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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2206.02558 | Sebastian Otte | Franziska Kaltenberger, Sebastian Otte, Martin V. Butz | Binding Dancers Into Attractors | null | null | null | null | q-bio.NC cs.AI cs.CV cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | To effectively perceive and process observations in our environment, feature
binding and perspective taking are crucial cognitive abilities. Feature binding
combines observed features into one entity, called a Gestalt. Perspective
taking transfers the percept into a canonical, observer-centered frame of
reference. Here we propose a recurrent neural network model that solves both
challenges. We first train an LSTM to predict 3D motion dynamics from a
canonical perspective. We then present similar motion dynamics with novel
viewpoints and feature arrangements. Retrospective inference enables the
deduction of the canonical perspective. Combined with a robust mutual-exclusive
softmax selection scheme, random feature arrangements are reordered and
precisely bound into known Gestalt percepts. To corroborate evidence for the
architecture's cognitive validity, we examine its behavior on the silhouette
illusion, which elicits two competitive Gestalt interpretations of a rotating
dancer. Our system flexibly binds the information of the rotating figure into
the alternative attractors resolving the illusion's ambiguity and imagining the
respective depth interpretation and the corresponding direction of rotation. We
finally discuss the potential universality of the proposed mechanisms.
| [
{
"created": "Wed, 1 Jun 2022 22:01:29 GMT",
"version": "v1"
}
] | 2022-06-07 | [
[
"Kaltenberger",
"Franziska",
""
],
[
"Otte",
"Sebastian",
""
],
[
"Butz",
"Martin V.",
""
]
] | To effectively perceive and process observations in our environment, feature binding and perspective taking are crucial cognitive abilities. Feature binding combines observed features into one entity, called a Gestalt. Perspective taking transfers the percept into a canonical, observer-centered frame of reference. Here we propose a recurrent neural network model that solves both challenges. We first train an LSTM to predict 3D motion dynamics from a canonical perspective. We then present similar motion dynamics with novel viewpoints and feature arrangements. Retrospective inference enables the deduction of the canonical perspective. Combined with a robust mutual-exclusive softmax selection scheme, random feature arrangements are reordered and precisely bound into known Gestalt percepts. To corroborate evidence for the architecture's cognitive validity, we examine its behavior on the silhouette illusion, which elicits two competitive Gestalt interpretations of a rotating dancer. Our system flexibly binds the information of the rotating figure into the alternative attractors resolving the illusion's ambiguity and imagining the respective depth interpretation and the corresponding direction of rotation. We finally discuss the potential universality of the proposed mechanisms. |
2208.14864 | Josinaldo Menezes | J. Menezes, B. Ferreira, E. Rangel, B. Moura | Adaptive altruistic strategy in cyclic models during an epidemic | 7 pages, 6 figures | Europhysics Letters,140, 57001 (2022) | 10.1209/0295-5075/aca354 | null | q-bio.PE nlin.AO nlin.PS physics.bio-ph q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We investigate a cyclic game system where organisms face an epidemic beyond
being threatened by natural enemies. As a survival strategy, individuals of one
out of the species usually safeguard themselves by approaching the enemies of
their enemies and performing social distancing to escape contamination when an
outbreak affects the neighbourhood. We simulate how the survival movement
strategy to local epidemic surges must adapt if a pathogen mutation makes the
disease deadlier. We study the spatial distribution of local outbreaks and
observe the influence of disease mortality on individuals' spatial
organisation. We show that adapting the survival movement strategy for a high
mortality disease demands an altruistic behaviour of the organisms since their
death risk increases. Despite weakening the disease transmission chain, which
benefits the species, abandoning refuges provided by safeguarding social
interaction increases the vulnerability to being eliminated in the cyclic game.
Considering that not all individuals exhibit altruism, we find the relative
growth in the species density as a function of the proportion of individuals
behaving altruistically. Our results may be helpful for biologists and data
scientists to understand how adaptive altruistic processes can affect
population dynamics in complex systems.
| [
{
"created": "Wed, 31 Aug 2022 13:45:47 GMT",
"version": "v1"
},
{
"created": "Fri, 6 Jan 2023 18:28:42 GMT",
"version": "v2"
}
] | 2023-01-09 | [
[
"Menezes",
"J.",
""
],
[
"Ferreira",
"B.",
""
],
[
"Rangel",
"E.",
""
],
[
"Moura",
"B.",
""
]
] | We investigate a cyclic game system where organisms face an epidemic beyond being threatened by natural enemies. As a survival strategy, individuals of one out of the species usually safeguard themselves by approaching the enemies of their enemies and performing social distancing to escape contamination when an outbreak affects the neighbourhood. We simulate how the survival movement strategy to local epidemic surges must adapt if a pathogen mutation makes the disease deadlier. We study the spatial distribution of local outbreaks and observe the influence of disease mortality on individuals' spatial organisation. We show that adapting the survival movement strategy for a high mortality disease demands an altruistic behaviour of the organisms since their death risk increases. Despite weakening the disease transmission chain, which benefits the species, abandoning refuges provided by safeguarding social interaction increases the vulnerability to being eliminated in the cyclic game. Considering that not all individuals exhibit altruism, we find the relative growth in the species density as a function of the proportion of individuals behaving altruistically. Our results may be helpful for biologists and data scientists to understand how adaptive altruistic processes can affect population dynamics in complex systems. |
1910.13357 | Alexander Mozeika | Alexander Mozeika, Franca Fraternali, Deborah Dunn-Walters, Anthony C.
C. Coolen | Roles of repertoire diversity in robustness of humoral immune response | null | null | null | null | q-bio.CB cond-mat.dis-nn physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The adaptive immune system relies on diversity of its repertoire of receptors
to protect the organism from a great variety of pathogens. Since the initial
repertoire is the result of random gene rearrangement, binding of receptors is
not limited to pathogen-associated antigens but also includes self antigens.
There is a fine balance between having a diverse repertoire, protecting from
many different pathogens, and yet reducing its self-reactivity as far as
possible to avoid damage to self. In the ageing immune system this balance is
altered, manifesting in reduced specificity of response to pathogens or
vaccination on a background of higher self-reactivity. To answer the question
whether age-related changes of repertoire in the diversity and self/non-self
affinity balance of antibodies could explain the reduced efficacy of the
humoral response in older people, we construct a minimal mathematical model of
the humoral immune response. The principle of least damage allows us, for a
given repertoire of antibodies, to resolve a tension between the necessity to
neutralise target antigens as quickly as possible and the requirement to limit
the damage to self antigens leading to an optimal dynamics of immune response.
The model predicts slowing down of immune response for repertoires with reduced
diversity and increased self-reactivity.
| [
{
"created": "Tue, 29 Oct 2019 16:24:16 GMT",
"version": "v1"
}
] | 2019-10-30 | [
[
"Mozeika",
"Alexander",
""
],
[
"Fraternali",
"Franca",
""
],
[
"Dunn-Walters",
"Deborah",
""
],
[
"Coolen",
"Anthony C. C.",
""
]
] | The adaptive immune system relies on diversity of its repertoire of receptors to protect the organism from a great variety of pathogens. Since the initial repertoire is the result of random gene rearrangement, binding of receptors is not limited to pathogen-associated antigens but also includes self antigens. There is a fine balance between having a diverse repertoire, protecting from many different pathogens, and yet reducing its self-reactivity as far as possible to avoid damage to self. In the ageing immune system this balance is altered, manifesting in reduced specificity of response to pathogens or vaccination on a background of higher self-reactivity. To answer the question whether age-related changes of repertoire in the diversity and self/non-self affinity balance of antibodies could explain the reduced efficacy of the humoral response in older people, we construct a minimal mathematical model of the humoral immune response. The principle of least damage allows us, for a given repertoire of antibodies, to resolve a tension between the necessity to neutralise target antigens as quickly as possible and the requirement to limit the damage to self antigens leading to an optimal dynamics of immune response. The model predicts slowing down of immune response for repertoires with reduced diversity and increased self-reactivity. |
2109.12358 | Karthik Raman | Sai Saranga Das M, Karthik Raman | Effect of Dormant Spare Capacity on the Attack Tolerance of Complex
Networks | 10 pages, 5 figures and 5 supplementary figures | null | null | null | q-bio.MN | http://creativecommons.org/licenses/by-nc-nd/4.0/ | The vulnerability of networks to targeted attacks is an issue of widespread
interest for policymakers, military strategists, network engineers and systems
biologists alike. Current approaches to circumvent targeted attacks seek to
increase the robustness of a network by changing the network structure in one
way or the other, leading to a higher size of the largest connected component
for a given fraction of nodes removed. In this work, we propose a strategy in
which there is a pre-existing, dormant spare capacity already built into the
network for an identified vulnerable node, such that the traffic of the
disrupted node can be diverted to another pre-existing node/set of nodes in the
network. Using our algorithm, the increase in robustness of canonical
scale-free networks was nearly 16-fold. We also analysed real-world networks
using our algorithm, where the mean increase in robustness was nearly
five-fold. To our knowledge, these numbers are significantly higher than those
hitherto reported in literature. The normalized cost of this spare capacity and
its effect on the operational parameters of the network have also been
discussed. Instances of spare capacity in biological networks, termed as
distributed robustness, are also presented.
| [
{
"created": "Sat, 25 Sep 2021 13:04:46 GMT",
"version": "v1"
}
] | 2021-09-28 | [
[
"M",
"Sai Saranga Das",
""
],
[
"Raman",
"Karthik",
""
]
] | The vulnerability of networks to targeted attacks is an issue of widespread interest for policymakers, military strategists, network engineers and systems biologists alike. Current approaches to circumvent targeted attacks seek to increase the robustness of a network by changing the network structure in one way or the other, leading to a higher size of the largest connected component for a given fraction of nodes removed. In this work, we propose a strategy in which there is a pre-existing, dormant spare capacity already built into the network for an identified vulnerable node, such that the traffic of the disrupted node can be diverted to another pre-existing node/set of nodes in the network. Using our algorithm, the increase in robustness of canonical scale-free networks was nearly 16-fold. We also analysed real-world networks using our algorithm, where the mean increase in robustness was nearly five-fold. To our knowledge, these numbers are significantly higher than those hitherto reported in literature. The normalized cost of this spare capacity and its effect on the operational parameters of the network have also been discussed. Instances of spare capacity in biological networks, termed as distributed robustness, are also presented. |
2001.06544 | Edward Tj\"ornhammar | Edward Tj\"ornhammar and Richard Tj\"ornhammar | Exploratory Projection to Latent Structure Models for use in
Transcriptomic Analysis | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by-sa/4.0/ | In this paper, we ask if it is possible to increase the interpretability in
multivariate analysis by aligning and projecting covariates onto comparative
subspaces. We demonstrate our method as well as the interpretative power of PLS
decomposed models and how robust interpretability can lead to quantitative
insights.
We discuss the statistical properties of the PLS weights, $p$-values
associated with specific axes, as well as their alignment properties.
The applicability of this approach within life science is also demonstrated
by applying it to three use cases of publically available datasets.
Further we present hierarchical pathway enrichment results stemming from
aligned $p$-values, which are compared with results derived from enrichment
analysis, as an external validation of our method.
We find that the method can uncover known results from genomics for all of
the studied use cases, i.e. microarray data from multiple sclerosis and
diabetes patients as well as RNA sequencing data from breast cancer patients.
| [
{
"created": "Fri, 17 Jan 2020 21:54:34 GMT",
"version": "v1"
},
{
"created": "Wed, 22 Apr 2020 11:35:11 GMT",
"version": "v2"
},
{
"created": "Wed, 17 Mar 2021 09:36:18 GMT",
"version": "v3"
}
] | 2021-03-18 | [
[
"Tjörnhammar",
"Edward",
""
],
[
"Tjörnhammar",
"Richard",
""
]
] | In this paper, we ask if it is possible to increase the interpretability in multivariate analysis by aligning and projecting covariates onto comparative subspaces. We demonstrate our method as well as the interpretative power of PLS decomposed models and how robust interpretability can lead to quantitative insights. We discuss the statistical properties of the PLS weights, $p$-values associated with specific axes, as well as their alignment properties. The applicability of this approach within life science is also demonstrated by applying it to three use cases of publically available datasets. Further we present hierarchical pathway enrichment results stemming from aligned $p$-values, which are compared with results derived from enrichment analysis, as an external validation of our method. We find that the method can uncover known results from genomics for all of the studied use cases, i.e. microarray data from multiple sclerosis and diabetes patients as well as RNA sequencing data from breast cancer patients. |
q-bio/0407029 | Gernot Schaller | Gernot Schaller and Michael Meyer-Hermann | Multicellular Tumor Spheroid in an off-lattice Voronoi/Delaunay cell
model | 38 pages, 10 figures, referees suggestions included | Physical Review E 71, p. 051910, 2005 | 10.1103/PhysRevE.71.051910 | null | q-bio.TO q-bio.CB | null | We study multicellular tumor spheroids by introducing a new three-dimensional
agent-based Voronoi/Delaunay hybrid model. In this model, the cell shape varies
from spherical in thin solution to convex polyhedral in dense tissues. The next
neighbors of the cells are provided by a weighted Delaunay triangulation with
in average linear computational complexity. The cellular interactions include
direct elastic forces and cell-cell as well as cell-matrix adhesion. The
spatiotemporal distribution of two nutrients -- oxygen and glucose -- is
described by reaction-diffusion equations. Viable cells consume the nutrients,
which are converted into biomass by increasing the cell size during G_1 phase.
We test hypotheses on the functional dependence of the uptake rates and use
the computer simulation to find suitable mechanisms for induction of necrosis.
This is done by comparing the outcome with experimental growth curves, where
the best fit leads to an unexpected ratio of oxygen and glucose uptake rates.
The model relies on physical quantities and can easily be generalized towards
tissues involving different cell types. In addition, it provides many features
that can be directly compared with the experiment.
| [
{
"created": "Thu, 22 Jul 2004 19:47:23 GMT",
"version": "v1"
},
{
"created": "Wed, 18 May 2005 13:09:08 GMT",
"version": "v2"
}
] | 2008-08-28 | [
[
"Schaller",
"Gernot",
""
],
[
"Meyer-Hermann",
"Michael",
""
]
] | We study multicellular tumor spheroids by introducing a new three-dimensional agent-based Voronoi/Delaunay hybrid model. In this model, the cell shape varies from spherical in thin solution to convex polyhedral in dense tissues. The next neighbors of the cells are provided by a weighted Delaunay triangulation with in average linear computational complexity. The cellular interactions include direct elastic forces and cell-cell as well as cell-matrix adhesion. The spatiotemporal distribution of two nutrients -- oxygen and glucose -- is described by reaction-diffusion equations. Viable cells consume the nutrients, which are converted into biomass by increasing the cell size during G_1 phase. We test hypotheses on the functional dependence of the uptake rates and use the computer simulation to find suitable mechanisms for induction of necrosis. This is done by comparing the outcome with experimental growth curves, where the best fit leads to an unexpected ratio of oxygen and glucose uptake rates. The model relies on physical quantities and can easily be generalized towards tissues involving different cell types. In addition, it provides many features that can be directly compared with the experiment. |
1505.03705 | Thomas Risler | Johannes Baumgart, Andrei S. Kozlov, Thomas Risler and A. James
Hudspeth | Damping Properties of the Hair Bundle | AIP Conference Proceeding | AIP Conf. Proc. 1403, 17 (2011) | 10.1063/1.3658053 | null | q-bio.SC physics.bio-ph physics.comp-ph physics.flu-dyn q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The viscous liquid surrounding a hair bundle dissipates energy and dampens
oscillations, which poses a fundamental physical challenge to the high
sensitivity and sharp frequency selectivity of hearing. To identify the
mechanical forces at play, we constructed a detailed finite-element model of
the hair bundle. Based on data from the hair bundle of the bullfrog's sacculus,
this model treats the interaction of stereocilia both with the surrounding
liquid and with the liquid in the narrow gaps between the individual
stereocilia. The investigation revealed that grouping stereocilia in a bundle
dramatically reduces the total drag. During hair-bundle deflections, the tip
links potentially induce drag by causing small but very dissipative relative
motions between stereocilia; this effect is offset by the horizontal top
connectors that restrain such relative movements at low frequencies. For higher
frequencies the coupling liquid is sufficient to assure that the hair bundle
moves as a unit with a low total drag. This work reveals the mechanical
characteristics originating from hair-bundle morphology and shows
quantitatively how a hair bundle is adapted for sensitive mechanotransduction.
| [
{
"created": "Thu, 14 May 2015 12:40:04 GMT",
"version": "v1"
}
] | 2015-05-15 | [
[
"Baumgart",
"Johannes",
""
],
[
"Kozlov",
"Andrei S.",
""
],
[
"Risler",
"Thomas",
""
],
[
"Hudspeth",
"A. James",
""
]
] | The viscous liquid surrounding a hair bundle dissipates energy and dampens oscillations, which poses a fundamental physical challenge to the high sensitivity and sharp frequency selectivity of hearing. To identify the mechanical forces at play, we constructed a detailed finite-element model of the hair bundle. Based on data from the hair bundle of the bullfrog's sacculus, this model treats the interaction of stereocilia both with the surrounding liquid and with the liquid in the narrow gaps between the individual stereocilia. The investigation revealed that grouping stereocilia in a bundle dramatically reduces the total drag. During hair-bundle deflections, the tip links potentially induce drag by causing small but very dissipative relative motions between stereocilia; this effect is offset by the horizontal top connectors that restrain such relative movements at low frequencies. For higher frequencies the coupling liquid is sufficient to assure that the hair bundle moves as a unit with a low total drag. This work reveals the mechanical characteristics originating from hair-bundle morphology and shows quantitatively how a hair bundle is adapted for sensitive mechanotransduction. |
1608.03616 | Rastko Ciric | Rastko Ciric, Daniel H. Wolf, Jonathan D. Power, David R. Roalf,
Graham Baum, Kosha Ruparel, Russell T. Shinohara, Mark A. Elliott, Simon B.
Eickhoff, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Danielle S.
Bassett, Theodore D. Satterthwaite | Benchmarking confound regression strategies for the control of motion
artifact in studies of functional connectivity | 16 pages, 5 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Since initial reports regarding the impact of motion artifact on measures of
functional connectivity, there has been a proliferation of confound regression
methods to limit its impact. However, recent techniques have not been
systematically evaluated using consistent outcome measures. Here, we provide a
systematic evaluation of 12 commonly used confound regression methods in 193
young adults. Specifically, we compare methods according to three benchmarks,
including the residual relationship between motion and connectivity,
distance-dependent effects of motion on connectivity, and additional degrees of
freedom lost in confound regression. Our results delineate two clear trade-offs
among methods. First, methods that include global signal regression minimize
the relationship between connectivity and motion, but unmask distance-dependent
artifact. In contrast, censoring methods mitigate both motion artifact and
distance-dependence, but use additional degrees of freedom. Taken together,
these results emphasize the heterogeneous efficacy of proposed methods, and
suggest that different confound regression strategies may be appropriate in the
context of specific scientific goals.
| [
{
"created": "Thu, 11 Aug 2016 20:48:18 GMT",
"version": "v1"
}
] | 2016-08-15 | [
[
"Ciric",
"Rastko",
""
],
[
"Wolf",
"Daniel H.",
""
],
[
"Power",
"Jonathan D.",
""
],
[
"Roalf",
"David R.",
""
],
[
"Baum",
"Graham",
""
],
[
"Ruparel",
"Kosha",
""
],
[
"Shinohara",
"Russell T.",
""
],
[
"Elliott",
"Mark A.",
""
],
[
"Eickhoff",
"Simon B.",
""
],
[
"Davatzikos",
"Christos",
""
],
[
"Gur",
"Ruben C.",
""
],
[
"Gur",
"Raquel E.",
""
],
[
"Bassett",
"Danielle S.",
""
],
[
"Satterthwaite",
"Theodore D.",
""
]
] | Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of confound regression methods to limit its impact. However, recent techniques have not been systematically evaluated using consistent outcome measures. Here, we provide a systematic evaluation of 12 commonly used confound regression methods in 193 young adults. Specifically, we compare methods according to three benchmarks, including the residual relationship between motion and connectivity, distance-dependent effects of motion on connectivity, and additional degrees of freedom lost in confound regression. Our results delineate two clear trade-offs among methods. First, methods that include global signal regression minimize the relationship between connectivity and motion, but unmask distance-dependent artifact. In contrast, censoring methods mitigate both motion artifact and distance-dependence, but use additional degrees of freedom. Taken together, these results emphasize the heterogeneous efficacy of proposed methods, and suggest that different confound regression strategies may be appropriate in the context of specific scientific goals. |
2010.08763 | Ariane Nunes-Alves | Ariane Nunes-Alves, Daria B. Kokh, Rebecca C. Wade | Ligand unbinding mechanisms and kinetics for T4 lysozyme mutants from
tauRAMD simulations | Changes in the format of the manuscript | null | 10.1016/j.crstbi.2021.04.001 | null | q-bio.QM q-bio.BM | http://creativecommons.org/licenses/by/4.0/ | The protein-ligand residence time, tau, influences molecular function in
biological networks and has been recognized as an important determinant of drug
efficacy. To predict tau, computational methods must overcome the problem that
tau often exceeds the timescales accessible to conventional molecular dynamics
(MD) simulation. Here, we apply the tau-Random Acceleration Molecular Dynamics
(tauRAMD) method to a set of kinetically characterized complexes of T4 lysozyme
mutants with engineered binding cavities. tauRAMD yields relative ligand
dissociation rates in good accordance with experiments and thereby allows a
comprehensive characterization of the ligand egress routes and determinants of
tau. Although ligand dissociation by multiple egress routes is observed, we
find that egress via the predominant route determines the value of tau. We also
find that the presence of metastable states along egress pathways slows down
protein-ligand dissociation. These physical insights could be exploited in the
rational optimization of the kinetic properties of drug candidates.
| [
{
"created": "Sat, 17 Oct 2020 10:52:42 GMT",
"version": "v1"
},
{
"created": "Thu, 12 Nov 2020 14:25:12 GMT",
"version": "v2"
},
{
"created": "Thu, 10 Dec 2020 09:56:59 GMT",
"version": "v3"
}
] | 2021-05-05 | [
[
"Nunes-Alves",
"Ariane",
""
],
[
"Kokh",
"Daria B.",
""
],
[
"Wade",
"Rebecca C.",
""
]
] | The protein-ligand residence time, tau, influences molecular function in biological networks and has been recognized as an important determinant of drug efficacy. To predict tau, computational methods must overcome the problem that tau often exceeds the timescales accessible to conventional molecular dynamics (MD) simulation. Here, we apply the tau-Random Acceleration Molecular Dynamics (tauRAMD) method to a set of kinetically characterized complexes of T4 lysozyme mutants with engineered binding cavities. tauRAMD yields relative ligand dissociation rates in good accordance with experiments and thereby allows a comprehensive characterization of the ligand egress routes and determinants of tau. Although ligand dissociation by multiple egress routes is observed, we find that egress via the predominant route determines the value of tau. We also find that the presence of metastable states along egress pathways slows down protein-ligand dissociation. These physical insights could be exploited in the rational optimization of the kinetic properties of drug candidates. |
1605.07294 | Michael Hinczewski | Michael Hinczewski, Changbong Hyeon, D. Thirumalai | Directly measuring single molecule heterogeneity using force
spectroscopy | Main text: 13 pages, 6 figures; SI: 9 pages, 6 figures | null | 10.1073/pnas.1518389113 | null | q-bio.BM cond-mat.soft physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | One of the most intriguing results of single molecule experiments on proteins
and nucleic acids is the discovery of functional heterogeneity: the observation
that complex cellular machines exhibit multiple, biologically active
conformations. The structural differences between these conformations may be
subtle, but each distinct state can be remarkably long-lived, with random
interconversions between states occurring only at macroscopic timescales,
fractions of a second or longer. Though we now have proof of functional
heterogeneity in a handful of systems---enzymes, motors, adhesion
complexes---identifying and measuring it remains a formidable challenge. Here
we show that evidence of this phenomenon is more widespread than previously
known, encoded in data collected from some of the most well-established single
molecule techniques: AFM or optical tweezer pulling experiments. We present a
theoretical procedure for analyzing distributions of rupture/unfolding forces
recorded at different pulling speeds. This results in a single parameter,
quantifying the degree of heterogeneity, and also leads to bounds on the
equilibration and conformational interconversion timescales. Surveying ten
published datasets, we find heterogeneity in five of them, all with
interconversion rates slower than 10 s$^{-1}$. Moreover, we identify two
systems where additional data at realizable pulling velocities is likely to
find a theoretically predicted, but so far unobserved cross-over regime between
heterogeneous and non-heterogeneous behavior. The significance of this regime
is that it will allow far more precise estimates of the slow conformational
switching times, one of the least understood aspects of functional
heterogeneity.
| [
{
"created": "Tue, 24 May 2016 05:37:15 GMT",
"version": "v1"
}
] | 2022-10-12 | [
[
"Hinczewski",
"Michael",
""
],
[
"Hyeon",
"Changbong",
""
],
[
"Thirumalai",
"D.",
""
]
] | One of the most intriguing results of single molecule experiments on proteins and nucleic acids is the discovery of functional heterogeneity: the observation that complex cellular machines exhibit multiple, biologically active conformations. The structural differences between these conformations may be subtle, but each distinct state can be remarkably long-lived, with random interconversions between states occurring only at macroscopic timescales, fractions of a second or longer. Though we now have proof of functional heterogeneity in a handful of systems---enzymes, motors, adhesion complexes---identifying and measuring it remains a formidable challenge. Here we show that evidence of this phenomenon is more widespread than previously known, encoded in data collected from some of the most well-established single molecule techniques: AFM or optical tweezer pulling experiments. We present a theoretical procedure for analyzing distributions of rupture/unfolding forces recorded at different pulling speeds. This results in a single parameter, quantifying the degree of heterogeneity, and also leads to bounds on the equilibration and conformational interconversion timescales. Surveying ten published datasets, we find heterogeneity in five of them, all with interconversion rates slower than 10 s$^{-1}$. Moreover, we identify two systems where additional data at realizable pulling velocities is likely to find a theoretically predicted, but so far unobserved cross-over regime between heterogeneous and non-heterogeneous behavior. The significance of this regime is that it will allow far more precise estimates of the slow conformational switching times, one of the least understood aspects of functional heterogeneity. |
2404.07528 | Rosalia Ferraro | Rosalia Ferraro, Jasmin Di Franco, Sergio Caserta, Stefano Guido | The morphology of cell spheroids in simple shear flow | 9 pages, 4 figures | null | null | null | q-bio.CB | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Cell spheroids are a widely used model to investigate cell-cell and
cell-matrix interactions in a 3D microenvironment in vitro. Most research on
cell spheroids has been focused on their response to various stimuli under
static conditions. Recently, the effect of flow on cell spheroids has been
investigated in the context of tumor invasion in interstitial space. In
particular, microfluidic perfusion of cell spheroids embedded in a collagen
matrix has been shown to modulate cell-cell adhesion and to represent a
possible mechanism promoting tumor invasion by interstitial flow. However,
studies on the effects of well-defined flow fields on cell spheroids are
lacking in the literature. Here, we apply simple shear flow to cell spheroids
in a parallel plate apparatus while observing their morphology by optical
microscopy. By using image analysis techniques, we show that cell spheroids
rotate under flow as rigid particles. As time goes on, cells from the outer
layer detach from the sheared cell spheroids and are carried away by the flow.
Hence, the size of cell spheroids declines with time at a rate increasing with
the external shear stress, which can be used to estimate cell-cell adhesion.
The technique proposed in this work allows one to correlate flow-induced
effects with microscopy imaging of cell spheroids in a well-established shear
flow field, thus providing a method to obtain quantitative results which are
relevant in the general field of mechanobiology.
| [
{
"created": "Thu, 11 Apr 2024 07:43:04 GMT",
"version": "v1"
}
] | 2024-04-12 | [
[
"Ferraro",
"Rosalia",
""
],
[
"Di Franco",
"Jasmin",
""
],
[
"Caserta",
"Sergio",
""
],
[
"Guido",
"Stefano",
""
]
] | Cell spheroids are a widely used model to investigate cell-cell and cell-matrix interactions in a 3D microenvironment in vitro. Most research on cell spheroids has been focused on their response to various stimuli under static conditions. Recently, the effect of flow on cell spheroids has been investigated in the context of tumor invasion in interstitial space. In particular, microfluidic perfusion of cell spheroids embedded in a collagen matrix has been shown to modulate cell-cell adhesion and to represent a possible mechanism promoting tumor invasion by interstitial flow. However, studies on the effects of well-defined flow fields on cell spheroids are lacking in the literature. Here, we apply simple shear flow to cell spheroids in a parallel plate apparatus while observing their morphology by optical microscopy. By using image analysis techniques, we show that cell spheroids rotate under flow as rigid particles. As time goes on, cells from the outer layer detach from the sheared cell spheroids and are carried away by the flow. Hence, the size of cell spheroids declines with time at a rate increasing with the external shear stress, which can be used to estimate cell-cell adhesion. The technique proposed in this work allows one to correlate flow-induced effects with microscopy imaging of cell spheroids in a well-established shear flow field, thus providing a method to obtain quantitative results which are relevant in the general field of mechanobiology. |
2207.01734 | Praphulla Bhawsar | Praphulla MS Bhawsar, Erich Bremer, M\'aire A Duggan, Stephen Chanock,
Montserrat Garcia-Closas, Joel Saltz, Jonas S Almeida | ImageBox3: No-Server Tile Serving to Traverse Whole Slide Images on the
Web | 9 pages, 3 figures | null | null | null | q-bio.QM cs.SE eess.IV | http://creativecommons.org/licenses/by/4.0/ | Whole slide imaging (WSI) has become the primary modality for digital
pathology data. However, due to the size and high-resolution nature of these
images, they are generally only accessed in smaller sections or tiles via
specialized platforms, most of which require extensive setup and/or costly
infrastructure. These platforms typically also need a copy of the images to be
locally available to them, potentially causing issues with data governance and
provenance. To address these concerns, we developed ImageBox3, an in-browser
tiling mechanism to enable zero-footprint traversal of remote WSI data. All
computation is performed client-side without compromising user governance,
operating public and private images alike as long as the storage service
supports HTTP range requests (standard in Cloud storage and most web servers).
ImageBox3 thus removes significant hurdles to WSI operation and effective
collaboration, allowing for the sort of democratized analytical tools needed to
establish participative, FAIR digital pathology data commons.
