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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1310.4232
|
Alexander Goltsev
|
K.-E. Lee, M. A. Lopes, J. F. F. Mendes, and A. V. Goltsev
|
Critical phenomena and noise-induced phase transitions in neuronal
networks
|
15 pages, 9 figures. arXiv admin note: substantial text overlap with
arXiv:1304.3237
|
Phys. Rev. E. 89, 012701 (2014)
|
10.1103/PhysRevE.89.012701
| null |
q-bio.NC nlin.AO physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study numerically and analytically first- and second-order phase
transitions in neuronal networks stimulated by shot noise (a flow of random
spikes bombarding neurons). Using an exactly solvable cortical model of
neuronal networks on classical random networks, we find critical phenomena
accompanying the transitions and their dependence on the shot noise intensity.
We show that a pattern of spontaneous neuronal activity near a critical point
of a phase transition is a characteristic property that can be used to identify
the bifurcation mechanism of the transition. We demonstrate that bursts and
avalanches are precursors of a first-order phase transition, paroxysmal-like
spikes of activity precede a second-order phase transition caused by a
saddle-node bifurcation, while irregular spindle oscillations represent
spontaneous activity near a second-order phase transition caused by a
supercritical Hopf bifurcation. Our most interesting result is the observation
of the paroxysmal-like spikes. We show that a paroxysmal-like spike is a single
nonlinear event that appears instantly from a low background activity with a
rapid onset, reaches a large amplitude, and ends up with an abrupt return to
lower activity. These spikes are similar to single paroxysmal spikes and sharp
waves observed in EEG measurements. Our analysis shows that above the
saddle-node bifurcation, sustained network oscillations appear with a large
amplitude but a small frequency in contrast to network oscillations near the
Hopf bifurcation that have a small amplitude but a large frequency. We discuss
an amazing similarity between excitability of the cortical model stimulated by
shot noise and excitability of the Morris-Lecar neuron stimulated by an applied
current.
|
[
{
"created": "Wed, 16 Oct 2013 00:42:29 GMT",
"version": "v1"
}
] |
2015-08-25
|
[
[
"Lee",
"K. -E.",
""
],
[
"Lopes",
"M. A.",
""
],
[
"Mendes",
"J. F. F.",
""
],
[
"Goltsev",
"A. V.",
""
]
] |
We study numerically and analytically first- and second-order phase transitions in neuronal networks stimulated by shot noise (a flow of random spikes bombarding neurons). Using an exactly solvable cortical model of neuronal networks on classical random networks, we find critical phenomena accompanying the transitions and their dependence on the shot noise intensity. We show that a pattern of spontaneous neuronal activity near a critical point of a phase transition is a characteristic property that can be used to identify the bifurcation mechanism of the transition. We demonstrate that bursts and avalanches are precursors of a first-order phase transition, paroxysmal-like spikes of activity precede a second-order phase transition caused by a saddle-node bifurcation, while irregular spindle oscillations represent spontaneous activity near a second-order phase transition caused by a supercritical Hopf bifurcation. Our most interesting result is the observation of the paroxysmal-like spikes. We show that a paroxysmal-like spike is a single nonlinear event that appears instantly from a low background activity with a rapid onset, reaches a large amplitude, and ends up with an abrupt return to lower activity. These spikes are similar to single paroxysmal spikes and sharp waves observed in EEG measurements. Our analysis shows that above the saddle-node bifurcation, sustained network oscillations appear with a large amplitude but a small frequency in contrast to network oscillations near the Hopf bifurcation that have a small amplitude but a large frequency. We discuss an amazing similarity between excitability of the cortical model stimulated by shot noise and excitability of the Morris-Lecar neuron stimulated by an applied current.
|
2311.00616
|
Steffen Werner
|
W. Mathijs Rozemuller, Steffen Werner, Antonio Carlos Costa, Liam
O'Shaughnessy, Greg J. Stephens, Thomas S. Shimizu
|
Statistics of C. elegans turning behavior reveals optimality under
biasing constraints
|
32 pages, 17 figures
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Animal locomotion is often subject to constraints arising from
anatomical/physiological asymmetries. We use the nematode C.~elegans as a
minimal model system to ask whether such constraints might shape locomotion
patterns optimized during evolution. We focus on turning behaviours in two
contrasting environmental contexts: (i) random exploration in the absence of
strong stimuli and (ii) acute avoidance (escape) navigation upon encountering a
strong aversive stimulus. We characterise the full repertoire of reorientation
behaviours, including gradual reorientations and various posturally distinct
sharp turns. During exploration, our measurements and theoretical modelling
indicate that orientation fluctuations on short timescales are, on average,
optimized to compensate the constraining gradual turn bias on long timescales.
During escape, our data suggests that the reorientation is controlled not by an
analog logic of continuous turn-amplitude modulations, but rather through the
digital logic of selecting discrete turn types, leading to a symmetric escape
performance despite strongly asymmetric turning biases.
|
[
{
"created": "Wed, 1 Nov 2023 16:08:26 GMT",
"version": "v1"
},
{
"created": "Mon, 15 Jan 2024 11:58:02 GMT",
"version": "v2"
}
] |
2024-01-17
|
[
[
"Rozemuller",
"W. Mathijs",
""
],
[
"Werner",
"Steffen",
""
],
[
"Costa",
"Antonio Carlos",
""
],
[
"O'Shaughnessy",
"Liam",
""
],
[
"Stephens",
"Greg J.",
""
],
[
"Shimizu",
"Thomas S.",
""
]
] |
Animal locomotion is often subject to constraints arising from anatomical/physiological asymmetries. We use the nematode C.~elegans as a minimal model system to ask whether such constraints might shape locomotion patterns optimized during evolution. We focus on turning behaviours in two contrasting environmental contexts: (i) random exploration in the absence of strong stimuli and (ii) acute avoidance (escape) navigation upon encountering a strong aversive stimulus. We characterise the full repertoire of reorientation behaviours, including gradual reorientations and various posturally distinct sharp turns. During exploration, our measurements and theoretical modelling indicate that orientation fluctuations on short timescales are, on average, optimized to compensate the constraining gradual turn bias on long timescales. During escape, our data suggests that the reorientation is controlled not by an analog logic of continuous turn-amplitude modulations, but rather through the digital logic of selecting discrete turn types, leading to a symmetric escape performance despite strongly asymmetric turning biases.
|
q-bio/0602023
|
Gyorgy Korniss
|
Lauren O'Malley, James Basham, Joseph A. Yasi, G. Korniss, Andrew
Allstadt, and Tom Caraco
|
Invasive advance of an advantageous mutation: nucleation theory
| null |
Theoretical Population Biology, 70, 464-478 (2006).
