dynamics as part of the
internal model adaptation. Together, the reactive and predictive feedback gains
explain the wide variety of previous experimental results of feedback changes
during adaptation.
| [
{
"created": "Mon, 17 Aug 2020 18:52:38 GMT",
"version": "v1"
},
{
"created": "Sat, 10 Apr 2021 17:25:22 GMT",
"version": "v2"
}
] | 2023-12-13 | [
[
"Franklin",
"Sae",
""
],
[
"Franklin",
"David W.",
""
]
] | A sudden change in dynamics produces large errors leading to increases in muscle co-contraction and feedback gains during early adaptation. We previously proposed that internal model uncertainty drives these changes, whereby the sensorimotor system reacts to the change in dynamics by up regulating stiffness and feedback gains to reduce the effect of model errors. However, these feedback gain increases have also been suggested to represent part of the adaptation mechanism. Here, we investigate this by examining changes in visuomotor feedback gains during gradual or abrupt force field adaptation. Participants grasped a robotic manipulandum and reached while a curl force field was introduced gradually or abruptly. Abrupt introduction of dynamics elicited large initial increases in kinematic error, muscle co-contraction and visuomotor feedback gains, while gradual introduction showed little initial change in these measures despite evidence of adaptation. After adaptation had plateaued,there was a change in the co-contraction and visuomotor feedback gains relative to null field movements, but no differences (apart from the final muscle activation pattern) between the abrupt and gradual introduction of dynamics. This suggests that the initial increase in feedback gains is not part of the adaptation process, but instead an automatic reactive response to internal model uncertainty. In contrast, the final level of feedback gains is a predictive tuning of the feedback gains to the external dynamics as part of the internal model adaptation. Together, the reactive and predictive feedback gains explain the wide variety of previous experimental results of feedback changes during adaptation. |
2402.03397 | Chung To (Andy) Kong | Y. Gua, C.T. Kong, D.D Zhangc, Y.J Baid, J.K.H. Tsoia, Hua Huangc,
Y.Q. Dengc, Y.M Zhue | A Comprehensive Approach to Diagnosing Temporomandibular Joint Diseases:
AI-driven TMD Diagnostic System | null | null | null | null | q-bio.QM eess.IV | http://creativecommons.org/licenses/by/4.0/ | AI-driven TMD diagnostic system uses AI segmentation method to diagnose
Temporomandibular Joint Disorders (TMD). By using segmentation, three important
parts: temporal bone, temporomandibular joint (TMJ) disc and the condyle can be
identified. The location and the size of each segment are used as the basic
information to determine if the patient has a high chance of having
Temporomandibular Joint Disorders (TMD).
| [
{
"created": "Mon, 5 Feb 2024 02:15:23 GMT",
"version": "v1"
}
] | 2024-02-07 | [
[
"Gua",
"Y.",
""
],
[
"Kong",
"C. T.",
""
],
[
"Zhangc",
"D. D",
""
],
[
"Baid",
"Y. J",
""
],
[
"Tsoia",
"J. K. H.",
""
],
[
"Huangc",
"Hua",
""
],
[
"Dengc",
"Y. Q.",
""
],
[
"Zhue",
"Y. M",
""
]
] | AI-driven TMD diagnostic system uses AI segmentation method to diagnose Temporomandibular Joint Disorders (TMD). By using segmentation, three important parts: temporal bone, temporomandibular joint (TMJ) disc and the condyle can be identified. The location and the size of each segment are used as the basic information to determine if the patient has a high chance of having Temporomandibular Joint Disorders (TMD). |
2407.03467 | Owen Visser | Owen Visser, Somnath Datta | Measure Adaptations and Rank Aggregation for the Selection of Clustering
Methods and Sizes For Single Cell Data | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | The growing efficiency of single-cell sequencing technology has provided
biologists with ample cells to identify and differentiate, often through
clustering. Heuristic approaches for clustering method choice have become more
prevalent and could lead to inaccurate reports if statistical evaluation of the
resulting clusters is omitted. During the advent of microarray data, a similar
dilemma was addressed in literature through the provision of supervised and
unsupervised measures, which were evaluated through Rank Aggregation. In this
paper, these measures are adapted into the single-cell framework through a
leave-one-out approach. Additionally, a scheme was created to utilize the
information of cluster sizes by using their ranking to assign importance to the
aggregation of methods, resulting in one table of methods ranked by cluster
sizes. To demonstrate the ensemble of measures and scheme, five benchmark
single-cell datasets were clustered with various methods at appropriate cluster
sizes. We show that through rank aggregation and our importance scheme, our
adapted measures select clustering methods that perform better at cluster sizes
associated with true biological groups compared to those selected through
traditional measures. For four of the five datasets and with internal measures
alone, the rank aggregation scheme could correctly identify methods that
performed the best at cluster sizes that match the original biological groups.
We plan to package this ensemble of measures in the hopes to provide others
with a tool to identify the best performing clustering methods and associated
sizes for a variety of single cell datasets.
| [
{
"created": "Wed, 3 Jul 2024 19:26:01 GMT",
"version": "v1"
}
] | 2024-07-08 | [
[
"Visser",
"Owen",
""
],
[
"Datta",
"Somnath",
""
]
] | The growing efficiency of single-cell sequencing technology has provided biologists with ample cells to identify and differentiate, often through clustering. Heuristic approaches for clustering method choice have become more prevalent and could lead to inaccurate reports if statistical evaluation of the resulting clusters is omitted. During the advent of microarray data, a similar dilemma was addressed in literature through the provision of supervised and unsupervised measures, which were evaluated through Rank Aggregation. In this paper, these measures are adapted into the single-cell framework through a leave-one-out approach. Additionally, a scheme was created to utilize the information of cluster sizes by using their ranking to assign importance to the aggregation of methods, resulting in one table of methods ranked by cluster sizes. To demonstrate the ensemble of measures and scheme, five benchmark single-cell datasets were clustered with various methods at appropriate cluster sizes. We show that through rank aggregation and our importance scheme, our adapted measures select clustering methods that perform better at cluster sizes associated with true biological groups compared to those selected through traditional measures. For four of the five datasets and with internal measures alone, the rank aggregation scheme could correctly identify methods that performed the best at cluster sizes that match the original biological groups. We plan to package this ensemble of measures in the hopes to provide others with a tool to identify the best performing clustering methods and associated sizes for a variety of single cell datasets. |
2207.08824 | Rui Jiao | Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu | Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs | AAAI 2023 | null | null | null | q-bio.QM cs.LG | http://creativecommons.org/licenses/by-sa/4.0/ | Pretraining molecular representation models without labels is fundamental to
various applications. Conventional methods mainly process 2D molecular graphs
and focus solely on 2D tasks, making their pretrained models incapable of
characterizing 3D geometry and thus defective for downstream 3D tasks. In this
work, we tackle 3D molecular pretraining in a complete and novel sense. In
particular, we first propose to adopt an equivariant energy-based model as the
backbone for pretraining, which enjoys the merits of fulfilling the symmetry of
3D space. Then we develop a node-level pretraining loss for force prediction,
where we further exploit the Riemann-Gaussian distribution to ensure the loss
to be E(3)-invariant, enabling more robustness. Moreover, a graph-level noise
scale prediction task is also leveraged to further promote the eventual
performance. We evaluate our model pretrained from a large-scale 3D dataset
GEOM-QM9 on two challenging 3D benchmarks: MD17 and QM9. Experimental results
demonstrate the efficacy of our method against current state-of-the-art
pretraining approaches, and verify the validity of our design for each proposed
component.