Availability:
code - https://github.com/episphere/imagebox3;
fig1 (live) - https://episphere.github.io/imagebox3/demo/scriptTag ;
fig2 (live) - https://episphere.github.io/imagebox3/demo/serviceWorker ;
fig 3 (live) - https://observablehq.com/@prafulb/imagebox3-in-observable .
| [
{
"created": "Mon, 4 Jul 2022 21:58:21 GMT",
"version": "v1"
},
{
"created": "Wed, 6 Jul 2022 00:39:03 GMT",
"version": "v2"
}
] | 2022-07-07 | [
[
"Bhawsar",
"Praphulla MS",
""
],
[
"Bremer",
"Erich",
""
],
[
"Duggan",
"Máire A",
""
],
[
"Chanock",
"Stephen",
""
],
[
"Garcia-Closas",
"Montserrat",
""
],
[
"Saltz",
"Joel",
""
],
[
"Almeida",
"Jonas S",
""
]
] | Whole slide imaging (WSI) has become the primary modality for digital pathology data. However, due to the size and high-resolution nature of these images, they are generally only accessed in smaller sections or tiles via specialized platforms, most of which require extensive setup and/or costly infrastructure. These platforms typically also need a copy of the images to be locally available to them, potentially causing issues with data governance and provenance. To address these concerns, we developed ImageBox3, an in-browser tiling mechanism to enable zero-footprint traversal of remote WSI data. All computation is performed client-side without compromising user governance, operating public and private images alike as long as the storage service supports HTTP range requests (standard in Cloud storage and most web servers). ImageBox3 thus removes significant hurdles to WSI operation and effective collaboration, allowing for the sort of democratized analytical tools needed to establish participative, FAIR digital pathology data commons. Availability: code - https://github.com/episphere/imagebox3; fig1 (live) - https://episphere.github.io/imagebox3/demo/scriptTag ; fig2 (live) - https://episphere.github.io/imagebox3/demo/serviceWorker ; fig 3 (live) - https://observablehq.com/@prafulb/imagebox3-in-observable . |
2207.07965 | Qihang Yao | Qihang Yao, Manoj Chandrasekaran, Constantine Dovrolis | Root-Cause Analysis of Activation Cascade Differences in Brain Networks | 14 pages, 4 figures, submitted to Brain Informatics 2022 | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Diffusion MRI imaging and tractography algorithms have enabled the mapping of
the macro-scale connectome of the entire brain. At the functional level,
probably the simplest way to study the dynamics of macro-scale brain activity
is to compute the "activation cascade" that follows the artificial stimulation
of a source region. Such cascades can be computed using the Linear Threshold
model on a weighted graph representation of the connectome. The question we
focus on is: if we are given such activation cascades for two groups, say A and
B (e.g. Controls versus a mental disorder), what is the smallest set of brain
connectivity (graph edge weight) changes that are sufficient to explain the
observed differences in the activation cascades between the two groups? We have
developed and computationally validated an efficient algorithm, TRACED, to
solve the previous problem. We argue that this approach to compare the
connectomes of two groups, based on activation cascades, is more insightful
than simply identifying "static" network differences (such as edges with large
weight or centrality differences). We have also applied the proposed method in
the comparison between a Major Depressive Disorder (MDD) group versus healthy
controls and briefly report the resulting set of connections that cause most of
the observed cascade differences.
| [
{
"created": "Sat, 16 Jul 2022 15:07:30 GMT",
"version": "v1"
}
] | 2022-07-19 | [
[
"Yao",
"Qihang",
""
],
[
"Chandrasekaran",
"Manoj",
""
],
[
"Dovrolis",
"Constantine",
""
]
] | Diffusion MRI imaging and tractography algorithms have enabled the mapping of the macro-scale connectome of the entire brain. At the functional level, probably the simplest way to study the dynamics of macro-scale brain activity is to compute the "activation cascade" that follows the artificial stimulation of a source region. Such cascades can be computed using the Linear Threshold model on a weighted graph representation of the connectome. The question we focus on is: if we are given such activation cascades for two groups, say A and B (e.g. Controls versus a mental disorder), what is the smallest set of brain connectivity (graph edge weight) changes that are sufficient to explain the observed differences in the activation cascades between the two groups? We have developed and computationally validated an efficient algorithm, TRACED, to solve the previous problem. We argue that this approach to compare the connectomes of two groups, based on activation cascades, is more insightful than simply identifying "static" network differences (such as edges with large weight or centrality differences). We have also applied the proposed method in the comparison between a Major Depressive Disorder (MDD) group versus healthy controls and briefly report the resulting set of connections that cause most of the observed cascade differences. |
0708.0111 | Karen Alim | Karen Alim and Erwin Frey | Fluctuating semiflexible polymer ribbon constrained to a ring | 6 pages, 3 figures, Version as published in Eur. Phys. J. E | Eur. Phys. J. E 24, 185 (2007) | 10.1140/epje/i2007-10228-x | LMU-ASC 52/07 | q-bio.BM cond-mat.soft | null | Twist stiffness and an asymmetric bending stiffness of a polymer or a polymer
bundle is captured by the elastic ribbon model. We investigate the effects a
ring geometry induces to a thermally fluctuating ribbon, finding bend-bend
coupling in addition to twist-bend coupling. Furthermore, due to the geometric
constraint the polymer's effective bending stiffness increases. A new parameter
for experimental investigations of polymer bundles is proposed: the mean square
diameter of a ribbonlike ring, which is determined analytically in the
semiflexible limit. Monte Carlo simulations are performed which affirm the
model's prediction up to high flexibility.
| [
{
"created": "Wed, 1 Aug 2007 10:17:15 GMT",
"version": "v1"
},
{
"created": "Thu, 7 Feb 2008 12:53:56 GMT",
"version": "v2"
}
] | 2008-02-07 | [
[
"Alim",
"Karen",
""
],
[
"Frey",
"Erwin",
""
]
] | Twist stiffness and an asymmetric bending stiffness of a polymer or a polymer bundle is captured by the elastic ribbon model. We investigate the effects a ring geometry induces to a thermally fluctuating ribbon, finding bend-bend coupling in addition to twist-bend coupling. Furthermore, due to the geometric constraint the polymer's effective bending stiffness increases. A new parameter for experimental investigations of polymer bundles is proposed: the mean square diameter of a ribbonlike ring, which is determined analytically in the semiflexible limit. Monte Carlo simulations are performed which affirm the model's prediction up to high flexibility. |
1608.00930 | Eric Werner | Eric Werner | Stem Cells: The Good, the Bad and the Ugly | 8 pages, explains why cancer stem cell networks and normal stem cell
networks are mostly equivalent but have very different effects | null | null | null | q-bio.TO q-bio.MN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cancer stem cells are controlled by developmental networks that are often
topologically indistinguishable from normal, healthy stem cells. The question
is why cancer stem cells can be both phenotypically distinct and have
morphological effects so different from normal stem cells. The difference
between cancer stem cells and normal stem cells lies not in differences their
network architecture, but rather in the spatial-temporal locality of their
activation in the genome and the resulting expression in the body. The
metastatic potential cancer stem cells is not based primarily on their network
divergence from normal stem cells, but on non-network based genetic changes
that enable the evolution of gene-based phenotypic properties of the cell that
permit its escape and travel to other parts of the body. Stem cell network
theory allows the precise prediction of stem cell behavioral dynamics and a
mathematical description of stem cell proliferation for both normal and cancer
stem cells. It indicates that the best therapeutic approach is to tackle the
highest order stem cells first, otherwise spontaneous remission of so called
cured cancers will always be a danger. Stem cell networks point to a pathway to
new methods to diagnose and cure not only stem cell cancers but cancers
generally.
| [
{
"created": "Mon, 1 Aug 2016 15:20:03 GMT",
"version": "v1"
}
] | 2016-08-03 | [
[
"Werner",
"Eric",
""
]
] | Cancer stem cells are controlled by developmental networks that are often topologically indistinguishable from normal, healthy stem cells. The question is why cancer stem cells can be both phenotypically distinct and have morphological effects so different from normal stem cells. The difference between cancer stem cells and normal stem cells lies not in differences their network architecture, but rather in the spatial-temporal locality of their activation in the genome and the resulting expression in the body. The metastatic potential cancer stem cells is not based primarily on their network divergence from normal stem cells, but on non-network based genetic changes that enable the evolution of gene-based phenotypic properties of the cell that permit its escape and travel to other parts of the body. Stem cell network theory allows the precise prediction of stem cell behavioral dynamics and a mathematical description of stem cell proliferation for both normal and cancer stem cells. It indicates that the best therapeutic approach is to tackle the highest order stem cells first, otherwise spontaneous remission of so called cured cancers will always be a danger. Stem cell networks point to a pathway to new methods to diagnose and cure not only stem cell cancers but cancers generally. |
2007.02206 | Shreyas Bhaban | Shreyas Bhaban, Rachit Srivastava, James Melbourne, Saurav Talukdar
and Murti V. Salapaka | Hindering loads prompt clustered configurations that enhance stability
during cargo transport by multiple Kinesin-1 | 13 pages, 7 figures | null | null | null | q-bio.SC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Transport of intracellular cargo is often mediated by teams of molecular
motors that function in a chaotic environment under varying conditions. We show
that the motors have unique steady state behavior which enables transport
modalities that are robust. Under reduced ATP concentrations, multi-motor
configurations are preferred over single motors. Higher load force drives
motors to cluster, but very high loads compel them to separate in a manner that
promotes immediate cargo movement once the load subsides. These inferences,
backed by analytical guarantees, provide unique insights into the coordination
strategies adopted by molecular motors to transport intracellular cargo.
| [
{
"created": "Sat, 4 Jul 2020 23:17:30 GMT",
"version": "v1"
},
{
"created": "Sat, 16 Sep 2023 11:46:40 GMT",
"version": "v2"
}
] | 2023-09-19 | [
[
"Bhaban",
"Shreyas",
""
],
[
"Srivastava",
"Rachit",
""
],
[
"Melbourne",
"James",
""
],
[
"Talukdar",
"Saurav",
""
],
[
"Salapaka",
"Murti V.",
""
]
] | Transport of intracellular cargo is often mediated by teams of molecular motors that function in a chaotic environment under varying conditions. We show that the motors have unique steady state behavior which enables transport modalities that are robust. Under reduced ATP concentrations, multi-motor configurations are preferred over single motors. Higher load force drives motors to cluster, but very high loads compel them to separate in a manner that promotes immediate cargo movement once the load subsides. These inferences, backed by analytical guarantees, provide unique insights into the coordination strategies adopted by molecular motors to transport intracellular cargo. |
0811.3502 | Noa Sela | Britta Mersch, Noa Sela, Gil Ast, Sandor Suhai, Agnes Hotz- Wagenblatt | SERpredict: Detection of tissue- or tumor-specific isoforms generated
through exonization of transposable elements | null | BMC Genetics 2007 8:78 | 10.1186/1471-2156-8-78 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Background: Transposed elements (TEs) are known to affect transcriptomes,
because either new exons are generated from intronic transposed elements (this
is called exonization), or the element inserts into the exon, leading to a new
transcript. Several examples in the literature show that isoforms generated by
an exonization are specific to a certain tissue (for example the heart muscle)
or inflict a disease. Thus, exonizations can have negative effects for the
transcriptome of an organism. Results: As we aimed at detecting other tissue-
or tumor-specific isoforms in human and mouse genomes which were generated
through exonization of a transposed element, we designed the automated analysis
pipeline SERpredict (SER = Specific Exonized Retroelement) making use of
Bayesian Statistics. With this pipeline, we found several genes in which a
transposed element formed a tissue- or tumor-specific isoform. Conclusion: Our
results show that SERpredict produces relevant results, demonstrating the
importance of transposed elements in shaping both the human and the mouse
transcriptomes. The effect of transposed elements on the human transcriptome is
several times higher than the effect on the mouse transcriptome, due to the
contribution of the primate-specific Alu elements
| [
{
"created": "Fri, 21 Nov 2008 10:40:38 GMT",
"version": "v1"
}
] | 2008-11-24 | [
[
"Mersch",
"Britta",
""
],
[
"Sela",
"Noa",
""
],
[
"Ast",
"Gil",
""
],
[
"Suhai",
"Sandor",
""
],
[
"Wagenblatt",
"Agnes Hotz-",
""
]
] | Background: Transposed elements (TEs) are known to affect transcriptomes, because either new exons are generated from intronic transposed elements (this is called exonization), or the element inserts into the exon, leading to a new transcript. Several examples in the literature show that isoforms generated by an exonization are specific to a certain tissue (for example the heart muscle) or inflict a disease. Thus, exonizations can have negative effects for the transcriptome of an organism. Results: As we aimed at detecting other tissue- or tumor-specific isoforms in human and mouse genomes which were generated through exonization of a transposed element, we designed the automated analysis pipeline SERpredict (SER = Specific Exonized Retroelement) making use of Bayesian Statistics. With this pipeline, we found several genes in which a transposed element formed a tissue- or tumor-specific isoform. Conclusion: Our results show that SERpredict produces relevant results, demonstrating the importance of transposed elements in shaping both the human and the mouse transcriptomes. The effect of transposed elements on the human transcriptome is several times higher than the effect on the mouse transcriptome, due to the contribution of the primate-specific Alu elements |
2204.04733 | Maria Kalweit | Gabriel Kalweit, Maria Kalweit, Mansour Alyahyay, Zoe Jaeckel, Florian
Steenbergen, Stefanie Hardung, Thomas Brox, Ilka Diester and Joschka
Boedecker | NeuRL: Closed-form Inverse Reinforcement Learning for Neural Decoding | null | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Current neural decoding methods typically aim at explaining behavior based on
neural activity via supervised learning. However, since generally there is a
strong connection between learning of subjects and their expectations on
long-term rewards, we propose NeuRL, an inverse reinforcement learning approach
that (1) extracts an intrinsic reward function from collected trajectories of a
subject in closed form, (2) maps neural signals to this intrinsic reward to
account for long-term dependencies in the behavior and (3) predicts the
simulated behavior for unseen neural signals by extracting Q-values and the
corresponding Boltzmann policy based on the intrinsic reward values for these
unseen neural signals. We show that NeuRL leads to better generalization and
improved decoding performance compared to supervised approaches. We study the
behavior of rats in a response-preparation task and evaluate the performance of
NeuRL within simulated inhibition and per-trial behavior prediction. By
assigning clear functional roles to defined neuronal populations our approach
offers a new interpretation tool for complex neuronal data with testable
predictions. In per-trial behavior prediction, our approach furthermore
improves accuracy by up to 15% compared to traditional methods.
| [
{
"created": "Sun, 10 Apr 2022 17:34:10 GMT",
"version": "v1"
}
] | 2022-04-12 | [
[
"Kalweit",
"Gabriel",
""
],
[
"Kalweit",
"Maria",
""
],
[
"Alyahyay",
"Mansour",
""
],
[
"Jaeckel",
"Zoe",
""
],
[
"Steenbergen",
"Florian",
""
],
[
"Hardung",
"Stefanie",
""
],
[
"Brox",
"Thomas",
""
],
[
"Diester",
"Ilka",
""
],
[
"Boedecker",
"Joschka",
""
]
] | Current neural decoding methods typically aim at explaining behavior based on neural activity via supervised learning. However, since generally there is a strong connection between learning of subjects and their expectations on long-term rewards, we propose NeuRL, an inverse reinforcement learning approach that (1) extracts an intrinsic reward function from collected trajectories of a subject in closed form, (2) maps neural signals to this intrinsic reward to account for long-term dependencies in the behavior and (3) predicts the simulated behavior for unseen neural signals by extracting Q-values and the corresponding Boltzmann policy based on the intrinsic reward values for these unseen neural signals. We show that NeuRL leads to better generalization and improved decoding performance compared to supervised approaches. We study the behavior of rats in a response-preparation task and evaluate the performance of NeuRL within simulated inhibition and per-trial behavior prediction. By assigning clear functional roles to defined neuronal populations our approach offers a new interpretation tool for complex neuronal data with testable predictions. In per-trial behavior prediction, our approach furthermore improves accuracy by up to 15% compared to traditional methods. |
1708.05765 | Gary Wilk | Gary Wilk, Rosemary Braun | Integrative analysis reveals disrupted pathways regulated by microRNAs
in cancer | null | Nucleic Acids Res. 2017 | 10.1093/nar/gkx1250 | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | MicroRNAs (miRNAs) are small endogenous regulatory molecules that modulate
gene expression post-transcriptionally. Although differential expression of
miRNAs have been implicated in many diseases (including cancers), the
underlying mechanisms of action remain unclear. Because each miRNA can target
multiple genes, miRNAs may potentially have functional implications for the
overall behavior of entire pathways. Here we investigate the functional
consequences of miRNA dysregulation through an integrative analysis of miRNA
and mRNA expression data using a novel approach that incorporates pathway
information a priori. By searching for miRNA-pathway associations that differ
between healthy and tumor tissue, we identify specific relationships at the
systems-level which are disrupted in cancer. Our approach is motivated by the
hypothesis that if a miRNA and pathway are associated, then the expression of
the miRNA and the collective behavior of the genes in a pathway will be
correlated. As such, we first obtain an expression-based summary of pathway
activity using Isomap, a dimension reduction method which can articulate
nonlinear structure in high-dimensional data. We then search for miRNAs that
exhibit differential correlations with the pathway summary between phenotypes
as a means of finding aberrant miRNA-pathway coregulation in tumors. We apply
our method to cancer data using gene and miRNA expression datasets from The
Cancer Genome Atlas (TCGA) and compare ${\sim}10^5$ miRNA-pathway relationships
between healthy and tumor samples from four tissues (breast, prostate, lung,
and liver). Many of the flagged pairs we identify have a biological basis for
disruption in cancer.
| [
{
"created": "Fri, 18 Aug 2017 21:29:59 GMT",
"version": "v1"
}
] | 2018-01-09 | [
[
"Wilk",
"Gary",
""
],
[
"Braun",
"Rosemary",
""
]
] | MicroRNAs (miRNAs) are small endogenous regulatory molecules that modulate gene expression post-transcriptionally. Although differential expression of miRNAs have been implicated in many diseases (including cancers), the underlying mechanisms of action remain unclear. Because each miRNA can target multiple genes, miRNAs may potentially have functional implications for the overall behavior of entire pathways. Here we investigate the functional consequences of miRNA dysregulation through an integrative analysis of miRNA and mRNA expression data using a novel approach that incorporates pathway information a priori. By searching for miRNA-pathway associations that differ between healthy and tumor tissue, we identify specific relationships at the systems-level which are disrupted in cancer. Our approach is motivated by the hypothesis that if a miRNA and pathway are associated, then the expression of the miRNA and the collective behavior of the genes in a pathway will be correlated. As such, we first obtain an expression-based summary of pathway activity using Isomap, a dimension reduction method which can articulate nonlinear structure in high-dimensional data. We then search for miRNAs that exhibit differential correlations with the pathway summary between phenotypes as a means of finding aberrant miRNA-pathway coregulation in tumors. We apply our method to cancer data using gene and miRNA expression datasets from The Cancer Genome Atlas (TCGA) and compare ${\sim}10^5$ miRNA-pathway relationships between healthy and tumor samples from four tissues (breast, prostate, lung, and liver). Many of the flagged pairs we identify have a biological basis for disruption in cancer. |
1803.06873 | Laura Orellana | Laura Orellana, Johan Gustavsson, Cathrine Bergh, Ozge Yoluk, and Erik
Lindahl | The eBDIMS path-sampling server: generation, classification and
interactive visualization of protein ensembles and transition pathways in
2D-motion space | null | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The recent rise of cryo-EM and X-ray high-throughput techniques is providing
a wealth of new structures trapped in different conformations. Understanding
how proteins transition between different conformers, and how they relate to
each other in terms of function is not straightforward, and highly depends on
the choice of the right set of degrees of freedom. Here we present eBDIMS
server, an online tool and software for automatic classification of structural
ensembles and reconstruction of transition pathways using coarse-grained (CG)
simulations. The server generates CG-pathways between two protein conformations
along with a representation in a simplified 2D-motion landscape based on the
Principal Components (PCs) from experimental structures. For a conformationally
rich ensemble, the PCs provide powerful reaction coordinates for automatic
structure classification, detection of on-pathway intermediates and validation
of in silico pathways. When the number of available structures is low or
sampling is limited, Normal Modes (NMs) provide alternative motion axes for
trajectory analysis. The path-generation eBDIMS method is available at a
user-friendly website: https://login.biophysics.kth.se/eBDIMS/ or as standalone
software. The server incorporates a powerful interactive graphical interface
for simultaneous visualization of transition pathways in 2D-motion space and
3D-molecular graphics, which greatly facilitates the exploration of the
relationships between different conformations.
| [
{
"created": "Mon, 19 Mar 2018 11:30:03 GMT",
"version": "v1"
}
] | 2018-03-20 | [
[
"Orellana",
"Laura",
""
],
[
"Gustavsson",
"Johan",
""
],
[
"Bergh",
"Cathrine",
""
],
[
"Yoluk",
"Ozge",
""
],
[
"Lindahl",
"Erik",
""
]
] | The recent rise of cryo-EM and X-ray high-throughput techniques is providing a wealth of new structures trapped in different conformations. Understanding how proteins transition between different conformers, and how they relate to each other in terms of function is not straightforward, and highly depends on the choice of the right set of degrees of freedom. Here we present eBDIMS server, an online tool and software for automatic classification of structural ensembles and reconstruction of transition pathways using coarse-grained (CG) simulations. The server generates CG-pathways between two protein conformations along with a representation in a simplified 2D-motion landscape based on the Principal Components (PCs) from experimental structures. For a conformationally rich ensemble, the PCs provide powerful reaction coordinates for automatic structure classification, detection of on-pathway intermediates and validation of in silico pathways. When the number of available structures is low or sampling is limited, Normal Modes (NMs) provide alternative motion axes for trajectory analysis. The path-generation eBDIMS method is available at a user-friendly website: https://login.biophysics.kth.se/eBDIMS/ or as standalone software. The server incorporates a powerful interactive graphical interface for simultaneous visualization of transition pathways in 2D-motion space and 3D-molecular graphics, which greatly facilitates the exploration of the relationships between different conformations. |
1903.09280 | Caroline Holmes | Caroline M. Holmes and Ilya Nemenman | Estimation of mutual information for real-valued data with error bars
and controlled bias | 10 pages, 8 figures | Phys. Rev. E 100, 022404 (2019) | 10.1103/PhysRevE.100.022404 | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Estimation of mutual information between (multidimensional) real-valued
variables is used in analysis of complex systems, biological systems, and
recently also quantum systems. This estimation is a hard problem, and
universally good estimators provably do not exist. Kraskov et al. (PRE, 2004)
introduced a successful mutual information estimation approach based on the
statistics of distances between neighboring data points, which empirically
works for a wide class of underlying probability distributions. Here we improve
this estimator by (i) expanding its range of applicability, and by providing
(ii) a self-consistent way of verifying the absence of bias, (iii) a method for
estimation of its variance, and (iv) a criterion for choosing the values of the
free parameter of the estimator. We demonstrate the performance of our
estimator on synthetic data sets, as well as on neurophysiological and systems
biology data sets.
| [
{
"created": "Fri, 22 Mar 2019 00:39:02 GMT",
"version": "v1"
}
] | 2019-08-14 | [
[
"Holmes",
"Caroline M.",
""
],
[
"Nemenman",
"Ilya",
""
]
] | Estimation of mutual information between (multidimensional) real-valued variables is used in analysis of complex systems, biological systems, and recently also quantum systems. This estimation is a hard problem, and universally good estimators provably do not exist. Kraskov et al. (PRE, 2004) introduced a successful mutual information estimation approach based on the statistics of distances between neighboring data points, which empirically works for a wide class of underlying probability distributions. Here we improve this estimator by (i) expanding its range of applicability, and by providing (ii) a self-consistent way of verifying the absence of bias, (iii) a method for estimation of its variance, and (iv) a criterion for choosing the values of the free parameter of the estimator. We demonstrate the performance of our estimator on synthetic data sets, as well as on neurophysiological and systems biology data sets. |
1503.00831 | Mike Steel Prof. | Mike Steel | Capturing a phylogenetic tree when the number of character states varies
with the number of leaves | 3 pages, 0 figures | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | We show that for any two values $\alpha, \beta >0 $ for which
$\alpha+\beta>1$ then there is a value $N$ so that for all $n \geq N$ the
following holds. For any binary phylogenetic tree $T$ on $n$ leaves there is a
set of $\lfloor n^\alpha \rfloor$ characters that capture $T$, and for which
each character takes at most $\lfloor n^\beta \rfloor$ distinct states. Here
`capture' means that $T$ is the unique perfect phylogeny for these characters.
Our short proof of this combinatorial result is based on the probabilistic
method.
| [
{
"created": "Tue, 3 Mar 2015 05:49:54 GMT",
"version": "v1"
},
{
"created": "Wed, 26 Aug 2015 19:52:08 GMT",
"version": "v2"
}
] | 2015-08-27 | [
[
"Steel",
"Mike",
""
]
] | We show that for any two values $\alpha, \beta >0 $ for which $\alpha+\beta>1$ then there is a value $N$ so that for all $n \geq N$ the following holds. For any binary phylogenetic tree $T$ on $n$ leaves there is a set of $\lfloor n^\alpha \rfloor$ characters that capture $T$, and for which each character takes at most $\lfloor n^\beta \rfloor$ distinct states. Here `capture' means that $T$ is the unique perfect phylogeny for these characters. Our short proof of this combinatorial result is based on the probabilistic method. |
1802.10224 | Rafael D'Andrea | Rafael D'Andrea, Annette Ostling, James P O'Dwyer | Translucent windows: How uncertainty in competitive interactions impacts
detection of community pattern | Main text: 18 pages, 6 figures. Appendices: A-G, 6 supplementary
figures. This is the peer reviewed version of the article of the same title
which has been accepted for publication at Ecology Letters. This article may
be used for non-commercial purposes in accordance with Wiley Terms and
Conditions for Self-Archiving | null | 10.1111/ele.12946 | null | q-bio.PE | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Trait variation and similarity among coexisting species can provide a window
into the mechanisms that maintain their coexistence. Recent theoretical
explorations suggest that competitive interactions will lead to groups, or
clusters, of species with similar traits. However, theoretical predictions
typically assume complete knowledge of the map between competition and measured
traits. These assumptions limit the plausible application of these patterns for
inferring competitive interactions in nature. Here we relax these restrictions
and find that the clustering pattern is robust to contributions of unknown or
unobserved niche axes. However, it may not be visible unless measured traits
are close proxies for niche strategies. We conclude that patterns along single
niche axes may reveal properties of interspecific competition in nature, but
detecting these patterns requires natural history expertise firmly tying traits
to niches.
| [
{
"created": "Wed, 28 Feb 2018 01:16:38 GMT",
"version": "v1"
}
] | 2018-03-01 | [
[
"D'Andrea",
"Rafael",
""
],
[
"Ostling",
"Annette",
""
],
[
"O'Dwyer",
"James P",
""
]
] | Trait variation and similarity among coexisting species can provide a window into the mechanisms that maintain their coexistence. Recent theoretical explorations suggest that competitive interactions will lead to groups, or clusters, of species with similar traits. However, theoretical predictions typically assume complete knowledge of the map between competition and measured traits. These assumptions limit the plausible application of these patterns for inferring competitive interactions in nature. Here we relax these restrictions and find that the clustering pattern is robust to contributions of unknown or unobserved niche axes. However, it may not be visible unless measured traits are close proxies for niche strategies. We conclude that patterns along single niche axes may reveal properties of interspecific competition in nature, but detecting these patterns requires natural history expertise firmly tying traits to niches. |
1705.11190 | Xerxes D. Arsiwalla | Xerxes D. Arsiwalla, Ricard Sole, Clement Moulin-Frier, Ivan Herreros,
Marti Sanchez-Fibla, Paul Verschure | The Morphospace of Consciousness | 23 pages, 3 figures | null | null | null | q-bio.NC cond-mat.dis-nn cs.AI physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We construct a complexity-based morphospace to study systems-level properties
of conscious & intelligent systems. The axes of this space label 3 complexity
types: autonomous, cognitive & social. Given recent proposals to synthesize
consciousness, a generic complexity-based conceptualization provides a useful
framework for identifying defining features of conscious & synthetic systems.
Based on current clinical scales of consciousness that measure cognitive
awareness and wakefulness, we take a perspective on how contemporary
artificially intelligent machines & synthetically engineered life forms measure
on these scales. It turns out that awareness & wakefulness can be associated to
computational & autonomous complexity respectively. Subsequently, building on
insights from cognitive robotics, we examine the function that consciousness
serves, & argue the role of consciousness as an evolutionary game-theoretic
strategy. This makes the case for a third type of complexity for describing
consciousness: social complexity. Having identified these complexity types,
allows for a representation of both, biological & synthetic systems in a common
morphospace. A consequence of this classification is a taxonomy of possible
conscious machines. We identify four types of consciousness, based on
embodiment: (i) biological consciousness, (ii) synthetic consciousness, (iii)
group consciousness (resulting from group interactions), & (iv) simulated
consciousness (embodied by virtual agents within a simulated reality). This
taxonomy helps in the investigation of comparative signatures of consciousness
across domains, in order to highlight design principles necessary to engineer
conscious machines. This is particularly relevant in the light of recent
developments at the crossroads of cognitive neuroscience, biomedical
engineering, artificial intelligence & biomimetics.
| [
{
"created": "Wed, 31 May 2017 17:45:39 GMT",
"version": "v1"
},
{
"created": "Thu, 8 Jun 2017 17:42:04 GMT",
"version": "v2"
},
{
"created": "Sat, 24 Nov 2018 23:05:40 GMT",
"version": "v3"
}
] | 2018-11-27 | [
[
"Arsiwalla",
"Xerxes D.",
""
],
[
"Sole",
"Ricard",
""
],
[
"Moulin-Frier",
"Clement",
""
],
[
"Herreros",
"Ivan",
""
],
[
"Sanchez-Fibla",
"Marti",
""
],
[
"Verschure",
"Paul",
""
]
] | We construct a complexity-based morphospace to study systems-level properties of conscious & intelligent systems. The axes of this space label 3 complexity types: autonomous, cognitive & social. Given recent proposals to synthesize consciousness, a generic complexity-based conceptualization provides a useful framework for identifying defining features of conscious & synthetic systems. Based on current clinical scales of consciousness that measure cognitive awareness and wakefulness, we take a perspective on how contemporary artificially intelligent machines & synthetically engineered life forms measure on these scales. It turns out that awareness & wakefulness can be associated to computational & autonomous complexity respectively. Subsequently, building on insights from cognitive robotics, we examine the function that consciousness serves, & argue the role of consciousness as an evolutionary game-theoretic strategy. This makes the case for a third type of complexity for describing consciousness: social complexity. Having identified these complexity types, allows for a representation of both, biological & synthetic systems in a common morphospace. A consequence of this classification is a taxonomy of possible conscious machines. We identify four types of consciousness, based on embodiment: (i) biological consciousness, (ii) synthetic consciousness, (iii) group consciousness (resulting from group interactions), & (iv) simulated consciousness (embodied by virtual agents within a simulated reality). This taxonomy helps in the investigation of comparative signatures of consciousness across domains, in order to highlight design principles necessary to engineer conscious machines. This is particularly relevant in the light of recent developments at the crossroads of cognitive neuroscience, biomedical engineering, artificial intelligence & biomimetics. |
0911.0645 | Ruriko Yoshida | Peter Huggins, Wenbin Li, David Haws, Thomas Friedrich, Jinze Liu,
Ruriko Yoshida | Bayes estimators for phylogenetic reconstruction | 31 pages, 4 figures, and 3 tables | null | null | null | q-bio.PE cs.LG q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Tree reconstruction methods are often judged by their accuracy, measured by
how close they get to the true tree. Yet most reconstruction methods like ML do
not explicitly maximize this accuracy. To address this problem, we propose a
Bayesian solution. Given tree samples, we propose finding the tree estimate
which is closest on average to the samples. This ``median'' tree is known as
the Bayes estimator (BE). The BE literally maximizes posterior expected
accuracy, measured in terms of closeness (distance) to the true tree. We
discuss a unified framework of BE trees, focusing especially on tree distances
which are expressible as squared euclidean distances. Notable examples include
Robinson--Foulds distance, quartet distance, and squared path difference. Using
simulated data, we show Bayes estimators can be efficiently computed in
practice by hill climbing. We also show that Bayes estimators achieve higher
accuracy, compared to maximum likelihood and neighbor joining.
| [
{
"created": "Tue, 3 Nov 2009 18:43:43 GMT",
"version": "v1"
},
{
"created": "Sun, 22 Nov 2009 00:09:42 GMT",
"version": "v2"
}
] | 2009-11-22 | [
[
"Huggins",
"Peter",
""
],
[
"Li",
"Wenbin",
""
],
[
"Haws",
"David",
""
],
[
"Friedrich",
"Thomas",
""
],
[
"Liu",
"Jinze",
""
],
[
"Yoshida",
"Ruriko",
""
]
] | Tree reconstruction methods are often judged by their accuracy, measured by how close they get to the true tree. Yet most reconstruction methods like ML do not explicitly maximize this accuracy. To address this problem, we propose a Bayesian solution. Given tree samples, we propose finding the tree estimate which is closest on average to the samples. This ``median'' tree is known as the Bayes estimator (BE). The BE literally maximizes posterior expected accuracy, measured in terms of closeness (distance) to the true tree. We discuss a unified framework of BE trees, focusing especially on tree distances which are expressible as squared euclidean distances. Notable examples include Robinson--Foulds distance, quartet distance, and squared path difference. Using simulated data, we show Bayes estimators can be efficiently computed in practice by hill climbing. We also show that Bayes estimators achieve higher accuracy, compared to maximum likelihood and neighbor joining. |
2109.13739 | Norman Fenton Prof | Martin Neil, Norman Fenton | Bayesian hypothesis testing and hierarchical modelling of ivermectin
effectiveness in treating Covid-19 | 13 pages | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Ivermectin is an antiparasitic drug that some have claimed is an effective
treatment for reducing Covid-19 deaths. To test this claim, two recent peer
reviewed papers both conducted a meta-analysis on a similar set of randomized
controlled trials data, applying the same classical statistical approach.