|
10.1016/j.tpb.2006.06.006
| null |
q-bio.PE cond-mat.stat-mech
| null |
For most organisms with viscous population structure, spatially localized
growth drives the invasive advance of a favorable mutation. We model a
two-allele competition where recurrent mutation introduces a genotype with a
rate of local propagation exceeding the resident's rate. We capture
ecologically important properties of the rare invader's stochastic dynamics by
assuming discrete individuals and neighborhood interactions. To understand how
individual-level processes may govern population patterns, we invoke the
physical theory for nucleation of spatial systems. Nucleation theory
discriminates between single-cluster and multi-cluster dynamics. A sufficiently
low mutation rate, or a sufficiently small environment, generates
single-cluster dynamics, an inherently stochastic process; a favorable mutation
advances only if the invader cluster reaches a critical radius. For this mode
of invasion we identify the probability distribution of waiting times until the
favored allele advances to competitive dominance, and we ask how the critical
cluster size varies as propagation or mortality rates vary. Increasing the
mutation rate or system size generates multi-cluster invasion, where spatial
averaging produces nearly deterministic global dynamics. For this process, an
analytical approximation from nucleation theory, called Avrami's Law, describes
the time-dependent behavior of the genotype densities with remarkable accuracy.
|
[
{
"created": "Wed, 22 Feb 2006 22:25:45 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"O'Malley",
"Lauren",
""
],
[
"Basham",
"James",
""
],
[
"Yasi",
"Joseph A.",
""
],
[
"Korniss",
"G.",
""
],
[
"Allstadt",
"Andrew",
""
],
[
"Caraco",
"Tom",
""
]
] |
For most organisms with viscous population structure, spatially localized growth drives the invasive advance of a favorable mutation. We model a two-allele competition where recurrent mutation introduces a genotype with a rate of local propagation exceeding the resident's rate. We capture ecologically important properties of the rare invader's stochastic dynamics by assuming discrete individuals and neighborhood interactions. To understand how individual-level processes may govern population patterns, we invoke the physical theory for nucleation of spatial systems. Nucleation theory discriminates between single-cluster and multi-cluster dynamics. A sufficiently low mutation rate, or a sufficiently small environment, generates single-cluster dynamics, an inherently stochastic process; a favorable mutation advances only if the invader cluster reaches a critical radius. For this mode of invasion we identify the probability distribution of waiting times until the favored allele advances to competitive dominance, and we ask how the critical cluster size varies as propagation or mortality rates vary. Increasing the mutation rate or system size generates multi-cluster invasion, where spatial averaging produces nearly deterministic global dynamics. For this process, an analytical approximation from nucleation theory, called Avrami's Law, describes the time-dependent behavior of the genotype densities with remarkable accuracy.
|
1409.1637
|
Toru Aonishi
|
Kazuhiko Morinaga, Ryota Miyata and Toru Aonishi
|
Optimal Colored Noise for Estimating Phase Response Curves
|
12 pages, 4 figures
|
J. Phys. Soc. Jpn., 84(9): 094801 (2015)
|
10.7566/JPSJ.84.094801
| null |
q-bio.QM nlin.CD
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The phase response curve (PRC) is an important measure representing the
interaction between oscillatory elements. To understand synchrony in biological
systems, many research groups have sought to measure PRCs directly from
biological cells including neurons. Ermentrout et al. and Ota et al. showed
that PRCs can be identified through measurement of white-noise spike-triggered
averages. The disadvantage of this method is that one has to collect more than
ten-thousand spikes to ensure the accuracy of the estimate. In this paper, to
achieve a more accurate estimation of PRCs with a limited sample size, we use
colored noise, which has recently drawn attention because of its unique effect
on dynamical systems. We numerically show that there is an optimal colored
noise to estimate PRCs in the most rigorous fashion.
|
[
{
"created": "Fri, 5 Sep 2014 01:11:26 GMT",
"version": "v1"
},
{
"created": "Wed, 7 Jan 2015 07:55:33 GMT",
"version": "v2"
},
{
"created": "Mon, 6 Jul 2015 03:30:50 GMT",
"version": "v3"
}
] |
2015-08-03
|
[
[
"Morinaga",
"Kazuhiko",
""
],
[
"Miyata",
"Ryota",
""
],
[
"Aonishi",
"Toru",
""
]
] |
The phase response curve (PRC) is an important measure representing the interaction between oscillatory elements. To understand synchrony in biological systems, many research groups have sought to measure PRCs directly from biological cells including neurons. Ermentrout et al. and Ota et al. showed that PRCs can be identified through measurement of white-noise spike-triggered averages. The disadvantage of this method is that one has to collect more than ten-thousand spikes to ensure the accuracy of the estimate. In this paper, to achieve a more accurate estimation of PRCs with a limited sample size, we use colored noise, which has recently drawn attention because of its unique effect on dynamical systems. We numerically show that there is an optimal colored noise to estimate PRCs in the most rigorous fashion.
|
2103.15182
|
Pan Wang
|
Pan Wang, Danlin Peng, Simiao Yu, Chao Wu, Peter Childs, Yike Guo and
Ling Li
|
Verifying Design through Generative Visualization of Neural Activities
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Current neuroscience focused approaches for evaluating the effectiveness of a
design do not use direct visualisation of mental activity. A recurrent neural
network is used as the encoder to learn latent representation from
electroencephalogram (EEG) signals, recorded while subjects looked at 50
categories of images. A generative adversarial network (GAN) conditioned on the
EEG latent representation is trained for reconstructing these images. After
training, the neural network is able to reconstruct images from brain activity
recordings. To demonstrate the proposed method in the context of the mental
association with a design, we performed a study that indicates an iconic design
image could inspire the subject to create cognitive associations with branding
and valued products. The proposed method could have the potential in verifying
designs by visualizing the cognitive understanding of underlying brain
activity.
|
[
{
"created": "Sun, 28 Mar 2021 17:42:21 GMT",
"version": "v1"
}
] |
2021-03-30
|
[
[
"Wang",
"Pan",
""
],
[
"Peng",
"Danlin",
""
],
[
"Yu",
"Simiao",
""
],
[
"Wu",
"Chao",
""
],
[
"Childs",
"Peter",
""
],
[
"Guo",
"Yike",
""
],
[
"Li",
"Ling",
""
]
] |
Current neuroscience focused approaches for evaluating the effectiveness of a design do not use direct visualisation of mental activity. A recurrent neural network is used as the encoder to learn latent representation from electroencephalogram (EEG) signals, recorded while subjects looked at 50 categories of images. A generative adversarial network (GAN) conditioned on the EEG latent representation is trained for reconstructing these images. After training, the neural network is able to reconstruct images from brain activity recordings. To demonstrate the proposed method in the context of the mental association with a design, we performed a study that indicates an iconic design image could inspire the subject to create cognitive associations with branding and valued products. The proposed method could have the potential in verifying designs by visualizing the cognitive understanding of underlying brain activity.