| [
{
"created": "Mon, 18 Jul 2022 16:26:24 GMT",
"version": "v1"
},
{
"created": "Wed, 20 Jul 2022 14:41:17 GMT",
"version": "v2"
},
{
"created": "Wed, 17 Aug 2022 15:42:49 GMT",
"version": "v3"
},
{
"created": "Tue, 29 Nov 2022 15:15:56 GMT",
"version": "v4"
}
] | 2022-11-30 | [
[
"Jiao",
"Rui",
""
],
[
"Han",
"Jiaqi",
""
],
[
"Huang",
"Wenbing",
""
],
[
"Rong",
"Yu",
""
],
[
"Liu",
"Yang",
""
]
] | Pretraining molecular representation models without labels is fundamental to various applications. Conventional methods mainly process 2D molecular graphs and focus solely on 2D tasks, making their pretrained models incapable of characterizing 3D geometry and thus defective for downstream 3D tasks. In this work, we tackle 3D molecular pretraining in a complete and novel sense. In particular, we first propose to adopt an equivariant energy-based model as the backbone for pretraining, which enjoys the merits of fulfilling the symmetry of 3D space. Then we develop a node-level pretraining loss for force prediction, where we further exploit the Riemann-Gaussian distribution to ensure the loss to be E(3)-invariant, enabling more robustness. Moreover, a graph-level noise scale prediction task is also leveraged to further promote the eventual performance. We evaluate our model pretrained from a large-scale 3D dataset GEOM-QM9 on two challenging 3D benchmarks: MD17 and QM9. Experimental results demonstrate the efficacy of our method against current state-of-the-art pretraining approaches, and verify the validity of our design for each proposed component. |
1404.6164 | Changbong Hyeon | Jeseong Yoon, Jong-Chin Lin, Changbong Hyeon, D. Thirumalai | Dynamical Transition and Heterogeneous Hydration Dynamics in RNA | 14 pages, 5 figures | J. Phys. Chem. B. (2014) vol. 118, 7910-7919 | null | null | q-bio.BM cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Enhanced dynamical fluctuations of RNAs, facilitated by a network of water
molecules with strong interactions with RNA, are suspected to be critical in
their ability to respond to a variety of cellular signals. Using atomically
detailed molecular dynamics simulations at various temperatures of purine
(adenine)- and preQ$_1$ sensing riboswitch aptamers, we show that water
molecules in the vicinity of RNAs undergo complex dynamics depending on the
local structures of the RNAs. The overall lifetimes of hydrogen bonds (HBs) of
surface bound waters are more than at least 1-2 orders of magnitude longer than
bulk water. Slow hydration dynamics, revealed in non-Arrhenius behavior of the
relaxation time, arises from high activation barriers to break water hydrogen
bonds with a nucleotide and by reduced diffusion of water. The relaxation
kinetics at specific locations in the two RNAs show a broad spectrum of time
scales reminiscent of glass-like behavior, suggesting that the hydration
dynamics is highly heterogeneous. Both RNAs undergo dynamic transition at $T =
T_D \gtrsim 200$ K as assessed by the mean square fluctuation of hydrogen atoms
$\langle x^2\rangle$, which undergoes an abrupt harmonic-to-anharmonic
transition at $T_D$. The near universal value of $T_D$ found for these RNAs and
previously for tRNA is strongly correlated with changes in hydration dynamics
as $T$ is altered. Hierarchical dynamics of waters associated with the RNA
surface, revealed in the motions of distinct classes of water with
well-separated time scales, reflects the heterogeneous local environment on the
molecular surface of RNA. At low temperatures slow water dynamics predominates
over structural transitions. Our study demonstrates that the complex interplay
of dynamics between water and local environment in the RNA structures could be
a key determinant of the functional activities of RNA.
| [
{
"created": "Thu, 24 Apr 2014 15:52:37 GMT",
"version": "v1"
}
] | 2015-01-15 | [
[
"Yoon",
"Jeseong",
""
],
[
"Lin",
"Jong-Chin",
""
],
[
"Hyeon",
"Changbong",
""
],
[
"Thirumalai",
"D.",
""
]
] | Enhanced dynamical fluctuations of RNAs, facilitated by a network of water molecules with strong interactions with RNA, are suspected to be critical in their ability to respond to a variety of cellular signals. Using atomically detailed molecular dynamics simulations at various temperatures of purine (adenine)- and preQ$_1$ sensing riboswitch aptamers, we show that water molecules in the vicinity of RNAs undergo complex dynamics depending on the local structures of the RNAs. The overall lifetimes of hydrogen bonds (HBs) of surface bound waters are more than at least 1-2 orders of magnitude longer than bulk water. Slow hydration dynamics, revealed in non-Arrhenius behavior of the relaxation time, arises from high activation barriers to break water hydrogen bonds with a nucleotide and by reduced diffusion of water. The relaxation kinetics at specific locations in the two RNAs show a broad spectrum of time scales reminiscent of glass-like behavior, suggesting that the hydration dynamics is highly heterogeneous. Both RNAs undergo dynamic transition at $T = T_D \gtrsim 200$ K as assessed by the mean square fluctuation of hydrogen atoms $\langle x^2\rangle$, which undergoes an abrupt harmonic-to-anharmonic transition at $T_D$. The near universal value of $T_D$ found for these RNAs and previously for tRNA is strongly correlated with changes in hydration dynamics as $T$ is altered. Hierarchical dynamics of waters associated with the RNA surface, revealed in the motions of distinct classes of water with well-separated time scales, reflects the heterogeneous local environment on the molecular surface of RNA. At low temperatures slow water dynamics predominates over structural transitions. Our study demonstrates that the complex interplay of dynamics between water and local environment in the RNA structures could be a key determinant of the functional activities of RNA. |
q-bio/0510018 | Sheng Bao | Shi Chen, Sheng Bao, Jian-Xiu Chen | A Model Analyzing Life Cycle of Periodical Cicadas | 4 pages,1 figure | null | null | null | q-bio.PE | null | This paper focuses on a mathematical model interpreting the prime number life
cycle of periodical cicadas.Changed the viewpoint to predators rather than the
prey,this model fits reality very well by utilizing some principles and
assumption.With the definition of the predator income,natural selection from
predators seems to be the main reason for such a long life cycle.Consequent
solution of this model is exactly the fact of real nature.
| [
{
"created": "Sun, 9 Oct 2005 12:21:11 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Chen",
"Shi",
""
],
[
"Bao",
"Sheng",
""
],
[
"Chen",
"Jian-Xiu",
""
]
] | This paper focuses on a mathematical model interpreting the prime number life cycle of periodical cicadas.Changed the viewpoint to predators rather than the prey,this model fits reality very well by utilizing some principles and assumption.With the definition of the predator income,natural selection from predators seems to be the main reason for such a long life cycle.Consequent solution of this model is exactly the fact of real nature. |
2104.06937 | Wilma Bainbridge | Wilma A. Bainbridge | Shared memories driven by the intrinsic memorability of items | null | null | null | null | q-bio.NC cs.CV | http://creativecommons.org/licenses/by-nc-nd/4.0/ | When we experience an event, it feels like our previous experiences, our
interpretations of that event (e.g., aesthetics, emotions), and our current
state will determine how we will remember it. However, recent work has revealed
a strong sway of the visual world itself in influencing what we remember and
forget. Certain items -- including certain faces, words, images, and movements
-- are intrinsically memorable or forgettable across observers, regardless of
individual differences. Further, neuroimaging research has revealed that the
brain is sensitive to memorability both rapidly and automatically during late
perception. These strong consistencies in memory across people may reflect the
broad organizational principles of our sensory environment, and may reveal how
the brain prioritizes information before encoding items into memory. In this
chapter, I will discuss our current state-of-the-art understanding of
memorability for visual information, and what these findings imply about how we
perceive and remember visual events.
| [
{
"created": "Wed, 14 Apr 2021 16:03:27 GMT",
"version": "v1"
}
] | 2021-04-15 | [
[
"Bainbridge",
"Wilma A.",
""
]
] | When we experience an event, it feels like our previous experiences, our interpretations of that event (e.g., aesthetics, emotions), and our current state will determine how we will remember it. However, recent work has revealed a strong sway of the visual world itself in influencing what we remember and forget. Certain items -- including certain faces, words, images, and movements -- are intrinsically memorable or forgettable across observers, regardless of individual differences. Further, neuroimaging research has revealed that the brain is sensitive to memorability both rapidly and automatically during late perception. These strong consistencies in memory across people may reflect the broad organizational principles of our sensory environment, and may reveal how the brain prioritizes information before encoding items into memory. In this chapter, I will discuss our current state-of-the-art understanding of memorability for visual information, and what these findings imply about how we perceive and remember visual events. |
2111.02068 | Ricardo Ruiz Baier | Katerina Kaouri, Paul E. M\'endez, Ricardo Ruiz-Baier | Mechanochemical models for calcium waves in embryonic epithelia | 29 pages | Vietnam Journal of Mathematics, volume 50, pages 947-975, year
2022 | 10.1007/s10013-022-00579-y | null | q-bio.TO cs.NA math.NA | http://creativecommons.org/licenses/by/4.0/ | In embryogenesis, epithelial cells, acting as individual entities or as
coordinated aggregates in a tissue, exhibit strong coupling between chemical
signalling and mechanical responses to internally or externally applied
stresses. Intercellular communication in combination with such coordination of
morphogenetic movements can lead to drastic modifications in the calcium
distribution in the cells. In this paper we extend the recent mechanochemical
model in [K. Kaouri, P.K. Maini, P.A. Skourides, N. Christodoulou, S.J.