Although the statistical results were similar, one of the papers (Bryant et al,
2021) concluded that ivermectin was effective for reducing Covid-19 deaths,
while the other (Roman et al, 2021) concluded that there was insufficient
quality of evidence to support the conclusion Ivermectin was effective. This
paper applies a Bayesian approach, to a subset of the same trial data, to test
several causal hypotheses linking Covid-19 severity and ivermectin to mortality
and produce an alternative analysis to the classical approach. Applying diverse
alternative analysis methods which reach the same conclusions should increase
overall confidence in the result. We show that there is strong evidence to
support a causal link between ivermectin, Covid-19 severity and mortality, and:
i) for severe Covid-19 there is a 90.7% probability the risk ratio favours
ivermectin; ii) for mild/moderate Covid-19 there is an 84.1% probability the
risk ratio favours ivermectin. To address concerns expressed about the veracity
of some of the studies we evaluate the sensitivity of the conclusions to any
single study by removing one study at a time. In the worst case, where
(Elgazzar 2020) is removed, the results remain robust, for both severe and mild
to moderate Covid-19. The paper also highlights advantages of using Bayesian
methods over classical statistical methods for meta-analysis. All studies
included in the analysis were prior to data on the delta variant.
| [
{
"created": "Wed, 18 Aug 2021 20:12:14 GMT",
"version": "v1"
},
{
"created": "Fri, 1 Oct 2021 15:15:41 GMT",
"version": "v2"
}
] | 2021-10-04 | [
[
"Neil",
"Martin",
""
],
[
"Fenton",
"Norman",
""
]
] | Ivermectin is an antiparasitic drug that some have claimed is an effective treatment for reducing Covid-19 deaths. To test this claim, two recent peer reviewed papers both conducted a meta-analysis on a similar set of randomized controlled trials data, applying the same classical statistical approach. Although the statistical results were similar, one of the papers (Bryant et al, 2021) concluded that ivermectin was effective for reducing Covid-19 deaths, while the other (Roman et al, 2021) concluded that there was insufficient quality of evidence to support the conclusion Ivermectin was effective. This paper applies a Bayesian approach, to a subset of the same trial data, to test several causal hypotheses linking Covid-19 severity and ivermectin to mortality and produce an alternative analysis to the classical approach. Applying diverse alternative analysis methods which reach the same conclusions should increase overall confidence in the result. We show that there is strong evidence to support a causal link between ivermectin, Covid-19 severity and mortality, and: i) for severe Covid-19 there is a 90.7% probability the risk ratio favours ivermectin; ii) for mild/moderate Covid-19 there is an 84.1% probability the risk ratio favours ivermectin. To address concerns expressed about the veracity of some of the studies we evaluate the sensitivity of the conclusions to any single study by removing one study at a time. In the worst case, where (Elgazzar 2020) is removed, the results remain robust, for both severe and mild to moderate Covid-19. The paper also highlights advantages of using Bayesian methods over classical statistical methods for meta-analysis. All studies included in the analysis were prior to data on the delta variant. |
1302.5055 | Marcus Kaiser | Iwo Jerzy Bohr, Eva Kenny, Andrew Blamire, John T. O'Brien, Alan J.
Thomas, Jonathan Richardson and Marcus Kaiser | Resting-State Functional Connectivity in Late-Life Depression: Higher
Global Connectivity and More Long Distance Connections | null | Front Psychiatry. 2012; 3: 116 | 10.3389/fpsyt.2012.00116 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Functional magnetic resonance imaging recordings in the resting-state (RS)
from the human brain are characterized by spontaneous low-frequency
fluctuations in the blood oxygenation level dependent signal that reveal
functional connectivity (FC) via their spatial synchronicity. This RS study
applied network analysis to compare FC between late-life depression (LLD)
patients and control subjects. Raw cross-correlation matrices (CM) for LLD were
characterized by higher FC. We analyzed the small-world (SW) and modular
organization of these networks consisting of 110 nodes each as well as the
connectivity patterns of individual nodes of the basal ganglia. Topological
network measures showed no significant differences between groups. The
composition of top hubs was similar between LLD and control subjects, however
in the LLD group posterior medial-parietal regions were more highly connected
compared to controls. In LLD, a number of brain regions showed connections with
more distant neighbors leading to an increase of the average Euclidean distance
between connected regions compared to controls. In addition, right caudate
nucleus connectivity was more diffuse in LLD. In summary, LLD was associated
with overall increased FC strength and changes in the average distance between
connected nodes, but did not lead to global changes in SW or modular
organization.
| [
{
"created": "Wed, 20 Feb 2013 18:04:58 GMT",
"version": "v1"
}
] | 2013-02-21 | [
[
"Bohr",
"Iwo Jerzy",
""
],
[
"Kenny",
"Eva",
""
],
[
"Blamire",
"Andrew",
""
],
[
"O'Brien",
"John T.",
""
],
[
"Thomas",
"Alan J.",
""
],
[
"Richardson",
"Jonathan",
""
],
[
"Kaiser",
"Marcus",
""
]
] | Functional magnetic resonance imaging recordings in the resting-state (RS) from the human brain are characterized by spontaneous low-frequency fluctuations in the blood oxygenation level dependent signal that reveal functional connectivity (FC) via their spatial synchronicity. This RS study applied network analysis to compare FC between late-life depression (LLD) patients and control subjects. Raw cross-correlation matrices (CM) for LLD were characterized by higher FC. We analyzed the small-world (SW) and modular organization of these networks consisting of 110 nodes each as well as the connectivity patterns of individual nodes of the basal ganglia. Topological network measures showed no significant differences between groups. The composition of top hubs was similar between LLD and control subjects, however in the LLD group posterior medial-parietal regions were more highly connected compared to controls. In LLD, a number of brain regions showed connections with more distant neighbors leading to an increase of the average Euclidean distance between connected regions compared to controls. In addition, right caudate nucleus connectivity was more diffuse in LLD. In summary, LLD was associated with overall increased FC strength and changes in the average distance between connected nodes, but did not lead to global changes in SW or modular organization. |
1602.07758 | Scott Hotton | Scott Hotton | A geometric invariant for the study of planar curves and its application
to spiral tip meander | 19 pages, 15 figures | null | null | null | q-bio.SC q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Planar curves with periodically varying curvature arise in the natural
sciences as the result of a wide variety of periodic processes. The total
curvature of a periodic arc in such curves constrains their symmetry. It is
shown how the total curvature can be computed without reparameterizing the
curve to unit speed. The use of the total curvature of the periodic arcs is
demonstrated through a series of four examples from various branches of
science. Insights gained from these examples are applied to improve the
modeling of spiral wave meander.
| [
{
"created": "Thu, 25 Feb 2016 00:34:13 GMT",
"version": "v1"
}
] | 2016-02-26 | [
[
"Hotton",
"Scott",
""
]
] | Planar curves with periodically varying curvature arise in the natural sciences as the result of a wide variety of periodic processes. The total curvature of a periodic arc in such curves constrains their symmetry. It is shown how the total curvature can be computed without reparameterizing the curve to unit speed. The use of the total curvature of the periodic arcs is demonstrated through a series of four examples from various branches of science. Insights gained from these examples are applied to improve the modeling of spiral wave meander. |
1206.4087 | Paul Gardner | Lars Barquist, Sarah W. Burge and Paul P. Gardner | Studying RNA homology and conservation with Infernal: from single
sequences to RNA families | Submitted as a chapter for "Protocols in Bioinformatics". 41 pages, 7
figures | null | null | null | q-bio.BM | http://creativecommons.org/licenses/by/4.0/ | Emerging high-throughput technologies have led to a deluge of putative
non-coding RNA (ncRNA) sequences identified in a wide variety of organisms.
Systematic characterization of these transcripts will be a tremendous
challenge. Homology detection is critical to making maximal use of functional
information gathered about ncRNAs: identifying homologous sequence allows us to
transfer information gathered in one organism to another quickly and with a
high degree of confidence. ncRNA presents a challenge for homology detection,
as the primary sequence is often poorly conserved and de novo secondary
structure prediction and search remains difficult. This protocol introduces
methods developed by the Rfam database for identifying "families" of homologous
ncRNAs starting from single "seed" sequences using manually curated sequence
alignments to build powerful statistical models of sequence and structure
conservation known as covariance models (CMs), implemented in the Infernal
software package. We provide a step-by-step iterative protocol for identifying
ncRNA homologs, then constructing an alignment and corresponding CM. We also
work through an example for the bacterial small RNA MicA, discovering a
previously unreported family of divergent MicA homologs in genus Xenorhabdus in
the process.
| [
{
"created": "Mon, 18 Jun 2012 22:02:35 GMT",
"version": "v1"
},
{
"created": "Tue, 26 Jan 2016 09:57:27 GMT",
"version": "v2"
}
] | 2016-01-27 | [
[
"Barquist",
"Lars",
""
],
[
"Burge",
"Sarah W.",
""
],
[
"Gardner",
"Paul P.",
""
]
] | Emerging high-throughput technologies have led to a deluge of putative non-coding RNA (ncRNA) sequences identified in a wide variety of organisms. Systematic characterization of these transcripts will be a tremendous challenge. Homology detection is critical to making maximal use of functional information gathered about ncRNAs: identifying homologous sequence allows us to transfer information gathered in one organism to another quickly and with a high degree of confidence. ncRNA presents a challenge for homology detection, as the primary sequence is often poorly conserved and de novo secondary structure prediction and search remains difficult. This protocol introduces methods developed by the Rfam database for identifying "families" of homologous ncRNAs starting from single "seed" sequences using manually curated sequence alignments to build powerful statistical models of sequence and structure conservation known as covariance models (CMs), implemented in the Infernal software package. We provide a step-by-step iterative protocol for identifying ncRNA homologs, then constructing an alignment and corresponding CM. We also work through an example for the bacterial small RNA MicA, discovering a previously unreported family of divergent MicA homologs in genus Xenorhabdus in the process. |
1909.01439 | Steffen Rulands Dr | Steffen Rulands, Fabienne Lescroart, Samira Chabab, Christopher J.
Hindley, Nicole Prior, Magdalena K. Sznurkowska, Meritxell Huch, Anna
Philpott, Cedric Blanpain and Benjamin D. Simons | Universality of clone dynamics during tissue development | 15 pages, 3 figures, supplement at the end of PDF file | Nature Physics, 14, 469-474 (2018) | 10.1038/s41567-018-0055-6 | null | q-bio.TO physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The emergence of complex organs is driven by the coordinated proliferation,
migration and differentiation of precursor cells. The fate behaviour of these
cells is reflected in the time evolution their progeny, termed clones, which
serve as a key experimental observable. In adult tissues, where cell dynamics
is constrained by the condition of homeostasis, clonal tracing studies based on
transgenic animal models have advanced our understanding of cell fate behaviour
and its dysregulation in disease. But what can be learned from clonal dynamics
in development, where the spatial cohesiveness of clones is impaired by tissue
deformations during tissue growth? Drawing on the results of clonal tracing
studies, we show that, despite the complexity of organ development, clonal
dynamics may converge to a critical state characterized by universal scaling
behaviour of clone sizes. By mapping clonal dynamics onto a generalization of
the classical theory of aerosols, we elucidate the origin and range of scaling
behaviours and show how the identification of universal scaling dependences may
allow lineage-specific information to be distilled from experiments. Our study
shows the emergence of core concepts of statistical physics in an unexpected
context, identifying cellular systems as a laboratory to study non-equilibrium
statistical physics.
| [
{
"created": "Fri, 30 Aug 2019 07:07:33 GMT",
"version": "v1"
}
] | 2019-09-05 | [
[
"Rulands",
"Steffen",
""
],
[
"Lescroart",
"Fabienne",
""
],
[
"Chabab",
"Samira",
""
],
[
"Hindley",
"Christopher J.",
""
],
[
"Prior",
"Nicole",
""
],
[
"Sznurkowska",
"Magdalena K.",
""
],
[
"Huch",
"Meritxell",
""
],
[
"Philpott",
"Anna",
""
],
[
"Blanpain",
"Cedric",
""
],
[
"Simons",
"Benjamin D.",
""
]
] | The emergence of complex organs is driven by the coordinated proliferation, migration and differentiation of precursor cells. The fate behaviour of these cells is reflected in the time evolution their progeny, termed clones, which serve as a key experimental observable. In adult tissues, where cell dynamics is constrained by the condition of homeostasis, clonal tracing studies based on transgenic animal models have advanced our understanding of cell fate behaviour and its dysregulation in disease. But what can be learned from clonal dynamics in development, where the spatial cohesiveness of clones is impaired by tissue deformations during tissue growth? Drawing on the results of clonal tracing studies, we show that, despite the complexity of organ development, clonal dynamics may converge to a critical state characterized by universal scaling behaviour of clone sizes. By mapping clonal dynamics onto a generalization of the classical theory of aerosols, we elucidate the origin and range of scaling behaviours and show how the identification of universal scaling dependences may allow lineage-specific information to be distilled from experiments. Our study shows the emergence of core concepts of statistical physics in an unexpected context, identifying cellular systems as a laboratory to study non-equilibrium statistical physics. |
1607.04836 | Raul Isea | Olaf Ilzins, Raul Isea, Johan Hoebeke | Can Bioinformatics Be Considered as an Experimental Biological Science? | 3 pages, Open Access | Open Science Journal of Bioscience and Bioengineering (2015), Vol.
2, pp: 60-62 | null | null | q-bio.OT | http://creativecommons.org/publicdomain/zero/1.0/ | The objective of this short report is to reconsider the subject of
bioinformatics as just being a tool of experimental biological science. To do
that, we introduce three examples to show how bioinformatics could be
considered as an experimental science. These examples show how the development
of theoretical biological models generates experimentally verifiable computer
hypotheses, which necessarily must be validated by experiments in vitro or in
vivo.
| [
{
"created": "Sun, 17 Jul 2016 08:46:39 GMT",
"version": "v1"
}
] | 2016-07-19 | [
[
"Ilzins",
"Olaf",
""
],
[
"Isea",
"Raul",
""
],
[
"Hoebeke",
"Johan",
""
]
] | The objective of this short report is to reconsider the subject of bioinformatics as just being a tool of experimental biological science. To do that, we introduce three examples to show how bioinformatics could be considered as an experimental science. These examples show how the development of theoretical biological models generates experimentally verifiable computer hypotheses, which necessarily must be validated by experiments in vitro or in vivo. |
1803.06410 | Paul M\"uller | Paul M\"uller, Mirjam Sch\"urmann, Salvatore Girardo, Gheorghe Cojoc,
Jochen Guck | Accurate evaluation of size and refractive index for spherical objects
in quantitative phase imaging | 14 pages, 10 figures, 1 table | null | 10.1364/OE.26.010729 | null | q-bio.QM physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Measuring the average refractive index (RI) of spherical objects, such as
suspended cells, in quantitative phase imaging (QPI) requires a decoupling of
RI and size from the QPI data. This has been commonly achieved by determining
the object's radius with geometrical approaches, neglecting light-scattering.
Here, we present a novel QPI fitting algorithm that reliably uncouples the RI
using Mie theory and a semi-analytical, corrected Rytov approach. We assess the
range of validity of this algorithm in silico and experimentally investigate
various objects (oil and protein droplets, microgel beads, cells) and noise
conditions. In addition, we provide important practical cues for future studies
in cell biology.
| [
{
"created": "Fri, 16 Mar 2018 21:51:33 GMT",
"version": "v1"
},
{
"created": "Thu, 26 Apr 2018 08:05:41 GMT",
"version": "v2"
}
] | 2018-04-27 | [
[
"Müller",
"Paul",
""
],
[
"Schürmann",
"Mirjam",
""
],
[
"Girardo",
"Salvatore",
""
],
[
"Cojoc",
"Gheorghe",
""
],
[
"Guck",
"Jochen",
""
]
] | Measuring the average refractive index (RI) of spherical objects, such as suspended cells, in quantitative phase imaging (QPI) requires a decoupling of RI and size from the QPI data. This has been commonly achieved by determining the object's radius with geometrical approaches, neglecting light-scattering. Here, we present a novel QPI fitting algorithm that reliably uncouples the RI using Mie theory and a semi-analytical, corrected Rytov approach. We assess the range of validity of this algorithm in silico and experimentally investigate various objects (oil and protein droplets, microgel beads, cells) and noise conditions. In addition, we provide important practical cues for future studies in cell biology. |
1612.06050 | Alyssa Barry PhD | Andreea Waltmann, Cristian Koepfli, Natacha Tessier, Stephan Karl,
Andrew W. Darcy, Lyndes Wini, G.L. Abby Harrison, Celine Barnadas, Charlie
Jennison, Harin Karunajeewa, Sarah Boyd, Maxine Whittaker, James Kazura,
Melanie Bahlo, Ivo Mueller and Alyssa E. Barry | Long-term sustained malaria control leads to inbreeding and
fragmentation of Plasmodium vivax populations | After peer review this has been extensively rewritten and is also
housed on another preprint server | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Plasmodium vivax populations are more resistant to malaria control strategies
than Plasmodium falciparum, maintaining high genetic diversity and gene flow
even at low transmission. To quantify the impact of declining transmission on
P. vivax populations, we investigated population genetic structure over time
during intensified control efforts and over a wide range of transmission
intensities and spatial scales in the Southwest Pacific. Analysis of 887 P.
vivax microsatellite haplotypes (Papua New Guinea, PNG = 443, Solomon Islands =
420, Vanuatu =24) revealed substantial population structure among countries and
modestly declining diversity as transmission decreases over space and time. In
the Solomon Islands, which has had sustained control efforts for 20 years,
significant population structure was observed on different spatial scales down
to the sub-village level. Up to 37% of alleles were partitioned between
populations and significant multilocus linkage disequilibrium was observed
indicating substantial inbreeding. High levels of haplotype relatedness around
households and within a range of 300m are consistent with a focal and clustered
infections suggesting that restricted local transmission occurs within the
range of vector movement and that subsequent focal inbreeding may be a key
factor contributing to the observed population structure. We conclude that
unique transmission strategies, including relapse allows P. vivax populations
to withstand pressure from control efforts for longer than P. falciparum.
However sustained control efforts do eventually impact parasite population
structure and with further control pressure, populations may eventually
fragment into clustered foci that could be targeted for elimination.
| [
{
"created": "Mon, 19 Dec 2016 05:07:32 GMT",
"version": "v1"
},
{
"created": "Wed, 21 Dec 2016 03:05:19 GMT",
"version": "v2"
},
{
"created": "Fri, 23 Jun 2017 02:47:18 GMT",
"version": "v3"
}
] | 2017-06-26 | [
[
"Waltmann",
"Andreea",
""
],
[
"Koepfli",
"Cristian",
""
],
[
"Tessier",
"Natacha",
""
],
[
"Karl",
"Stephan",
""
],
[
"Darcy",
"Andrew W.",
""
],
[
"Wini",
"Lyndes",
""
],
[
"Harrison",
"G. L. Abby",
""
],
[
"Barnadas",
"Celine",
""
],
[
"Jennison",
"Charlie",
""
],
[
"Karunajeewa",
"Harin",
""
],
[
"Boyd",
"Sarah",
""
],
[
"Whittaker",
"Maxine",
""
],
[
"Kazura",
"James",
""
],
[
"Bahlo",
"Melanie",
""
],
[
"Mueller",
"Ivo",
""
],
[
"Barry",
"Alyssa E.",
""
]
] | Plasmodium vivax populations are more resistant to malaria control strategies than Plasmodium falciparum, maintaining high genetic diversity and gene flow even at low transmission. To quantify the impact of declining transmission on P. vivax populations, we investigated population genetic structure over time during intensified control efforts and over a wide range of transmission intensities and spatial scales in the Southwest Pacific. Analysis of 887 P. vivax microsatellite haplotypes (Papua New Guinea, PNG = 443, Solomon Islands = 420, Vanuatu =24) revealed substantial population structure among countries and modestly declining diversity as transmission decreases over space and time. In the Solomon Islands, which has had sustained control efforts for 20 years, significant population structure was observed on different spatial scales down to the sub-village level. Up to 37% of alleles were partitioned between populations and significant multilocus linkage disequilibrium was observed indicating substantial inbreeding. High levels of haplotype relatedness around households and within a range of 300m are consistent with a focal and clustered infections suggesting that restricted local transmission occurs within the range of vector movement and that subsequent focal inbreeding may be a key factor contributing to the observed population structure. We conclude that unique transmission strategies, including relapse allows P. vivax populations to withstand pressure from control efforts for longer than P. falciparum. However sustained control efforts do eventually impact parasite population structure and with further control pressure, populations may eventually fragment into clustered foci that could be targeted for elimination. |
1801.03707 | Robert Endres | Giovanna De Palo, Darvin Yi, Robert G. Endres | A Critical-like Collective State Leads to Long-range Cell Communication
in Dictyostelium discoideum Aggregation | 19 pages, 4 figures. This is an earlier version which contains cell
steering by applied perturbations in Fig. 4 | Final version (mainly different Fig. 4 and a bit less technical):
De Palo G, Yi D, Endres RG. PLoS Biol. 15(4): e1002602 (2017) | 10.1371/journal.pbio.1002602 | null | q-bio.CB q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | The transition from single-cell to multicellular behavior is important in
early development but rarely studied. The starvation-induced aggregation of the
social amoeba Dictyostelium discoideum into a multicellular slug is known to
result from single-cell chemotaxis towards emitted pulses of cyclic adenosine
monophosphate (cAMP). However, how exactly do transient short-range chemical
gradients lead to coherent collective movement at a macroscopic scale? Here, we
use a multiscale model verified by quantitative microscopy to describe
wide-ranging behaviors from chemotaxis and excitability of individual cells to
aggregation of thousands of cells. To better understand the mechanism of
long-range cell-cell communication and hence aggregation, we analyze cell-cell
correlations, showing evidence for self-organization at the onset of
aggregation (as opposed to following a leader cell). Surprisingly, cell
collectives, despite their finite size, show features of criticality known from
phase transitions in physical systems. Application of external cAMP
perturbations in our simulations near the sensitive critical point allows
steering cells into early aggregation and towards certain locations but not
once an aggregation center has been chosen.
| [
{
"created": "Thu, 11 Jan 2018 10:59:35 GMT",
"version": "v1"
}
] | 2018-01-12 | [
[
"De Palo",
"Giovanna",
""
],
[
"Yi",
"Darvin",
""
],
[
"Endres",
"Robert G.",
""
]
] | The transition from single-cell to multicellular behavior is important in early development but rarely studied. The starvation-induced aggregation of the social amoeba Dictyostelium discoideum into a multicellular slug is known to result from single-cell chemotaxis towards emitted pulses of cyclic adenosine monophosphate (cAMP). However, how exactly do transient short-range chemical gradients lead to coherent collective movement at a macroscopic scale? Here, we use a multiscale model verified by quantitative microscopy to describe wide-ranging behaviors from chemotaxis and excitability of individual cells to aggregation of thousands of cells. To better understand the mechanism of long-range cell-cell communication and hence aggregation, we analyze cell-cell correlations, showing evidence for self-organization at the onset of aggregation (as opposed to following a leader cell). Surprisingly, cell collectives, despite their finite size, show features of criticality known from phase transitions in physical systems. Application of external cAMP perturbations in our simulations near the sensitive critical point allows steering cells into early aggregation and towards certain locations but not once an aggregation center has been chosen. |
1908.10101 | Kenneth Miller | Yashar Ahmadian and Kenneth D. Miller | What is the dynamical regime of cerebral cortex? | 21 pages, 2 figures | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Many studies have shown that the excitation and inhibition received by
cortical neurons remain roughly balanced across many conditions. A key question
for understanding the dynamical regime of cortex is the nature of this
balancing. Theorists have shown that network dynamics can yield systematic
cancellation of most of a neuron's excitatory input by inhibition. We review a
wide range of evidence pointing to this cancellation occurring in a regime in
which the balance is loose, meaning that the net input remaining after
cancellation of excitation and inhibition is comparable in size to the factors
that cancel, rather than tight, meaning that the net input is very small
relative to the cancelling factors. This choice of regime has important
implications for cortical functional responses, as we describe: loose balance,
but not tight balance, can yield many nonlinear population behaviors seen in
sensory cortical neurons, allow the presence of correlated variability, and
yield decrease of that variability with increasing external stimulus drive as
observed across multiple cortical areas.
| [
{
"created": "Tue, 27 Aug 2019 09:29:45 GMT",
"version": "v1"
},
{
"created": "Wed, 28 Aug 2019 09:44:21 GMT",
"version": "v2"
}
] | 2019-08-29 | [
[
"Ahmadian",
"Yashar",
""
],
[
"Miller",
"Kenneth D.",
""
]
] | Many studies have shown that the excitation and inhibition received by cortical neurons remain roughly balanced across many conditions. A key question for understanding the dynamical regime of cortex is the nature of this balancing. Theorists have shown that network dynamics can yield systematic cancellation of most of a neuron's excitatory input by inhibition. We review a wide range of evidence pointing to this cancellation occurring in a regime in which the balance is loose, meaning that the net input remaining after cancellation of excitation and inhibition is comparable in size to the factors that cancel, rather than tight, meaning that the net input is very small relative to the cancelling factors. This choice of regime has important implications for cortical functional responses, as we describe: loose balance, but not tight balance, can yield many nonlinear population behaviors seen in sensory cortical neurons, allow the presence of correlated variability, and yield decrease of that variability with increasing external stimulus drive as observed across multiple cortical areas. |
2303.04808 | Mrinmoy Roy | Mrinmoy Roy, Anica Tasnim Protity, Srabonti Das, Porarthi Dhar | Prevalence and Major Risk Factors of Non-communicable Diseases: A
Machine Learning based Cross-Sectional Study | 25 pages, 10 figures, 3 tables | null | null | null | q-bio.QM cs.LG stat.AP | http://creativecommons.org/publicdomain/zero/1.0/ | Objective: The study aimed to determine the prevalence of several
non-communicable diseases (NCD) and analyze risk factors among adult patients
seeking nutritional guidance in Dhaka, Bangladesh. Result: Our study observed
the relationships between gender, age groups, obesity, and NCDs (DM, CKD, IBS,
CVD, CRD, thyroid). The most frequently reported NCD was cardiovascular issues
(CVD), which was present in 83.56% of all participants. CVD was more common in
male participants. Consequently, male participants had a higher blood pressure
distribution than females. Diabetes mellitus (DM), on the other hand, did not
have a gender-based inclination. Both CVD and DM had an age-based progression.
Our study showed that chronic respiratory illness was more frequent in
middle-aged participants than in younger or elderly individuals. Based on the
data, every one in five hospitalized patients was obese. We analyzed the
co-morbidities and found that 31.5% of the population has only one NCD, 30.1%
has two NCDs, and 38.3% has more than two NCDs. Besides, 86.25% of all diabetic
patients had cardiovascular issues. All thyroid patients in our study had CVD.
Using a t-test, we found a relationship between CKD and thyroid (p-value
0.061). Males under 35 years have a statistically significant relationship
between thyroid and chronic respiratory diseases (p-value 0.018). We also found
an association between DM and CKD among patients over 65 (p-value 0.038).