|
1709.01852
|
Marcos Amaku
|
Eduardo Massad, Marcos Amaku, Francisco Antonio Bezerra Coutinho,
Claudio Jos\'e Struchiner, Luis Fernandez Lopez, Annelies Wilder-Smith and
Marcelo Nascimento Burattini
|
Estimating the Size of Aedes aegypti Populations from Dengue Incidence
Data: Implications for the Risk of Yellow Fever, Zika Virus and Chikungunya
Outbreaks
|
31 pages, 9 figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper we present a model to estimate the density of aedes mosquitoes
in a community affected by dengue. The model is based on the fitting of a
continuous function to the incidence of dengue infections, from which the
density of infected mosquitoes is derived straightforwardly. Further
derivations allows the calculation of the latent and susceptible mosquitoes'
densities, the sum of the three equals the total mosquitoes' density. The model
is illustrated with the case of the risk of urban yellow fever resurgence in
dengue infested areas but the same methods apply for other aedes-transmitted
infections like Zika and chikungunya viruses.
|
[
{
"created": "Wed, 6 Sep 2017 15:09:31 GMT",
"version": "v1"
},
{
"created": "Thu, 26 Oct 2017 16:11:47 GMT",
"version": "v2"
},
{
"created": "Tue, 7 Nov 2017 16:04:14 GMT",
"version": "v3"
}
] |
2017-11-08
|
[
[
"Massad",
"Eduardo",
""
],
[
"Amaku",
"Marcos",
""
],
[
"Coutinho",
"Francisco Antonio Bezerra",
""
],
[
"Struchiner",
"Claudio José",
""
],
[
"Lopez",
"Luis Fernandez",
""
],
[
"Wilder-Smith",
"Annelies",
""
],
[
"Burattini",
"Marcelo Nascimento",
""
]
] |
In this paper we present a model to estimate the density of aedes mosquitoes in a community affected by dengue. The model is based on the fitting of a continuous function to the incidence of dengue infections, from which the density of infected mosquitoes is derived straightforwardly. Further derivations allows the calculation of the latent and susceptible mosquitoes' densities, the sum of the three equals the total mosquitoes' density. The model is illustrated with the case of the risk of urban yellow fever resurgence in dengue infested areas but the same methods apply for other aedes-transmitted infections like Zika and chikungunya viruses.
|
2108.06264
|
Marta Bienkiewicz Dr
|
M. M. N. Bie\'nkiewicz (1), A. Smykovskyi (1), T. Olugbade (2), S.
Janaqi (1), A. Camurri (3), N. Bianchi-Berthouze (2), M. Bj\"orkman (4), B.
G. Bardy (1) ((1) EuroMov Digital Health in Motion Univ. Montpellier IMT
Mines Ales France, (2) UCL, University College of London UK, (3) UNIGE
InfoMus Casa Paganini Italy, (4) KTH Royal Institute of Technology Sweden)
|
Bridging the gap between emotion and joint action
|
Pages 44, Figures 6, Table 1, Article in press, Neuroscience and
Biobehavioral Reviews
| null | null | null |
q-bio.NC cs.LG cs.MA cs.RO math.DS
|
http://creativecommons.org/licenses/by/4.0/
|
Our daily human life is filled with a myriad of joint action moments, be it
children playing, adults working together (i.e., team sports), or strangers
navigating through a crowd. Joint action brings individuals (and embodiment of
their emotions) together, in space and in time. Yet little is known about how
individual emotions propagate through embodied presence in a group, and how
joint action changes individual emotion. In fact, the multi-agent component is
largely missing from neuroscience-based approaches to emotion, and reversely
joint action research has not found a way yet to include emotion as one of the
key parameters to model socio-motor interaction. In this review, we first
identify the gap and then stockpile evidence showing strong entanglement
between emotion and acting together from various branches of sciences. We
propose an integrative approach to bridge the gap, highlight five research
avenues to do so in behavioral neuroscience and digital sciences, and address
some of the key challenges in the area faced by modern societies.
|
[
{
"created": "Fri, 13 Aug 2021 14:21:37 GMT",
"version": "v1"
}
] |
2021-08-16
|
[
[
"Bieńkiewicz",
"M. M. N.",
""
],
[
"Smykovskyi",
"A.",
""
],
[
"Olugbade",
"T.",
""
],
[
"Janaqi",
"S.",
""
],
[
"Camurri",
"A.",
""
],
[
"Bianchi-Berthouze",
"N.",
""
],
[
"Björkman",
"M.",
""
],
[
"Bardy",
"B. G.",
""
]
] |
Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd. Joint action brings individuals (and embodiment of their emotions) together, in space and in time. Yet little is known about how individual emotions propagate through embodied presence in a group, and how joint action changes individual emotion. In fact, the multi-agent component is largely missing from neuroscience-based approaches to emotion, and reversely joint action research has not found a way yet to include emotion as one of the key parameters to model socio-motor interaction. In this review, we first identify the gap and then stockpile evidence showing strong entanglement between emotion and acting together from various branches of sciences. We propose an integrative approach to bridge the gap, highlight five research avenues to do so in behavioral neuroscience and digital sciences, and address some of the key challenges in the area faced by modern societies.
|
2102.12299
|
Jennifer Loria Sorio
|
Vinicius V. L. Albani, Jennifer Loria, Eduardo Massad and Jorge P.
Zubelli
|
The Impact of COVID-19 Vaccination Delay: A Modelling Study for Chicago
and NYC Data
|
21 pages, 6 figures, 3 tables
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Background: By the beginning of December 2020, some vaccines against COVID-19
already presented efficacy and security, which qualify them to be used in mass
vaccination campaigns. Thus, setting up strategies of vaccination became
crucial to control the COVID19 pandemic. Methods: We use daily COVID-19 reports
from Chicago and NYC from 01-Mar2020 to 28- Nov-2020 to estimate the parameters
of an SEIR-like epidemiological model that accounts for different severity
levels. To achieve data adherent predictions, we let the model parameters to be
time-dependent. The model is used to forecast different vaccination scenarios,
where the campaign starts at different dates, from 01-Oct-2020 to 01-Apr-2021.