Chapman. J. Math. Biol., 78 (2019) 2059--2092], for an epithelial continuum in
one dimension, to a more realistic multi-dimensional case. The resulting
parametrised governing equations consist of an advection-diffusion-reaction
system for calcium signalling coupled with active-stress linear viscoelasticity
and equipped with pure Neumann boundary conditions. We implement a mixed finite
element method for the simulation of this complex multiphysics problem. Special
care is taken in the treatment of the stress-free boundary conditions for the
viscoelasticity in order to eliminate rigid motions from the space of
admissible displacements. The stability and solvability of the continuous weak
formulation is shown using fixed-point theory. We investigate numerically the
solutions of this system and show that solitary waves and periodic wavetrains
of calcium propagate through the embryonic epithelial sheet. We analyse the
bifurcations of the system guided by the bifurcation analysis of the
one-dimensional model. We also demonstrate the nucleation of calcium sparks
into synchronous calcium waves coupled with contraction. This coupled model can
be employed to gain insights into recent experimental observations in the
context of embryogenesis, but also in other biological systems such as cancer
cells, wound healing, keratinocytes, or white blood cells.
| [
{
"created": "Wed, 3 Nov 2021 08:34:18 GMT",
"version": "v1"
}
] | 2023-06-27 | [
[
"Kaouri",
"Katerina",
""
],
[
"Méndez",
"Paul E.",
""
],
[
"Ruiz-Baier",
"Ricardo",
""
]
] | In embryogenesis, epithelial cells, acting as individual entities or as coordinated aggregates in a tissue, exhibit strong coupling between chemical signalling and mechanical responses to internally or externally applied stresses. Intercellular communication in combination with such coordination of morphogenetic movements can lead to drastic modifications in the calcium distribution in the cells. In this paper we extend the recent mechanochemical model in [K. Kaouri, P.K. Maini, P.A. Skourides, N. Christodoulou, S.J. Chapman. J. Math. Biol., 78 (2019) 2059--2092], for an epithelial continuum in one dimension, to a more realistic multi-dimensional case. The resulting parametrised governing equations consist of an advection-diffusion-reaction system for calcium signalling coupled with active-stress linear viscoelasticity and equipped with pure Neumann boundary conditions. We implement a mixed finite element method for the simulation of this complex multiphysics problem. Special care is taken in the treatment of the stress-free boundary conditions for the viscoelasticity in order to eliminate rigid motions from the space of admissible displacements. The stability and solvability of the continuous weak formulation is shown using fixed-point theory. We investigate numerically the solutions of this system and show that solitary waves and periodic wavetrains of calcium propagate through the embryonic epithelial sheet. We analyse the bifurcations of the system guided by the bifurcation analysis of the one-dimensional model. We also demonstrate the nucleation of calcium sparks into synchronous calcium waves coupled with contraction. This coupled model can be employed to gain insights into recent experimental observations in the context of embryogenesis, but also in other biological systems such as cancer cells, wound healing, keratinocytes, or white blood cells. |
2103.09747 | Peter D. Harrington | Peter D. Harrington, Mark A. Lewis, and P. van den Driessche | A framework for studying transients in marine metapopulations | 34 pages, 11 figures | null | 10.1137/21M140451X | null | q-bio.PE math.DS | http://creativecommons.org/licenses/by/4.0/ | Transient dynamics can often differ drastically from the asymptotic dynamics
of systems. In this paper we provide a unifying framework for analysing
transient dynamics in marine metapopulations, from the choice of norms to the
addition of stage structure. We use the $\ell_1$ norm, because of its
biological interpretation, to extend the transient metrics of reactivity and
attenuation to marine metapopulations, and use examples to compare these
metrics under the more commonly used $\ell_2$ norm. We then connect the
reactivity and attenuation of marine metapopulations to the source-sink
distribution of habitat patches and demonstrate how to meaningfully measure
reactivity when metapopulations are stage-structured.
| [
{
"created": "Wed, 17 Mar 2021 16:12:12 GMT",
"version": "v1"
}
] | 2022-06-14 | [
[
"Harrington",
"Peter D.",
""
],
[
"Lewis",
"Mark A.",
""
],
[
"Driessche",
"P. van den",
""
]
] | Transient dynamics can often differ drastically from the asymptotic dynamics of systems. In this paper we provide a unifying framework for analysing transient dynamics in marine metapopulations, from the choice of norms to the addition of stage structure. We use the $\ell_1$ norm, because of its biological interpretation, to extend the transient metrics of reactivity and attenuation to marine metapopulations, and use examples to compare these metrics under the more commonly used $\ell_2$ norm. We then connect the reactivity and attenuation of marine metapopulations to the source-sink distribution of habitat patches and demonstrate how to meaningfully measure reactivity when metapopulations are stage-structured. |
1809.11030 | Andrea De Martino | Andrea De Martino, Thomas Gueudr\'e, Mattia Miotto | Exploration-exploitation tradeoffs dictate the optimal distributions of
phenotypes for populations subject to fitness fluctuations | 13 pages, 5 figures | Phys. Rev. E 99, 012417 (2019) | 10.1103/PhysRevE.99.012417 | null | q-bio.PE cond-mat.dis-nn cond-mat.stat-mech physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study a minimal model for the growth of a phenotypically heterogeneous
population of cells subject to a fluctuating environment in which they can
replicate (by exploiting available resources) and modify their phenotype within
a given landscape (thereby exploring novel configurations). The model displays
an exploration-exploitation trade-off whose specifics depend on the statistics
of the environment. Most notably, the phenotypic distribution corresponding to
maximum population fitness (i.e. growth rate) requires a non-zero exploration
rate when the magnitude of environmental fluctuations changes randomly over
time, while a purely exploitative strategy turns out to be optimal in two-state
environments, independently of the statistics of switching times. We obtain
analytical insight into the limiting cases of very fast and very slow
exploration rates by directly linking population growth to the features of the
environment.
| [
{
"created": "Fri, 28 Sep 2018 13:53:34 GMT",
"version": "v1"
},
{
"created": "Thu, 17 Jan 2019 14:50:55 GMT",
"version": "v2"
}
] | 2019-01-23 | [
[
"De Martino",
"Andrea",
""
],
[
"Gueudré",
"Thomas",
""
],
[
"Miotto",
"Mattia",
""
]
] | We study a minimal model for the growth of a phenotypically heterogeneous population of cells subject to a fluctuating environment in which they can replicate (by exploiting available resources) and modify their phenotype within a given landscape (thereby exploring novel configurations). The model displays an exploration-exploitation trade-off whose specifics depend on the statistics of the environment. Most notably, the phenotypic distribution corresponding to maximum population fitness (i.e. growth rate) requires a non-zero exploration rate when the magnitude of environmental fluctuations changes randomly over time, while a purely exploitative strategy turns out to be optimal in two-state environments, independently of the statistics of switching times. We obtain analytical insight into the limiting cases of very fast and very slow exploration rates by directly linking population growth to the features of the environment. |
1212.5538 | Janusz Szwabi\'nski | Janusz Szwabi\'nski | Density outbursts in a food web model with closed nutrient cycle | 23 pages, 12 figures | null | 10.1016/j.physa.2013.03.047 | null | q-bio.PE physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | A spatial three level food web model with a closed nutrient cycle is
presented and analyzed via Monte Carlo simulations. The time evolution of the
model reveals two asymptotic states: an absorbing one with all species being
extinct, and a coexisting one, in which concentrations of all species are
non-zero. There are two possible ways for the system to reach the absorbing
state. In some cases the densities increase very quickly at the beginning of a
simulation and then decline slowly and almost monotonically. In others, well
pronounced peaks in the $R$, $C$ and $D$ densities appear regularly before the
extinction. Those peaks correspond to density outbursts (waves) traveling
through the system. We investigate the mechanisms leading to the waves. In
particular, we show that the percolation of the detritus (i. e. the
accumulation of nutrients) is necessary for the emergence of the waves.
Moreover, our results corroborate the hypothesis that top-level predators play
an essential role in maintaining the stability of a food web (top-down
control).
| [
{
"created": "Fri, 21 Dec 2012 17:47:46 GMT",
"version": "v1"
}
] | 2015-06-12 | [
[
"Szwabiński",
"Janusz",
""
]
] | A spatial three level food web model with a closed nutrient cycle is presented and analyzed via Monte Carlo simulations. The time evolution of the model reveals two asymptotic states: an absorbing one with all species being extinct, and a coexisting one, in which concentrations of all species are non-zero. There are two possible ways for the system to reach the absorbing state. In some cases the densities increase very quickly at the beginning of a simulation and then decline slowly and almost monotonically. In others, well pronounced peaks in the $R$, $C$ and $D$ densities appear regularly before the extinction. Those peaks correspond to density outbursts (waves) traveling through the system. We investigate the mechanisms leading to the waves. In particular, we show that the percolation of the detritus (i. e. the accumulation of nutrients) is necessary for the emergence of the waves. Moreover, our results corroborate the hypothesis that top-level predators play an essential role in maintaining the stability of a food web (top-down control). |
2109.11960 | Marcello Ienca | Marcello Ienca, Joseph J. Fins, Ralf J. Jox, Fabrice Jotterand, Silja
Voeneky, Roberto Andorno, Tonio Ball, Claude Castelluccia, Ricardo
Chavarriaga, Herv\'e Chneiweiss, Agata Ferretti, Orsolya Friedrich, Samia
Hurst, Grischa Merkel, Fruzsina Molnar-Gabor, Jean-Marc Rickli, James
Scheibner, Effy Vayena, Rafael Yuste, Philipp Kellmeyer | Towards a Governance Framework for Brain Data | null | null | null | null | q-bio.NC cs.CY | http://creativecommons.org/licenses/by/4.0/ | The increasing availability of brain data within and outside the biomedical
field, combined with the application of artificial intelligence (AI) to brain
data analysis, poses a challenge for ethics and governance. We identify
distinctive ethical implications of brain data acquisition and processing, and
outline a multi-level governance framework. This framework is aimed at
maximizing the benefits of facilitated brain data collection and further
processing for science and medicine whilst minimizing risks and preventing
harmful use. The framework consists of four primary areas of regulatory
intervention: binding regulation, ethics and soft law, responsible innovation,
and human rights.