Moreover, there has been a statistically significant relationship between CKD
and Thyroid (P < 0.05) for those below 35 and 35-65. We used a two-way ANOVA
test to find the statistically significant interaction of heart issues and
chronic respiratory illness, in combination with diabetes. The combination of
DM and RTI also affected CKD in male patients over 65 years old.
| [
{
"created": "Fri, 3 Mar 2023 21:58:35 GMT",
"version": "v1"
},
{
"created": "Fri, 5 May 2023 04:32:53 GMT",
"version": "v2"
},
{
"created": "Thu, 18 May 2023 06:23:47 GMT",
"version": "v3"
}
] | 2023-05-19 | [
[
"Roy",
"Mrinmoy",
""
],
[
"Protity",
"Anica Tasnim",
""
],
[
"Das",
"Srabonti",
""
],
[
"Dhar",
"Porarthi",
""
]
] | Objective: The study aimed to determine the prevalence of several non-communicable diseases (NCD) and analyze risk factors among adult patients seeking nutritional guidance in Dhaka, Bangladesh. Result: Our study observed the relationships between gender, age groups, obesity, and NCDs (DM, CKD, IBS, CVD, CRD, thyroid). The most frequently reported NCD was cardiovascular issues (CVD), which was present in 83.56% of all participants. CVD was more common in male participants. Consequently, male participants had a higher blood pressure distribution than females. Diabetes mellitus (DM), on the other hand, did not have a gender-based inclination. Both CVD and DM had an age-based progression. Our study showed that chronic respiratory illness was more frequent in middle-aged participants than in younger or elderly individuals. Based on the data, every one in five hospitalized patients was obese. We analyzed the co-morbidities and found that 31.5% of the population has only one NCD, 30.1% has two NCDs, and 38.3% has more than two NCDs. Besides, 86.25% of all diabetic patients had cardiovascular issues. All thyroid patients in our study had CVD. Using a t-test, we found a relationship between CKD and thyroid (p-value 0.061). Males under 35 years have a statistically significant relationship between thyroid and chronic respiratory diseases (p-value 0.018). We also found an association between DM and CKD among patients over 65 (p-value 0.038). Moreover, there has been a statistically significant relationship between CKD and Thyroid (P < 0.05) for those below 35 and 35-65. We used a two-way ANOVA test to find the statistically significant interaction of heart issues and chronic respiratory illness, in combination with diabetes. The combination of DM and RTI also affected CKD in male patients over 65 years old. |
2008.03846 | Xiaoxian Tang | Xiaoxian Tang and Hao Xu | Multistability of Small Reaction Networks | 23 pages, 5 tables | null | null | null | q-bio.MN math.AG math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | For three typical sets of small reaction networks (networks with two
reactions, one irreversible and one reversible reaction, or two
reversible-reaction pairs), we completely answer the challenging question: what
is the smallest subset of all multistable networks such that any multistable
network outside of the subset contains either more species or more reactants
than any network in this subset?
| [
{
"created": "Mon, 10 Aug 2020 00:50:22 GMT",
"version": "v1"
},
{
"created": "Thu, 28 Jan 2021 10:17:58 GMT",
"version": "v2"
}
] | 2021-01-29 | [
[
"Tang",
"Xiaoxian",
""
],
[
"Xu",
"Hao",
""
]
] | For three typical sets of small reaction networks (networks with two reactions, one irreversible and one reversible reaction, or two reversible-reaction pairs), we completely answer the challenging question: what is the smallest subset of all multistable networks such that any multistable network outside of the subset contains either more species or more reactants than any network in this subset? |
1801.01913 | Federico Battiston | Federico Battiston, Jeremy Guillon, Mario Chavez, Vito Latora,
Fabrizio De Vico Fallani | Multiplex core-periphery organization of the human connectome | Main text (12 pages, 5 figures) + Supplementary material (6 pages, 5
figures, 1 table) | J. R. Soc. Interface 2018 | 10.1098/rsif.2018.0514 | null | q-bio.NC cs.SI physics.soc-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The behavior of many complex systems is determined by a core of densely
interconnected units. While many methods are available to identify the core of
a network when connections between nodes are all of the same type, a principled
approach to define the core when multiple types of connectivity are allowed is
still lacking. Here we introduce a general framework to define and extract the
core-periphery structure of multi-layer networks by explicitly taking into
account the connectivity of the nodes at each layer. We show how our method
works on synthetic networks with different size, density, and overlap between
the cores at the different layers. We then apply the method to multiplex brain
networks whose layers encode information both on the anatomical and the
functional connectivity among regions of the human cortex. Results confirm the
presence of the main known hubs, but also suggest the existence of novel brain
core regions that have been discarded by previous analysis which focused
exclusively on the structural layer. Our work is a step forward in the
identification of the core of the human connectome, and contributes to shed
light to a fundamental question in modern neuroscience.
| [
{
"created": "Sat, 23 Dec 2017 16:03:45 GMT",
"version": "v1"
}
] | 2018-09-14 | [
[
"Battiston",
"Federico",
""
],
[
"Guillon",
"Jeremy",
""
],
[
"Chavez",
"Mario",
""
],
[
"Latora",
"Vito",
""
],
[
"Fallani",
"Fabrizio De Vico",
""
]
] | The behavior of many complex systems is determined by a core of densely interconnected units. While many methods are available to identify the core of a network when connections between nodes are all of the same type, a principled approach to define the core when multiple types of connectivity are allowed is still lacking. Here we introduce a general framework to define and extract the core-periphery structure of multi-layer networks by explicitly taking into account the connectivity of the nodes at each layer. We show how our method works on synthetic networks with different size, density, and overlap between the cores at the different layers. We then apply the method to multiplex brain networks whose layers encode information both on the anatomical and the functional connectivity among regions of the human cortex. Results confirm the presence of the main known hubs, but also suggest the existence of novel brain core regions that have been discarded by previous analysis which focused exclusively on the structural layer. Our work is a step forward in the identification of the core of the human connectome, and contributes to shed light to a fundamental question in modern neuroscience. |
1303.0281 | Marek Czachor | Diederik Aerts, Marek Czachor, Maciej Kuna, Sandro Sozzo | Systems, environments, and soliton rate equations: A non-Kolmogorovian
framework for population dynamics | 51 pages, 15 eps figures | Ecological Modelling 267, 80-92 (2013) | null | null | q-bio.PE nlin.PS nlin.SI quant-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Soliton rate equations are based on non-Kolmogorovian models of probability
and naturally include autocatalytic processes. The formalism is not widely
known but has great unexplored potential for applications to systems
interacting with environments. Beginning with links of contextuality to
non-Kolmogorovity we introduce the general formalism of soliton rate equations
and work out explicit examples of subsystems interacting with environments. Of
particular interest is the case of a soliton autocatalytic rate equation
coupled to a linear conservative environment, a formal way of expressing
seasonal changes. Depending on strength of the system-environment coupling we
observe phenomena analogous to hibernation or even complete blocking of decay
of a population.
| [
{
"created": "Sun, 3 Mar 2013 10:00:36 GMT",
"version": "v1"
},
{
"created": "Tue, 9 Jul 2013 08:51:08 GMT",
"version": "v2"
}
] | 2013-09-10 | [
[
"Aerts",
"Diederik",
""
],
[
"Czachor",
"Marek",
""
],
[
"Kuna",
"Maciej",
""
],
[
"Sozzo",
"Sandro",
""
]
] | Soliton rate equations are based on non-Kolmogorovian models of probability and naturally include autocatalytic processes. The formalism is not widely known but has great unexplored potential for applications to systems interacting with environments. Beginning with links of contextuality to non-Kolmogorovity we introduce the general formalism of soliton rate equations and work out explicit examples of subsystems interacting with environments. Of particular interest is the case of a soliton autocatalytic rate equation coupled to a linear conservative environment, a formal way of expressing seasonal changes. Depending on strength of the system-environment coupling we observe phenomena analogous to hibernation or even complete blocking of decay of a population. |
0808.3312 | Matti Peltom\"aki | Matti Peltomaki and Mikko Alava | Three- and four-state rock-paper-scissors games with diffusion | Accepted for publication in Physical Review E | Physical Review E 78, 031906 (2008) | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Cyclic dominance of three species is a commonly occurring interaction
dynamics, often denoted the rock-paper-scissors (RPS) game. Such type of
interactions is known to promote species coexistence. Here, we generalize
recent results of Reichenbach et al. (e.g. Nature 448, 1046 (2007)) of a
four-state variant of RPS. We show that spiral formation takes place only
without a conservation law for the total density. Nevertheless, in general fast
diffusion can destroy species coexistence. We also generalize the four-state
model to slightly varying reaction rates. This is shown both analytically and
numerically not to change pattern formation, or the effective wave length of
the spirals, and therefore does not alter the qualitative properties of the
cross-over to extinction.
| [
{
"created": "Mon, 25 Aug 2008 07:32:33 GMT",
"version": "v1"
}
] | 2008-09-11 | [
[
"Peltomaki",
"Matti",
""
],
[
"Alava",
"Mikko",
""
]
] | Cyclic dominance of three species is a commonly occurring interaction dynamics, often denoted the rock-paper-scissors (RPS) game. Such type of interactions is known to promote species coexistence. Here, we generalize recent results of Reichenbach et al. (e.g. Nature 448, 1046 (2007)) of a four-state variant of RPS. We show that spiral formation takes place only without a conservation law for the total density. Nevertheless, in general fast diffusion can destroy species coexistence. We also generalize the four-state model to slightly varying reaction rates. This is shown both analytically and numerically not to change pattern formation, or the effective wave length of the spirals, and therefore does not alter the qualitative properties of the cross-over to extinction. |
2312.01275 | Satyaki Roy | Ahmad F. Al Musawi, Satyaki Roy, Preetam Ghosh | A Review of Link Prediction Applications in Network Biology | null | null | null | null | q-bio.MN cs.LG cs.SI | http://creativecommons.org/licenses/by/4.0/ | In the domain of network biology, the interactions among heterogeneous
genomic and molecular entities are represented through networks. Link
prediction (LP) methodologies are instrumental in inferring missing or
prospective associations within these biological networks. In this review, we
systematically dissect the attributes of local, centrality, and embedding-based
LP approaches, applied to static and dynamic biological networks. We undertake
an examination of the current applications of LP metrics for predicting links
between diseases, genes, proteins, RNA, microbiomes, drugs, and neurons. We
carry out comprehensive performance evaluations on established biological
network datasets to show the practical applications of standard LP models.
Moreover, we compare the similarity in prediction trends among the models and
the specific network attributes that contribute to effective link prediction,
before underscoring the role of LP in addressing the formidable challenges
prevalent in biological systems, ranging from noise, bias, and data sparseness
to interpretability. We conclude the review with an exploration of the
essential characteristics expected from future LP models, poised to advance our
comprehension of the intricate interactions governing biological systems.
| [
{
"created": "Sun, 3 Dec 2023 04:23:51 GMT",
"version": "v1"
}
] | 2023-12-05 | [
[
"Musawi",
"Ahmad F. Al",
""
],
[
"Roy",
"Satyaki",
""
],
[
"Ghosh",
"Preetam",
""
]
] | In the domain of network biology, the interactions among heterogeneous genomic and molecular entities are represented through networks. Link prediction (LP) methodologies are instrumental in inferring missing or prospective associations within these biological networks. In this review, we systematically dissect the attributes of local, centrality, and embedding-based LP approaches, applied to static and dynamic biological networks. We undertake an examination of the current applications of LP metrics for predicting links between diseases, genes, proteins, RNA, microbiomes, drugs, and neurons. We carry out comprehensive performance evaluations on established biological network datasets to show the practical applications of standard LP models. Moreover, we compare the similarity in prediction trends among the models and the specific network attributes that contribute to effective link prediction, before underscoring the role of LP in addressing the formidable challenges prevalent in biological systems, ranging from noise, bias, and data sparseness to interpretability. We conclude the review with an exploration of the essential characteristics expected from future LP models, poised to advance our comprehension of the intricate interactions governing biological systems. |
2106.07089 | Luca Cardelli | Luca Cardelli, Marta Kwiatkowska, Luca Laurenti | A Language for Modeling And Optimizing Experimental Biological Protocols | null | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Automation is becoming ubiquitous in all laboratory activities, leading
towards precisely defined and codified laboratory protocols. However, the
integration between laboratory protocols and mathematical models is still
lacking. Models describe physical processes, while protocols define the steps
carried out during an experiment: neither cover the domain of the other,
although they both attempt to characterize the same phenomena. We should
ideally start from an integrated description of both the model and the steps
carried out to test it, to concurrently analyze uncertainties in model
parameters, equipment tolerances, and data collection. To this end, we present
a language to model and optimize experimental biochemical protocols that
facilitates such an integrated description, and that can be combined with
experimental data. We provide a probabilistic semantics for our language based
on a Bayesian interpretation that formally characterizes the uncertainties in
both the data collection, the underlying model, and the protocol operations. On
a set of case studies we illustrate how the resulting framework allows for
automated analysis and optimization of experimental protocols, including Gibson
assembly protocols.
| [
{
"created": "Sun, 13 Jun 2021 20:45:09 GMT",
"version": "v1"
},
{
"created": "Mon, 29 Nov 2021 16:29:25 GMT",
"version": "v2"
}
] | 2021-11-30 | [
[
"Cardelli",
"Luca",
""
],
[
"Kwiatkowska",
"Marta",
""
],
[
"Laurenti",
"Luca",
""
]
] | Automation is becoming ubiquitous in all laboratory activities, leading towards precisely defined and codified laboratory protocols. However, the integration between laboratory protocols and mathematical models is still lacking. Models describe physical processes, while protocols define the steps carried out during an experiment: neither cover the domain of the other, although they both attempt to characterize the same phenomena. We should ideally start from an integrated description of both the model and the steps carried out to test it, to concurrently analyze uncertainties in model parameters, equipment tolerances, and data collection. To this end, we present a language to model and optimize experimental biochemical protocols that facilitates such an integrated description, and that can be combined with experimental data. We provide a probabilistic semantics for our language based on a Bayesian interpretation that formally characterizes the uncertainties in both the data collection, the underlying model, and the protocol operations. On a set of case studies we illustrate how the resulting framework allows for automated analysis and optimization of experimental protocols, including Gibson assembly protocols. |
2310.01792 | Massimiliano Bonomi | Samuel Hoff, Maximilian Zinke, Nadia Izadi-Pruneyre, Massimiliano
Bonomi | Bonds and Bytes: the Odyssey of Structural Biology | 16 pages, 2 figures | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | Characterizing structural and dynamic properties of proteins and large
macromolecular assemblies is crucial to understand the molecular mechanisms
underlying biological functions. In the field of Structural Biology, no single
method comprehensively reveals the behavior of biological systems across
various spatio-temporal scales. Instead, we have a versatile toolkit of
techniques, each contributing a piece to the overall puzzle. Integrative
Structural Biology combines different techniques to create accurate and precise
multi-scale models that expand our understanding of complex biological systems.
This review outlines recent advancements in computational and experimental
methods in Structural Biology, with special focus on recent Artificial
Intelligence techniques, emphasizes integrative approaches that combine
different types of data for precise spatio-temporal modeling, and provides an
outlook into future directions of this field.
| [
{
"created": "Tue, 3 Oct 2023 04:42:24 GMT",
"version": "v1"
}
] | 2023-10-04 | [
[
"Hoff",
"Samuel",
""
],
[
"Zinke",
"Maximilian",
""
],
[
"Izadi-Pruneyre",
"Nadia",
""
],
[
"Bonomi",
"Massimiliano",
""
]
] | Characterizing structural and dynamic properties of proteins and large macromolecular assemblies is crucial to understand the molecular mechanisms underlying biological functions. In the field of Structural Biology, no single method comprehensively reveals the behavior of biological systems across various spatio-temporal scales. Instead, we have a versatile toolkit of techniques, each contributing a piece to the overall puzzle. Integrative Structural Biology combines different techniques to create accurate and precise multi-scale models that expand our understanding of complex biological systems. This review outlines recent advancements in computational and experimental methods in Structural Biology, with special focus on recent Artificial Intelligence techniques, emphasizes integrative approaches that combine different types of data for precise spatio-temporal modeling, and provides an outlook into future directions of this field. |
1007.3184 | Jonathan A D Wattis | Jonathan AD Wattis | Mathematical models of homochiralisation by grinding of crystals | 36 pp, 13 figs, to appear in Origins of Life and Evolution of
Biospheres | null | null | null | q-bio.BM math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We review the existing mathematical models which describe physicochemical
mechanisms capable of producing a symmetry-breaking transition to a state in
which one chirality dominates the other. A new model is proposed, with the aim
of elucidating the fundamental processes at work in the crystal grinding
systems of Viedma [Phys Rev Lett 94, 065504, (2005)] and Noorduin [J Am Chem
Soc 130, 1158, (2008)]. We simplify the model as far as possible to uncover the
fundamental competitive process which causes the symmetry-breaking, and analyse
other simplifications which might be expected to show symmetry-breaking.
| [
{
"created": "Mon, 19 Jul 2010 15:35:13 GMT",
"version": "v1"
}
] | 2010-07-20 | [
[
"Wattis",
"Jonathan AD",
""
]
] | We review the existing mathematical models which describe physicochemical mechanisms capable of producing a symmetry-breaking transition to a state in which one chirality dominates the other. A new model is proposed, with the aim of elucidating the fundamental processes at work in the crystal grinding systems of Viedma [Phys Rev Lett 94, 065504, (2005)] and Noorduin [J Am Chem Soc 130, 1158, (2008)]. We simplify the model as far as possible to uncover the fundamental competitive process which causes the symmetry-breaking, and analyse other simplifications which might be expected to show symmetry-breaking. |
1212.1488 | Artem Novozhilov S | Alexander S. Bratus, Chin-Kun Hu, Mikhail V. Safro, and Artem S.
Novozhilov | On diffusive stability of Eigen's quasispecies model | 16 pages, 1 figure, several typos are fixed | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Eigen's quasispecies system with explicit space and global regulation is
considered. Limit behavior and stability of the system in a functional space
under perturbations of a diffusion matrix with nonnegative spectrum are
investigated. It is proven that if the diffusion matrix has only positive
eigenvalues then the solutions of the distributed system converge to the
equilibrium solution of the corresponding local dynamical system. These results
imply that the error threshold does not change if the spatial interactions
under the principle of global regulation are taken into account.
| [
{
"created": "Thu, 6 Dec 2012 22:27:20 GMT",
"version": "v1"
},
{
"created": "Mon, 30 Dec 2013 19:35:15 GMT",
"version": "v2"
}
] | 2013-12-31 | [
[
"Bratus",
"Alexander S.",
""
],
[
"Hu",
"Chin-Kun",
""
],
[
"Safro",
"Mikhail V.",
""
],
[
"Novozhilov",
"Artem S.",
""
]
] | Eigen's quasispecies system with explicit space and global regulation is considered. Limit behavior and stability of the system in a functional space under perturbations of a diffusion matrix with nonnegative spectrum are investigated. It is proven that if the diffusion matrix has only positive eigenvalues then the solutions of the distributed system converge to the equilibrium solution of the corresponding local dynamical system. These results imply that the error threshold does not change if the spatial interactions under the principle of global regulation are taken into account. |
1202.2353 | Branko Dragovich | Branko Dragovich | p-Adic Structure of the Genetic Code | 21 pages, 7 tables. arXiv admin note: substantial text overlap with
arXiv:0707.3043 and arXiv:0911.4014 | NeuroQuantology 9 (2011) 716-727 | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The genetic code is connection between 64 codons, which are building blocks
of the genes, and 20 amino acids, which are building blocks of the proteins. In
addition to coding amino acids, a few codons code stop signal, which is at the
end of genes, i.e. it terminates process of protein synthesis. This article is
a review of simple modelling of the genetic code and related subjects by
concept of p-adic distance. It also contains some new results. In particular,
the article presents appropriate structure of the codon space, degeneration and
possible evolution of the genetic code. p-Adic modelling of the genetic code is
viewed as the first step in further application of p-adic tools in the
information sector of life science.
| [
{
"created": "Fri, 10 Feb 2012 16:58:47 GMT",
"version": "v1"
}
] | 2012-02-14 | [
[
"Dragovich",
"Branko",
""
]
] | The genetic code is connection between 64 codons, which are building blocks of the genes, and 20 amino acids, which are building blocks of the proteins. In addition to coding amino acids, a few codons code stop signal, which is at the end of genes, i.e. it terminates process of protein synthesis. This article is a review of simple modelling of the genetic code and related subjects by concept of p-adic distance. It also contains some new results. In particular, the article presents appropriate structure of the codon space, degeneration and possible evolution of the genetic code. p-Adic modelling of the genetic code is viewed as the first step in further application of p-adic tools in the information sector of life science. |
1003.0575 | Jose del Carmen Rodriguez Santamaria | Jose Rodriguez | The genome is software and evolution is a software developer | 53 pages, 1 figure | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The genome is software because it a set of verbal instructions for a
programmable computer, the ribosome. The theory of evolution now reads:
evolution is the software developer responsible for the existence of the
genome. We claim that this setting, whose official name is genetic programming,
is necessary and sufficient to discuss all important questions about evolution.
A great effort has been made to pass from wording to science, i.e., from naive
theories to robust models to predictions to testing for falsification.
| [
{
"created": "Tue, 2 Mar 2010 12:45:51 GMT",
"version": "v1"
}
] | 2010-03-03 | [
[
"Rodriguez",
"Jose",
""
]
] | The genome is software because it a set of verbal instructions for a programmable computer, the ribosome. The theory of evolution now reads: evolution is the software developer responsible for the existence of the genome. We claim that this setting, whose official name is genetic programming, is necessary and sufficient to discuss all important questions about evolution. A great effort has been made to pass from wording to science, i.e., from naive theories to robust models to predictions to testing for falsification. |
q-bio/0612029 | Jingshan Zhang | Jingshan Zhang and Eugene I. Shakhnovich | Sensitivity dependent model of protein-protein interaction networks | organization improved, and experimental evidence of predicted
dependence on sensitivity is addressed | Physical Biology 5, 036011 (2008) | 10.1088/1478-3975/5/3/036011 | null | q-bio.MN physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The scale free structure p(k)~k^{-gamma} of protein-protein interaction
networks can be reproduced by a static physical model in simulation. We inspect
the model theoretically, and find the key reason for the model to generate
apparent scale free degree distributions. This explanation provides a generic
mechanism of "scale free" networks. Moreover, we predict the dependence of
gamma on experimental protein concentrations or other sensitivity factors in
detecting interactions, and find experimental evidence to support the
prediction.
| [
{
"created": "Fri, 15 Dec 2006 17:26:26 GMT",
"version": "v1"
},
{
"created": "Wed, 28 Mar 2007 19:10:39 GMT",
"version": "v2"
},
{
"created": "Fri, 5 Sep 2008 19:39:32 GMT",
"version": "v3"
}
] | 2015-06-26 | [
[
"Zhang",
"Jingshan",
""
],
[
"Shakhnovich",
"Eugene I.",
""
]
] | The scale free structure p(k)~k^{-gamma} of protein-protein interaction networks can be reproduced by a static physical model in simulation. We inspect the model theoretically, and find the key reason for the model to generate apparent scale free degree distributions. This explanation provides a generic mechanism of "scale free" networks. Moreover, we predict the dependence of gamma on experimental protein concentrations or other sensitivity factors in detecting interactions, and find experimental evidence to support the prediction. |
1908.03342 | Farhang Yeganegi | Salman Mohamadi, Farhang Yeganegi, Hamidreza Amindavar | A New Framework For Spatial Modeling And Synthesis of Genome Sequence | 6 pages, 5 figures | null | null | null | q-bio.OT | http://creativecommons.org/licenses/by/4.0/ | This paper provides a framework in order to statistically model sequences
from human genome, which is allowing a formulation to synthesize gene
sequences. We start by converting the alphabetic sequence of genome to decimal
sequence by Huffman coding. Then, this decimal sequence is decomposed by HP
filter into two components, trend and cyclic. Next, a statistical modeling,
ARIMA-GARCH, is implemented on trend component exhibiting heteroskedasticity,
autoregressive integrated moving average (ARIMA) to capture the linear
characteristics of the sequence and later, generalized autoregressive
conditional heteroskedasticity (GARCH) is then appropriated for the statistical
nonlinearity of genome sequence. This modeling approach synthesizes a given
genome sequence regarding to its statistical features. Finally, the PDF of a
given sequence is estimated using Gaussian mixture model and based on estimated
PDF, we determine a new PDF presenting sequences that counteract statistically
the original sequence. Our strategy is performed on several genes as well as
HIV nucleotide sequence and corresponding results is presented.
| [
{
"created": "Fri, 9 Aug 2019 07:21:13 GMT",
"version": "v1"
}
] | 2019-08-12 | [
[
"Mohamadi",
"Salman",
""
],
[
"Yeganegi",
"Farhang",
""
],
[
"Amindavar",
"Hamidreza",
""
]
] | This paper provides a framework in order to statistically model sequences from human genome, which is allowing a formulation to synthesize gene sequences. We start by converting the alphabetic sequence of genome to decimal sequence by Huffman coding. Then, this decimal sequence is decomposed by HP filter into two components, trend and cyclic. Next, a statistical modeling, ARIMA-GARCH, is implemented on trend component exhibiting heteroskedasticity, autoregressive integrated moving average (ARIMA) to capture the linear characteristics of the sequence and later, generalized autoregressive conditional heteroskedasticity (GARCH) is then appropriated for the statistical nonlinearity of genome sequence. This modeling approach synthesizes a given genome sequence regarding to its statistical features. Finally, the PDF of a given sequence is estimated using Gaussian mixture model and based on estimated PDF, we determine a new PDF presenting sequences that counteract statistically the original sequence. Our strategy is performed on several genes as well as HIV nucleotide sequence and corresponding results is presented. |
2108.13486 | Benjamin Hayden | Benjamin Hayden, Hyun Soo Park, Jan Zimmermann | Automated Tracking of Primate Behavior | Invited manuscript to AJP | null | null | null | q-bio.QM | http://creativecommons.org/publicdomain/zero/1.0/ | Understanding primate behavior is a mission-critical goal of both biology and
biomedicine. Despite the importance of behavior, our ability to rigorously
quantify it has heretofore been limited to low-information measures like
preference, looking time, and reaction time, or to non-scaleable measures like
ethograms. However, recent technological advances have led to a major
revolution in behavioral measurement. Specifically, digital video cameras and
automated pose tracking software can provide detailed measures of full body
position (i.e., pose) of multiple primates over time (i.e., behavior) with high
spatial and temporal resolution. Pose-tracking technology in turn can be used
to detect behavioral states, such as eating, sleeping, and mating. The
availability of such data has in turn spurred developments in data analysis
techniques. Together, these changes are poised to lead to major advances in
scientific fields that rely on behavioral as a dependent variable. In this
review, we situate the tracking revolution in the history of the study of
behavior, argue for investment in and development of analytical and research
techniques that can profit from the advent of the era of big behavior, and
propose that zoos will have a central role to play in this era.
| [
{
"created": "Mon, 30 Aug 2021 19:16:00 GMT",
"version": "v1"
}
] | 2021-09-01 | [
[
"Hayden",
"Benjamin",
""
],
[
"Park",
"Hyun Soo",
""
],
[
"Zimmermann",
"Jan",
""
]
] | Understanding primate behavior is a mission-critical goal of both biology and biomedicine. Despite the importance of behavior, our ability to rigorously quantify it has heretofore been limited to low-information measures like preference, looking time, and reaction time, or to non-scaleable measures like ethograms. However, recent technological advances have led to a major revolution in behavioral measurement. Specifically, digital video cameras and automated pose tracking software can provide detailed measures of full body position (i.e., pose) of multiple primates over time (i.e., behavior) with high spatial and temporal resolution. Pose-tracking technology in turn can be used to detect behavioral states, such as eating, sleeping, and mating. The availability of such data has in turn spurred developments in data analysis techniques. Together, these changes are poised to lead to major advances in scientific fields that rely on behavioral as a dependent variable. In this review, we situate the tracking revolution in the history of the study of behavior, argue for investment in and development of analytical and research techniques that can profit from the advent of the era of big behavior, and propose that zoos will have a central role to play in this era. |
1502.06025 | Benjamin Good | Benjamin M. Good, Gavin Ha, Chi K. Ho, Mark D. Wilkinson | OntoLoki: an automatic, instance-based method for the evaluation of
biological ontologies on the Semantic Web | null | null | null | null | q-bio.QM cs.AI | http://creativecommons.org/licenses/by/3.0/ | The delineation of logical definitions for each class in an ontology and the
consistent application of these definitions to the assignment of instances to
classes are important criteria for ontology evaluation. If ontologies are
specified with property-based restrictions on class membership, then such
consistency can be checked automatically. If no such logical restrictions are
applied, as is the case with many biological ontologies, there are currently no
automated methods for measuring the semantic consistency of instance assignment
on an ontology-wide scale, nor for inferring the patterns of properties that
might define a particular class. We constructed a program that takes as its
input an OWL/RDF knowledge base containing an ontology, instances associated
with each of the classes in the ontology, and properties of those instances.
For each class, it outputs: 1) a rule for determining class membership based on
the properties of the instances and 2) a quantitative score for the class that
reflects the ability of the identified rule to correctly predict class
membership for the instances in the knowledge base. We evaluated this program
using both artificial knowledge bases of known quality and real, widely used
ontologies. The results indicate that the suggested method can be used to
conduct objective, automatic, data-driven evaluations of biological ontologies
without formal class definitions in regards to the property-based consistency
of instance-assignment. This inductive method complements existing, purely
deductive approaches to automatic consistency checking, offering not just the
potential to help in the ontology engineering process but also in the knowledge
discovery process.
| [
{
"created": "Fri, 20 Feb 2015 22:34:10 GMT",
"version": "v1"
}
] | 2015-02-24 | [
[
"Good",
"Benjamin M.",
""
],
[
"Ha",
"Gavin",
""
],
[
"Ho",
"Chi K.",
""
],
[
"Wilkinson",
"Mark D.",
""
]
] | The delineation of logical definitions for each class in an ontology and the consistent application of these definitions to the assignment of instances to classes are important criteria for ontology evaluation. If ontologies are specified with property-based restrictions on class membership, then such consistency can be checked automatically. If no such logical restrictions are applied, as is the case with many biological ontologies, there are currently no automated methods for measuring the semantic consistency of instance assignment on an ontology-wide scale, nor for inferring the patterns of properties that might define a particular class. We constructed a program that takes as its input an OWL/RDF knowledge base containing an ontology, instances associated with each of the classes in the ontology, and properties of those instances. For each class, it outputs: 1) a rule for determining class membership based on the properties of the instances and 2) a quantitative score for the class that reflects the ability of the identified rule to correctly predict class membership for the instances in the knowledge base. We evaluated this program using both artificial knowledge bases of known quality and real, widely used ontologies. The results indicate that the suggested method can be used to conduct objective, automatic, data-driven evaluations of biological ontologies without formal class definitions in regards to the property-based consistency of instance-assignment. This inductive method complements existing, purely deductive approaches to automatic consistency checking, offering not just the potential to help in the ontology engineering process but also in the knowledge discovery process. |
1710.03355 | Yue Zhao | Yue Zhao | An Extension of Deep Pathway Analysis: A Pathway Route Analysis
Framework Incorporating Multi-dimensional Cancer Genomics Data | null | null | null | null | q-bio.GN cs.OH stat.ME | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Recent breakthroughs in cancer research have come via the up-and-coming field
of pathway analysis. By applying statistical methods to prior known gene and
protein regulatory information, pathway analysis provides a meaningful way to
interpret genomic data. While many gene/protein regulatory relationships have
been studied, never before has such a significant amount data been made
available in organized forms of gene/protein regulatory networks and pathways.
However, pathway analysis research is still in its infancy, especially when
applying it to solve practical problems.
In this paper we propose a new method of studying biological pathways, one
that cross analyzes mutation information, transcriptome and proteomics data.
Using this outcome, we identify routes of aberrant pathways potentially
responsible for the etiology of disease. Each pathway route is encoded as a
bayesian network which is initialized with a sequence of conditional
probabilities specifically designed to encode directionality of regulatory
relationships encoded in the pathways. Far more complex interactions, such as
phosphorylation and methylation, among others, in the pathways can be modeled
using this approach. The effectiveness of our model is demonstrated through its
ability to distinguish real pathways from decoys on TCGA mRNA-seq, mutation,
Copy Number Variation and phosphorylation data for both Breast cancer and
Ovarian cancer study. The majority of pathways distinguished can be confirmed
by biological literature. Moreover, the proportion of correctly indentified
pathways is \% higher than previous work where only mRNA-seq mutation data is
incorporated for breast cancer patients. Consequently, such an in-depth pathway
analysis incorporating more diverse data can give rise to the accuracy of
perturbed pathway detection.
| [
{
"created": "Tue, 10 Oct 2017 00:04:04 GMT",
"version": "v1"
}
] | 2017-10-11 | [
[
"Zhao",
"Yue",
""
]
] | Recent breakthroughs in cancer research have come via the up-and-coming field of pathway analysis. By applying statistical methods to prior known gene and protein regulatory information, pathway analysis provides a meaningful way to interpret genomic data. While many gene/protein regulatory relationships have been studied, never before has such a significant amount data been made available in organized forms of gene/protein regulatory networks and pathways. However, pathway analysis research is still in its infancy, especially when applying it to solve practical problems. In this paper we propose a new method of studying biological pathways, one that cross analyzes mutation information, transcriptome and proteomics data. Using this outcome, we identify routes of aberrant pathways potentially responsible for the etiology of disease. Each pathway route is encoded as a bayesian network which is initialized with a sequence of conditional probabilities specifically designed to encode directionality of regulatory relationships encoded in the pathways. Far more complex interactions, such as phosphorylation and methylation, among others, in the pathways can be modeled using this approach. The effectiveness of our model is demonstrated through its ability to distinguish real pathways from decoys on TCGA mRNA-seq, mutation, Copy Number Variation and phosphorylation data for both Breast cancer and Ovarian cancer study. The majority of pathways distinguished can be confirmed by biological literature. Moreover, the proportion of correctly indentified pathways is \% higher than previous work where only mRNA-seq mutation data is incorporated for breast cancer patients. Consequently, such an in-depth pathway analysis incorporating more diverse data can give rise to the accuracy of perturbed pathway detection. |
1406.7391 | Fabrizio De Vico Fallani | Fabrizio De Vico Fallani, Jonas Richiardi, Mario Chavez, Sophie Achard | Graph analysis of functional brain networks: practical issues in
translational neuroscience | null | null | 10.1098/rstb.2013.0521 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The brain can be regarded as a network: a connected system where nodes, or
units, represent different specialized regions and links, or connections,
represent communication pathways. From a functional perspective communication
is coded by temporal dependence between the activities of different brain
areas. In the last decade, the abstract representation of the brain as a graph
has allowed to visualize functional brain networks and describe their
non-trivial topological properties in a compact and objective way. Nowadays,
the use of graph analysis in translational neuroscience has become essential to
quantify brain dysfunctions in terms of aberrant reconfiguration of functional
brain networks. Despite its evident impact, graph analysis of functional brain
networks is not a simple toolbox that can be blindly applied to brain signals.