To generate realistic scenarios, disease control strategies are implemented
whenever the number of predicted daily hospitalizations reaches a preset
threshold. Results: The model reproduces the empirical data with remarkable
accuracy. Delaying the vaccination severely affects the mortality,
hospitalization, and recovery projections. In Chicago, the disease spread was
under control, reducing the mortality increment as the start of the vaccination
was postponed. In NYC, the number of cases was increasing, thus, the estimated
model predicted a much larger impact, despite the implementation of contention
measures. The earlier the vaccination campaign begins, the larger is its
potential impact in reducing the COVID-19 cases, as well as in the
hospitalizations and deaths. Moreover, the rate at which cases,
hospitalizations and deaths increase with the delay in the vaccination
beginning strongly depends on the shape of the incidence of infection in each
city.
|
[
{
"created": "Wed, 24 Feb 2021 14:29:30 GMT",
"version": "v1"
}
] |
2021-02-25
|
[
[
"Albani",
"Vinicius V. L.",
""
],
[
"Loria",
"Jennifer",
""
],
[
"Massad",
"Eduardo",
""
],
[
"Zubelli",
"Jorge P.",
""
]
] |
Background: By the beginning of December 2020, some vaccines against COVID-19 already presented efficacy and security, which qualify them to be used in mass vaccination campaigns. Thus, setting up strategies of vaccination became crucial to control the COVID19 pandemic. Methods: We use daily COVID-19 reports from Chicago and NYC from 01-Mar2020 to 28- Nov-2020 to estimate the parameters of an SEIR-like epidemiological model that accounts for different severity levels. To achieve data adherent predictions, we let the model parameters to be time-dependent. The model is used to forecast different vaccination scenarios, where the campaign starts at different dates, from 01-Oct-2020 to 01-Apr-2021. To generate realistic scenarios, disease control strategies are implemented whenever the number of predicted daily hospitalizations reaches a preset threshold. Results: The model reproduces the empirical data with remarkable accuracy. Delaying the vaccination severely affects the mortality, hospitalization, and recovery projections. In Chicago, the disease spread was under control, reducing the mortality increment as the start of the vaccination was postponed. In NYC, the number of cases was increasing, thus, the estimated model predicted a much larger impact, despite the implementation of contention measures. The earlier the vaccination campaign begins, the larger is its potential impact in reducing the COVID-19 cases, as well as in the hospitalizations and deaths. Moreover, the rate at which cases, hospitalizations and deaths increase with the delay in the vaccination beginning strongly depends on the shape of the incidence of infection in each city.
|
1910.09510
|
Emmanuelle Jousselin
|
Emmanuelle Jousselin, Marianne Elias
|
Testing host-plant driven speciation in phytophagous insects : a
phylogenetic perspective
|
35 pages, 3 figures, 2 tables. Peer-reviewed and recommended by PCI
Evolutionary Biology (2019)
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
During the last two decades, ecological speciation has been a major research
theme in evolutionary biology. Ecological speciation occurs when reproductive
isolation between populations evolves as a result of niche differentiation.
Phytophagous insects represent model systems for the study of this evolutionary
process. The host-plants on which these insects feed and often spend parts of
their life cycle constitute ideal agents of divergent selection for these
organisms. Adaptation to feeding on different host-plant species can
potentially lead to ecological specialization of populations and subsequent
speciation. This process is thought to have given birth to the astonishing
diversity of phytophagous insects and is often put forward in macroevolutionary
scenarios of insect diversification. Consequently, numerous phylogenetic
studies on phytophagous insects have aimed at testing whether speciation driven
by host-plant adaptation is the main pathway for the diversification of the
groups under investigation. The increasing availability of comprehensive and
well-resolved phylogenies and the recent developments in phylogenetic
comparative methods are offering an unprecedented opportunity to test
hypotheses on insect diversification at a macroevolutionary scale, in a robust
phylogenetic framework. Our purpose here is to review the contribution of
phylogenetic analyses to investigate the importance of plant-mediated
speciation in the diversification of phytophagous insects and to present
suggestions for future developments in this field.
|
[
{
"created": "Mon, 21 Oct 2019 16:58:23 GMT",
"version": "v1"
},
{
"created": "Wed, 23 Oct 2019 08:55:08 GMT",
"version": "v2"
}
] |
2019-10-24
|
[
[
"Jousselin",
"Emmanuelle",
""
],
[
"Elias",
"Marianne",
""
]
] |
During the last two decades, ecological speciation has been a major research theme in evolutionary biology. Ecological speciation occurs when reproductive isolation between populations evolves as a result of niche differentiation. Phytophagous insects represent model systems for the study of this evolutionary process. The host-plants on which these insects feed and often spend parts of their life cycle constitute ideal agents of divergent selection for these organisms. Adaptation to feeding on different host-plant species can potentially lead to ecological specialization of populations and subsequent speciation. This process is thought to have given birth to the astonishing diversity of phytophagous insects and is often put forward in macroevolutionary scenarios of insect diversification. Consequently, numerous phylogenetic studies on phytophagous insects have aimed at testing whether speciation driven by host-plant adaptation is the main pathway for the diversification of the groups under investigation. The increasing availability of comprehensive and well-resolved phylogenies and the recent developments in phylogenetic comparative methods are offering an unprecedented opportunity to test hypotheses on insect diversification at a macroevolutionary scale, in a robust phylogenetic framework. Our purpose here is to review the contribution of phylogenetic analyses to investigate the importance of plant-mediated speciation in the diversification of phytophagous insects and to present suggestions for future developments in this field.
|
2301.05782
|
Steven Rossi
|
Steven P. Rossi, Sean P. Cox, Samuel D.N. Johnson, Ashleen J. Benson
|
Evaluating the sustainability of a de facto harvest strategy for British
Columbia's Spot Prawn (Pandalus platyceros) fishery in the presence of
environmental drivers of recruitment and hyperstable catch rates
|
86 pages, 12 figures, 33 appendix figures
| null | null | null |
q-bio.PE q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The Spot Prawn trap fishery off the west coast of British Columbia (BC) is
managed using a fixed escapement strategy that aims to prevent recruitment
overfishing while maximizing expected long-term yield by closing the fishery
when the catch rate of spawners, projected to the following spring, drops below
1.7 spawners per trap (the de jure rule). We develop a management strategy
evaluation framework for BC's Spot Prawn fishery that examines the expected
performance of the management procedure implemented in practice (the de facto
rule), which was significantly more conservative than the de jure rule, usually
closing the fishery when spawner catch rates were at least twice as high as
specified by the de jure rule. Simulations indicate that the de facto spawner
index rule using average empirical March 31st targets from 2000 to 2019
maintains most stocks near or above 0.8 BMSY with or without accounting for
environmental effects and/or increasing future SST on recruitment. Abundance
indices were found to be strongly hyperstable, with fishing efficiency 1.5 to
3.0 times higher under low biomass than high biomass.