| [
{
"created": "Fri, 24 Sep 2021 13:44:39 GMT",
"version": "v1"
},
{
"created": "Tue, 28 Sep 2021 12:21:33 GMT",
"version": "v2"
}
] | 2021-09-29 | [
[
"Ienca",
"Marcello",
""
],
[
"Fins",
"Joseph J.",
""
],
[
"Jox",
"Ralf J.",
""
],
[
"Jotterand",
"Fabrice",
""
],
[
"Voeneky",
"Silja",
""
],
[
"Andorno",
"Roberto",
""
],
[
"Ball",
"Tonio",
""
],
[
"Castelluccia",
"Claude",
""
],
[
"Chavarriaga",
"Ricardo",
""
],
[
"Chneiweiss",
"Hervé",
""
],
[
"Ferretti",
"Agata",
""
],
[
"Friedrich",
"Orsolya",
""
],
[
"Hurst",
"Samia",
""
],
[
"Merkel",
"Grischa",
""
],
[
"Molnar-Gabor",
"Fruzsina",
""
],
[
"Rickli",
"Jean-Marc",
""
],
[
"Scheibner",
"James",
""
],
[
"Vayena",
"Effy",
""
],
[
"Yuste",
"Rafael",
""
],
[
"Kellmeyer",
"Philipp",
""
]
] | The increasing availability of brain data within and outside the biomedical field, combined with the application of artificial intelligence (AI) to brain data analysis, poses a challenge for ethics and governance. We identify distinctive ethical implications of brain data acquisition and processing, and outline a multi-level governance framework. This framework is aimed at maximizing the benefits of facilitated brain data collection and further processing for science and medicine whilst minimizing risks and preventing harmful use. The framework consists of four primary areas of regulatory intervention: binding regulation, ethics and soft law, responsible innovation, and human rights. |
1011.5096 | Florian Markowetz | Roland F. Schwarz, William Fletcher, Frank F\"orster, Benjamin Merget,
Matthias Wolf, J\"org Schultz, Florian Markowetz | Evolutionary distances in the twilight zone -- a rational kernel
approach | to appear in PLoS ONE | PLoS One. 2010 Dec 31;5(12):e15788 | 10.1371/journal.pone.0015788 | null | q-bio.PE stat.ML | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Phylogenetic tree reconstruction is traditionally based on multiple sequence
alignments (MSAs) and heavily depends on the validity of this information
bottleneck. With increasing sequence divergence, the quality of MSAs decays
quickly. Alignment-free methods, on the other hand, are based on abstract
string comparisons and avoid potential alignment problems. However, in general
they are not biologically motivated and ignore our knowledge about the
evolution of sequences. Thus, it is still a major open question how to define
an evolutionary distance metric between divergent sequences that makes use of
indel information and known substitution models without the need for a multiple
alignment. Here we propose a new evolutionary distance metric to close this
gap. It uses finite-state transducers to create a biologically motivated
similarity score which models substitutions and indels, and does not depend on
a multiple sequence alignment. The sequence similarity score is defined in
analogy to pairwise alignments and additionally has the positive semi-definite
property. We describe its derivation and show in simulation studies and
real-world examples that it is more accurate in reconstructing phylogenies than
competing methods. The result is a new and accurate way of determining
evolutionary distances in and beyond the twilight zone of sequence alignments
that is suitable for large datasets.
| [
{
"created": "Tue, 23 Nov 2010 13:40:56 GMT",
"version": "v1"
}
] | 2011-01-11 | [
[
"Schwarz",
"Roland F.",
""
],
[
"Fletcher",
"William",
""
],
[
"Förster",
"Frank",
""
],
[
"Merget",
"Benjamin",
""
],
[
"Wolf",
"Matthias",
""
],
[
"Schultz",
"Jörg",
""
],
[
"Markowetz",
"Florian",
""
]
] | Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly. Alignment-free methods, on the other hand, are based on abstract string comparisons and avoid potential alignment problems. However, in general they are not biologically motivated and ignore our knowledge about the evolution of sequences. Thus, it is still a major open question how to define an evolutionary distance metric between divergent sequences that makes use of indel information and known substitution models without the need for a multiple alignment. Here we propose a new evolutionary distance metric to close this gap. It uses finite-state transducers to create a biologically motivated similarity score which models substitutions and indels, and does not depend on a multiple sequence alignment. The sequence similarity score is defined in analogy to pairwise alignments and additionally has the positive semi-definite property. We describe its derivation and show in simulation studies and real-world examples that it is more accurate in reconstructing phylogenies than competing methods. The result is a new and accurate way of determining evolutionary distances in and beyond the twilight zone of sequence alignments that is suitable for large datasets. |
0901.2293 | Richard Matthews | R Matthews, A.A. Louis and J.M. Yeomans | Knot-controlled ejection of a polymer from a virus capsid | 4 pages, 5 figures | Phys. Rev. Lett. 102 (2009) 088101 | 10.1103/PhysRevLett.102.088101 | null | q-bio.BM cond-mat.soft | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We present a numerical study of the effect of knotting on the ejection of
flexible and semiflexible polymers from a spherical, virus-like capsid. The
polymer ejection rate is primarily controlled by the knot, which moves to the
hole in the capsid and then acts as a ratchet. Polymers with more complex knots
eject more slowly and, for large knots, the knot type, and not the flexibility
of the polymer, determines the rate of ejection. We discuss the relation of our
results to the ejection of DNA from viral capsids and conjecture that this
process has the biological advantage of unknotting the DNA before it enters a
cell.
| [
{
"created": "Thu, 15 Jan 2009 16:02:30 GMT",
"version": "v1"
}
] | 2009-02-23 | [
[
"Matthews",
"R",
""
],
[
"Louis",
"A. A.",
""
],
[
"Yeomans",
"J. M.",
""
]
] | We present a numerical study of the effect of knotting on the ejection of flexible and semiflexible polymers from a spherical, virus-like capsid. The polymer ejection rate is primarily controlled by the knot, which moves to the hole in the capsid and then acts as a ratchet. Polymers with more complex knots eject more slowly and, for large knots, the knot type, and not the flexibility of the polymer, determines the rate of ejection. We discuss the relation of our results to the ejection of DNA from viral capsids and conjecture that this process has the biological advantage of unknotting the DNA before it enters a cell. |
2304.02873 | Kensuke Yoshida | Kensuke Yoshida and Taro Toyoizumi | Computational role of sleep in memory reorganization | Accepted for publication in Current Opinion in Neurobiology | Current Opinion in Neurobiology 83, 102799 (2023) | 10.1016/j.conb.2023.102799 | null | q-bio.NC | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Sleep is considered to play an essential role in memory reorganization.
Despite its importance, classical theoretical models did not focus on some
sleep characteristics. Here, we review recent theoretical approaches
investigating their roles in learning and discuss the possibility that
non-rapid eye movement (NREM) sleep selectively consolidates memory, and rapid
eye movement (REM) sleep reorganizes the representations of memories. We first
review the possibility that slow waves during NREM sleep contribute to memory
selection by using sequential firing patterns and the existence of up and down
states. Second, we discuss the role of dreaming during REM sleep in developing
neuronal representations. We finally discuss how to develop these points
further, emphasizing the connections to experimental neuroscience and machine
learning.
| [
{
"created": "Thu, 6 Apr 2023 05:34:55 GMT",
"version": "v1"
},
{
"created": "Fri, 22 Sep 2023 04:21:28 GMT",
"version": "v2"
}
] | 2023-10-23 | [
[
"Yoshida",
"Kensuke",
""
],
[
"Toyoizumi",
"Taro",
""
]
] | Sleep is considered to play an essential role in memory reorganization. Despite its importance, classical theoretical models did not focus on some sleep characteristics. Here, we review recent theoretical approaches investigating their roles in learning and discuss the possibility that non-rapid eye movement (NREM) sleep selectively consolidates memory, and rapid eye movement (REM) sleep reorganizes the representations of memories. We first review the possibility that slow waves during NREM sleep contribute to memory selection by using sequential firing patterns and the existence of up and down states. Second, we discuss the role of dreaming during REM sleep in developing neuronal representations. We finally discuss how to develop these points further, emphasizing the connections to experimental neuroscience and machine learning. |
1811.04355 | Hyekyoung Lee | Hyekyoung Lee, Moo K. Chung, Hongyoon Choi, Hyejin Kang, Seunggyun Ha,
Yu Kyeong Kim, Dong Soo Lee | Harmonic holes as the submodules of brain network and network
dissimilarity | The paper is accepted for publication at the 7th Workshop on
Computational Topology in Image Context (CTIC) (http://www.ctic2019.uma.es) | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Persistent homology has been applied to brain network analysis for finding
the shape of brain networks across multiple thresholds. In the persistent
homology, the shape of networks is often quantified by the sequence of
$k$-dimensional holes and Betti numbers.The Betti numbers are more widely used
than holes themselves in topological brain network analysis. However, the holes
show the local connectivity of networks, and they can be very informative
features in analysis. In this study, we propose a new method of measuring
network differences based on the dissimilarity measure of harmonic holes (HHs).