On the one hand, it requires a know-how of all the methodological steps of the
processing pipeline that manipulates the input brain signals and extract the
functional network properties. On the other hand, a knowledge of the neural
phenomenon under study is required to perform physiological-relevant analysis.
The aim of this review is to provide practical indications to make sense of
brain network analysis and contrast counterproductive attitudes.
| [
{
"created": "Sat, 28 Jun 2014 11:51:07 GMT",
"version": "v1"
}
] | 2014-09-10 | [
[
"Fallani",
"Fabrizio De Vico",
""
],
[
"Richiardi",
"Jonas",
""
],
[
"Chavez",
"Mario",
""
],
[
"Achard",
"Sophie",
""
]
] | The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires a know-how of all the methodological steps of the processing pipeline that manipulates the input brain signals and extract the functional network properties. On the other hand, a knowledge of the neural phenomenon under study is required to perform physiological-relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. |
1308.0798 | John Herrick | John Herrick and Bianca Sclavi | Lineage specific reductions in genome size in salamanders are associated
with increased rates of mutation | 16 pages, 5 figures | null | null | null | q-bio.GN q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Very low levels of genetic diversity have been reported in vertebrates with
large genomes, notably salamanders and lungfish [1-3]. Interpreting differences
in heterozygosity, which reflects genetic diversity in a population, is
complicated because levels of heterozygosity vary widely between conspecific
populations, and correlate with many different physiological and demographic
variables such as body size and effective population size. Here we return to
the question of genetic variability in salamanders and report on the
relationship between evolutionary rates and genome sizes in five different
salamander families. We found that rates of evolution are exceptionally low in
salamanders as a group. Evolutionary rates are as low as those reported for
cartilaginous fish, which have the slowest rates recorded so far in vertebrates
[4]. We also found that, independent of life history, salamanders with the
smallest genomes (14 pg) are evolving at rates two to three times faster than
salamanders with the largest genomes (>50 pg). After accounting for
evolutionary duration, we conclude that more recently evolved species have
correspondingly smaller genomes compared to older taxa and concomitantly higher
rates of mutation and evolution.
| [
{
"created": "Sun, 4 Aug 2013 12:08:32 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Sep 2013 21:50:45 GMT",
"version": "v2"
}
] | 2013-09-05 | [
[
"Herrick",
"John",
""
],
[
"Sclavi",
"Bianca",
""
]
] | Very low levels of genetic diversity have been reported in vertebrates with large genomes, notably salamanders and lungfish [1-3]. Interpreting differences in heterozygosity, which reflects genetic diversity in a population, is complicated because levels of heterozygosity vary widely between conspecific populations, and correlate with many different physiological and demographic variables such as body size and effective population size. Here we return to the question of genetic variability in salamanders and report on the relationship between evolutionary rates and genome sizes in five different salamander families. We found that rates of evolution are exceptionally low in salamanders as a group. Evolutionary rates are as low as those reported for cartilaginous fish, which have the slowest rates recorded so far in vertebrates [4]. We also found that, independent of life history, salamanders with the smallest genomes (14 pg) are evolving at rates two to three times faster than salamanders with the largest genomes (>50 pg). After accounting for evolutionary duration, we conclude that more recently evolved species have correspondingly smaller genomes compared to older taxa and concomitantly higher rates of mutation and evolution. |
2208.01918 | Daniele Brambilla | Daniele Brambilla (1), Davide Maria Giacomini (1), Luca Muscarnera,
Andrea Mazzoleni (1) ((1) TheProphetAI) | DeepProphet2 -- A Deep Learning Gene Recommendation Engine | null | null | null | null | q-bio.QM cs.IR cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | New powerful tools for tackling life science problems have been created by
recent advances in machine learning. The purpose of the paper is to discuss the
potential advantages of gene recommendation performed by artificial
intelligence (AI). Indeed, gene recommendation engines try to solve this
problem: if the user is interested in a set of genes, which other genes are
likely to be related to the starting set and should be investigated? This task
was solved with a custom deep learning recommendation engine, DeepProphet2
(DP2), which is freely available to researchers worldwide via
https://www.generecommender.com?utm_source=DeepProphet2_paper&utm_medium=pdf.
Hereafter, insights behind the algorithm and its practical applications are
illustrated.
The gene recommendation problem can be addressed by mapping the genes to a
metric space where a distance can be defined to represent the real semantic
distance between them. To achieve this objective a transformer-based model has
been trained on a well-curated freely available paper corpus, PubMed. The paper
describes multiple optimization procedures that were employed to obtain the
best bias-variance trade-off, focusing on embedding size and network depth. In
this context, the model's ability to discover sets of genes implicated in
diseases and pathways was assessed through cross-validation. A simple
assumption guided the procedure: the network had no direct knowledge of
pathways and diseases but learned genes' similarities and the interactions
among them. Moreover, to further investigate the space where the neural network
represents genes, the dimensionality of the embedding was reduced, and the
results were projected onto a human-comprehensible space. In conclusion, a set
of use cases illustrates the algorithm's potential applications in a real word
setting.
| [
{
"created": "Wed, 3 Aug 2022 08:54:13 GMT",
"version": "v1"
},
{
"created": "Tue, 23 Aug 2022 10:52:52 GMT",
"version": "v2"
},
{
"created": "Mon, 13 Feb 2023 11:11:00 GMT",
"version": "v3"
},
{
"created": "Wed, 22 Mar 2023 11:15:58 GMT",
"version": "v4"
}
] | 2023-03-23 | [
[
"Brambilla",
"Daniele",
"",
"TheProphetAI"
],
[
"Giacomini",
"Davide Maria",
"",
"TheProphetAI"
],
[
"Muscarnera",
"Luca",
"",
"TheProphetAI"
],
[
"Mazzoleni",
"Andrea",
"",
"TheProphetAI"
]
] | New powerful tools for tackling life science problems have been created by recent advances in machine learning. The purpose of the paper is to discuss the potential advantages of gene recommendation performed by artificial intelligence (AI). Indeed, gene recommendation engines try to solve this problem: if the user is interested in a set of genes, which other genes are likely to be related to the starting set and should be investigated? This task was solved with a custom deep learning recommendation engine, DeepProphet2 (DP2), which is freely available to researchers worldwide via https://www.generecommender.com?utm_source=DeepProphet2_paper&utm_medium=pdf. Hereafter, insights behind the algorithm and its practical applications are illustrated. The gene recommendation problem can be addressed by mapping the genes to a metric space where a distance can be defined to represent the real semantic distance between them. To achieve this objective a transformer-based model has been trained on a well-curated freely available paper corpus, PubMed. The paper describes multiple optimization procedures that were employed to obtain the best bias-variance trade-off, focusing on embedding size and network depth. In this context, the model's ability to discover sets of genes implicated in diseases and pathways was assessed through cross-validation. A simple assumption guided the procedure: the network had no direct knowledge of pathways and diseases but learned genes' similarities and the interactions among them. Moreover, to further investigate the space where the neural network represents genes, the dimensionality of the embedding was reduced, and the results were projected onto a human-comprehensible space. In conclusion, a set of use cases illustrates the algorithm's potential applications in a real word setting. |
2311.08428 | Tahmina Sultana Priya | Tahmina Sultana Priya, Fan Leng, Anthony C. Luehrs, Eric W. Klee,
Alina M. Allen, Konstantinos N. Lazaridis, Danfeng (Daphne) Yao, Shulan Tian | Deep Phenotyping of Non-Alcoholic Fatty Liver Disease Patients with
Genetic Factors for Insights into the Complex Disease | Extended Abstract presented at Machine Learning for Health (ML4H)
symposium 2023, December 10th, 2023, New Orleans, United States, 11 pages | null | null | null | q-bio.QM cs.LG | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver
disorder characterized by the excessive accumulation of fat in the liver in
individuals who do not consume significant amounts of alcohol, including risk
factors like obesity, insulin resistance, type 2 diabetes, etc. We aim to
identify subgroups of NAFLD patients based on demographic, clinical, and
genetic characteristics for precision medicine. The genomic and phenotypic data
(3,408 cases and 4,739 controls) for this study were gathered from participants
in Mayo Clinic Tapestry Study (IRB#19-000001) and their electric health
records, including their demographic, clinical, and comorbidity data, and the
genotype information through whole exome sequencing performed at Helix using
the Exome+$^\circledR$ Assay according to standard procedure
(www$.$helix$.$com). Factors highly relevant to NAFLD were determined by the
chi-square test and stepwise backward-forward regression model. Latent class
analysis (LCA) was performed on NAFLD cases using significant indicator
variables to identify subgroups. The optimal clustering revealed 5 latent
subgroups from 2,013 NAFLD patients (mean age 60.6 years and 62.1% women),
while a polygenic risk score based on 6 single-nucleotide polymorphism (SNP)
variants and disease outcomes were used to analyze the subgroups. The groups
are characterized by metabolic syndrome, obesity, different comorbidities,
psychoneurological factors, and genetic factors. Odds ratios were utilized to
compare the risk of complex diseases, such as fibrosis, cirrhosis, and
hepatocellular carcinoma (HCC), as well as liver failure between the clusters.
Cluster 2 has a significantly higher complex disease outcome compared to other
clusters. Keywords: Fatty liver disease; Polygenic risk score; Precision
medicine; Deep phenotyping; NAFLD comorbidities; Latent class analysis.
| [
{
"created": "Mon, 13 Nov 2023 19:31:12 GMT",
"version": "v1"
}
] | 2023-11-16 | [
[
"Priya",
"Tahmina Sultana",
"",
"Daphne"
],
[
"Leng",
"Fan",
"",
"Daphne"
],
[
"Luehrs",
"Anthony C.",
"",
"Daphne"
],
[
"Klee",
"Eric W.",
"",
"Daphne"
],
[
"Allen",
"Alina M.",
"",
"Daphne"
],
[
"Lazaridis",
"Konstantinos N.",
"",
"Daphne"
],
[
"Danfeng",
"",
"",
"Daphne"
],
[
"Yao",
"",
""
],
[
"Tian",
"Shulan",
""
]
] | Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver disorder characterized by the excessive accumulation of fat in the liver in individuals who do not consume significant amounts of alcohol, including risk factors like obesity, insulin resistance, type 2 diabetes, etc. We aim to identify subgroups of NAFLD patients based on demographic, clinical, and genetic characteristics for precision medicine. The genomic and phenotypic data (3,408 cases and 4,739 controls) for this study were gathered from participants in Mayo Clinic Tapestry Study (IRB#19-000001) and their electric health records, including their demographic, clinical, and comorbidity data, and the genotype information through whole exome sequencing performed at Helix using the Exome+$^\circledR$ Assay according to standard procedure (www$.$helix$.$com). Factors highly relevant to NAFLD were determined by the chi-square test and stepwise backward-forward regression model. Latent class analysis (LCA) was performed on NAFLD cases using significant indicator variables to identify subgroups. The optimal clustering revealed 5 latent subgroups from 2,013 NAFLD patients (mean age 60.6 years and 62.1% women), while a polygenic risk score based on 6 single-nucleotide polymorphism (SNP) variants and disease outcomes were used to analyze the subgroups. The groups are characterized by metabolic syndrome, obesity, different comorbidities, psychoneurological factors, and genetic factors. Odds ratios were utilized to compare the risk of complex diseases, such as fibrosis, cirrhosis, and hepatocellular carcinoma (HCC), as well as liver failure between the clusters. Cluster 2 has a significantly higher complex disease outcome compared to other clusters. Keywords: Fatty liver disease; Polygenic risk score; Precision medicine; Deep phenotyping; NAFLD comorbidities; Latent class analysis. |
1901.06431 | Martin Frasch | Christophe L. Herry, Patrick Burns, Andre Desrochers, Gilles Fecteau,
Lucien Daniel Durosier, Mingju Cao, Andrew JE Seely and Martin G. Frasch | Vagal contributions to fetal heart rate variability: an omics approach | null | null | 10.1088/1361-6579/ab21ae | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Fetal heart rate variability (fHRV) is an important indicator of health and
disease, yet its physiological origins, neural contributions in particular, are
not well understood. We aimed to develop novel experimental and data analytical
approaches to identify fHRV measures reflecting the vagus nerve contributions
to fHRV. In near-term ovine fetuses, a comprehensive set of 46 fHRV measures
was computed from fetal pre-cordial electrocardiogram recorded during surgery
and 72 hours later without (n=24) and with intra-surgical bilateral cervical
vagotomy (n=15). The fetal heart rate did not change due to vagotomy. We
identify fHRV measures specific to the vagal modulation of fHRV: Multiscale
time irreversibility asymmetry index (AsymI), Detrended fluctuation analysis
(DFA) alpha1, Kullback-Leibler permutation entropy (KLPE) and Scale dependent
Lyapunov exponent slope (SDLE alpha). We provide a systematic delineation of
vagal contributions to fHRV across signal-analytical domains which should be
relevant for the emerging field of bioelectronic medicine and the deciphering
of the vagus code. Our findings also have clinical significance for in utero
monitoring of fetal health during surgery.
| [
{
"created": "Fri, 18 Jan 2019 22:12:39 GMT",
"version": "v1"
},
{
"created": "Mon, 18 Mar 2019 20:29:18 GMT",
"version": "v2"
}
] | 2019-07-19 | [
[
"Herry",
"Christophe L.",
""
],
[
"Burns",
"Patrick",
""
],
[
"Desrochers",
"Andre",
""
],
[
"Fecteau",
"Gilles",
""
],
[
"Durosier",
"Lucien Daniel",
""
],
[
"Cao",
"Mingju",
""
],
[
"Seely",
"Andrew JE",
""
],
[
"Frasch",
"Martin G.",
""
]
] | Fetal heart rate variability (fHRV) is an important indicator of health and disease, yet its physiological origins, neural contributions in particular, are not well understood. We aimed to develop novel experimental and data analytical approaches to identify fHRV measures reflecting the vagus nerve contributions to fHRV. In near-term ovine fetuses, a comprehensive set of 46 fHRV measures was computed from fetal pre-cordial electrocardiogram recorded during surgery and 72 hours later without (n=24) and with intra-surgical bilateral cervical vagotomy (n=15). The fetal heart rate did not change due to vagotomy. We identify fHRV measures specific to the vagal modulation of fHRV: Multiscale time irreversibility asymmetry index (AsymI), Detrended fluctuation analysis (DFA) alpha1, Kullback-Leibler permutation entropy (KLPE) and Scale dependent Lyapunov exponent slope (SDLE alpha). We provide a systematic delineation of vagal contributions to fHRV across signal-analytical domains which should be relevant for the emerging field of bioelectronic medicine and the deciphering of the vagus code. Our findings also have clinical significance for in utero monitoring of fetal health during surgery. |
1911.06603 | Pavel Karpov Dr | Pavel Karpov and Guillaume Godin and Igor V. Tetko | Transformer-CNN: Fast and Reliable tool for QSAR | null | null | 10.1186/s13321-020-00423-w | null | q-bio.QM cs.CL cs.LG | http://creativecommons.org/licenses/by-nc-sa/4.0/ | We present SMILES-embeddings derived from the internal encoder state of a
Transformer [1] model trained to canonize SMILES as a Seq2Seq problem. Using a
CharNN [2] architecture upon the embeddings results in higher quality
interpretable QSAR/QSPR models on diverse benchmark datasets including
regression and classification tasks. The proposed Transformer-CNN method uses
SMILES augmentation for training and inference, and thus the prognosis is based
on an internal consensus. That both the augmentation and transfer learning are
based on embeddings allows the method to provide good results for small
datasets. We discuss the reasons for such effectiveness and draft future
directions for the development of the method. The source code and the
embeddings needed to train a QSAR model are available on
https://github.com/bigchem/transformer-cnn. The repository also has a
standalone program for QSAR prognosis which calculates individual atoms
contributions, thus interpreting the model's result. OCHEM [3] environment
(https://ochem.eu) hosts the on-line implementation of the method proposed.
| [
{
"created": "Mon, 21 Oct 2019 12:49:55 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Feb 2020 13:35:29 GMT",
"version": "v2"
},
{
"created": "Wed, 26 Feb 2020 14:43:18 GMT",
"version": "v3"
}
] | 2020-09-23 | [
[
"Karpov",
"Pavel",
""
],
[
"Godin",
"Guillaume",
""
],
[
"Tetko",
"Igor V.",
""
]
] | We present SMILES-embeddings derived from the internal encoder state of a Transformer [1] model trained to canonize SMILES as a Seq2Seq problem. Using a CharNN [2] architecture upon the embeddings results in higher quality interpretable QSAR/QSPR models on diverse benchmark datasets including regression and classification tasks. The proposed Transformer-CNN method uses SMILES augmentation for training and inference, and thus the prognosis is based on an internal consensus. That both the augmentation and transfer learning are based on embeddings allows the method to provide good results for small datasets. We discuss the reasons for such effectiveness and draft future directions for the development of the method. The source code and the embeddings needed to train a QSAR model are available on https://github.com/bigchem/transformer-cnn. The repository also has a standalone program for QSAR prognosis which calculates individual atoms contributions, thus interpreting the model's result. OCHEM [3] environment (https://ochem.eu) hosts the on-line implementation of the method proposed. |
1411.3956 | Gabriel Ocker | Gabriel Koch Ocker and Ashok Litwin-Kumar and Brent Doiron | Self-organization of microcircuits in networks of neurons with plastic
synapses | first edit: typo in arxiv title, rearranged article to put methods
after discussion. second edit: results section significantly rewritten for
style and presentation, figure 9 revised | null | null | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The synaptic connectivity of cortical networks features an overrepresentation
of certain wiring motifs compared to simple random-network models. This
structure is shaped, in part, by synaptic plasticity that promotes or
suppresses connections between neurons depending on their spiking activity.
Frequently, theoretical studies focus on how feedforward inputs drive
plasticity to create this network structure. We study the complementary
scenario of self-organized structure in a recurrent network, with spike
timing-dependent plasticity driven by spontaneous dynamics. We develop a
self-consistent theory that describes the evolution of network structure by
combining fast spiking covariance with a fast-slow theory for synaptic weight
dynamics. Through a finite-size expansion of network dynamics, we obtain a
low-dimensional set of nonlinear differential equations for the evolution of
two-synapse connectivity motifs. With this theory in hand, we explore how the
form of the plasticity rule drives the evolution of microcircuits in cortical
networks. When potentiation and depression are in approximate balance, synaptic
dynamics depend on the frequency of weighted divergent, convergent, and chain
motifs. For additive, Hebbian STDP, these motif interactions create
instabilities in synaptic dynamics that either promote or suppress the initial
network structure. Our work provides a consistent theoretical framework for
studying how spiking activity in recurrent networks interacts with synaptic
plasticity to determine network structure.
| [
{
"created": "Fri, 14 Nov 2014 16:24:42 GMT",
"version": "v1"
},
{
"created": "Sat, 22 Nov 2014 20:41:51 GMT",
"version": "v2"
},
{
"created": "Sat, 20 Dec 2014 17:45:43 GMT",
"version": "v3"
}
] | 2014-12-23 | [
[
"Ocker",
"Gabriel Koch",
""
],
[
"Litwin-Kumar",
"Ashok",
""
],
[
"Doiron",
"Brent",
""
]
] | The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory that describes the evolution of network structure by combining fast spiking covariance with a fast-slow theory for synaptic weight dynamics. Through a finite-size expansion of network dynamics, we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on the frequency of weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP, these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. |
2004.06033 | Jan Vandenbroucke | Jan P Vandenbroucke, Elizabeth B Brickley, Christina M J E
Vandenbroucke-Grauls, Neil Pearce | The test-negative design with additional population controls: a
practical approach to rapidly obtain information on the causes of the
SARS-CoV-2 epidemic | 13 pages, 1 figure, Appendices 9 pages. PMID: 32841988 | Epidemiology: November 2020 - Volume 31 - Issue 6 - p 836-843 | 10.1097/EDE.0000000000001251 | null | q-bio.PE stat.AP | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Testing of symptomatic persons for infection with SARS-CoV-2 is occurring
worldwide. We propose two types of case-control studies that can be carried out
jointly in test-settings for symptomatic persons. The first, the test-negative
case-control design (TND) is the easiest to implement; it only demands
collecting information about potential risk factors for COVID-19 from the
tested symptomatic persons. The second, standard case-control studies with
population controls, requires the collection of data on one or more population
controls for each person who is tested in the test facilities, so that
test-positives and test-negatives can each be compared with population
controls. The TND will detect differences in risk factors between symptomatic
persons who have COVID-19 (test-positives) and those who have other respiratory
infections (test-negatives). However, risk factors with effect sizes of equal
magnitude for both COVID-19 and other respiratory infections will not be
identified by the TND. Therefore, we discuss how to add population controls to
compare with the test-positives and the test-negatives, yielding two additional
case-control studies. We describe two options for population control groups:
one composed of accompanying persons to the test facilities, the other drawn
from existing country-wide health care databases. We also describe other
possibilities for population controls. Combining the TND with population
controls yields a triangulation approach that distinguishes between exposures
that are risk factors for both COVID-19 and other respiratory infections, and
exposures that are risk factors for just COVID-19. This combined design can be
applied to future epidemics, but also to study causes of non-epidemic disease.
| [
{
"created": "Mon, 13 Apr 2020 16:05:35 GMT",
"version": "v1"
},
{
"created": "Thu, 14 May 2020 12:49:59 GMT",
"version": "v2"
},
{
"created": "Tue, 7 Jul 2020 14:34:57 GMT",
"version": "v3"
}
] | 2021-06-08 | [
[
"Vandenbroucke",
"Jan P",
""
],
[
"Brickley",
"Elizabeth B",
""
],
[
"Vandenbroucke-Grauls",
"Christina M J E",
""
],
[
"Pearce",
"Neil",
""
]
] | Testing of symptomatic persons for infection with SARS-CoV-2 is occurring worldwide. We propose two types of case-control studies that can be carried out jointly in test-settings for symptomatic persons. The first, the test-negative case-control design (TND) is the easiest to implement; it only demands collecting information about potential risk factors for COVID-19 from the tested symptomatic persons. The second, standard case-control studies with population controls, requires the collection of data on one or more population controls for each person who is tested in the test facilities, so that test-positives and test-negatives can each be compared with population controls. The TND will detect differences in risk factors between symptomatic persons who have COVID-19 (test-positives) and those who have other respiratory infections (test-negatives). However, risk factors with effect sizes of equal magnitude for both COVID-19 and other respiratory infections will not be identified by the TND. Therefore, we discuss how to add population controls to compare with the test-positives and the test-negatives, yielding two additional case-control studies. We describe two options for population control groups: one composed of accompanying persons to the test facilities, the other drawn from existing country-wide health care databases. We also describe other possibilities for population controls. Combining the TND with population controls yields a triangulation approach that distinguishes between exposures that are risk factors for both COVID-19 and other respiratory infections, and exposures that are risk factors for just COVID-19. This combined design can be applied to future epidemics, but also to study causes of non-epidemic disease. |
0903.2210 | Mark Kramer | Mark A. Kramer, Uri T. Eden, Sydney S. Cash, Eric D. Kolaczyk | Network inference - with confidence - from multivariate time series | 12 pages, 7 figures (low resolution), submitted | null | 10.1103/PhysRevE.79.061916 | null | q-bio.QM q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Networks - collections of interacting elements or nodes - abound in the
natural and manmade worlds. For many networks, complex spatiotemporal dynamics
stem from patterns of physical interactions unknown to us. To infer these
interactions, it is common to include edges between those nodes whose time
series exhibit sufficient functional connectivity, typically defined as a
measure of coupling exceeding a pre-determined threshold. However, when
uncertainty exists in the original network measurements, uncertainty in the
inferred network is likely, and hence a statistical propagation-of-error is
needed. In this manuscript, we describe a principled and systematic procedure
for the inference of functional connectivity networks from multivariate time
series data. Our procedure yields as output both the inferred network and a
quantification of uncertainty of the most fundamental interest: uncertainty in
the number of edges. To illustrate this approach, we apply our procedure to
simulated data and electrocorticogram data recorded from a human subject during
an epileptic seizure. We demonstrate that the procedure is accurate and robust
in both the determination of edges and the reporting of uncertainty associated
with that determination.
| [
{
"created": "Thu, 12 Mar 2009 16:25:38 GMT",
"version": "v1"
}
] | 2015-05-13 | [
[
"Kramer",
"Mark A.",
""
],
[
"Eden",
"Uri T.",
""
],
[
"Cash",
"Sydney S.",
""
],
[
"Kolaczyk",
"Eric D.",
""
]
] | Networks - collections of interacting elements or nodes - abound in the natural and manmade worlds. For many networks, complex spatiotemporal dynamics stem from patterns of physical interactions unknown to us. To infer these interactions, it is common to include edges between those nodes whose time series exhibit sufficient functional connectivity, typically defined as a measure of coupling exceeding a pre-determined threshold. However, when uncertainty exists in the original network measurements, uncertainty in the inferred network is likely, and hence a statistical propagation-of-error is needed. In this manuscript, we describe a principled and systematic procedure for the inference of functional connectivity networks from multivariate time series data. Our procedure yields as output both the inferred network and a quantification of uncertainty of the most fundamental interest: uncertainty in the number of edges. To illustrate this approach, we apply our procedure to simulated data and electrocorticogram data recorded from a human subject during an epileptic seizure. We demonstrate that the procedure is accurate and robust in both the determination of edges and the reporting of uncertainty associated with that determination. |
2309.15174 | Andrew Gordus | Andrew Margolis, Andrew Gordus | A stochastic explanation for observed local-to-global foraging states in
Caenorhabditis elegans | 6 pages, 1 figure | null | null | null | q-bio.NC q-bio.PE | http://creativecommons.org/licenses/by-nc-sa/4.0/ | Abrupt changes in behavior can often be associated with changes in underlying
behavioral states. When placed off food, the foraging behavior of C. elegans
can be described as a change between an initial local-search behavior
characterized by a high rate of reorientations, followed by a global-search
behavior characterized by sparse reorientations. This is commonly observed in
individual worms, but when numerous worms are characterized, only about half
appear to exhibit this behavior. We propose an alternative model that predicts
both abrupt and continuous changes to reorientation that does not rely on
behavioral states. This model is inspired by molecular dynamics modeling that
defines the foraging reorientation rate as a decaying parameter. By
stochastically sampling from the probability distribution defined by this rate,
both abrupt and gradual changes to reorientation rates can occur, matching
experimentally observed results. Crucially, this model does not depend on
behavioral states or information accumulation. Even though abrupt behavioral
changes do occur, they may not necessarily be indicative of abrupt changes in
behavioral states, especially when abrupt changes are not universally observed
in the population.
| [
{
"created": "Tue, 26 Sep 2023 18:19:20 GMT",
"version": "v1"
}
] | 2023-09-28 | [
[
"Margolis",
"Andrew",
""
],
[
"Gordus",
"Andrew",
""
]
] | Abrupt changes in behavior can often be associated with changes in underlying behavioral states. When placed off food, the foraging behavior of C. elegans can be described as a change between an initial local-search behavior characterized by a high rate of reorientations, followed by a global-search behavior characterized by sparse reorientations. This is commonly observed in individual worms, but when numerous worms are characterized, only about half appear to exhibit this behavior. We propose an alternative model that predicts both abrupt and continuous changes to reorientation that does not rely on behavioral states. This model is inspired by molecular dynamics modeling that defines the foraging reorientation rate as a decaying parameter. By stochastically sampling from the probability distribution defined by this rate, both abrupt and gradual changes to reorientation rates can occur, matching experimentally observed results. Crucially, this model does not depend on behavioral states or information accumulation. Even though abrupt behavioral changes do occur, they may not necessarily be indicative of abrupt changes in behavioral states, especially when abrupt changes are not universally observed in the population. |
1805.00685 | Yannick Ramonet | Yannick Ramonet, Ana\"is Tertre | Activit{\'e} motrice des truies en groupes dans les diff{\'e}rents
syst{\`e}mes de logement | in French | null | null | null | q-bio.OT | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Assessment of the motor activity of group-housed sows in commercial farms.
The objective of this study was to specify the level of motor activity of
pregnant sows housed in groups in different housing systems. Eleven commercial
farms were selected for this study. Four housing systems were represented:
small groups of five to seven sows (SG), free access stalls (FS) with exercise
area, electronic sow feeder with a stable group (ESFsta) or a dynamic group
(ESFdyn). Ten sows in mid-gestation were observed in each farm. The
observations of motor activity were made for 6 hours at the first meal or at
the start of the feeding sequence, two consecutive days and at regular
intervals of 4 minutes. The results show that the motor activity of
group-housed sows depends on the housing system. The activity is higher with
the ESFdyn system (standing: 55.7%), sows are less active in the SG system
(standing: 26.5%), and FS system is intermediate. The distance traveled by sows
in ESF system is linked to a larger area available. Thus, sows travel an
average of 362 m $\pm$ 167 m in the ESFdyn system with an average available
surface of 446 m${}^2$ whereas sows in small groups travel 50 m $\pm$ 15 m for
15 m${}^2$ available.
| [
{
"created": "Wed, 2 May 2018 09:09:38 GMT",
"version": "v1"
}
] | 2018-05-03 | [
[
"Ramonet",
"Yannick",
""
],
[
"Tertre",
"Anaïs",
""
]
] | Assessment of the motor activity of group-housed sows in commercial farms. The objective of this study was to specify the level of motor activity of pregnant sows housed in groups in different housing systems. Eleven commercial farms were selected for this study. Four housing systems were represented: small groups of five to seven sows (SG), free access stalls (FS) with exercise area, electronic sow feeder with a stable group (ESFsta) or a dynamic group (ESFdyn). Ten sows in mid-gestation were observed in each farm. The observations of motor activity were made for 6 hours at the first meal or at the start of the feeding sequence, two consecutive days and at regular intervals of 4 minutes. The results show that the motor activity of group-housed sows depends on the housing system. The activity is higher with the ESFdyn system (standing: 55.7%), sows are less active in the SG system (standing: 26.5%), and FS system is intermediate. The distance traveled by sows in ESF system is linked to a larger area available. Thus, sows travel an average of 362 m $\pm$ 167 m in the ESFdyn system with an average available surface of 446 m${}^2$ whereas sows in small groups travel 50 m $\pm$ 15 m for 15 m${}^2$ available. |
2306.10952 | Jamie Burke | Jamie Burke, Dan Pugh, Tariq Farrah, Charlene Hamid, Emily Godden, Tom
MacGillivray, Neeraj Dhaun, J. Kenneth Baillie, Stuart King and Ian J.C.
MacCormick | Evaluation of an automated choroid segmentation algorithm in a
longitudinal kidney donor and recipient cohort | 15 pages (12 + 3 supplemental), 9 figures (6 + 3 supplemental).