|
[
{
"created": "Fri, 13 Jan 2023 22:56:21 GMT",
"version": "v1"
}
] |
2023-01-18
|
[
[
"Rossi",
"Steven P.",
""
],
[
"Cox",
"Sean P.",
""
],
[
"Johnson",
"Samuel D. N.",
""
],
[
"Benson",
"Ashleen J.",
""
]
] |
The Spot Prawn trap fishery off the west coast of British Columbia (BC) is managed using a fixed escapement strategy that aims to prevent recruitment overfishing while maximizing expected long-term yield by closing the fishery when the catch rate of spawners, projected to the following spring, drops below 1.7 spawners per trap (the de jure rule). We develop a management strategy evaluation framework for BC's Spot Prawn fishery that examines the expected performance of the management procedure implemented in practice (the de facto rule), which was significantly more conservative than the de jure rule, usually closing the fishery when spawner catch rates were at least twice as high as specified by the de jure rule. Simulations indicate that the de facto spawner index rule using average empirical March 31st targets from 2000 to 2019 maintains most stocks near or above 0.8 BMSY with or without accounting for environmental effects and/or increasing future SST on recruitment. Abundance indices were found to be strongly hyperstable, with fishing efficiency 1.5 to 3.0 times higher under low biomass than high biomass.
|
1512.09370
|
Emma Perracchione
|
Giorgio Sabetta, Emma Perracchione, Ezio Venturino
|
Wild herbivores in forests: four case studies
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A three population system with a top predator population, i.e. the
herbivores, and two prey populations, grass and trees, is considered to model
the interaction of herbivores with natural resources. We apply the model for
four natural mountain parks in Northern Italy, three located in the Eastern
Alps, two of which in the Dolomites and one in the Julian Alps, and one in the
Maritime Alps, Northwest Italy. The simulations, based on actual data gathered
from contacts with rangers and parks administrators, field samplings and
published material, provide useful information on the behavior of the
vegetation-wild herbivores interactions and the possible medium-long term
evolution of these ecosystems. At the same time they show that these ecosystems
are in a very delicate situation, for which the animal populations could become
extinguished in case of adverse environmental conditions. The determination of
the so called sensitivity surfaces support our findings and indicate some
possible preventive measures to the park admistrators.
|
[
{
"created": "Sat, 12 Dec 2015 19:02:03 GMT",
"version": "v1"
}
] |
2019-07-09
|
[
[
"Sabetta",
"Giorgio",
""
],
[
"Perracchione",
"Emma",
""
],
[
"Venturino",
"Ezio",
""
]
] |
A three population system with a top predator population, i.e. the herbivores, and two prey populations, grass and trees, is considered to model the interaction of herbivores with natural resources. We apply the model for four natural mountain parks in Northern Italy, three located in the Eastern Alps, two of which in the Dolomites and one in the Julian Alps, and one in the Maritime Alps, Northwest Italy. The simulations, based on actual data gathered from contacts with rangers and parks administrators, field samplings and published material, provide useful information on the behavior of the vegetation-wild herbivores interactions and the possible medium-long term evolution of these ecosystems. At the same time they show that these ecosystems are in a very delicate situation, for which the animal populations could become extinguished in case of adverse environmental conditions. The determination of the so called sensitivity surfaces support our findings and indicate some possible preventive measures to the park admistrators.
|
1701.07243
|
Francois Meyer
|
Fran\c{c}ois G. Meyer, Alexander M. Benison, Zachariah Smith, and
Daniel S. Barth
|
Decoding Epileptogenesis in a Reduced State Space
| null | null | null | null |
q-bio.NC cs.LG q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We describe here the recent results of a multidisciplinary effort to design a
biomarker that can actively and continuously decode the progressive changes in
neuronal organization leading to epilepsy, a process known as epileptogenesis.
Using an animal model of acquired epilepsy, wechronically record hippocampal
evoked potentials elicited by an auditory stimulus. Using a set of reduced
coordinates, our algorithm can identify universal smooth low-dimensional
configurations of the auditory evoked potentials that correspond to distinct
stages of epileptogenesis. We use a hidden Markov model to learn the dynamics
of the evoked potential, as it evolves along these smooth low-dimensional
subsets. We provide experimental evidence that the biomarker is able to exploit
subtle changes in the evoked potential to reliably decode the stage of
epileptogenesis and predict whether an animal will eventually recover from the
injury, or develop spontaneous seizures.
|
[
{
"created": "Wed, 25 Jan 2017 10:25:59 GMT",
"version": "v1"
}
] |
2017-01-26
|
[
[
"Meyer",
"François G.",
""
],
[
"Benison",
"Alexander M.",
""
],
[
"Smith",
"Zachariah",
""
],
[
"Barth",
"Daniel S.",
""
]
] |
We describe here the recent results of a multidisciplinary effort to design a biomarker that can actively and continuously decode the progressive changes in neuronal organization leading to epilepsy, a process known as epileptogenesis. Using an animal model of acquired epilepsy, wechronically record hippocampal evoked potentials elicited by an auditory stimulus. Using a set of reduced coordinates, our algorithm can identify universal smooth low-dimensional configurations of the auditory evoked potentials that correspond to distinct stages of epileptogenesis. We use a hidden Markov model to learn the dynamics of the evoked potential, as it evolves along these smooth low-dimensional subsets. We provide experimental evidence that the biomarker is able to exploit subtle changes in the evoked potential to reliably decode the stage of epileptogenesis and predict whether an animal will eventually recover from the injury, or develop spontaneous seizures.
|
1912.13417
|
Changcheng Sheng
|
Changcheng Sheng, Qun Zhao, Wanjie Niu, Xiaoyan Qiu, Ming Zhang, Zheng
Jiao
|
Effect of protein binding on exposure of unbound and total mycophenolic
acid: a population pharmacokinetic analysis in Chinese adult kidney
transplant recipients
|
39 pages, 3 tables, 5 figures, 1 supplementary table and 1
supplementary figure
|
Front. Pharmacol. (2020) 11:340
|
10.3389/fphar.2020.00340
| null |
q-bio.TO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
AIMS A population pharmacokinetic (PK) analysis was performed to: (1)
characterise the PK of unbound and total mycophenolic acid (MPA) and its
7-O-mycophenolic acid glucuronide (MPAG) metabolite, and (2) identify the
clinically significant covariates that cause variability in the dose-exposure
relationship to facilitate dose optimisation. METHODS A total of 740 unbound
MPA (uMPA), 741 total MPA (tMPA) and 734 total MPAG (tMPAG) concentration-time
data from 58 Chinese kidney transplant patients were analysed using a nonlinear
mixed-effect model. The influence of covariates was tested using a stepwise
procedure. RESULTS The PK of unbound MPA and MPAG were characterised by a two-
and one-compartment model with first-order elimination, respectively. Apparent
clearance of uMPA (CLuMPA/F) was estimated to be 852 L/h with a relative
standard error (RSE) of 7.1%. The tMPA and uMPA were connected using a linear
protein binding model, in which the protein binding rate constant (kB)
increased non-linearly with the serum albumin (ALB) concentration. The
estimated kB was 53.4 /h (RSE, 2.3%) for patients with ALB of 40 g/L. In
addition, model-based simulation showed that changes in ALB substantially
affected tMPA but not uMPA exposure. CONCLUSIONS The established model
adequately described the population PK characteristics of the uMPA, tMPA, and
MPAG. The estimated CLuMPA/F and unbound fraction of MPA (FUMPA) in Chinese
kidney transplant recipients were comparable to those published previously in
Caucasians. We recommend monitoring uMPA instead of tMPA to optimise
mycophenolate mofetil (MMF) dosing for patients with lower ALB levels.