The HHs, which represent the substructure of brain networks, are extracted by
the Hodge Laplacian of brain networks. We also find the most contributed HHs to
the network difference based on the HH dissimilarity. We applied our proposed
method to clustering the networks of 4 groups, normal control (NC), stable and
progressive mild cognitive impairment (sMCI and pMCI), and Alzheimer's disease
(AD). The results showed that the clustering performance of the proposed method
was better than that of network distances based on only the global change of
topology.
| [
{
"created": "Sun, 11 Nov 2018 05:30:35 GMT",
"version": "v1"
}
] | 2018-11-13 | [
[
"Lee",
"Hyekyoung",
""
],
[
"Chung",
"Moo K.",
""
],
[
"Choi",
"Hongyoon",
""
],
[
"Kang",
"Hyejin",
""
],
[
"Ha",
"Seunggyun",
""
],
[
"Kim",
"Yu Kyeong",
""
],
[
"Lee",
"Dong Soo",
""
]
] | Persistent homology has been applied to brain network analysis for finding the shape of brain networks across multiple thresholds. In the persistent homology, the shape of networks is often quantified by the sequence of $k$-dimensional holes and Betti numbers.The Betti numbers are more widely used than holes themselves in topological brain network analysis. However, the holes show the local connectivity of networks, and they can be very informative features in analysis. In this study, we propose a new method of measuring network differences based on the dissimilarity measure of harmonic holes (HHs). The HHs, which represent the substructure of brain networks, are extracted by the Hodge Laplacian of brain networks. We also find the most contributed HHs to the network difference based on the HH dissimilarity. We applied our proposed method to clustering the networks of 4 groups, normal control (NC), stable and progressive mild cognitive impairment (sMCI and pMCI), and Alzheimer's disease (AD). The results showed that the clustering performance of the proposed method was better than that of network distances based on only the global change of topology. |
2006.07772 | Manuel Razo-Mejia | Muir J. Morrison, Manuel Razo-Mejia, and Rob Phillips | Reconciling Kinetic and Equilibrium Models of Bacterial Transcription | 4 figures | null | 10.1371/journal.pcbi.1008572 | null | q-bio.SC q-bio.MN | http://creativecommons.org/licenses/by-nc-sa/4.0/ | The study of transcription remains one of the centerpieces of modern biology
with implications in settings from development to metabolism to evolution to
disease. Precision measurements using a host of different techniques including
fluorescence and sequencing readouts have raised the bar for what it means to
quantitatively understand transcriptional regulation. In particular our
understanding of the simplest genetic circuit is sufficiently refined both
experimentally and theoretically that it has become possible to carefully
discriminate between different conceptual pictures of how this regulatory
system works. This regulatory motif, originally posited by Jacob and Monod in
the 1960s, consists of a single transcriptional repressor binding to a promoter
site and inhibiting transcription. In this paper, we show how seven distinct
models of this so-called simple-repression motif, based both on equilibrium and
kinetic thinking, can be used to derive the predicted levels of gene expression
and shed light on the often surprising past success of the equilbrium models.
These different models are then invoked to confront a variety of different data
on mean, variance and full gene expression distributions, illustrating the
extent to which such models can and cannot be distinguished, and suggesting a
two-state model with a distribution of burst sizes as the most potent of the
seven for describing the simple-repression motif.
| [
{
"created": "Sun, 14 Jun 2020 02:28:56 GMT",
"version": "v1"
}
] | 2021-06-09 | [
[
"Morrison",
"Muir J.",
""
],
[
"Razo-Mejia",
"Manuel",
""
],
[
"Phillips",
"Rob",
""
]
] | The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on equilibrium and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the equilbrium models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif. |
0801.4365 | Wang Weiming | Lei Zhang, Weiming Wang, Yakui Xue, Zhen Jin | Complex dynamics of a Holling-type IV predator-prey model | null | null | null | null | q-bio.PE | null | In this paper, we focus on a spatial Holling-type IV predator-prey model
which contains some important factors, such as diffusion, noise (random
fluctuations) and external periodic forcing. By a brief stability and
bifurcation analysis, we arrive at the Hopf and Turing bifurcation surface and
derive the symbolic conditions for Hopf and Turing bifurcation in the spatial
domain. Based on the stability and bifurcation analysis, we obtain spiral
pattern formation via numerical simulation. Additionally, we study the model
with colored noise and external periodic forcing. From the numerical results,
we know that noise or external periodic forcing can induce instability and
enhance the oscillation of the species, and resonant response. Our results show
that modeling by reaction-diffusion equations is an appropriate tool for
investigating fundamental mechanisms of complex spatiotemporal dynamics.
| [
{
"created": "Mon, 28 Jan 2008 19:17:09 GMT",
"version": "v1"
}
] | 2008-01-29 | [
[
"Zhang",
"Lei",
""
],
[
"Wang",
"Weiming",
""
],
[
"Xue",
"Yakui",
""
],
[
"Jin",
"Zhen",
""
]
] | In this paper, we focus on a spatial Holling-type IV predator-prey model which contains some important factors, such as diffusion, noise (random fluctuations) and external periodic forcing. By a brief stability and bifurcation analysis, we arrive at the Hopf and Turing bifurcation surface and derive the symbolic conditions for Hopf and Turing bifurcation in the spatial domain. Based on the stability and bifurcation analysis, we obtain spiral pattern formation via numerical simulation. Additionally, we study the model with colored noise and external periodic forcing. From the numerical results, we know that noise or external periodic forcing can induce instability and enhance the oscillation of the species, and resonant response. Our results show that modeling by reaction-diffusion equations is an appropriate tool for investigating fundamental mechanisms of complex spatiotemporal dynamics. |
1402.5323 | Francis Bell III | Francis Bell, Chunyu Zhao, Ahmet Sacan | PDBCirclePlot: A Novel Visualization Method for Protein Structures | Application note, 5 pages, 1 figure | null | null | null | q-bio.QM cs.CE q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Interactive molecular graphics applications facilitate analysis of three
dimensional protein structures. Naturally, non-interactive 2-D snapshots of the
protein structures do not convey the same level of geometric detail. Several
2-D visualization methods have been in use to summarize structural information,
including contact maps and 2-D cartoon views. We present a new approach for 2-D
visualization of protein structures where amino acid residues are displayed on
a circle and spatially close residues are depicted by links. Furthermore,
residue-specific properties, such as conservation, accessibility, temperature
factor, can be displayed as plots on the same circular view.
| [
{
"created": "Thu, 20 Feb 2014 20:35:48 GMT",
"version": "v1"
}
] | 2014-02-24 | [
[
"Bell",
"Francis",
""
],
[
"Zhao",
"Chunyu",
""
],
[
"Sacan",
"Ahmet",
""
]
] | Interactive molecular graphics applications facilitate analysis of three dimensional protein structures. Naturally, non-interactive 2-D snapshots of the protein structures do not convey the same level of geometric detail. Several 2-D visualization methods have been in use to summarize structural information, including contact maps and 2-D cartoon views. We present a new approach for 2-D visualization of protein structures where amino acid residues are displayed on a circle and spatially close residues are depicted by links. Furthermore, residue-specific properties, such as conservation, accessibility, temperature factor, can be displayed as plots on the same circular view. |
1002.4579 | Henrik Jeldtoft Jensen | Tomas Alarcon and Henrik Jeldtoft Jensen | Quiescence: a mechanism for escaping the effects of drug on cell
populations | 18 pages and 9 figures | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We point out that a simple and generic strategy to lower the risk for
extinction consists in the developing a dormant stage in which the organism is
unable to multiply but may die. The dormant organism is protected against the
poisonous environment. The result is to increase the survival probability of
the entire population by introducing a type of zero reproductive fitness. This
is possible, because the reservoir of dormant individuals act as a buffer that
can cushion fatal fluctuations in the number of births and deaths which without
the dormant population would have driven the entire population to extinction.