Submitted to and in peer review at ARVO TVST (Association for Research in
Vision and Ophthalmology, Translational Vision Science & Technology) | null | null | null | q-bio.QM eess.IV physics.med-ph | http://creativecommons.org/licenses/by/4.0/ | Purpose: To evaluate the performance of an automated choroid segmentation
algorithm in optical coherence tomography (OCT) data using a longitudinal
kidney donor and recipient cohort. Methods: We assessed 22 donors and 23
patients requiring renal transplantation over up to 1 year post-transplant. We
measured choroidal thickness (CT) and area and compared our automated CT
measurements to manual ones at the same locations. We estimated associations
between choroidal measurements and markers of renal function (estimated
glomerular filtration rate (eGFR), serum creatinine and urea) using correlation
and linear mixed-effects (LME) modelling. Results: There was good agreement
between manual and automated CT. Automated measures were more precise because
of smaller measurement error over time. External adjudication of major
discrepancies were in favour of automated measures. Significant differences
were observed in the choroid pre- and post-transplant in both cohorts, and LME
modelling revealed significant linear associations observed between choroidal
measures and renal function in recipients. Significant associations were mostly
stronger with automated CT (eGFR P<0.001, creatinine P=0.004, urea P=0.04)
compared to manual CT (eGFR P=0.002, creatinine P=0.01, urea P=0.03).
Conclusions: Our automated approach has greater precision than human-performed
manual measurements, which may explain stronger associations with renal
function compared to manual measurements. To improve detection of meaningful
associations with clinical endpoints in longitudinal studies of OCT, reducing
measurement error should be a priority, and automated measurements help achieve
this. Translational relevance: We introduce a novel choroid segmentation
algorithm which can replace manual grading for studying the choroid in renal
disease, and other clinical conditions.
| [
{
"created": "Mon, 19 Jun 2023 14:10:54 GMT",
"version": "v1"
},
{
"created": "Wed, 23 Aug 2023 09:12:31 GMT",
"version": "v2"
}
] | 2023-08-24 | [
[
"Burke",
"Jamie",
""
],
[
"Pugh",
"Dan",
""
],
[
"Farrah",
"Tariq",
""
],
[
"Hamid",
"Charlene",
""
],
[
"Godden",
"Emily",
""
],
[
"MacGillivray",
"Tom",
""
],
[
"Dhaun",
"Neeraj",
""
],
[
"Baillie",
"J. Kenneth",
""
],
[
"King",
"Stuart",
""
],
[
"MacCormick",
"Ian J. C.",
""
]
] | Purpose: To evaluate the performance of an automated choroid segmentation algorithm in optical coherence tomography (OCT) data using a longitudinal kidney donor and recipient cohort. Methods: We assessed 22 donors and 23 patients requiring renal transplantation over up to 1 year post-transplant. We measured choroidal thickness (CT) and area and compared our automated CT measurements to manual ones at the same locations. We estimated associations between choroidal measurements and markers of renal function (estimated glomerular filtration rate (eGFR), serum creatinine and urea) using correlation and linear mixed-effects (LME) modelling. Results: There was good agreement between manual and automated CT. Automated measures were more precise because of smaller measurement error over time. External adjudication of major discrepancies were in favour of automated measures. Significant differences were observed in the choroid pre- and post-transplant in both cohorts, and LME modelling revealed significant linear associations observed between choroidal measures and renal function in recipients. Significant associations were mostly stronger with automated CT (eGFR P<0.001, creatinine P=0.004, urea P=0.04) compared to manual CT (eGFR P=0.002, creatinine P=0.01, urea P=0.03). Conclusions: Our automated approach has greater precision than human-performed manual measurements, which may explain stronger associations with renal function compared to manual measurements. To improve detection of meaningful associations with clinical endpoints in longitudinal studies of OCT, reducing measurement error should be a priority, and automated measurements help achieve this. Translational relevance: We introduce a novel choroid segmentation algorithm which can replace manual grading for studying the choroid in renal disease, and other clinical conditions. |
1901.06552 | Andrew Murphy | Andrew C. Murphy, Maxwell A. Bertolero, Lia Papadopoulos, David M.
Lydon-Staley, Danielle S. Bassett | Multiscale and multimodal network dynamics underpinning working memory | null | null | 10.1038/s41467-020-15541-0 | null | q-bio.NC | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Working memory (WM) allows information to be stored and manipulated over
short time scales. Performance on WM tasks is thought to be supported by the
frontoparietal system (FPS), the default mode system (DMS), and interactions
between them. Yet little is known about how these systems and their
interactions relate to individual differences in WM performance. We address
this gap in knowledge using functional MRI data acquired during the performance
of a 2-back WM task, as well as diffusion tensor imaging data collected in the
same individuals. We show that the strength of functional interactions between
the FPS and DMS during task engagement is inversely correlated with WM
performance, and that this strength is modulated by the activation of FPS
regions but not DMS regions. Next, we use a clustering algorithm to identify
two distinct subnetworks of the FPS, and find that these subnetworks display
distinguishable patterns of gene expression. Activity in one subnetwork is
positively associated with the strength of FPS-DMS functional interactions,
while activity in the second subnetwork is negatively associated. Further, the
pattern of structural linkages of these subnetworks explains their differential
capacity to influence the strength of FPS-DMS functional interactions. To
determine whether these observations could provide a mechanistic account of
large-scale neural underpinnings of WM, we build a computational model of the
system composed of coupled oscillators. Modulating the amplitude of the
subnetworks in the model causes the expected change in the strength of FPS-DMS
functional interactions, thereby offering support for a mechanism in which
subnetwork activity tunes functional interactions. Broadly, our study presents
a holistic account of how regional activity, functional interactions, and
structural linkages together support individual differences in WM in humans.
| [
{
"created": "Sat, 19 Jan 2019 16:41:31 GMT",
"version": "v1"
}
] | 2020-09-09 | [
[
"Murphy",
"Andrew C.",
""
],
[
"Bertolero",
"Maxwell A.",
""
],
[
"Papadopoulos",
"Lia",
""
],
[
"Lydon-Staley",
"David M.",
""
],
[
"Bassett",
"Danielle S.",
""
]
] | Working memory (WM) allows information to be stored and manipulated over short time scales. Performance on WM tasks is thought to be supported by the frontoparietal system (FPS), the default mode system (DMS), and interactions between them. Yet little is known about how these systems and their interactions relate to individual differences in WM performance. We address this gap in knowledge using functional MRI data acquired during the performance of a 2-back WM task, as well as diffusion tensor imaging data collected in the same individuals. We show that the strength of functional interactions between the FPS and DMS during task engagement is inversely correlated with WM performance, and that this strength is modulated by the activation of FPS regions but not DMS regions. Next, we use a clustering algorithm to identify two distinct subnetworks of the FPS, and find that these subnetworks display distinguishable patterns of gene expression. Activity in one subnetwork is positively associated with the strength of FPS-DMS functional interactions, while activity in the second subnetwork is negatively associated. Further, the pattern of structural linkages of these subnetworks explains their differential capacity to influence the strength of FPS-DMS functional interactions. To determine whether these observations could provide a mechanistic account of large-scale neural underpinnings of WM, we build a computational model of the system composed of coupled oscillators. Modulating the amplitude of the subnetworks in the model causes the expected change in the strength of FPS-DMS functional interactions, thereby offering support for a mechanism in which subnetwork activity tunes functional interactions. Broadly, our study presents a holistic account of how regional activity, functional interactions, and structural linkages together support individual differences in WM in humans. |
1001.0740 | Mark Bathe | Do-Nyun Kim, Cong-Tri Nguyen and Mark Bathe | Conformational Dynamics of Supramolecular Protein Assemblies in the EMDB | Associated online data bank available at:
http://lcbb.mit.edu/~em-nmdb/ | null | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The Electron Microscopy Data Bank (EMDB) is a rapidly growing repository for
the dissemination of structural data from single-particle reconstructions of
supramolecular protein assemblies including motors, chaperones, cytoskeletal
assemblies, and viral capsids. While the static structure of these assemblies
provides essential insight into their biological function, their conformational
dynamics and mechanics provide additional important information regarding the
mechanism of their biological function. Here, we present an unsupervised
computational framework to analyze and store for public access the
conformational dynamics of supramolecular protein assemblies deposited in the
EMDB. Conformational dynamics are analyzed using normal mode analysis in the
finite element framework, which is used to compute equilibrium thermal
fluctuations, cross-correlations in molecular motions, and strain energy
distributions for 452 of the 681 entries stored in the EMDB at present. Results
for the viral capsid of hepatitis B, ribosome-bound termination factor RF2, and
GroEL are presented in detail and validated with all-atom based models. The
conformational dynamics of protein assemblies in the EMDB may be useful in the
interpretation of their biological function, as well as in the classification
and refinement of EM-based structures.
| [
{
"created": "Tue, 5 Jan 2010 18:26:13 GMT",
"version": "v1"
}
] | 2010-01-06 | [
[
"Kim",
"Do-Nyun",
""
],
[
"Nguyen",
"Cong-Tri",
""
],
[
"Bathe",
"Mark",
""
]
] | The Electron Microscopy Data Bank (EMDB) is a rapidly growing repository for the dissemination of structural data from single-particle reconstructions of supramolecular protein assemblies including motors, chaperones, cytoskeletal assemblies, and viral capsids. While the static structure of these assemblies provides essential insight into their biological function, their conformational dynamics and mechanics provide additional important information regarding the mechanism of their biological function. Here, we present an unsupervised computational framework to analyze and store for public access the conformational dynamics of supramolecular protein assemblies deposited in the EMDB. Conformational dynamics are analyzed using normal mode analysis in the finite element framework, which is used to compute equilibrium thermal fluctuations, cross-correlations in molecular motions, and strain energy distributions for 452 of the 681 entries stored in the EMDB at present. Results for the viral capsid of hepatitis B, ribosome-bound termination factor RF2, and GroEL are presented in detail and validated with all-atom based models. The conformational dynamics of protein assemblies in the EMDB may be useful in the interpretation of their biological function, as well as in the classification and refinement of EM-based structures. |
1606.06336 | Rebekah Rogers | Rebekah L. Rogers and Montgomery Slatkin | Excess of genomic defects in a woolly mammoth on Wrangel island | 43 pages, 2 main figures, 7 supplementary figures, 2 main tables, 10
supplementary tables | null | null | null | q-bio.PE q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Woolly mammoths (Mammuthus primigenius) populated Siberia, Beringia, and
North America during the Pleistocene and early Holocene. Recent breakthroughs
in ancient DNA sequencing have allowed for complete genome sequencing for two
specimens of woolly mammoths (Palkopoulou et al. 2015). One mammoth specimen is
from a mainland population ~45,000 years ago when mammoths were plentiful. The
second, a 4300 yr old specimen, is derived from an isolated population on
Wrangel island where mammoths subsisted with small effective population size
more than 43-fold lower than previous populations. These extreme differences in
effective population size offer a rare opportunity to test nearly neutral
models of genome architecture evolution within a single species. Using these
previously published mammoth sequences, we identify deletions, retrogenes, and
non-functionalizing point mutations. In the Wrangel island mammoth, we identify
a greater number of deletions, a larger proportion of deletions affecting gene
sequences, a greater number of candidate retrogenes, and an increased number of
premature stop codons. This accumulation of detrimental mutations is consistent
with genomic meltdown in response to low effective population sizes in the
dwindling mammoth population on Wrangel island. In addition, we observe high
rates of loss of olfactory receptors and urinary proteins, either because these
loci are non-essential or because they were favored by divergent selective
pressures in island environments. Finally, at the locus of FOXQ1 we observe two
independent loss-of-function mutations, which would confer a satin coat
phenotype in this island woolly mammoth.
| [
{
"created": "Mon, 20 Jun 2016 21:13:47 GMT",
"version": "v1"
},
{
"created": "Thu, 19 Jan 2017 18:11:13 GMT",
"version": "v2"
}
] | 2017-01-20 | [
[
"Rogers",
"Rebekah L.",
""
],
[
"Slatkin",
"Montgomery",
""
]
] | Woolly mammoths (Mammuthus primigenius) populated Siberia, Beringia, and North America during the Pleistocene and early Holocene. Recent breakthroughs in ancient DNA sequencing have allowed for complete genome sequencing for two specimens of woolly mammoths (Palkopoulou et al. 2015). One mammoth specimen is from a mainland population ~45,000 years ago when mammoths were plentiful. The second, a 4300 yr old specimen, is derived from an isolated population on Wrangel island where mammoths subsisted with small effective population size more than 43-fold lower than previous populations. These extreme differences in effective population size offer a rare opportunity to test nearly neutral models of genome architecture evolution within a single species. Using these previously published mammoth sequences, we identify deletions, retrogenes, and non-functionalizing point mutations. In the Wrangel island mammoth, we identify a greater number of deletions, a larger proportion of deletions affecting gene sequences, a greater number of candidate retrogenes, and an increased number of premature stop codons. This accumulation of detrimental mutations is consistent with genomic meltdown in response to low effective population sizes in the dwindling mammoth population on Wrangel island. In addition, we observe high rates of loss of olfactory receptors and urinary proteins, either because these loci are non-essential or because they were favored by divergent selective pressures in island environments. Finally, at the locus of FOXQ1 we observe two independent loss-of-function mutations, which would confer a satin coat phenotype in this island woolly mammoth. |
1903.02346 | Daniela Sapienza | Daniela Sapienza, Alessio Asmundo, Salvatore Silipigni, Ugo Barbaro,
Antonella Cinquegrani, Francesca Granata, Valeria Barresi, Patrizia
Gualniera, Antonio Bottari, Michele Gaeta | Quantitative MRI molecular imaging in the evaluation of early post
mortem changes in muscles. A feasibility study on a pig phantom | 8 figures | Scientific Reports 2018 | null | SREP-18-42605-T | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Estimating early postmortem interval EPI is a difficult task in daily
forensic activity due to limitations of accurate and reliable methods. The aim
of the present work is to describe a novel approach in the estimation of EPI
based on quantitative magnetic resonance molecular imaging qMRMI using a pig
phantom since post mortem degradation of pig meat is similar to that of human
muscles. On a pig phantom maintained at 20 degree, using a 1.5 T MRI scanner we
performed 10 scans, every 4 hours, monitoring apparent diffusion coefficient
ADC, fractional anisotropy FA, magnetization transfer ration MTR, tractography
and susceptibility weighted changes in muscles until 36 hours after death.
Cooling of the phantom during the experiment was recorded. Histology was also
obtained. Pearson's Test was carried out for statistical correlation. We found
a significative statistical inverse correlation between ADC, FA, MT and PMI.
Our preliminary data shows that post mortem qMRMI is a potential powerful tool
in accurately determining EPI and is worth of further investigation.
| [
{
"created": "Wed, 6 Mar 2019 13:01:41 GMT",
"version": "v1"
}
] | 2019-03-12 | [
[
"Sapienza",
"Daniela",
""
],
[
"Asmundo",
"Alessio",
""
],
[
"Silipigni",
"Salvatore",
""
],
[
"Barbaro",
"Ugo",
""
],
[
"Cinquegrani",
"Antonella",
""
],
[
"Granata",
"Francesca",
""
],
[
"Barresi",
"Valeria",
""
],
[
"Gualniera",
"Patrizia",
""
],
[
"Bottari",
"Antonio",
""
],
[
"Gaeta",
"Michele",
""
]
] | Estimating early postmortem interval EPI is a difficult task in daily forensic activity due to limitations of accurate and reliable methods. The aim of the present work is to describe a novel approach in the estimation of EPI based on quantitative magnetic resonance molecular imaging qMRMI using a pig phantom since post mortem degradation of pig meat is similar to that of human muscles. On a pig phantom maintained at 20 degree, using a 1.5 T MRI scanner we performed 10 scans, every 4 hours, monitoring apparent diffusion coefficient ADC, fractional anisotropy FA, magnetization transfer ration MTR, tractography and susceptibility weighted changes in muscles until 36 hours after death. Cooling of the phantom during the experiment was recorded. Histology was also obtained. Pearson's Test was carried out for statistical correlation. We found a significative statistical inverse correlation between ADC, FA, MT and PMI. Our preliminary data shows that post mortem qMRMI is a potential powerful tool in accurately determining EPI and is worth of further investigation. |
1505.03905 | Jicun Wang-Michelitsch | Jicun Wang-Michelitsch and Thomas M. Michelitsch | Premature aging as a consequence of Mis-construction of tissues and
organs during body development | 10 pages, 1 figure | null | null | null | q-bio.TO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Hutchinson-Gilford Progeria syndrome, Werner syndrome, and Cockayne syndrome
are three genetic disorders, in which the children have premature aging
features. To understand the phenomenon of premature aging, the similarity of
aging features in these syndromes to that in normal aging is investigated.
Although these three syndromes have different genetic backgrounds, all the
patients have abnormal structures of tissues/organs like that in normal aging.
Therefore, the abnormality in tissue structure is the common point in premature
aging and normal aging. This abnormality links also a defective development and
a defective repair, the Misrepair. Defective development is a result of
Mis-construction of the structure of tissues and organs as consequence of
genetic mutations. Aging is a result of Mis-reconstructions, the Misrepairs,
for maintaining the structure of tissues/organs. Construction-reconstruction of
the structure of an organism is thus the coupling point of development and
aging. Mis- construction and Mis-reconstruction (Misrepair) are the essential
processes for the development of aging-like feathers. In conclusion, premature
aging is a result of Mis- construction of tissues and organs during body
development as consequence of genetic disorders.
| [
{
"created": "Thu, 14 May 2015 22:15:05 GMT",
"version": "v1"
},
{
"created": "Wed, 6 Sep 2017 08:50:11 GMT",
"version": "v2"
}
] | 2017-09-07 | [
[
"Wang-Michelitsch",
"Jicun",
""
],
[
"Michelitsch",
"Thomas M.",
""
]
] | Hutchinson-Gilford Progeria syndrome, Werner syndrome, and Cockayne syndrome are three genetic disorders, in which the children have premature aging features. To understand the phenomenon of premature aging, the similarity of aging features in these syndromes to that in normal aging is investigated. Although these three syndromes have different genetic backgrounds, all the patients have abnormal structures of tissues/organs like that in normal aging. Therefore, the abnormality in tissue structure is the common point in premature aging and normal aging. This abnormality links also a defective development and a defective repair, the Misrepair. Defective development is a result of Mis-construction of the structure of tissues and organs as consequence of genetic mutations. Aging is a result of Mis-reconstructions, the Misrepairs, for maintaining the structure of tissues/organs. Construction-reconstruction of the structure of an organism is thus the coupling point of development and aging. Mis- construction and Mis-reconstruction (Misrepair) are the essential processes for the development of aging-like feathers. In conclusion, premature aging is a result of Mis- construction of tissues and organs during body development as consequence of genetic disorders. |
2401.05714 | Simone Pigolotti | Qiao Lu and Simone Pigolotti | Target search in the CRISPR/Cas9 system: Facilitated diffusion with
target cues | 9 pages, 6 figures | null | null | null | q-bio.SC q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We study how Cas9, a central component of the CRISPR/Cas9 system, searches
for a target sequence on the DNA. We propose a model that includes as key
ingredients 3D diffusion, 1D sliding along the DNA, and the effect of short
binding sequences preceding the target (protospacer adjacent sequences --
PAMs). This latter aspect constitutes the main difference with traditional
facilitated diffusion of transcription factors. We solve our model, obtaining
an expression for the average search time of Cas9 for its target. We find that
experimentally measured kinetic parameters are close to the values yielding an
optimal search time. Our results rationalize the role of PAMs in guiding the
search process, and show that Cas9 searches for its targets in a nearly optimal
way.
| [
{
"created": "Thu, 11 Jan 2024 07:38:34 GMT",
"version": "v1"
}
] | 2024-01-12 | [
[
"Lu",
"Qiao",
""
],
[
"Pigolotti",
"Simone",
""
]
] | We study how Cas9, a central component of the CRISPR/Cas9 system, searches for a target sequence on the DNA. We propose a model that includes as key ingredients 3D diffusion, 1D sliding along the DNA, and the effect of short binding sequences preceding the target (protospacer adjacent sequences -- PAMs). This latter aspect constitutes the main difference with traditional facilitated diffusion of transcription factors. We solve our model, obtaining an expression for the average search time of Cas9 for its target. We find that experimentally measured kinetic parameters are close to the values yielding an optimal search time. Our results rationalize the role of PAMs in guiding the search process, and show that Cas9 searches for its targets in a nearly optimal way. |
1506.02323 | Arvind Murugan | Arvind Murugan, Suriyanarayanan Vaikuntanathan | Biological implications of dynamical phases in non-equilibrium networks | 10 figures. Submitted to the Journal of Statistical Physics (special
issue on "Information Processing in Living Systems") | null | 10.1007/s10955-015-1445-0 | null | q-bio.MN cond-mat.stat-mech physics.bio-ph | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Biology achieves novel functions like error correction, ultra-sensitivity and
accurate concentration measurement at the expense of free energy through
Maxwell Demon-like mechanisms. The design principles and free energy trade-offs
have been studied for a variety of such mechanisms. In this review, we
emphasize a perspective based on dynamical phases that can explain
commonalities shared by these mechanisms. Dynamical phases are defined by
typical trajectories executed by non-equilibrium systems in the space of
internal states. We find that coexistence of dynamical phases can have dramatic
consequences for function vs free energy cost trade-offs. Dynamical phases can
also provide an intuitive picture of the design principles behind such
biological Maxwell Demons.
| [
{
"created": "Sun, 7 Jun 2015 23:01:41 GMT",
"version": "v1"
}
] | 2016-05-27 | [
[
"Murugan",
"Arvind",
""
],
[
"Vaikuntanathan",
"Suriyanarayanan",
""
]
] | Biology achieves novel functions like error correction, ultra-sensitivity and accurate concentration measurement at the expense of free energy through Maxwell Demon-like mechanisms. The design principles and free energy trade-offs have been studied for a variety of such mechanisms. In this review, we emphasize a perspective based on dynamical phases that can explain commonalities shared by these mechanisms. Dynamical phases are defined by typical trajectories executed by non-equilibrium systems in the space of internal states. We find that coexistence of dynamical phases can have dramatic consequences for function vs free energy cost trade-offs. Dynamical phases can also provide an intuitive picture of the design principles behind such biological Maxwell Demons. |
2203.01862 | Maria Tsfasman | Maria Tsfasman, Anja Philippsen, Carlo Mazzola, Serge Thill,
Alessandra Sciutti, Yukie Nagai | The world seems different in a social context: a neural network analysis
of human experimental data | null | null | 10.1371/journal.pone.0273643 | null | q-bio.NC cs.AI cs.HC cs.LG | http://creativecommons.org/licenses/by/4.0/ | Human perception and behavior are affected by the situational context, in
particular during social interactions. A recent study demonstrated that humans
perceive visual stimuli differently depending on whether they do the task by
themselves or together with a robot. Specifically, it was found that the
central tendency effect is stronger in social than in non-social task settings.
The particular nature of such behavioral changes induced by social interaction,
and their underlying cognitive processes in the human brain are, however, still
not well understood. In this paper, we address this question by training an
artificial neural network inspired by the predictive coding theory on the above
behavioral data set. Using this computational model, we investigate whether the
change in behavior that was caused by the situational context in the human
experiment could be explained by continuous modifications of a parameter
expressing how strongly sensory and prior information affect perception. We
demonstrate that it is possible to replicate human behavioral data in both
individual and social task settings by modifying the precision of prior and
sensory signals, indicating that social and non-social task settings might in
fact exist on a continuum. At the same time an analysis of the neural
activation traces of the trained networks provides evidence that information is
coded in fundamentally different ways in the network in the individual and in
the social conditions. Our results emphasize the importance of computational
replications of behavioral data for generating hypotheses on the underlying
cognitive mechanisms of shared perception and may provide inspiration for
follow-up studies in the field of neuroscience.
| [
{
"created": "Thu, 3 Mar 2022 17:19:12 GMT",
"version": "v1"
}
] | 2022-10-12 | [
[
"Tsfasman",
"Maria",
""
],
[
"Philippsen",
"Anja",
""
],
[
"Mazzola",
"Carlo",
""
],
[
"Thill",
"Serge",
""
],
[
"Sciutti",
"Alessandra",
""
],
[
"Nagai",
"Yukie",
""
]
] | Human perception and behavior are affected by the situational context, in particular during social interactions. A recent study demonstrated that humans perceive visual stimuli differently depending on whether they do the task by themselves or together with a robot. Specifically, it was found that the central tendency effect is stronger in social than in non-social task settings. The particular nature of such behavioral changes induced by social interaction, and their underlying cognitive processes in the human brain are, however, still not well understood. In this paper, we address this question by training an artificial neural network inspired by the predictive coding theory on the above behavioral data set. Using this computational model, we investigate whether the change in behavior that was caused by the situational context in the human experiment could be explained by continuous modifications of a parameter expressing how strongly sensory and prior information affect perception. We demonstrate that it is possible to replicate human behavioral data in both individual and social task settings by modifying the precision of prior and sensory signals, indicating that social and non-social task settings might in fact exist on a continuum. At the same time an analysis of the neural activation traces of the trained networks provides evidence that information is coded in fundamentally different ways in the network in the individual and in the social conditions. Our results emphasize the importance of computational replications of behavioral data for generating hypotheses on the underlying cognitive mechanisms of shared perception and may provide inspiration for follow-up studies in the field of neuroscience. |
2405.16695 | Michael Lindstrom | Elliot M. Miller, Tat Chung D. Chan, Carlos Montes-Matamoros, Omar
Sharif, Laurent Pujo-Menjouet, Michael R. Lindstrom | Oscillations in neuronal activity: a neuron-centered spatiotemporal
model of the Unfolded Protein Response in prion diseases | 35 pages, 11 tables, 13 figures | null | null | null | q-bio.NC math.DS | http://creativecommons.org/licenses/by/4.0/ | Many neurodegenerative diseases (NDs) are characterized by the slow spatial
spread of toxic protein species in the brain. The toxic proteins can induce
neuronal stress, triggering the Unfolded Protein Response (UPR), which slows or
stops protein translation and can indirectly reduce the toxic load. However,
the UPR may also trigger processes leading to apoptotic cell death and the UPR
is implicated in the progression of several NDs. In this paper, we develop a
novel mathematical model to describe the spatiotemporal dynamics of the UPR
mechanism for prion diseases. Our model is centered around a single neuron,
with representative proteins P (healthy) and S (toxic) interacting with
heterodimer dynamics (S interacts with P to form two S's). The model takes the
form of a coupled system of nonlinear reaction-diffusion equations with a
delayed, nonlinear flux for P (delay from the UPR). Through the delay, we find
parameter regimes that exhibit oscillations in the P- and S-protein levels. We
find that oscillations are more pronounced when the S-clearance rate and
S-diffusivity are small in comparison to the P-clearance rate and
P-diffusivity, respectively. The oscillations become more pronounced as delays
in initiating the UPR increase. We also consider quasi-realistic clinical
parameters to understand how possible drug therapies can alter the course of a
prion disease. We find that decreasing the production of P, decreasing the
recruitment rate, increasing the diffusivity of S, increasing the UPR
S-threshold, and increasing the S clearance rate appear to be the most powerful
modifications to reduce the mean UPR intensity and potentially moderate the
disease progression.
| [
{
"created": "Sun, 26 May 2024 21:00:30 GMT",
"version": "v1"
}
] | 2024-05-28 | [
[
"Miller",
"Elliot M.",
""
],
[
"Chan",
"Tat Chung D.",
""
],
[
"Montes-Matamoros",
"Carlos",
""
],
[
"Sharif",
"Omar",
""
],
[
"Pujo-Menjouet",
"Laurent",
""
],
[
"Lindstrom",
"Michael R.",
""
]
] | Many neurodegenerative diseases (NDs) are characterized by the slow spatial spread of toxic protein species in the brain. The toxic proteins can induce neuronal stress, triggering the Unfolded Protein Response (UPR), which slows or stops protein translation and can indirectly reduce the toxic load. However, the UPR may also trigger processes leading to apoptotic cell death and the UPR is implicated in the progression of several NDs. In this paper, we develop a novel mathematical model to describe the spatiotemporal dynamics of the UPR mechanism for prion diseases. Our model is centered around a single neuron, with representative proteins P (healthy) and S (toxic) interacting with heterodimer dynamics (S interacts with P to form two S's). The model takes the form of a coupled system of nonlinear reaction-diffusion equations with a delayed, nonlinear flux for P (delay from the UPR). Through the delay, we find parameter regimes that exhibit oscillations in the P- and S-protein levels. We find that oscillations are more pronounced when the S-clearance rate and S-diffusivity are small in comparison to the P-clearance rate and P-diffusivity, respectively. The oscillations become more pronounced as delays in initiating the UPR increase. We also consider quasi-realistic clinical parameters to understand how possible drug therapies can alter the course of a prion disease. We find that decreasing the production of P, decreasing the recruitment rate, increasing the diffusivity of S, increasing the UPR S-threshold, and increasing the S clearance rate appear to be the most powerful modifications to reduce the mean UPR intensity and potentially moderate the disease progression. |
1907.03061 | Zachary Kilpatrick PhD | Subekshya Bidari, Orit Peleg, and Zachary P Kilpatrick | Social inhibition maintains adaptivity and consensus of foraging
honeybee swarms in dynamic environments | 27 pages, 13 figures | null | null | null | q-bio.PE math.DS | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | To effectively forage in natural environments, organisms must adapt to
changes in the quality and yield of food sources across multiple timescales.
Individuals foraging in groups act based on both their private observations and
the opinions of their neighbors. How do these information sources interact in
changing environments? We address this problem in the context of honeybee
swarms, showing inhibitory social interactions help maintain adaptivity and
consensus needed for effective foraging. Individual and social interactions of
a mathematical swarm model shape the nutrition yield of a group foraging from
feeders with temporally switching food quality. Social interactions improve
foraging from a single feeder if temporal switching is fast or feeder quality
is low. When the swarm chooses from multiple feeders, the most effective form
of social interaction is direct switching, whereby bees flip the opinion of
nestmates foraging at lower yielding feeders. Model linearization shows that
effective social interactions increase the fraction of the swarm at the correct
feeder (consensus) and the rate at which bees reach that feeder (adaptivity).
Our mathematical framework allows us to compare a suite of social inhibition
mechanisms, suggesting experimental protocols for revealing effective swarm
foraging strategies in dynamic environments.
| [
{
"created": "Sat, 6 Jul 2019 02:19:10 GMT",
"version": "v1"
}
] | 2019-07-09 | [
[
"Bidari",
"Subekshya",
""
],
[
"Peleg",
"Orit",
""
],
[
"Kilpatrick",
"Zachary P",
""
]
] | To effectively forage in natural environments, organisms must adapt to changes in the quality and yield of food sources across multiple timescales. Individuals foraging in groups act based on both their private observations and the opinions of their neighbors. How do these information sources interact in changing environments? We address this problem in the context of honeybee swarms, showing inhibitory social interactions help maintain adaptivity and consensus needed for effective foraging. Individual and social interactions of a mathematical swarm model shape the nutrition yield of a group foraging from feeders with temporally switching food quality. Social interactions improve foraging from a single feeder if temporal switching is fast or feeder quality is low. When the swarm chooses from multiple feeders, the most effective form of social interaction is direct switching, whereby bees flip the opinion of nestmates foraging at lower yielding feeders. Model linearization shows that effective social interactions increase the fraction of the swarm at the correct feeder (consensus) and the rate at which bees reach that feeder (adaptivity). Our mathematical framework allows us to compare a suite of social inhibition mechanisms, suggesting experimental protocols for revealing effective swarm foraging strategies in dynamic environments. |
2201.06074 | Dmytro Fishman | Dmytro Fishman | Developing a data analysis pipeline for automated protein profiling in
immunology | The public defense was held on 28 June, 2021 (for video, see
https://www.uttv.ee/naita?id=31430; slide: https://bit.ly/3fzIaks).
Supervisors: Prof. Hedi Peterson, Prof. Jaak Vilo and Prof. P\"art Peterson
from University of Tarty, Estonia. Opponents: Dr. Jessica Da Gama Duarte
(Olivia Newton-John Cancer Research Institute, Australia), Dr. Fridtjof
Lund-Johansen (Oslo University Hospital, Norway) | null | null | Dissertationes Informaticae Universitatis Tartuensis 28 | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Accurate information about protein content in the organism is instrumental
for a better understanding of human biology and disease mechanisms. While the
presence of certain types of proteins can be life-threatening, the abundance of
others is an essential condition for an individual's overall well-being.