|
[
{
"created": "Sat, 21 Dec 2019 03:11:22 GMT",
"version": "v1"
}
] |
2020-03-24
|
[
[
"Sheng",
"Changcheng",
""
],
[
"Zhao",
"Qun",
""
],
[
"Niu",
"Wanjie",
""
],
[
"Qiu",
"Xiaoyan",
""
],
[
"Zhang",
"Ming",
""
],
[
"Jiao",
"Zheng",
""
]
] |
AIMS A population pharmacokinetic (PK) analysis was performed to: (1) characterise the PK of unbound and total mycophenolic acid (MPA) and its 7-O-mycophenolic acid glucuronide (MPAG) metabolite, and (2) identify the clinically significant covariates that cause variability in the dose-exposure relationship to facilitate dose optimisation. METHODS A total of 740 unbound MPA (uMPA), 741 total MPA (tMPA) and 734 total MPAG (tMPAG) concentration-time data from 58 Chinese kidney transplant patients were analysed using a nonlinear mixed-effect model. The influence of covariates was tested using a stepwise procedure. RESULTS The PK of unbound MPA and MPAG were characterised by a two- and one-compartment model with first-order elimination, respectively. Apparent clearance of uMPA (CLuMPA/F) was estimated to be 852 L/h with a relative standard error (RSE) of 7.1%. The tMPA and uMPA were connected using a linear protein binding model, in which the protein binding rate constant (kB) increased non-linearly with the serum albumin (ALB) concentration. The estimated kB was 53.4 /h (RSE, 2.3%) for patients with ALB of 40 g/L. In addition, model-based simulation showed that changes in ALB substantially affected tMPA but not uMPA exposure. CONCLUSIONS The established model adequately described the population PK characteristics of the uMPA, tMPA, and MPAG. The estimated CLuMPA/F and unbound fraction of MPA (FUMPA) in Chinese kidney transplant recipients were comparable to those published previously in Caucasians. We recommend monitoring uMPA instead of tMPA to optimise mycophenolate mofetil (MMF) dosing for patients with lower ALB levels.
|
1003.1896
|
Dietrich Stauffer
|
D. Stauffer and S. Cebrat
|
Love kills Penna ageing model
|
Two pages including figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
No abstract needed since short
|
[
{
"created": "Tue, 9 Mar 2010 15:18:26 GMT",
"version": "v1"
}
] |
2010-03-10
|
[
[
"Stauffer",
"D.",
""
],
[
"Cebrat",
"S.",
""
]
] |
No abstract needed since short
|
1310.0424
|
Susan Holmes
|
Paul J. McMurdie and Susan Holmes
|
Waste Not, Want Not: Why Rarefying Microbiome Data is Inadmissible
|
22 pages, 5 figures, 2 supplementary sections
| null |
10.1371/journal.pcbi.1003531
| null |
q-bio.QM q-bio.GN stat.AP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The interpretation of count data originating from the current generation of
DNA sequencing platforms requires special attention. In particular, the
per-sample library sizes often vary by orders of magnitude from the same
sequencing run, and the counts are overdispersed relative to a simple Poisson
model These challenges can be addressed using an appropriate mixture model that
simultaneously accounts for library size differences and biological
variability. This approach is already well-characterized and implemented for
RNA-Seq data in R packages such as edgeR and DESeq.
We use statistical theory, extensive simulations, and empirical data to show
that variance stabilizing normalization using a mixture model like the negative
binomial is appropriate for microbiome count data. In simulations detecting
differential abundance, normalization procedures based on a Gamma-Poisson
mixture model provided systematic improvement in performance over crude
proportions or rarefied counts -- both of which led to a high rate of false
positives. In simulations evaluating clustering accuracy, we found that the
rarefying procedure discarded samples that were nevertheless accurately
clustered by alternative methods, and that the choice of minimum library size
threshold was critical in some settings, but with an optimum that is unknown in
practice. Techniques that use variance stabilizing transformations by modeling
microbiome count data with a mixture distribution, such as those implemented in
edgeR and DESeq, substantially improved upon techniques that attempt to
normalize by rarefying or crude proportions. Based on these results and
well-established statistical theory, we advocate that investigators avoid
rarefying altogether. We have provided microbiome-specific extensions to these
tools in the R package, phyloseq.
|
[
{
"created": "Tue, 1 Oct 2013 18:54:24 GMT",
"version": "v1"
},
{
"created": "Thu, 12 Dec 2013 08:57:05 GMT",
"version": "v2"
}
] |
2015-06-17
|
[
[
"McMurdie",
"Paul J.",
""
],
[
"Holmes",
"Susan",
""
]
] |
The interpretation of count data originating from the current generation of DNA sequencing platforms requires special attention. In particular, the per-sample library sizes often vary by orders of magnitude from the same sequencing run, and the counts are overdispersed relative to a simple Poisson model These challenges can be addressed using an appropriate mixture model that simultaneously accounts for library size differences and biological variability. This approach is already well-characterized and implemented for RNA-Seq data in R packages such as edgeR and DESeq. We use statistical theory, extensive simulations, and empirical data to show that variance stabilizing normalization using a mixture model like the negative binomial is appropriate for microbiome count data. In simulations detecting differential abundance, normalization procedures based on a Gamma-Poisson mixture model provided systematic improvement in performance over crude proportions or rarefied counts -- both of which led to a high rate of false positives. In simulations evaluating clustering accuracy, we found that the rarefying procedure discarded samples that were nevertheless accurately clustered by alternative methods, and that the choice of minimum library size threshold was critical in some settings, but with an optimum that is unknown in practice. Techniques that use variance stabilizing transformations by modeling microbiome count data with a mixture distribution, such as those implemented in edgeR and DESeq, substantially improved upon techniques that attempt to normalize by rarefying or crude proportions. Based on these results and well-established statistical theory, we advocate that investigators avoid rarefying altogether. We have provided microbiome-specific extensions to these tools in the R package, phyloseq.
|
0811.0055
|
Christopher L. Henley
|
Christopher L. Henley (Cornell Univ.)
|
Possible mechanisms for initiating macroscopic left-right asymmetry in
developing organisms
|
9 pp latex, 6 figures. Proc. Landau 100 Memorial Conf.