| [
{
"created": "Wed, 24 Feb 2010 16:39:41 GMT",
"version": "v1"
}
] | 2010-02-25 | [
[
"Alarcon",
"Tomas",
""
],
[
"Jensen",
"Henrik Jeldtoft",
""
]
] | We point out that a simple and generic strategy to lower the risk for extinction consists in the developing a dormant stage in which the organism is unable to multiply but may die. The dormant organism is protected against the poisonous environment. The result is to increase the survival probability of the entire population by introducing a type of zero reproductive fitness. This is possible, because the reservoir of dormant individuals act as a buffer that can cushion fatal fluctuations in the number of births and deaths which without the dormant population would have driven the entire population to extinction. |
2308.09431 | Tim Kietzmann | Zejin Lu, Adrien Doerig, Victoria Bosch, Bas Krahmer, Daniel Kaiser,
Radoslaw M Cichy, Tim C Kietzmann | End-to-end topographic networks as models of cortical map formation and
human visual behaviour: moving beyond convolutions | null | null | null | null | q-bio.NC cs.LG | http://creativecommons.org/licenses/by/4.0/ | Computational models are an essential tool for understanding the origin and
functions of the topographic organisation of the primate visual system. Yet,
vision is most commonly modelled by convolutional neural networks that ignore
topography by learning identical features across space. Here, we overcome this
limitation by developing All-Topographic Neural Networks (All-TNNs). Trained on
visual input, several features of primate topography emerge in All-TNNs: smooth
orientation maps and cortical magnification in their first layer, and
category-selective areas in their final layer. In addition, we introduce a
novel dataset of human spatial biases in object recognition, which enables us
to directly link models to behaviour. We demonstrate that All-TNNs
significantly better align with human behaviour than previous state-of-the-art
convolutional models due to their topographic nature. All-TNNs thereby mark an
important step forward in understanding the spatial organisation of the visual
brain and how it mediates visual behaviour.
| [
{
"created": "Fri, 18 Aug 2023 10:03:51 GMT",
"version": "v1"
}
] | 2023-08-21 | [
[
"Lu",
"Zejin",
""
],
[
"Doerig",
"Adrien",
""
],
[
"Bosch",
"Victoria",
""
],
[
"Krahmer",
"Bas",
""
],
[
"Kaiser",
"Daniel",
""
],
[
"Cichy",
"Radoslaw M",
""
],
[
"Kietzmann",
"Tim C",
""
]
] | Computational models are an essential tool for understanding the origin and functions of the topographic organisation of the primate visual system. Yet, vision is most commonly modelled by convolutional neural networks that ignore topography by learning identical features across space. Here, we overcome this limitation by developing All-Topographic Neural Networks (All-TNNs). Trained on visual input, several features of primate topography emerge in All-TNNs: smooth orientation maps and cortical magnification in their first layer, and category-selective areas in their final layer. In addition, we introduce a novel dataset of human spatial biases in object recognition, which enables us to directly link models to behaviour. We demonstrate that All-TNNs significantly better align with human behaviour than previous state-of-the-art convolutional models due to their topographic nature. All-TNNs thereby mark an important step forward in understanding the spatial organisation of the visual brain and how it mediates visual behaviour. |
2205.01014 | Athulya Ram | Leonid Bunimovich, Athulya Ram, Pavel Skums | Antigenic cooperation in Viral Populations: Transformation of Functions
of Intra-Host Viral Variants | 39 pages (including Appendix), 21 images | null | null | null | q-bio.PE math.DS | http://creativecommons.org/licenses/by/4.0/ | In this paper we study intra-host viral adaptation by antigenic cooperation -
a mechanism of immune escape that serves as an alternative to the standard
mechanism of escape by continuous genomic diversification and allows to explain
a number of experimental observations associated with the establishment of
chronic infections by highly mutable viruses. Within this mechanism, the
topology of a cross-immunoreactivity network forces intra-host viral variants
to specialize for complementary roles and adapt to host's immune response as a
quasi-social ecosystem. Here we study dynamical changes in immune adaptation
caused by evolutionary and epidemiological events. First, we show that the
emergence of a viral variant with altered antigenic features may result in a
rapid re-arrangement of the viral ecosystem and a change in the roles played by
existing viral variants. In particular, it may push the population under immune
escape by genomic diversification towards the stable state of adaptation by
antigenic cooperation. Next, we study the effect of a viral transmission
between two chronically infected hosts, which results in merging of two
intra-host viral populations in the state of stable immune-adapted equilibrium.
In this case, we also describe how the newly formed viral population adapts to
the host's environment by changing the functions of its members. The results
are obtained analytically for minimal cross-immunoreactivity networks and
numerically for larger populations.
| [
{
"created": "Mon, 2 May 2022 16:29:18 GMT",
"version": "v1"
},
{
"created": "Wed, 5 Apr 2023 21:22:18 GMT",
"version": "v2"
}
] | 2023-04-07 | [
[
"Bunimovich",
"Leonid",
""
],
[
"Ram",
"Athulya",
""
],
[
"Skums",
"Pavel",
""
]
] | In this paper we study intra-host viral adaptation by antigenic cooperation - a mechanism of immune escape that serves as an alternative to the standard mechanism of escape by continuous genomic diversification and allows to explain a number of experimental observations associated with the establishment of chronic infections by highly mutable viruses. Within this mechanism, the topology of a cross-immunoreactivity network forces intra-host viral variants to specialize for complementary roles and adapt to host's immune response as a quasi-social ecosystem. Here we study dynamical changes in immune adaptation caused by evolutionary and epidemiological events. First, we show that the emergence of a viral variant with altered antigenic features may result in a rapid re-arrangement of the viral ecosystem and a change in the roles played by existing viral variants. In particular, it may push the population under immune escape by genomic diversification towards the stable state of adaptation by antigenic cooperation. Next, we study the effect of a viral transmission between two chronically infected hosts, which results in merging of two intra-host viral populations in the state of stable immune-adapted equilibrium. In this case, we also describe how the newly formed viral population adapts to the host's environment by changing the functions of its members. The results are obtained analytically for minimal cross-immunoreactivity networks and numerically for larger populations. |
2007.11151 | Luke Hallum | Luke E Hallum, Shaun L Cloherty | Liquid-crystal display (LCD) of achromatic, mean-modulated flicker in
clinical assessment and experimental studies of visual systems | null | null | 10.1371/journal.pone.0248180 | null | q-bio.NC cs.HC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Achromatic, mean-modulated flicker (wherein luminance increments and
decrements of equal magnitude are applied, over time, to a test field) is
commonly used in both clinical assessment of vision and experimental studies of
visual systems. However, presenting flicker on computer-controlled displays is
problematic; displays typically introduce luminance artifacts at high flicker
frequency or contrast, potentially interfering with the validity of findings.
Here, we present a battery of tests used to weigh the relative merits of two
displays for presenting achromatic, mean-modulated flicker. These tests
revealed marked differences between a new high-performance liquid-crystal
display (LCD; EIZO ColorEdge CG247X) and a new consumer-grade LCD (Dell
U2415b), despite displays' vendor-supplied specifications being almost
identical. We measured displayed luminance using a spot meter and a linearized
photodiode. We derived several measures, including spatial uniformity, the
effect of viewing angle, response times, Fourier amplitude spectra, and
cycle-averaged luminance. We presented paired luminance pulses to quantify the
displays' nonlinear dynamics. The CG247X showed relatively good spatial
uniformity (e.g., at moderate luminance, standard deviation 2.8% versus
U2415b's 5.3%). Fourier transformation of nominally static test patches
revealed spectra free of artifacts, with the exception of a frame response. The
CG247X's rise and fall times depended on both the luminance from which, and to
which, it responded, as is to be generally expected from LCDs. Despite this
nonlinear behaviour, we were able to define a contrast and frequency range
wherein the CG247X appeared largely artifact-free; the relationship between
nominal luminance and displayed luminance was accurately modelled using a
causal, linear time-invariant system. This range included contrasts up to 80%,
and flicker frequencies up to 30 Hz.