Protein microarray is a technology that enables the quantification of thousands
of proteins in hundreds of human samples in a parallel manner. In a series of
studies involving protein microarrays, we have explored and implemented various
data science methods for all-around analysing of these data. This analysis has
enabled the identification and characterisation of proteins targeted by the
autoimmune reaction in patients with the APS1 condition. We have also assessed
the utility of applying machine learning methods alongside statistical tests in
a study based on protein expression data to evaluate potential biomarkers for
endometriosis. The keystone of this work is a web-tool PAWER. PAWER implements
relevant computational methods, and provides a semi-automatic way to run the
analysis of protein microarray data online in a drag-and-drop and
click-and-play style. The source code of the tool is publicly available. The
work that laid the foundation of this thesis has been instrumental for a number
of subsequent studies of human disease and also inspired a contribution to
refining standards for validation of machine learning methods in biology.
| [
{
"created": "Sun, 16 Jan 2022 15:37:50 GMT",
"version": "v1"
}
] | 2022-01-19 | [
[
"Fishman",
"Dmytro",
""
]
] | Accurate information about protein content in the organism is instrumental for a better understanding of human biology and disease mechanisms. While the presence of certain types of proteins can be life-threatening, the abundance of others is an essential condition for an individual's overall well-being. Protein microarray is a technology that enables the quantification of thousands of proteins in hundreds of human samples in a parallel manner. In a series of studies involving protein microarrays, we have explored and implemented various data science methods for all-around analysing of these data. This analysis has enabled the identification and characterisation of proteins targeted by the autoimmune reaction in patients with the APS1 condition. We have also assessed the utility of applying machine learning methods alongside statistical tests in a study based on protein expression data to evaluate potential biomarkers for endometriosis. The keystone of this work is a web-tool PAWER. PAWER implements relevant computational methods, and provides a semi-automatic way to run the analysis of protein microarray data online in a drag-and-drop and click-and-play style. The source code of the tool is publicly available. The work that laid the foundation of this thesis has been instrumental for a number of subsequent studies of human disease and also inspired a contribution to refining standards for validation of machine learning methods in biology. |
2312.06824 | Ramon Diaz-Uriarte | Ramon Diaz-Uriarte, Iain G. Johnston | A picture guide to cancer progression and monotonic accumulation models:
evolutionary assumptions, plausible interpretations, and alternative uses | fixed wrong fig. ref; driv./pass.; [Previous: Abstract 200 words;
details BML; consistent Brit. spell.; Iain G. Johnston coauthor; clarified
LOD/POM; clarified scenarios; comment Schill et al. 2024 selection bias;
fixed typos; additional annotation in some figures and figure legends. Added
URLs and DOIs to references; corrected typos; added URL to software] | null | null | null | q-bio.PE q-bio.QM | http://creativecommons.org/licenses/by-sa/4.0/ | Cancer progression and monotonic accumulation models were developed to
discover dependencies in the irreversible acquisition of binary traits from
cross-sectional data. They have been used in computational oncology and
virology but also in widely different problems such as malaria progression.
These methods have been applied to predict future states of the system,
identify routes of feature acquisition, and improve patient stratification, and
they hold promise for evolutionary-based treatments. New methods continue to be
developed.
But these methods have shortcomings, which are yet to be systematically
critiqued, regarding key evolutionary assumptions and interpretations. After an
overview of the available methods, we focus on why inferences might not be
about the processes we intend. Using fitness landscapes, we highlight
difficulties that arise from bulk sequencing and reciprocal sign epistasis,
from conflating lines of descent, path of the maximum, and mutational profiles,
and from ambiguous use of the idea of exclusivity. We examine how the previous
concerns change when bulk sequencing is explicitly considered, and underline
opportunities for addressing dependencies due to frequency-dependent selection.
This review identifies major standing issues, and should encourage the use of
these methods in other areas with a better alignment between entities and model
assumptions.
| [
{
"created": "Mon, 11 Dec 2023 20:24:11 GMT",
"version": "v1"
},
{
"created": "Thu, 14 Dec 2023 11:15:30 GMT",
"version": "v2"
},
{
"created": "Fri, 7 Jun 2024 14:59:13 GMT",
"version": "v3"
},
{
"created": "Wed, 19 Jun 2024 01:21:46 GMT",
"version": "v4"
},
{
"created": "Sun, 30 Jun 2024 19:26:09 GMT",
"version": "v5"
}
] | 2024-07-02 | [
[
"Diaz-Uriarte",
"Ramon",
""
],
[
"Johnston",
"Iain G.",
""
]
] | Cancer progression and monotonic accumulation models were developed to discover dependencies in the irreversible acquisition of binary traits from cross-sectional data. They have been used in computational oncology and virology but also in widely different problems such as malaria progression. These methods have been applied to predict future states of the system, identify routes of feature acquisition, and improve patient stratification, and they hold promise for evolutionary-based treatments. New methods continue to be developed. But these methods have shortcomings, which are yet to be systematically critiqued, regarding key evolutionary assumptions and interpretations. After an overview of the available methods, we focus on why inferences might not be about the processes we intend. Using fitness landscapes, we highlight difficulties that arise from bulk sequencing and reciprocal sign epistasis, from conflating lines of descent, path of the maximum, and mutational profiles, and from ambiguous use of the idea of exclusivity. We examine how the previous concerns change when bulk sequencing is explicitly considered, and underline opportunities for addressing dependencies due to frequency-dependent selection. This review identifies major standing issues, and should encourage the use of these methods in other areas with a better alignment between entities and model assumptions. |
2312.01966 | Kevin Doran | Kevin Doran, Marvin Seifert, Carola A. M. Yovanovich, Tom Baden | Spike distance function as a learning objective for spike prediction | 27 pages, 19 figures | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | Approaches to predicting neuronal spike responses commonly use a Poisson
learning objective. This objective quantizes responses into spike counts within
a fixed summation interval, typically on the order of 10 to 100 milliseconds in
duration; however, neuronal responses are often time accurate down to a few
milliseconds, and Poisson models struggle to precisely model them at these
timescales. We propose the concept of a spike distance function that maps
points in time to the temporal distance to the nearest spike. We show that
neural networks can be trained to approximate spike distance functions, and we
present an efficient algorithm for inferring spike trains from the outputs of
these models. Using recordings of chicken and frog retinal ganglion cells
responding to visual stimuli, we compare the performance of our approach to
that of Poisson models trained with various summation intervals. We show that
our approach outperforms the use of Poisson models at spike train inference.
| [
{
"created": "Mon, 4 Dec 2023 15:24:48 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Jul 2024 13:41:55 GMT",
"version": "v2"
}
] | 2024-07-03 | [
[
"Doran",
"Kevin",
""
],
[
"Seifert",
"Marvin",
""
],
[
"Yovanovich",
"Carola A. M.",
""
],
[
"Baden",
"Tom",
""
]
] | Approaches to predicting neuronal spike responses commonly use a Poisson learning objective. This objective quantizes responses into spike counts within a fixed summation interval, typically on the order of 10 to 100 milliseconds in duration; however, neuronal responses are often time accurate down to a few milliseconds, and Poisson models struggle to precisely model them at these timescales. We propose the concept of a spike distance function that maps points in time to the temporal distance to the nearest spike. We show that neural networks can be trained to approximate spike distance functions, and we present an efficient algorithm for inferring spike trains from the outputs of these models. Using recordings of chicken and frog retinal ganglion cells responding to visual stimuli, we compare the performance of our approach to that of Poisson models trained with various summation intervals. We show that our approach outperforms the use of Poisson models at spike train inference. |
1305.1861 | Rajat Roy | Rajat Shuvro Roy, Debashish Bhattacharya and Alexander Schliep | Turtle: Identifying frequent k-mers with cache-efficient algorithms | null | null | null | null | q-bio.GN cs.CE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Counting the frequencies of k-mers in read libraries is often a first step in
the analysis of high-throughput sequencing experiments. Infrequent k-mers are
assumed to be a result of sequencing errors. The frequent k-mers constitute a
reduced but error-free representation of the experiment, which can inform read
error correction or serve as the input to de novo assembly methods. Ideally,
the memory requirement for counting should be linear in the number of frequent
k-mers and not in the, typically much larger, total number of k-mers in the
read library.
We present a novel method that balances time, space and accuracy requirements
to efficiently extract frequent k-mers even for high coverage libraries and
large genomes such as human. Our method is designed to minimize cache-misses in
a cache-efficient manner by using a Pattern-blocked Bloom filter to remove
infrequent k-mers from consideration in combination with a novel
sort-and-compact scheme, instead of a Hash, for the actual counting. While this
increases theoretical complexity, the savings in cache misses reduce the
empirical running times. A variant can resort to a counting Bloom filter for
even larger savings in memory at the expense of false negatives in addition to
the false positives common to all Bloom filter based approaches. A comparison
to the state-of-the-art shows reduced memory requirements and running times.
Note that we also provide the first competitive method to count k-mers up to
size 64.
| [
{
"created": "Wed, 8 May 2013 15:49:39 GMT",
"version": "v1"
}
] | 2013-05-09 | [
[
"Roy",
"Rajat Shuvro",
""
],
[
"Bhattacharya",
"Debashish",
""
],
[
"Schliep",
"Alexander",
""
]
] | Counting the frequencies of k-mers in read libraries is often a first step in the analysis of high-throughput sequencing experiments. Infrequent k-mers are assumed to be a result of sequencing errors. The frequent k-mers constitute a reduced but error-free representation of the experiment, which can inform read error correction or serve as the input to de novo assembly methods. Ideally, the memory requirement for counting should be linear in the number of frequent k-mers and not in the, typically much larger, total number of k-mers in the read library. We present a novel method that balances time, space and accuracy requirements to efficiently extract frequent k-mers even for high coverage libraries and large genomes such as human. Our method is designed to minimize cache-misses in a cache-efficient manner by using a Pattern-blocked Bloom filter to remove infrequent k-mers from consideration in combination with a novel sort-and-compact scheme, instead of a Hash, for the actual counting. While this increases theoretical complexity, the savings in cache misses reduce the empirical running times. A variant can resort to a counting Bloom filter for even larger savings in memory at the expense of false negatives in addition to the false positives common to all Bloom filter based approaches. A comparison to the state-of-the-art shows reduced memory requirements and running times. Note that we also provide the first competitive method to count k-mers up to size 64. |
1707.03329 | Yani Zhao | Yani Zhao and Marek Cieplak | Structural changes in barley protein LTP1 isoforms at air-water
interfaces | 18 pages, 18 figures | Langmuir (2017), 33(19), 4769-4780 | null | null | q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We use a coarse-grained model to study the conformational changes in two
barley proteins, LTP1 and its ligand adduct isoform LTP1b, that result from
their adsorption to the air-water interface. The model introduces the interface
through hydropathy indices. We justify the model by all-atom simulations. The
choice of the proteins is motivated by making attempts to understand formation
and stability of foam in beer. We demonstrate that both proteins flatten out at
the interface and can make a continuous stabilizing and denser film. We show
that the degree of the flattening depends on the protein -- the layers of LTP1b
should be denser than those of LTP1 -- and on the presence of glycation. It
also depends on the number ($\le 4$) of the disulfide bonds in the proteins.
The geometry of the proteins is sensitive to the specificity of the absent
bonds. We provide estimates of the volume of cavities of the proteins when away
from the interface.
| [
{
"created": "Tue, 11 Jul 2017 15:38:33 GMT",
"version": "v1"
}
] | 2017-07-12 | [
[
"Zhao",
"Yani",
""
],
[
"Cieplak",
"Marek",
""
]
] | We use a coarse-grained model to study the conformational changes in two barley proteins, LTP1 and its ligand adduct isoform LTP1b, that result from their adsorption to the air-water interface. The model introduces the interface through hydropathy indices. We justify the model by all-atom simulations. The choice of the proteins is motivated by making attempts to understand formation and stability of foam in beer. We demonstrate that both proteins flatten out at the interface and can make a continuous stabilizing and denser film. We show that the degree of the flattening depends on the protein -- the layers of LTP1b should be denser than those of LTP1 -- and on the presence of glycation. It also depends on the number ($\le 4$) of the disulfide bonds in the proteins. The geometry of the proteins is sensitive to the specificity of the absent bonds. We provide estimates of the volume of cavities of the proteins when away from the interface. |
1603.04548 | Marco Kienzle | Marco Kienzle and David Sterling | Rising temperatures increased recruitment of brown tiger prawn (Penaeus
esculentus) in Moreton Bay (Australia) | 24 pages | null | 10.1093/icesjms/fsw191 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Abiotic factors are fundamental drivers of the dynamics of wild marine fish
populations. Identifying and quantifying their influence on species targeted by
the fishing industry is difficult and very important for managing fisheries in
a changing climate. Using multiple regression, we investigated the influence of
both temperature and rainfall on the variability of recruitment of a tropical
species, the brown tiger prawn (Penaeus esculentus), in Moreton Bay which is
located near the southern limit of its distribution on the east coast of
Australia. A step-wise selection between environmental variables identified
that variations in recruitment from 1990 to 2014 were best explained by a
combination of temperature and spawning stock biomass. Temperature explains 35%
of recruitment variability and spawning stock biomass 33%. This analysis
suggests that increasing temperatures have increased recruitment of brown tiger
prawn in Moreton Bay.
| [
{
"created": "Tue, 15 Mar 2016 04:13:06 GMT",
"version": "v1"
}
] | 2017-01-23 | [
[
"Kienzle",
"Marco",
""
],
[
"Sterling",
"David",
""
]
] | Abiotic factors are fundamental drivers of the dynamics of wild marine fish populations. Identifying and quantifying their influence on species targeted by the fishing industry is difficult and very important for managing fisheries in a changing climate. Using multiple regression, we investigated the influence of both temperature and rainfall on the variability of recruitment of a tropical species, the brown tiger prawn (Penaeus esculentus), in Moreton Bay which is located near the southern limit of its distribution on the east coast of Australia. A step-wise selection between environmental variables identified that variations in recruitment from 1990 to 2014 were best explained by a combination of temperature and spawning stock biomass. Temperature explains 35% of recruitment variability and spawning stock biomass 33%. This analysis suggests that increasing temperatures have increased recruitment of brown tiger prawn in Moreton Bay. |
1101.2434 | Tiago Ribeiro | Tiago L. Ribeiro, Mauro Copelli, F\'abio Caixeta, Hindiael Belchior,
Dante R. Chialvo, Miguel A. L. Nicolelis, Sidarta Ribeiro | Spike Avalanches Exhibit Universal Dynamics across the Sleep-Wake Cycle | 14 pages, 9 figures, supporting material included (published in Plos
One) | PLoS ONE 5(11): e14129, 2010 | 10.1371/journal.pone.0014129 | null | q-bio.NC physics.data-an | http://creativecommons.org/licenses/by/3.0/ | Scale-invariant neuronal avalanches have been observed in cell cultures and
slices as well as anesthetized and awake brains, suggesting that the brain
operates near criticality, i.e. within a narrow margin between avalanche
propagation and extinction. In theory, criticality provides many desirable
features for the behaving brain, optimizing computational capabilities,
information transmission, sensitivity to sensory stimuli and size of memory
repertoires. However, a thorough characterization of neuronal avalanches in
freely-behaving (FB) animals is still missing, thus raising doubts about their
relevance for brain function. To address this issue, we employed chronically
implanted multielectrode arrays (MEA) to record avalanches of spikes from the
cerebral cortex (V1 and S1) and hippocampus (HP) of 14 rats, as they
spontaneously traversed the wake-sleep cycle, explored novel objects or were
subjected to anesthesia (AN). We then modeled spike avalanches to evaluate the
impact of sparse MEA sampling on their statistics. We found that the size
distribution of spike avalanches are well fit by lognormal distributions in FB
animals, and by truncated power laws in the AN group. The FB data are also
characterized by multiple key features compatible with criticality in the
temporal domain, such as 1/f spectra and long-term correlations as measured by
detrended fluctuation analysis. These signatures are very stable across waking,
slow-wave sleep and rapid-eye-movement sleep, but collapse during anesthesia.
Likewise, waiting time distributions obey a single scaling function during all
natural behavioral states, but not during anesthesia. Results are equivalent
for neuronal ensembles recorded from V1, S1 and HP. Altogether, the data
provide a comprehensive link between behavior and brain criticality, revealing
a unique scale-invariant regime of spike avalanches across all major behaviors.
| [
{
"created": "Mon, 10 Jan 2011 16:24:46 GMT",
"version": "v1"
}
] | 2011-01-18 | [
[
"Ribeiro",
"Tiago L.",
""
],
[
"Copelli",
"Mauro",
""
],
[
"Caixeta",
"Fábio",
""
],
[
"Belchior",
"Hindiael",
""
],
[
"Chialvo",
"Dante R.",
""
],
[
"Nicolelis",
"Miguel A. L.",
""
],
[
"Ribeiro",
"Sidarta",
""
]
] | Scale-invariant neuronal avalanches have been observed in cell cultures and slices as well as anesthetized and awake brains, suggesting that the brain operates near criticality, i.e. within a narrow margin between avalanche propagation and extinction. In theory, criticality provides many desirable features for the behaving brain, optimizing computational capabilities, information transmission, sensitivity to sensory stimuli and size of memory repertoires. However, a thorough characterization of neuronal avalanches in freely-behaving (FB) animals is still missing, thus raising doubts about their relevance for brain function. To address this issue, we employed chronically implanted multielectrode arrays (MEA) to record avalanches of spikes from the cerebral cortex (V1 and S1) and hippocampus (HP) of 14 rats, as they spontaneously traversed the wake-sleep cycle, explored novel objects or were subjected to anesthesia (AN). We then modeled spike avalanches to evaluate the impact of sparse MEA sampling on their statistics. We found that the size distribution of spike avalanches are well fit by lognormal distributions in FB animals, and by truncated power laws in the AN group. The FB data are also characterized by multiple key features compatible with criticality in the temporal domain, such as 1/f spectra and long-term correlations as measured by detrended fluctuation analysis. These signatures are very stable across waking, slow-wave sleep and rapid-eye-movement sleep, but collapse during anesthesia. Likewise, waiting time distributions obey a single scaling function during all natural behavioral states, but not during anesthesia. Results are equivalent for neuronal ensembles recorded from V1, S1 and HP. Altogether, the data provide a comprehensive link between behavior and brain criticality, revealing a unique scale-invariant regime of spike avalanches across all major behaviors. |
1901.07327 | Heng Li | Heng Li | Identifying centromeric satellites with dna-brnn | null | null | null | null | q-bio.GN | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Summary: Human alpha satellite and satellite 2/3 contribute to several
percent of the human genome. However, identifying these sequences with
traditional algorithms is computationally intensive. Here we develop dna-brnn,
a recurrent neural network to learn the sequences of the two classes of
centromeric repeats. It achieves high similarity to RepeatMasker and is times
faster. Dna-brnn explores a novel application of deep learning and may
accelerate the study of the evolution of the two repeat classes.
Availability and implementation: https://github.com/lh3/dna-nn
Contact: hli@jimmy.harvard.edu
| [
{
"created": "Tue, 22 Jan 2019 14:31:26 GMT",
"version": "v1"
},
{
"created": "Mon, 18 Mar 2019 15:07:50 GMT",
"version": "v2"
}
] | 2019-03-19 | [
[
"Li",
"Heng",
""
]
] | Summary: Human alpha satellite and satellite 2/3 contribute to several percent of the human genome. However, identifying these sequences with traditional algorithms is computationally intensive. Here we develop dna-brnn, a recurrent neural network to learn the sequences of the two classes of centromeric repeats. It achieves high similarity to RepeatMasker and is times faster. Dna-brnn explores a novel application of deep learning and may accelerate the study of the evolution of the two repeat classes. Availability and implementation: https://github.com/lh3/dna-nn Contact: hli@jimmy.harvard.edu |
1809.08920 | Artem Novozhilov | Georgy P. Karev, Artem S. Novozhilov | How trait distributions evolve in heterogeneous populations | 14 pages, 2 figures. arXiv admin note: text overlap with
arXiv:1504.00372 | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We consider the problem of determining the time evolution of a trait
distribution in a mathematical model of non-uniform populations with parametric
heterogeneity. This means that we consider only heterogeneous populations in
which heterogeneity is described by an individual specific parameter that
differs in general from individual to individual, but does not change with time
for the whole lifespan of this individual. Such a restriction allows obtaining
a number of simple and yet important analytical results. In particular we show
that initial assumptions on time-dependent behavior of various characteristics,
such as the mean, variance, of coefficient of variation, restrict severely
possible choices for the exact form of the trait distribution. We illustrate
our findings by in-depth analysis of the variance evolution. We also reanalyze
a well known mathematical model for gypsy moth population showing that the
knowledge of how distributions evolve allows producing oscillatory behaviors
for highly heterogeneous populations.
| [
{
"created": "Fri, 21 Sep 2018 01:44:27 GMT",
"version": "v1"
}
] | 2018-09-25 | [
[
"Karev",
"Georgy P.",
""
],
[
"Novozhilov",
"Artem S.",
""
]
] | We consider the problem of determining the time evolution of a trait distribution in a mathematical model of non-uniform populations with parametric heterogeneity. This means that we consider only heterogeneous populations in which heterogeneity is described by an individual specific parameter that differs in general from individual to individual, but does not change with time for the whole lifespan of this individual. Such a restriction allows obtaining a number of simple and yet important analytical results. In particular we show that initial assumptions on time-dependent behavior of various characteristics, such as the mean, variance, of coefficient of variation, restrict severely possible choices for the exact form of the trait distribution. We illustrate our findings by in-depth analysis of the variance evolution. We also reanalyze a well known mathematical model for gypsy moth population showing that the knowledge of how distributions evolve allows producing oscillatory behaviors for highly heterogeneous populations. |
1401.2469 | Joel Nishimura | Joel Nishimura | Frequency adjustment and synchrony in networks of delayed pulse coupled
oscillators | 5 pages, 2 figures, for submission to PRL | null | 10.1103/PhysRevE.91.012916 | null | q-bio.NC nlin.AO | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | We introduce a system of pulse coupled oscillators that can change both their
phases and frequencies; and prove that when there is a separation of time
scales between phase and frequency adjustment the system converges to exact
synchrony on strongly connected graphs with time delays. The analysis involves
decomposing the network into a forest of tree-like structures that capture
causality. Furthermore, we provide a lower bound for the size of the basin of
attraction with immediate implications for empirical networks and random graph
models. These results provide a robust method of sensor net synchronization as
well as demonstrate a new avenue of possible pulse coupled oscillator research.
| [
{
"created": "Fri, 10 Jan 2014 21:20:38 GMT",
"version": "v1"
}
] | 2015-06-18 | [
[
"Nishimura",
"Joel",
""
]
] | We introduce a system of pulse coupled oscillators that can change both their phases and frequencies; and prove that when there is a separation of time scales between phase and frequency adjustment the system converges to exact synchrony on strongly connected graphs with time delays. The analysis involves decomposing the network into a forest of tree-like structures that capture causality. Furthermore, we provide a lower bound for the size of the basin of attraction with immediate implications for empirical networks and random graph models. These results provide a robust method of sensor net synchronization as well as demonstrate a new avenue of possible pulse coupled oscillator research. |
2110.14598 | Iegor Reznikoff | Iegor Reznikoff | A logical and topological proof of the irreducibility of consciousness
to physical data | 6 pages, 1 figure | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by/4.0/ | We show here that what we call visual space of consciousness, the space of
what we see, is a specific space different from the purely physical one and
that its properties imply that it cannot be reduced to or deduced from physical
laws. Some biological points are also briefly considered. The arguments are of
logical, mathematical and physical character, and although elementary they
require a careful reading. A first shorter version of this paper appeared in a
hardly accessible Journal [1], and presented at the International Congress of
Logic, Methodology and Philosophy of Sciences, in Beijing, August 2007. There
is no need to define consciousness; we only observe some of its properties,
namely geometric and topological properties of visual consciousness, and show
that these properties cannot be based on physics only. Now, if a part of
consciousness cannot be grounded on physics only, it is the same for
consciousness as a whole and we speak of the irreducibility of consciousness to
physical data. We do not consider philosophical questions or issues; in a
simple physical and mathematical frame we give a logical proof of this
irreducibility. Elements for a formal mathematical, logical proof are mentioned
at the end of the paper.
| [
{
"created": "Sat, 16 Oct 2021 21:45:59 GMT",
"version": "v1"
}
] | 2021-10-28 | [
[
"Reznikoff",
"Iegor",
""
]
] | We show here that what we call visual space of consciousness, the space of what we see, is a specific space different from the purely physical one and that its properties imply that it cannot be reduced to or deduced from physical laws. Some biological points are also briefly considered. The arguments are of logical, mathematical and physical character, and although elementary they require a careful reading. A first shorter version of this paper appeared in a hardly accessible Journal [1], and presented at the International Congress of Logic, Methodology and Philosophy of Sciences, in Beijing, August 2007. There is no need to define consciousness; we only observe some of its properties, namely geometric and topological properties of visual consciousness, and show that these properties cannot be based on physics only. Now, if a part of consciousness cannot be grounded on physics only, it is the same for consciousness as a whole and we speak of the irreducibility of consciousness to physical data. We do not consider philosophical questions or issues; in a simple physical and mathematical frame we give a logical proof of this irreducibility. Elements for a formal mathematical, logical proof are mentioned at the end of the paper. |
2111.04174 | Angela Tam | Angela Tam, C\'esar Laurent, Serge Gauthier, Christian Dansereau | Prediction of cognitive decline for enrichment of Alzheimer's disease
clinical trials | 11 pages, 3 main figures, 3 main tables, supplementary material (3
tables, 2 figures), incorporated feedback from reviewers in the introduction
and discussion | null | 10.14283/jpad.2022.49 | null | q-bio.QM | http://creativecommons.org/licenses/by-nc-nd/4.0/ | A key issue to Alzheimer's disease clinical trial failures is poor
participant selection. Participants have heterogeneous cognitive trajectories
and many do not decline during trials, which reduces a study's power to detect
treatment effects. Trials need enrichment strategies to enroll individuals who
will decline. We developed machine learning models to predict cognitive
trajectories in participants with early Alzheimer's disease (n=1342) and
presymptomatic individuals (n=756) over 24 and 48 months respectively. Baseline
magnetic resonance imaging, cognitive tests, demographics, and APOE genotype
were used to classify decliners, measured by an increase in CDR-Sum of Boxes,
and non-decliners with up to 79% area under the curve (cross-validated and
out-of-sample). Using these prognostic models to recruit enriched cohorts of
decliners can reduce required sample sizes by as much as 51%, while maintaining
the same detection power, and thus may improve trial quality, derisk endpoint
failures, and accelerate therapeutic development in Alzheimer's disease.
| [
{
"created": "Sun, 7 Nov 2021 20:26:05 GMT",
"version": "v1"
},
{
"created": "Wed, 24 Nov 2021 18:41:23 GMT",
"version": "v2"
},
{
"created": "Thu, 25 Nov 2021 22:33:00 GMT",
"version": "v3"
},
{
"created": "Wed, 4 May 2022 14:59:55 GMT",
"version": "v4"
}
] | 2022-05-05 | [
[
"Tam",
"Angela",
""
],
[
"Laurent",
"César",
""
],
[
"Gauthier",
"Serge",
""
],
[
"Dansereau",
"Christian",
""
]
] | A key issue to Alzheimer's disease clinical trial failures is poor participant selection. Participants have heterogeneous cognitive trajectories and many do not decline during trials, which reduces a study's power to detect treatment effects. Trials need enrichment strategies to enroll individuals who will decline. We developed machine learning models to predict cognitive trajectories in participants with early Alzheimer's disease (n=1342) and presymptomatic individuals (n=756) over 24 and 48 months respectively. Baseline magnetic resonance imaging, cognitive tests, demographics, and APOE genotype were used to classify decliners, measured by an increase in CDR-Sum of Boxes, and non-decliners with up to 79% area under the curve (cross-validated and out-of-sample). Using these prognostic models to recruit enriched cohorts of decliners can reduce required sample sizes by as much as 51%, while maintaining the same detection power, and thus may improve trial quality, derisk endpoint failures, and accelerate therapeutic development in Alzheimer's disease. |
q-bio/0410014 | Kosuke Hamaguchi | Kosuke Hamaguchi, Masato Okada and Kazuyuki Aihara | Theory of localized synfire chain | 9 pages, 4 figures | null | null | null | q-bio.NC | null | Neuron is a noisy information processing unit and conventional view is that
information in the cortex is carried on the rate of neurons spike emission.
More recent studies on the activity propagation through the homogeneous network
have demonstrated that signals can be transmitted with millisecond fidelity;
this model is called the Synfire chain and suggests the possibility of the
spatio-temporal coding. However, the more biologically realistic, structured
feedforward network generates spatially distributed inputs. It results in the
difference of spike timing. This poses a question on how the spatial structure
of a network effect the stability of spatio-temporal spike patterns, and the
speed of a spike packet propagation. By formulating the Fokker-Planck equation
for the feedforwardly coupled network with Mexican-Hat type connectivity, we
show the stability of localized spike packet and existence of Multi-stable
phase where both uniform and localized spike packets are stable depending on
the initial input structure. The Multi-stable phase enables us to show that a
spike pattern, or the information of its own, determines the propagation speed.
| [
{
"created": "Wed, 13 Oct 2004 19:20:31 GMT",
"version": "v1"
}
] | 2007-05-23 | [
[
"Hamaguchi",
"Kosuke",
""
],
[
"Okada",
"Masato",
""
],
[
"Aihara",
"Kazuyuki",
""
]
] | Neuron is a noisy information processing unit and conventional view is that information in the cortex is carried on the rate of neurons spike emission. More recent studies on the activity propagation through the homogeneous network have demonstrated that signals can be transmitted with millisecond fidelity; this model is called the Synfire chain and suggests the possibility of the spatio-temporal coding. However, the more biologically realistic, structured feedforward network generates spatially distributed inputs. It results in the difference of spike timing. This poses a question on how the spatial structure of a network effect the stability of spatio-temporal spike patterns, and the speed of a spike packet propagation. By formulating the Fokker-Planck equation for the feedforwardly coupled network with Mexican-Hat type connectivity, we show the stability of localized spike packet and existence of Multi-stable phase where both uniform and localized spike packets are stable depending on the initial input structure. The Multi-stable phase enables us to show that a spike pattern, or the information of its own, determines the propagation speed. |
2109.13680 | David Kennedy | Troy Day, David A. Kennedy, Andrew F. Read, Sylvain Gandon | The evolutionary epidemiology of pathogens during vaccination campaigns | 12 pages, 5 figures, 3 boxes, 2 appendices, 1 supplemental figure | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | With the unprecedented global vaccination campaign against SARS-CoV-2
attention has now turned to the potential impact of this large-scale
intervention on the evolution of the virus. In this perspective we summarize
what is currently known about evolution in the context of vaccination from
research on other pathogen species, with an eye towards the future evolution of
SARS-CoV-2.
| [
{
"created": "Tue, 28 Sep 2021 12:52:08 GMT",
"version": "v1"
},
{
"created": "Mon, 31 Jan 2022 16:21:43 GMT",
"version": "v2"
}
] | 2022-02-01 | [
[
"Day",
"Troy",
""
],
[
"Kennedy",
"David A.",
""
],
[
"Read",
"Andrew F.",
""
],
[
"Gandon",
"Sylvain",
""
]
] | With the unprecedented global vaccination campaign against SARS-CoV-2 attention has now turned to the potential impact of this large-scale intervention on the evolution of the virus. In this perspective we summarize what is currently known about evolution in the context of vaccination from research on other pathogen species, with an eye towards the future evolution of SARS-CoV-2. |
2101.11401 | Atiyeh Fotoohinasab | Atiyeh Fotoohinasab | A new generalization of Parrondo's games to three players and its
application in genetic switches | Summary of Master Dissertation | null | null | null | q-bio.PE | http://creativecommons.org/licenses/by/4.0/ | Parrondo's paradox indicates a paradoxical situation in which a winning
expectation may occur in sequences of losing games. There are many versions of
the original Parrondo's games in the literature, but the games are played by
two players in all of them. We introduce a new extended version of games played
by three players and a three-sided biased dice instead of two players and a
biased coin in this work. In the first step, we find the part of the parameters
space where the games are played fairly. After adding noise to fair
probabilities, we combine two games randomly, periodically, and nonlinearly and
obtain the conditions under which the paradox can occur. This generalized model
can be applied in all science and engineering fields. It can also be used for
genetic switches. Genetic switches are often made by two reactive elements, but
the existence of more elements can lead to more existing decisions for cells.