(Chernogolovka, June 2008); to appear AIP Conf. series. (v2: added 4 ref's +
revised Sec 2.2.)
| null |
10.1063/1.3149499
| null |
q-bio.TO q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
How might systematic left-right (L/R) asymmetry of the body plan originate in
multicellular animals (and plants)? Somehow, the microscopic handedness of
biological molecules must be brought up to macroscopic scales. Basic symmetry
principles suggest that the usual "biological" mechanisms -- diffusion and gene
regulation -- are insufficient to implement the "right-hand rule" defining a
third body axis from the other two. Instead, on the cellular level, "physical"
mechanisms (forces and collective dynamic states) are needed involving the long
stiff fibers of the cytoskeleton. I discuss some possible scenarios; only in
the case of vertebrate internal organs is the answer currently known (and even
that is in dispute).
|
[
{
"created": "Sat, 1 Nov 2008 02:52:58 GMT",
"version": "v1"
},
{
"created": "Sat, 29 Nov 2008 19:40:29 GMT",
"version": "v2"
}
] |
2015-05-13
|
[
[
"Henley",
"Christopher L.",
"",
"Cornell Univ."
]
] |
How might systematic left-right (L/R) asymmetry of the body plan originate in multicellular animals (and plants)? Somehow, the microscopic handedness of biological molecules must be brought up to macroscopic scales. Basic symmetry principles suggest that the usual "biological" mechanisms -- diffusion and gene regulation -- are insufficient to implement the "right-hand rule" defining a third body axis from the other two. Instead, on the cellular level, "physical" mechanisms (forces and collective dynamic states) are needed involving the long stiff fibers of the cytoskeleton. I discuss some possible scenarios; only in the case of vertebrate internal organs is the answer currently known (and even that is in dispute).
|
1302.3022
|
Michel Destrade
|
Aisling Ni Annaidh, Karine Bruyere, Michel Destrade, Michael D.
Gilchrist, Melanie Ottenio
|
Characterising the Anisotropic Mechanical Properties of Excised Human
Skin
|
23 pages
|
Journal of the Mechanical Behavior of Biomedical Materials, 5
(2012) 139-148
|
10.1016/j.jmbbm.2011.08.016
| null |
q-bio.TO cond-mat.soft physics.bio-ph physics.med-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The mechanical properties of skin are important for a number of applications
including surgery, dermatology, impact biomechanics and forensic science. In
this study we have investigated the influence of location and orientation on
the deformation characteristics of 56 samples of excised human skin. Uniaxial
tensile tests were carried out at a strain rate of 0.012s$^{-1}$ on skin from
the back. Digital Image Correlation was used for 2D strain measurement and a
histological examination of the dermis was also performed. The mean ultimate
tensile strength (UTS) was 21.6$\pm$8.4MPa, the mean failure strain 54$\pm$17%,
the mean initial slope 1.18$\pm$0.88MPa, the mean elastic modulus
83.3$\pm$34.9MPa and the mean strain energy was 3.6$\pm$1.6MJ/m$^3$. A
multivariate analysis of variance has shown that these mechanical properties of
skin are dependent upon the orientation of Langer lines (P$<$0.0001-P=0.046).
The location of specimens on the back was also found to have a significant
effect on the UTS (P =0.0002), the elastic modulus (P=0.001) and the strain
energy (P=0.0052). The histological investigation concluded that there is a
definite correlation between the orientation of Langer Lines and the preferred
orientation of collagen fibres in the dermis (P$<$0.001). The data obtained in
this study will provide essential information for those wishing to model the
skin using a structural constitutive model.
|
[
{
"created": "Wed, 13 Feb 2013 09:06:42 GMT",
"version": "v1"
}
] |
2013-02-14
|
[
[
"Annaidh",
"Aisling Ni",
""
],
[
"Bruyere",
"Karine",
""
],
[
"Destrade",
"Michel",
""
],
[
"Gilchrist",
"Michael D.",
""
],
[
"Ottenio",
"Melanie",
""
]
] |
The mechanical properties of skin are important for a number of applications including surgery, dermatology, impact biomechanics and forensic science. In this study we have investigated the influence of location and orientation on the deformation characteristics of 56 samples of excised human skin. Uniaxial tensile tests were carried out at a strain rate of 0.012s$^{-1}$ on skin from the back. Digital Image Correlation was used for 2D strain measurement and a histological examination of the dermis was also performed. The mean ultimate tensile strength (UTS) was 21.6$\pm$8.4MPa, the mean failure strain 54$\pm$17%, the mean initial slope 1.18$\pm$0.88MPa, the mean elastic modulus 83.3$\pm$34.9MPa and the mean strain energy was 3.6$\pm$1.6MJ/m$^3$. A multivariate analysis of variance has shown that these mechanical properties of skin are dependent upon the orientation of Langer lines (P$<$0.0001-P=0.046). The location of specimens on the back was also found to have a significant effect on the UTS (P =0.0002), the elastic modulus (P=0.001) and the strain energy (P=0.0052). The histological investigation concluded that there is a definite correlation between the orientation of Langer Lines and the preferred orientation of collagen fibres in the dermis (P$<$0.001). The data obtained in this study will provide essential information for those wishing to model the skin using a structural constitutive model.
|
1411.4704
|
Neil Page
|
N.W. Page, C. Hall and S.D. Page
|
Deep Brain Stimulation for Parkinson's Disease: a survey of experiences
perceived by recipients and carers
|
45 pages, 32 figures and 23 tables
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Perceived outcomes from DBS for PD were sampled for 52 cases by surveying 46
DBS recipients and 45 carers. Post-DBS experience ranged from 10-129 months.