| [
{
"created": "Wed, 22 Jul 2020 01:10:16 GMT",
"version": "v1"
},
{
"created": "Tue, 17 Nov 2020 04:12:01 GMT",
"version": "v2"
}
] | 2021-06-09 | [
[
"Hallum",
"Luke E",
""
],
[
"Cloherty",
"Shaun L",
""
]
] | Achromatic, mean-modulated flicker (wherein luminance increments and decrements of equal magnitude are applied, over time, to a test field) is commonly used in both clinical assessment of vision and experimental studies of visual systems. However, presenting flicker on computer-controlled displays is problematic; displays typically introduce luminance artifacts at high flicker frequency or contrast, potentially interfering with the validity of findings. Here, we present a battery of tests used to weigh the relative merits of two displays for presenting achromatic, mean-modulated flicker. These tests revealed marked differences between a new high-performance liquid-crystal display (LCD; EIZO ColorEdge CG247X) and a new consumer-grade LCD (Dell U2415b), despite displays' vendor-supplied specifications being almost identical. We measured displayed luminance using a spot meter and a linearized photodiode. We derived several measures, including spatial uniformity, the effect of viewing angle, response times, Fourier amplitude spectra, and cycle-averaged luminance. We presented paired luminance pulses to quantify the displays' nonlinear dynamics. The CG247X showed relatively good spatial uniformity (e.g., at moderate luminance, standard deviation 2.8% versus U2415b's 5.3%). Fourier transformation of nominally static test patches revealed spectra free of artifacts, with the exception of a frame response. The CG247X's rise and fall times depended on both the luminance from which, and to which, it responded, as is to be generally expected from LCDs. Despite this nonlinear behaviour, we were able to define a contrast and frequency range wherein the CG247X appeared largely artifact-free; the relationship between nominal luminance and displayed luminance was accurately modelled using a causal, linear time-invariant system. This range included contrasts up to 80%, and flicker frequencies up to 30 Hz. |
2004.07738 | Mauro Giudici | Mauro Giudici, Alessandro Comunian, and Romina Gaburro | Inversion of a SIR-based model: a critical analysis about the
application to COVID-19 epidemic | null | null | null | null | q-bio.PE physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Calibration of a SIR (Susceptibles-Infected-Recovered) model with official
international data for the COVID-19 pandemics provides a good example of the
difficulties inherent the solution of inverse problems. Inverse modeling is set
up in a framework of discrete inverse problems, which explicitly considers the
role and the relevance of data. Together with a physical vision of the model,
the present work addresses numerically the issue of parameters calibration in
SIR models, it discusses the uncertainties in the data provided by
international authorities, how they influence the reliability of calibrated
model parameters and, ultimately, of model predictions.
| [
{
"created": "Thu, 16 Apr 2020 16:22:25 GMT",
"version": "v1"
},
{
"created": "Mon, 8 Jun 2020 15:10:29 GMT",
"version": "v2"
}
] | 2020-06-09 | [
[
"Giudici",
"Mauro",
""
],
[
"Comunian",
"Alessandro",
""
],
[
"Gaburro",
"Romina",
""
]
] | Calibration of a SIR (Susceptibles-Infected-Recovered) model with official international data for the COVID-19 pandemics provides a good example of the difficulties inherent the solution of inverse problems. Inverse modeling is set up in a framework of discrete inverse problems, which explicitly considers the role and the relevance of data. Together with a physical vision of the model, the present work addresses numerically the issue of parameters calibration in SIR models, it discusses the uncertainties in the data provided by international authorities, how they influence the reliability of calibrated model parameters and, ultimately, of model predictions. |
0912.1175 | Changbong Hyeon | U. Deva Priyakumar and Changbong Hyeon and D. Thirumalai and Alexander
D. MacKerell Jr | Urea destabilizes RNA by forming stacking interactions and multiple
hydrogen bonds with nucleic acid bases | 22 pages, 17 figures | J. Am. Chem. Soc. (2009) vol.131, 17759-17761 | null | null | q-bio.BM cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Urea titration of RNA by urea is an effective approach to investigate the
forces stabilizing this biologically important molecule. We used all atom
molecular dynamics simulations using two urea force fields and two RNA
constructs to elucidate in atomic detail the destabilization mechanism of
folded RNA in aqueous urea solutions. Urea denatures RNA by forming multiple
hydrogen bonds with the RNA bases and has little influence on the
phosphodiester backbone. Most significantly we discovered that urea engages in
stacking interactions with the bases. We also estimate, for the first time,
m-value for RNA, which is a measure of the strength of urea-RNA interactions.
Our work provides a conceptual understanding of the mechanism by which urea
enhances RNA folding rates.
| [
{
"created": "Mon, 7 Dec 2009 07:45:04 GMT",
"version": "v1"
}
] | 2017-01-24 | [
[
"Priyakumar",
"U. Deva",
""
],
[
"Hyeon",
"Changbong",
""
],
[
"Thirumalai",
"D.",
""
],
[
"MacKerell",
"Alexander D.",
"Jr"
]
] | Urea titration of RNA by urea is an effective approach to investigate the forces stabilizing this biologically important molecule. We used all atom molecular dynamics simulations using two urea force fields and two RNA constructs to elucidate in atomic detail the destabilization mechanism of folded RNA in aqueous urea solutions. Urea denatures RNA by forming multiple hydrogen bonds with the RNA bases and has little influence on the phosphodiester backbone. Most significantly we discovered that urea engages in stacking interactions with the bases. We also estimate, for the first time, m-value for RNA, which is a measure of the strength of urea-RNA interactions. Our work provides a conceptual understanding of the mechanism by which urea enhances RNA folding rates. |
1612.09378 | Sanzo Miyazawa | Sanzo Miyazawa | Selection originating from protein foldability: I. A new method to
estimate selection temperature | This article was replaced by a new version (arXiv:1612.09379) that
merged "I. A new method to estimate selection temperature" (arXiv:1612.09378)
and "II. Folding free energy, sequence ensemble, and fitness"
(arXiv:1612.09379) | null | null | null | q-bio.PE q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The probability distribution of sequences with maximum entropy that satisfies
a given amino acid composition at each site and a given pairwise amino acid
frequency at each site pair is a Boltzmann distribution with $\exp(-\psi_N)$,
where the total interaction $\psi_N$ is represented as the sum of one body and
pairwise interactions. A protein folding theory based on the random energy
model (REM) indicates that the equilibrium ensemble of natural protein
sequences is a canonical ensemble characterized by $\exp(-\Delta G_{ND}/k_B
T_s)$ or by $\exp(- G_{N}/k_B T_s)$ if an amino acid composition is kept
constant, meaning $\psi_N = \Delta G_{ND}/k_B T_s +$ constant, where $\Delta
G_{ND} \equiv G_N - G_D$, $G_N$ and $G_D$ are the native and denatured free
energies, and $T_s$ is the effective temperature of natural selection. Here, we
examine interaction changes ($\Delta \psi_N$) due to single nucleotide
nonsynonymous mutations, and have found that the variance of their $\Delta
\psi_N$ over all sites hardly depends on the $\psi_N$ of each homologous
sequence, indicating that the variance of $\Delta G_N (= k_B T_s \Delta
\psi_N)$ is nearly constant irrespective of protein families. As a result,
$T_s$ is estimated from the ratio of the variance of $\Delta \psi_N$ to that of
a reference protein, which is determined by a direct comparison between
$\Delta\Delta \psi_{ND} (\simeq \Delta \psi_N)$ and experimental $\Delta\Delta
G_{ND}$. Based on the REM, glass transition temperature $T_g$ and $\Delta
G_{ND}$ are estimated from $T_s$ and experimental melting temperatures ($T_m$)
for 14 protein domains. The estimates of $\Delta G_{ND}$ agree well with their
experimental values for 5 proteins, and those of $T_s$ and $T_g$ are all within
a reasonable range. This method is coarse-grained but much simpler in
estimating $T_s$, $T_g$ and $\Delta\Delta G_{ND}$ than previous methods.