Each genetic switch can be considered a game in which the reactive elements
compete to increase their molecular concentrations. We present three genetic
networks based on a new generalized Parrondo's games model, consisting of two
noisy genetic switches. The combination of them can increase network robustness
to noise. Each switch can also be used as an initial pattern to construct a
synthetic switch to change undesirable cells' fate.
| [
{
"created": "Sat, 23 Jan 2021 22:37:56 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Feb 2021 04:47:33 GMT",
"version": "v2"
}
] | 2021-02-03 | [
[
"Fotoohinasab",
"Atiyeh",
""
]
] | Parrondo's paradox indicates a paradoxical situation in which a winning expectation may occur in sequences of losing games. There are many versions of the original Parrondo's games in the literature, but the games are played by two players in all of them. We introduce a new extended version of games played by three players and a three-sided biased dice instead of two players and a biased coin in this work. In the first step, we find the part of the parameters space where the games are played fairly. After adding noise to fair probabilities, we combine two games randomly, periodically, and nonlinearly and obtain the conditions under which the paradox can occur. This generalized model can be applied in all science and engineering fields. It can also be used for genetic switches. Genetic switches are often made by two reactive elements, but the existence of more elements can lead to more existing decisions for cells. Each genetic switch can be considered a game in which the reactive elements compete to increase their molecular concentrations. We present three genetic networks based on a new generalized Parrondo's games model, consisting of two noisy genetic switches. The combination of them can increase network robustness to noise. Each switch can also be used as an initial pattern to construct a synthetic switch to change undesirable cells' fate. |
0907.2004 | Branislav Brutovsky | B. Brutovsky and D. Horvath | Optimization Aspects of Carcinogenesis | null | null | 10.1016/j.mehy.2009.10.019 | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Any process in which competing solutions replicate with errors and numbers of
their copies depend on their respective fitnesses is the evolutionary
optimization process. As during carcinogenesis mutated genomes replicate
according to their respective qualities, carcinogenesis obviously qualifies as
the evolutionary optimization process and conforms to common mathematical
basis. The optimization view accents statistical nature of carcinogenesis
proposing that during it the crucial role is actually played by the allocation
of trials. Optimal allocation of trials requires reliable schemas' fitnesses
estimations which necessitate appropriate, fitness landscape dependent,
statistics of population. In the spirit of the applied conceptual framework,
features which are known to decrease efficiency of any evolutionary
optimization procedure (or inhibit it completely) are anticipated as
"therapies" and reviewed. Strict adherence to the evolutionary optimization
framework leads us to some counterintuitive implications which are, however, in
agreement with recent experimental findings, such as sometimes observed more
aggressive and malignant growth of therapy surviving cancer cells.
| [
{
"created": "Sun, 12 Jul 2009 04:40:29 GMT",
"version": "v1"
},
{
"created": "Mon, 3 Aug 2009 19:46:06 GMT",
"version": "v2"
},
{
"created": "Mon, 2 Nov 2009 17:53:32 GMT",
"version": "v3"
}
] | 2009-12-15 | [
[
"Brutovsky",
"B.",
""
],
[
"Horvath",
"D.",
""
]
] | Any process in which competing solutions replicate with errors and numbers of their copies depend on their respective fitnesses is the evolutionary optimization process. As during carcinogenesis mutated genomes replicate according to their respective qualities, carcinogenesis obviously qualifies as the evolutionary optimization process and conforms to common mathematical basis. The optimization view accents statistical nature of carcinogenesis proposing that during it the crucial role is actually played by the allocation of trials. Optimal allocation of trials requires reliable schemas' fitnesses estimations which necessitate appropriate, fitness landscape dependent, statistics of population. In the spirit of the applied conceptual framework, features which are known to decrease efficiency of any evolutionary optimization procedure (or inhibit it completely) are anticipated as "therapies" and reviewed. Strict adherence to the evolutionary optimization framework leads us to some counterintuitive implications which are, however, in agreement with recent experimental findings, such as sometimes observed more aggressive and malignant growth of therapy surviving cancer cells. |
q-bio/0501022 | Alan McKane | A. J. McKane and T. J. Newman | Stochastic models in population biology and their deterministic analogs | 47 pages, 9 figures | Phys. Rev. E 70, 041902 (2004) | 10.1103/PhysRevE.70.041902 | null | q-bio.PE | null | In this paper we introduce a class of stochastic population models based on
"patch dynamics". The size of the patch may be varied, and this allows one to
quantify the departures of these stochastic models from various mean field
theories, which are generally valid as the patch size becomes very large. These
models may be used to formulate a broad range of biological processes in both
spatial and non-spatial contexts. Here, we concentrate on two-species
competition. We present both a mathematical analysis of the patch model, in
which we derive the precise form of the competition mean field equations (and
their first order corrections in the non-spatial case), and simulation results.
These mean field equations differ, in some important ways, from those which are
normally written down on phenomenological grounds. Our general conclusion is
that mean field theory is more robust for spatial models than for a single
isolated patch. This is due to the dilution of stochastic effects in a spatial
setting resulting from repeated rescue events mediated by inter-patch
diffusion. However, discrete effects due to modest patch sizes lead to striking
deviations from mean field theory even in a spatial setting.
| [
{
"created": "Sun, 16 Jan 2005 14:25:18 GMT",
"version": "v1"
}
] | 2009-11-11 | [
[
"McKane",
"A. J.",
""
],
[
"Newman",
"T. J.",
""
]
] | In this paper we introduce a class of stochastic population models based on "patch dynamics". The size of the patch may be varied, and this allows one to quantify the departures of these stochastic models from various mean field theories, which are generally valid as the patch size becomes very large. These models may be used to formulate a broad range of biological processes in both spatial and non-spatial contexts. Here, we concentrate on two-species competition. We present both a mathematical analysis of the patch model, in which we derive the precise form of the competition mean field equations (and their first order corrections in the non-spatial case), and simulation results. These mean field equations differ, in some important ways, from those which are normally written down on phenomenological grounds. Our general conclusion is that mean field theory is more robust for spatial models than for a single isolated patch. This is due to the dilution of stochastic effects in a spatial setting resulting from repeated rescue events mediated by inter-patch diffusion. However, discrete effects due to modest patch sizes lead to striking deviations from mean field theory even in a spatial setting. |
2110.12252 | Alejandro Tabas | Alejandro Tabas and Katharina von Kriegstein | Concurrent generative models inform prediction error in the human
auditory pathway | null | null | null | null | q-bio.NC | http://creativecommons.org/licenses/by-sa/4.0/ | Predictive coding is the leading algorithmic framework to understand how
expectations shape our experience of reality. Its main tenet is that sensory
neurons encode prediction error: the residuals between a generative model of
the sensory world and the actual sensory input. However, it is yet unclear how
this scheme generalises to the multi-level hierarchical architecture of sensory
processing. Theoretical accounts of predictive coding agree that neurons
computing prediction error and the generative model exist at all levels of the
processing hierarchy. However, there is not a current consensus of how
predictions from independent models at different stages are integrated during
the computation of prediction error. Here we investigated predictive processing
with respect to two independent concurrent generative models in the auditory
pathway using functional magnetic resonance imaging. We used two paradigms
where human participants listened to sequences of either pure tones or
FM-sweeps while we recorded BOLD responses in inferior colliculus (IC), medial
geniculate body (MGB), and auditory cortex (AC). Each paradigm included the
induction of two generative models: one based on local stimulus statistics; and
another model based on the subjective expectations induced by task instruction.
We used Bayesian model comparison to test whether neural responses in IC, MGB,
and AC encoded prediction error with respect to either of the two generative
models, or a combination of both. Results showed that neural populations in
bilateral IC, MGB, and AC encode prediction error with respect to a combination
of the two generative models, suggesting that the predictive architecture of
predictive coding might be more complex than previously hypothesised.
| [
{
"created": "Sat, 23 Oct 2021 15:53:22 GMT",
"version": "v1"
},
{
"created": "Tue, 18 Jan 2022 19:36:56 GMT",
"version": "v2"
}
] | 2022-01-20 | [
[
"Tabas",
"Alejandro",
""
],
[
"von Kriegstein",
"Katharina",
""
]
] | Predictive coding is the leading algorithmic framework to understand how expectations shape our experience of reality. Its main tenet is that sensory neurons encode prediction error: the residuals between a generative model of the sensory world and the actual sensory input. However, it is yet unclear how this scheme generalises to the multi-level hierarchical architecture of sensory processing. Theoretical accounts of predictive coding agree that neurons computing prediction error and the generative model exist at all levels of the processing hierarchy. However, there is not a current consensus of how predictions from independent models at different stages are integrated during the computation of prediction error. Here we investigated predictive processing with respect to two independent concurrent generative models in the auditory pathway using functional magnetic resonance imaging. We used two paradigms where human participants listened to sequences of either pure tones or FM-sweeps while we recorded BOLD responses in inferior colliculus (IC), medial geniculate body (MGB), and auditory cortex (AC). Each paradigm included the induction of two generative models: one based on local stimulus statistics; and another model based on the subjective expectations induced by task instruction. We used Bayesian model comparison to test whether neural responses in IC, MGB, and AC encoded prediction error with respect to either of the two generative models, or a combination of both. Results showed that neural populations in bilateral IC, MGB, and AC encode prediction error with respect to a combination of the two generative models, suggesting that the predictive architecture of predictive coding might be more complex than previously hypothesised. |
0711.2799 | German Andres Enciso | German A. Enciso and Winfried Just | Large attractors in cooperative bi-quadratic Boolean networks. Part I | 13 pages, 2 figures resubmission with additional references | null | null | null | q-bio.MN q-bio.QM | null | Boolean networks have been the object of much attention, especially since S.
Kauffman proposed them in the 1960's as models for gene regulatory networks.
These systems are characterized by being defined on a Boolean state space and
by simultaneous updating at discrete time steps. Of particular importance for
biological applications are networks in which the indegree for each variable is
bounded by a fixed constant, as was stressed by Kauffman in his original
papers.
An important question is which conditions on the network topology can rule
out exponentially long periodic orbits in the system. In this paper, we
consider systems with positive feedback interconnections among all variables
(known as cooperative systems), which in a continuous setting guarantees a very
stable dynamics. We show that for an arbitrary constant 0<c<2 and sufficiently
large n there exist n-dimensional cooperative Boolean networks in which both
the indegree and outdegree of each variable is bounded by two, and which
nevertheless contain periodic orbits of length at least c^n. In Part II of this
paper we will prove an inverse result showing that any system with such a
dynamic behavior must in a sense be similar to the example described.
| [
{
"created": "Sun, 18 Nov 2007 17:04:01 GMT",
"version": "v1"
},
{
"created": "Wed, 21 Nov 2007 17:50:40 GMT",
"version": "v2"
}
] | 2007-11-21 | [
[
"Enciso",
"German A.",
""
],
[
"Just",
"Winfried",
""
]
] | Boolean networks have been the object of much attention, especially since S. Kauffman proposed them in the 1960's as models for gene regulatory networks. These systems are characterized by being defined on a Boolean state space and by simultaneous updating at discrete time steps. Of particular importance for biological applications are networks in which the indegree for each variable is bounded by a fixed constant, as was stressed by Kauffman in his original papers. An important question is which conditions on the network topology can rule out exponentially long periodic orbits in the system. In this paper, we consider systems with positive feedback interconnections among all variables (known as cooperative systems), which in a continuous setting guarantees a very stable dynamics. We show that for an arbitrary constant 0<c<2 and sufficiently large n there exist n-dimensional cooperative Boolean networks in which both the indegree and outdegree of each variable is bounded by two, and which nevertheless contain periodic orbits of length at least c^n. In Part II of this paper we will prove an inverse result showing that any system with such a dynamic behavior must in a sense be similar to the example described. |
1604.03052 | Sabrina Rashid | Shashank Singh, Sabrina Rashid, Zhicheng Long, Saket Navlakha, Hanna
Salman, Zoltan N. Oltvai, Ziv Bar-Joseph | Distributed Gradient Descent in Bacterial Food Search | null | null | null | null | q-bio.QM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Communication and coordination play a major role in the ability of bacterial
cells to adapt to ever changing environments and conditions. Recent work has
shown that such coordination underlies several aspects of bacterial responses
including their ability to develop antibiotic resistance. Here we develop a new
distributed gradient descent method that helps explain how bacterial cells
collectively search for food in harsh environments using extremely limited
communication and computational complexity. This method can also be used for
computational tasks when agents are facing similarly restricted conditions. We
formalize the communication and computation assumptions required for successful
coordination and prove that the method we propose leads to convergence even
when using a dynamically changing interaction network. The proposed method
improves upon prior models suggested for bacterial foraging despite making
fewer assumptions. Simulation studies and analysis of experimental data
illustrate the ability of the method to explain and further predict several
aspects of bacterial swarm food search.
| [
{
"created": "Mon, 11 Apr 2016 18:19:33 GMT",
"version": "v1"
}
] | 2016-04-12 | [
[
"Singh",
"Shashank",
""
],
[
"Rashid",
"Sabrina",
""
],
[
"Long",
"Zhicheng",
""
],
[
"Navlakha",
"Saket",
""
],
[
"Salman",
"Hanna",
""
],
[
"Oltvai",
"Zoltan N.",
""
],
[
"Bar-Joseph",
"Ziv",
""
]
] | Communication and coordination play a major role in the ability of bacterial cells to adapt to ever changing environments and conditions. Recent work has shown that such coordination underlies several aspects of bacterial responses including their ability to develop antibiotic resistance. Here we develop a new distributed gradient descent method that helps explain how bacterial cells collectively search for food in harsh environments using extremely limited communication and computational complexity. This method can also be used for computational tasks when agents are facing similarly restricted conditions. We formalize the communication and computation assumptions required for successful coordination and prove that the method we propose leads to convergence even when using a dynamically changing interaction network. The proposed method improves upon prior models suggested for bacterial foraging despite making fewer assumptions. Simulation studies and analysis of experimental data illustrate the ability of the method to explain and further predict several aspects of bacterial swarm food search. |
1306.1339 | Mike Steel Prof. | Dietrich Radel, Andreas Sand, Mike Steel | Hide and seek: placing and finding an optimal tree for thousands of
homoplasy-rich sequences | 8 pages, 2 figures, 1 table | null | null | null | q-bio.PE | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | Finding optimal evolutionary trees from sequence data is typically an
intractable problem, and there is usually no way of knowing how close to
optimal the best tree from some search truly is. The problem would seem to be
particularly acute when we have many taxa and when that data has high levels of
homoplasy, in which the individual characters require many changes to fit on
the best tree. However, a recent mathematical result has provided a precise
tool to generate a short number of high-homoplasy characters for any given
tree, so that this tree is provably the optimal tree under the maximum
parsimony criterion. This provides, for the first time, a rigorous way to test
tree search algorithms on homoplasy-rich data, where we know in advance what
the `best' tree is. In this short note we consider just one search program
(TNT) but show that it is able to locate the globally optimal tree correctly
for 32,768 taxa, even though the characters in the dataset requires, on
average, 1148 state-changes each to fit on this tree, and the number of
characters is only 57.
| [
{
"created": "Thu, 6 Jun 2013 08:43:37 GMT",
"version": "v1"
}
] | 2013-06-07 | [
[
"Radel",
"Dietrich",
""
],
[
"Sand",
"Andreas",
""
],
[
"Steel",
"Mike",
""
]
] | Finding optimal evolutionary trees from sequence data is typically an intractable problem, and there is usually no way of knowing how close to optimal the best tree from some search truly is. The problem would seem to be particularly acute when we have many taxa and when that data has high levels of homoplasy, in which the individual characters require many changes to fit on the best tree. However, a recent mathematical result has provided a precise tool to generate a short number of high-homoplasy characters for any given tree, so that this tree is provably the optimal tree under the maximum parsimony criterion. This provides, for the first time, a rigorous way to test tree search algorithms on homoplasy-rich data, where we know in advance what the `best' tree is. In this short note we consider just one search program (TNT) but show that it is able to locate the globally optimal tree correctly for 32,768 taxa, even though the characters in the dataset requires, on average, 1148 state-changes each to fit on this tree, and the number of characters is only 57. |
2103.02044 | Sara Zullino PhD | Sara Zullino, Alessandro Paglialonga, Walter Dastr\`u, Dario Livio
Longo, Silvio Aime | XNAT-PIC: Extending XNAT to Preclinical Imaging Centers | null | null | null | null | q-bio.QM eess.IV | http://creativecommons.org/licenses/by/4.0/ | Molecular imaging generates large volumes of heterogeneous biomedical imagery
with an impelling need of guidelines for handling image data. Although several
successful solutions have been implemented for human epidemiologic studies, few
and limited approaches have been proposed for animal population studies.
Preclinical imaging research deals with a variety of machinery yielding tons of
raw data but the current practices to store and distribute image data are
inadequate. Therefore, standard tools for the analysis of large image datasets
need to be established. In this paper, we present an extension of XNAT for
Preclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-source
platform for securely hosting, sharing, and processing of clinical imaging
studies. Despite its success, neither tools for importing large, multimodal
preclinical image datasets nor pipelines for processing whole imaging studies
are yet available in XNAT. In order to overcome these limitations, we have
developed several tools to expand the XNAT core functionalities for supporting
preclinical imaging facilities. Our aim is to streamline the management and
exchange of image data within the preclinical imaging community, thereby
enhancing the reproducibility of the results of image processing and promoting
open science practices.
| [
{
"created": "Tue, 23 Feb 2021 17:15:27 GMT",
"version": "v1"
}
] | 2021-03-04 | [
[
"Zullino",
"Sara",
""
],
[
"Paglialonga",
"Alessandro",
""
],
[
"Dastrù",
"Walter",
""
],
[
"Longo",
"Dario Livio",
""
],
[
"Aime",
"Silvio",
""
]
] | Molecular imaging generates large volumes of heterogeneous biomedical imagery with an impelling need of guidelines for handling image data. Although several successful solutions have been implemented for human epidemiologic studies, few and limited approaches have been proposed for animal population studies. Preclinical imaging research deals with a variety of machinery yielding tons of raw data but the current practices to store and distribute image data are inadequate. Therefore, standard tools for the analysis of large image datasets need to be established. In this paper, we present an extension of XNAT for Preclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-source platform for securely hosting, sharing, and processing of clinical imaging studies. Despite its success, neither tools for importing large, multimodal preclinical image datasets nor pipelines for processing whole imaging studies are yet available in XNAT. In order to overcome these limitations, we have developed several tools to expand the XNAT core functionalities for supporting preclinical imaging facilities. Our aim is to streamline the management and exchange of image data within the preclinical imaging community, thereby enhancing the reproducibility of the results of image processing and promoting open science practices. |
0708.0187 | Eduardo Candelario-Jalil | E. Candelario-Jalil, A. Gonzalez-Falcon, M. Garcia-Cabrera, O. S.
Leon, B. L. Fiebich | Wide therapeutic time window for nimesulide neuroprotection in a model
of transient focal cerebral ischemia in the rat | null | Brain Research 1007(1-2): 98-108 (2004) | null | null | q-bio.NC q-bio.TO | null | Results from several studies indicate that cyclooxygenase-2 (COX-2) is
involved in ischemic brain injury. The purpose of this study was to evaluate
the neuroprotective effects of the selective COX-2 inhibitor nimesulide on
cerebral infarction and neurological deficits in a standardized model of
transient focal cerebral ischemia in rats. Three doses of nimesulide (3, 6 and
12 mg/kg; i.p.) or vehicle were administered immediately after stroke and
additional doses were given at 6, 12, 24, 36 and 48 h after ischemia. In other
set of experiments, the effect of nimesulide was studied in a situation in
which its first administration was delayed for 3-24 h after ischemia. Total,
cortical and subcortical infarct volumes and functional outcome (assessed by
neurological deficit score and rotarod performance) were determined 3 days
after ischemia. The effect of nimesulide on prostaglandin E(2) (PGE(2)) levels
in the injured brain was also investigated. Nimesulide dose-dependently reduced
infarct volume and improved functional recovery when compared to vehicle. Of
interest is the finding that neuroprotection conferred by nimesulide (reduction
of infarct size and neurological deficits and improvement of rotarod
performance) was also observed when treatment was delayed until 24 h after
ischemia. Further, administration of nimesulide in a delayed treatment paradigm
completely abolished PGE(2) accumulation in the postischemic brain, suggesting
that COX-2 inhibition is a promising therapeutic strategy for cerebral ischemia
to target the late-occurring inflammatory events which amplify initial damage.
| [
{
"created": "Wed, 1 Aug 2007 16:09:39 GMT",
"version": "v1"
}
] | 2007-08-02 | [
[
"Candelario-Jalil",
"E.",
""
],
[
"Gonzalez-Falcon",
"A.",
""
],
[
"Garcia-Cabrera",
"M.",
""
],
[
"Leon",
"O. S.",
""
],
[
"Fiebich",
"B. L.",
""
]
] | Results from several studies indicate that cyclooxygenase-2 (COX-2) is involved in ischemic brain injury. The purpose of this study was to evaluate the neuroprotective effects of the selective COX-2 inhibitor nimesulide on cerebral infarction and neurological deficits in a standardized model of transient focal cerebral ischemia in rats. Three doses of nimesulide (3, 6 and 12 mg/kg; i.p.) or vehicle were administered immediately after stroke and additional doses were given at 6, 12, 24, 36 and 48 h after ischemia. In other set of experiments, the effect of nimesulide was studied in a situation in which its first administration was delayed for 3-24 h after ischemia. Total, cortical and subcortical infarct volumes and functional outcome (assessed by neurological deficit score and rotarod performance) were determined 3 days after ischemia. The effect of nimesulide on prostaglandin E(2) (PGE(2)) levels in the injured brain was also investigated. Nimesulide dose-dependently reduced infarct volume and improved functional recovery when compared to vehicle. Of interest is the finding that neuroprotection conferred by nimesulide (reduction of infarct size and neurological deficits and improvement of rotarod performance) was also observed when treatment was delayed until 24 h after ischemia. Further, administration of nimesulide in a delayed treatment paradigm completely abolished PGE(2) accumulation in the postischemic brain, suggesting that COX-2 inhibition is a promising therapeutic strategy for cerebral ischemia to target the late-occurring inflammatory events which amplify initial damage. |
2008.04531 | Alexandre de Brevern | Andrea Hill, Salwa Karboune, Tarun Narwani (BIGR, INTS, Labex Gr-Ex),
Alexandre de Brevern (BIGR, INTS, Labex Gr-Ex) | Investigating the Product Profiles and Structural Relationships of New
Levansucrases with Conventional and Non-Conventional Substrates | null | International Journal of Molecular Sciences, MDPI, 2020, 21 (15),
pp.5402 | 10.3390/ijms21155402 | null | q-bio.QM q-bio.BM | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ | The synthesis of complex oligosaccharides is desired for their potential as
prebiotics, and their role in the pharmaceutical and food industry.
Levansucrase (LS, EC 2.4.1.10), a fructosyl-transferase, can catalyze the
synthesis of these compounds. LS acquires a fructosyl residue from a donor
molecule and performs a non-Lenoir transfer to an acceptor molecule, via
$\beta$-(2$\to$6)-glycosidic linkages. Genome mining was used to uncover new LS
enzymes with increased transfructosylating activity and wider acceptor
promiscuity, with an initial screening revealing five LS enzymes. The product
profiles and activities of these enzymes were examined after their incubation
with sucrose. Alternate acceptor molecules were also incubated with the enzymes
to study their consumption. LSs from Gluconobacter oxydans and Novosphingobium
aromaticivorans synthesized fructooligosaccharides (FOSs) with up to 13 units
in length. Alignment of their amino acid sequences and substrate docking with
homology models identified structural elements causing differences in their
product spectra. Raffinose, over sucrose, was the preferred donor molecule for
the LS from Vibrio natriegens, N. aromaticivorans, and Paraburkolderia
graminis. The LSs examined were found to have wide acceptor promiscuity,
utilizing monosaccharides, disaccharides, and two alcohols to a high degree.
| [
{
"created": "Tue, 11 Aug 2020 06:09:38 GMT",
"version": "v1"
}
] | 2020-08-12 | [
[
"Hill",
"Andrea",
"",
"BIGR, INTS, Labex Gr-Ex"
],
[
"Karboune",
"Salwa",
"",
"BIGR, INTS, Labex Gr-Ex"
],
[
"Narwani",
"Tarun",
"",
"BIGR, INTS, Labex Gr-Ex"
],
[
"de Brevern",
"Alexandre",
"",
"BIGR, INTS, Labex Gr-Ex"
]
] | The synthesis of complex oligosaccharides is desired for their potential as prebiotics, and their role in the pharmaceutical and food industry. Levansucrase (LS, EC 2.4.1.10), a fructosyl-transferase, can catalyze the synthesis of these compounds. LS acquires a fructosyl residue from a donor molecule and performs a non-Lenoir transfer to an acceptor molecule, via $\beta$-(2$\to$6)-glycosidic linkages. Genome mining was used to uncover new LS enzymes with increased transfructosylating activity and wider acceptor promiscuity, with an initial screening revealing five LS enzymes. The product profiles and activities of these enzymes were examined after their incubation with sucrose. Alternate acceptor molecules were also incubated with the enzymes to study their consumption. LSs from Gluconobacter oxydans and Novosphingobium aromaticivorans synthesized fructooligosaccharides (FOSs) with up to 13 units in length. Alignment of their amino acid sequences and substrate docking with homology models identified structural elements causing differences in their product spectra. Raffinose, over sucrose, was the preferred donor molecule for the LS from Vibrio natriegens, N. aromaticivorans, and Paraburkolderia graminis. The LSs examined were found to have wide acceptor promiscuity, utilizing monosaccharides, disaccharides, and two alcohols to a high degree. |
q-bio/0501033 | Nigel Goldenfeld | Kalin Vetsigian and Nigel Goldenfeld (University of Illinois at
Urbana-Champaign) | Global divergence of microbial genome sequences mediated by propagating
fronts | null | null | 10.1073/pnas.0502757102 | null | q-bio.GN | null | We model the competition between recombination and point mutation in
microbial genomes, and present evidence for two distinct phases, one uniform,
the other genetically diverse. Depending on the specifics of homologous
recombination, we find that global sequence divergence can be mediated by
fronts propagating along the genome, whose characteristic signature on genome
structure is elucidated, and apparently observed in closely-related {\it
Bacillus} strains. Front propagation provides an emergent, generic mechanism
for microbial "speciation", and suggests a classification of microorganisms on
the basis of their propensity to support propagating fronts.
| [
{
"created": "Wed, 26 Jan 2005 18:03:38 GMT",
"version": "v1"
},
{
"created": "Thu, 27 Jan 2005 02:01:52 GMT",
"version": "v2"
},
{
"created": "Wed, 13 Apr 2005 16:27:12 GMT",
"version": "v3"
}
] | 2009-11-11 | [
[
"Vetsigian",
"Kalin",
"",
"University of Illinois at\n Urbana-Champaign"
],
[
"Goldenfeld",
"Nigel",
"",
"University of Illinois at\n Urbana-Champaign"
]
] | We model the competition between recombination and point mutation in microbial genomes, and present evidence for two distinct phases, one uniform, the other genetically diverse. Depending on the specifics of homologous recombination, we find that global sequence divergence can be mediated by fronts propagating along the genome, whose characteristic signature on genome structure is elucidated, and apparently observed in closely-related {\it Bacillus} strains. Front propagation provides an emergent, generic mechanism for microbial "speciation", and suggests a classification of microorganisms on the basis of their propensity to support propagating fronts. |
2402.02203 | Erin Weisbart | Erin Weisbart, Ankur Kumar, John Arevalo, Anne E. Carpenter, Beth A.
Cimini, Shantanu Singh | Cell Painting Gallery: an open resource for image-based profiling | 9 pages, 1 table | null | null | null | q-bio.QM | http://creativecommons.org/licenses/by/4.0/ | Image-based or morphological profiling is a rapidly expanding field wherein
cells are "profiled" by extracting hundreds to thousands of unbiased,
quantitative features from images of cells that have been perturbed by genetic
or chemical perturbations. The Cell Painting assay is the most popular
imaged-based profiling assay wherein six small-molecule dyes label eight
cellular compartments and thousands of measurements are made, describing
quantitative traits such as size, shape, intensity, and texture within the
nucleus, cytoplasm, and whole cell (Cimini et al., 2023). We have created the
Cell Painting Gallery, a publicly available collection of Cell Painting
datasets, with granular dataset descriptions and access instructions. It is
hosted by AWS on the Registry of Open Data (RODA). As of January 2024, the Cell
Painting Gallery holds 656 terabytes (TB) of image and associated numerical
data. It includes the largest publicly available Cell Painting dataset, in
terms of perturbations tested (Joint Undertaking for Morphological Profiling or
JUMP (Chandrasekaran et al., 2023)), along with many other canonical datasets
using Cell Painting, close derivatives of Cell Painting (such as
LipocyteProfiler (Laber et al., 2023) and Pooled Cell Painting (Ramezani et
al., 2023)).
| [
{
"created": "Sat, 3 Feb 2024 16:35:31 GMT",
"version": "v1"
}
] | 2024-02-06 | [
[
"Weisbart",
"Erin",
""
],
[
"Kumar",
"Ankur",
""
],
[
"Arevalo",
"John",
""
],
[
"Carpenter",
"Anne E.",
""
],
[
"Cimini",
"Beth A.",
""
],
[
"Singh",
"Shantanu",
""
]
] | Image-based or morphological profiling is a rapidly expanding field wherein cells are "profiled" by extracting hundreds to thousands of unbiased, quantitative features from images of cells that have been perturbed by genetic or chemical perturbations. The Cell Painting assay is the most popular imaged-based profiling assay wherein six small-molecule dyes label eight cellular compartments and thousands of measurements are made, describing quantitative traits such as size, shape, intensity, and texture within the nucleus, cytoplasm, and whole cell (Cimini et al., 2023). We have created the Cell Painting Gallery, a publicly available collection of Cell Painting datasets, with granular dataset descriptions and access instructions. It is hosted by AWS on the Registry of Open Data (RODA). As of January 2024, the Cell Painting Gallery holds 656 terabytes (TB) of image and associated numerical data. It includes the largest publicly available Cell Painting dataset, in terms of perturbations tested (Joint Undertaking for Morphological Profiling or JUMP (Chandrasekaran et al., 2023)), along with many other canonical datasets using Cell Painting, close derivatives of Cell Painting (such as LipocyteProfiler (Laber et al., 2023) and Pooled Cell Painting (Ramezani et al., 2023)). |
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