| [
{
"created": "Fri, 30 Dec 2016 04:11:09 GMT",
"version": "v1"
},
{
"created": "Sun, 2 Apr 2017 04:54:32 GMT",
"version": "v2"
}
] | 2017-04-04 | [
[
"Miyazawa",
"Sanzo",
""
]
] | The probability distribution of sequences with maximum entropy that satisfies a given amino acid composition at each site and a given pairwise amino acid frequency at each site pair is a Boltzmann distribution with $\exp(-\psi_N)$, where the total interaction $\psi_N$ is represented as the sum of one body and pairwise interactions. A protein folding theory based on the random energy model (REM) indicates that the equilibrium ensemble of natural protein sequences is a canonical ensemble characterized by $\exp(-\Delta G_{ND}/k_B T_s)$ or by $\exp(- G_{N}/k_B T_s)$ if an amino acid composition is kept constant, meaning $\psi_N = \Delta G_{ND}/k_B T_s +$ constant, where $\Delta G_{ND} \equiv G_N - G_D$, $G_N$ and $G_D$ are the native and denatured free energies, and $T_s$ is the effective temperature of natural selection. Here, we examine interaction changes ($\Delta \psi_N$) due to single nucleotide nonsynonymous mutations, and have found that the variance of their $\Delta \psi_N$ over all sites hardly depends on the $\psi_N$ of each homologous sequence, indicating that the variance of $\Delta G_N (= k_B T_s \Delta \psi_N)$ is nearly constant irrespective of protein families. As a result, $T_s$ is estimated from the ratio of the variance of $\Delta \psi_N$ to that of a reference protein, which is determined by a direct comparison between $\Delta\Delta \psi_{ND} (\simeq \Delta \psi_N)$ and experimental $\Delta\Delta G_{ND}$. Based on the REM, glass transition temperature $T_g$ and $\Delta G_{ND}$ are estimated from $T_s$ and experimental melting temperatures ($T_m$) for 14 protein domains. The estimates of $\Delta G_{ND}$ agree well with their experimental values for 5 proteins, and those of $T_s$ and $T_g$ are all within a reasonable range. This method is coarse-grained but much simpler in estimating $T_s$, $T_g$ and $\Delta\Delta G_{ND}$ than previous methods. |
2306.04886 | Jiaxian Yan | Jiaxian Yan, Zhaofeng Ye, Ziyi Yang, Chengqiang Lu, Shengyu Zhang, Qi
Liu, Jiezhong Qiu | Multi-task Bioassay Pre-training for Protein-ligand Binding Affinity
Prediction | 21 pages, 7 figures | null | null | null | q-bio.BM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Protein-ligand binding affinity (PLBA) prediction is the fundamental task in
drug discovery. Recently, various deep learning-based models predict binding
affinity by incorporating the three-dimensional structure of protein-ligand
complexes as input and achieving astounding progress. However, due to the
scarcity of high-quality training data, the generalization ability of current
models is still limited. In addition, different bioassays use varying affinity
measurement labels (i.e., IC50, Ki, Kd), and different experimental conditions
inevitably introduce systematic noise, which poses a significant challenge to
constructing high-precision affinity prediction models. To address these
issues, we (1) propose Multi-task Bioassay Pre-training (MBP), a pre-training
framework for structure-based PLBA prediction; (2) construct a pre-training
dataset called ChEMBL-Dock with more than 300k experimentally measured affinity
labels and about 2.8M docked three-dimensional structures. By introducing
multi-task pre-training to treat the prediction of different affinity labels as
different tasks and classifying relative rankings between samples from the same
bioassay, MBP learns robust and transferrable structural knowledge from our new
ChEMBL-Dock dataset with varied and noisy labels. Experiments substantiate the
capability of MBP as a general framework that can improve and be tailored to
mainstream structure-based PLBA prediction tasks. To the best of our knowledge,
MBP is the first affinity pre-training model and shows great potential for
future development.
| [
{
"created": "Thu, 8 Jun 2023 02:29:49 GMT",
"version": "v1"
},
{
"created": "Wed, 20 Dec 2023 11:27:01 GMT",
"version": "v2"
}
] | 2023-12-21 | [
[
"Yan",
"Jiaxian",
""
],
[
"Ye",
"Zhaofeng",
""
],
[
"Yang",
"Ziyi",
""
],
[
"Lu",
"Chengqiang",
""
],
[
"Zhang",
"Shengyu",
""
],
[
"Liu",
"Qi",
""
],
[
"Qiu",
"Jiezhong",
""
]
] | Protein-ligand binding affinity (PLBA) prediction is the fundamental task in drug discovery. Recently, various deep learning-based models predict binding affinity by incorporating the three-dimensional structure of protein-ligand complexes as input and achieving astounding progress. However, due to the scarcity of high-quality training data, the generalization ability of current models is still limited. In addition, different bioassays use varying affinity measurement labels (i.e., IC50, Ki, Kd), and different experimental conditions inevitably introduce systematic noise, which poses a significant challenge to constructing high-precision affinity prediction models. To address these issues, we (1) propose Multi-task Bioassay Pre-training (MBP), a pre-training framework for structure-based PLBA prediction; (2) construct a pre-training dataset called ChEMBL-Dock with more than 300k experimentally measured affinity labels and about 2.8M docked three-dimensional structures. By introducing multi-task pre-training to treat the prediction of different affinity labels as different tasks and classifying relative rankings between samples from the same bioassay, MBP learns robust and transferrable structural knowledge from our new ChEMBL-Dock dataset with varied and noisy labels. Experiments substantiate the capability of MBP as a general framework that can improve and be tailored to mainstream structure-based PLBA prediction tasks. To the best of our knowledge, MBP is the first affinity pre-training model and shows great potential for future development. |
2112.10688 | Gurvan Hermange | Gurvan Hermange, William Vainchenker, Isabelle Plo, and Paul-Henry
Courn\`ede | Mathematical modelling, selection and hierarchical inference to
determine the minimal dose in IFN$\alpha$ therapy against Myeloproliferative
Neoplasms | 18 pages and 9 figures for the article, 20 additional pages for the
Appendix | null | null | null | q-bio.QM stat.AP stat.CO | http://creativecommons.org/licenses/by/4.0/ | Myeloproliferative Neoplasms (MPN) are blood cancers that appear after
acquiring a driver mutation in a hematopoietic stem cell. These hematological
malignancies result in the overproduction of mature blood cells and, if not
treated, induce a risk of cardiovascular events and thrombosis. Pegylated
IFN$\alpha$ is commonly used to treat MPN, but no clear guidelines exist
concerning the dose prescribed to patients. We applied a model selection
procedure and ran a hierarchical Bayesian inference method to decipher how dose
variations impact the response to the therapy. We inferred that IFN$\alpha$
acts on mutated stem cells by inducing their differentiation into progenitor
cells, the higher the dose, the higher the effect. We found that when a
sufficient (patient-dependent) dose is reached, the treatment can induce a
long-term remission. We determined this minimal dose for individuals in a
cohort of patients and estimated the most suitable starting dose to give to a
new patient to increase the chances of being cured.
| [
{
"created": "Mon, 20 Dec 2021 17:14:30 GMT",
"version": "v1"
}
] | 2021-12-21 | [
[
"Hermange",
"Gurvan",
""
],
[
"Vainchenker",
"William",
""
],
[
"Plo",
"Isabelle",
""
],
[
"Cournède",
"Paul-Henry",
""
]
] | Myeloproliferative Neoplasms (MPN) are blood cancers that appear after acquiring a driver mutation in a hematopoietic stem cell. These hematological malignancies result in the overproduction of mature blood cells and, if not treated, induce a risk of cardiovascular events and thrombosis. Pegylated IFN$\alpha$ is commonly used to treat MPN, but no clear guidelines exist concerning the dose prescribed to patients. We applied a model selection procedure and ran a hierarchical Bayesian inference method to decipher how dose variations impact the response to the therapy. We inferred that IFN$\alpha$ acts on mutated stem cells by inducing their differentiation into progenitor cells, the higher the dose, the higher the effect. We found that when a sufficient (patient-dependent) dose is reached, the treatment can induce a long-term remission. We determined this minimal dose for individuals in a cohort of patients and estimated the most suitable starting dose to give to a new patient to increase the chances of being cured. |
1705.10820 | Murad Banaji | Murad Banaji | Counting chemical reaction networks with NAUTY | null | null | null | null | q-bio.MN math.CO math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | It is useful to have complete lists of nonisomorphic chemical reaction
networks (CRNs) of a given size, with or without various restrictions. One may,
for example, be interested in exploring how often certain dynamical behaviours
occur in small CRNs, or wish to find examples to illustrate some aspect of the
theory. In such cases, it is natural to examine one representative from each
isomorphism class of CRNs. Inspired by the related project of Deckard et al
(Enumeration and online library of mass-action reaction networks.
http://arXiv.org/abs/0901.3067, 2009), this document outlines the methodology
involved in listing all CRNs in various classes of interest including, for
example, general CRNs, dynamically nontrivial CRNs, weakly reversible CRNs,
fully open CRNs, etc. The accompanying data (i.e., lists of nonisomorphic CRNs
in the various classes) is at https://reaction-networks.net/networks/. Note
that both document and data are work in progress.
| [
{
"created": "Fri, 19 May 2017 11:02:57 GMT",
"version": "v1"
}
] | 2017-06-01 | [
[
"Banaji",
"Murad",
""
]
] | It is useful to have complete lists of nonisomorphic chemical reaction networks (CRNs) of a given size, with or without various restrictions. One may, for example, be interested in exploring how often certain dynamical behaviours occur in small CRNs, or wish to find examples to illustrate some aspect of the theory. In such cases, it is natural to examine one representative from each isomorphism class of CRNs. Inspired by the related project of Deckard et al (Enumeration and online library of mass-action reaction networks. http://arXiv.org/abs/0901.3067, 2009), this document outlines the methodology involved in listing all CRNs in various classes of interest including, for example, general CRNs, dynamically nontrivial CRNs, weakly reversible CRNs, fully open CRNs, etc. The accompanying data (i.e., lists of nonisomorphic CRNs in the various classes) is at https://reaction-networks.net/networks/. Note that both document and data are work in progress. |
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