There were significant variations in perceived outcomes over time. In some
cases extreme variations were experienced as a consequence of hardware and
other problems requiring additional surgery. Nevertheless most in this group
went on to ultimately report good outcomes. Holistic assessments of experiences
were largely positive, but in some cases there were significant differences in
the assessments by recipients and carers. For assessments valid at the time of
interview 26 recipients and 17 carers commented that the outcome was good. A
second group of 11 recipients and 12 carers reported mixed results but overall
a positive experience. A third group of 6 recipients and 8 carers reported
negatively about the outcomes. Many considered overall quality of life much
better following DBS, more so recipients than carers. Post-DBS experiences of
both motor and non-motor symptoms varied greatly between cases. When
considering the average of participant responses, tremor and dyskinesias were
considered better or much better following DBS, with benefits sustained with
time. 12 months after DBS many symptoms were on average considered the same or
better after DBS, but for many, some decline in benefits was apparent over this
period. Some symptoms were reported to show no improvement, or be worse
following DBS. 12 months after the procedure the average of participant
responses indicated that symptoms including speech, postural stability,
swallowing, handwriting, cognitive function and incontinence were worse.
|
[
{
"created": "Tue, 18 Nov 2014 00:45:44 GMT",
"version": "v1"
},
{
"created": "Mon, 10 Aug 2015 00:00:51 GMT",
"version": "v2"
}
] |
2015-08-11
|
[
[
"Page",
"N. W.",
""
],
[
"Hall",
"C.",
""
],
[
"Page",
"S. D.",
""
]
] |
Perceived outcomes from DBS for PD were sampled for 52 cases by surveying 46 DBS recipients and 45 carers. Post-DBS experience ranged from 10-129 months. There were significant variations in perceived outcomes over time. In some cases extreme variations were experienced as a consequence of hardware and other problems requiring additional surgery. Nevertheless most in this group went on to ultimately report good outcomes. Holistic assessments of experiences were largely positive, but in some cases there were significant differences in the assessments by recipients and carers. For assessments valid at the time of interview 26 recipients and 17 carers commented that the outcome was good. A second group of 11 recipients and 12 carers reported mixed results but overall a positive experience. A third group of 6 recipients and 8 carers reported negatively about the outcomes. Many considered overall quality of life much better following DBS, more so recipients than carers. Post-DBS experiences of both motor and non-motor symptoms varied greatly between cases. When considering the average of participant responses, tremor and dyskinesias were considered better or much better following DBS, with benefits sustained with time. 12 months after DBS many symptoms were on average considered the same or better after DBS, but for many, some decline in benefits was apparent over this period. Some symptoms were reported to show no improvement, or be worse following DBS. 12 months after the procedure the average of participant responses indicated that symptoms including speech, postural stability, swallowing, handwriting, cognitive function and incontinence were worse.
|
1304.4201
|
Karin Vadovi\v{c}ov\'a
|
Karin Vadovi\v{c}ov\'a, Roberto Gasparotti
|
Reward and adversity processing circuits, their competition and
interactions with dopamine and serotonin signaling
|
Reference [27] was updated to: Vadovi\v{c}ov\'a K: Affective and
cognitive prefrontal cortex projections to the lateral habenula in humans.
arXiv:1402.2196, re-published in Front Hum Neurosci 2014, 8:819. doi:
10.3389/fnhum.2014.00819 Few English errors were corrected and the
Abbreviations chapter was deleted
| null |
10.14293/S2199-1006.1.SOR-LIFE.AEKZPZ.v1
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We propose that dACC, AI and caudolateral OFC(clOFC) project to lateral
habenula (LHb) and D2 loop of ventral striatum (VS), forming a functional
adversity processing circuit, directed towards inhibitory avoidance and
self-control. This circuit learns what is bad or harmful to us and predicts
risks, to stop us from going/moving for bad or suboptimal choices that decrease
our well-being and survival chances. Proposed dACC role is to generate a
WARNING signal when things are going (or might end) bad or wrong to prevent
negative consequences: pain, harm, loss or failure. The AI signals about bad
low aversive qualities, which make us sick or cause discomfort. These cortical
inputs activate directly and indirectly (via D2 loop of VS) the LHb, which
inhibits dopamine and serotonin release (and is reciprocally inhibited by VTA,
DRN) to avoid choosing and doing things leading to harm or loss, but also to
make us feel worse, down when overstimulated. We propose that dopamine
attenuates the output of the adversity processing circuit, thus decreasing
inhibitory avoidance and self-control, while serotonin attenuates dACC, AI,
clOFC, D1 loop of VS, LHb, amygdala and pain pathway. Thus, by reciprocal
inhibition, by causing dopamine and serotonin suppression - and by being
suppressed by them, the adversity processing circuit competes with reward
processing circuit for control of choice behaviour and affective states. We
propose stimulating effect of dopamine and calming inhibitory effect of
serotonin on the active avoidance circuit involving amygdala, linked to threat
processing, anger, fear, self-defense and violences. We describe causes and
roles of dopamine and serotonin signaling, and mental dysfunctions. We add new
idea on vACC role in signaling that we are doing well and in inducing
serotonin, when we gain/reach safety, comfort, valuable resources,
social/biological rewards, affection or goals.
|
[
{
"created": "Mon, 15 Apr 2013 19:05:50 GMT",
"version": "v1"
},
{
"created": "Wed, 14 May 2014 14:54:51 GMT",
"version": "v10"
},
{
"created": "Tue, 9 Sep 2014 10:10:38 GMT",
"version": "v11"
},
{
"created": "Thu, 16 Oct 2014 08:18:23 GMT",
"version": "v12"
},
{
"created": "Mon, 27 Oct 2014 15:03:28 GMT",
"version": "v13"
},
{
"created": "Fri, 31 Oct 2014 17:29:02 GMT",
"version": "v14"
},
{
"created": "Sat, 15 Nov 2014 12:52:33 GMT",
"version": "v15"
},
{
"created": "Tue, 7 May 2013 19:30:10 GMT",
"version": "v2"
},
{
"created": "Wed, 26 Jun 2013 07:23:15 GMT",
"version": "v3"
},
{
"created": "Wed, 16 Oct 2013 12:10:03 GMT",
"version": "v4"
},
{
"created": "Wed, 22 Jan 2014 15:13:33 GMT",
"version": "v5"
},
{
"created": "Thu, 6 Feb 2014 08:09:15 GMT",
"version": "v6"
},
{
"created": "Fri, 7 Feb 2014 09:10:46 GMT",
"version": "v7"
},
{
"created": "Wed, 12 Feb 2014 10:39:41 GMT",
"version": "v8"
},
{
"created": "Fri, 28 Feb 2014 18:04:34 GMT",
"version": "v9"
}
] |
2014-11-18
|
[
[
"Vadovičová",
"Karin",
""
],
[
"Gasparotti",
"Roberto",
""
]
] |
We propose that dACC, AI and caudolateral OFC(clOFC) project to lateral habenula (LHb) and D2 loop of ventral striatum (VS), forming a functional adversity processing circuit, directed towards inhibitory avoidance and self-control. This circuit learns what is bad or harmful to us and predicts risks, to stop us from going/moving for bad or suboptimal choices that decrease our well-being and survival chances. Proposed dACC role is to generate a WARNING signal when things are going (or might end) bad or wrong to prevent negative consequences: pain, harm, loss or failure. The AI signals about bad low aversive qualities, which make us sick or cause discomfort. These cortical inputs activate directly and indirectly (via D2 loop of VS) the LHb, which inhibits dopamine and serotonin release (and is reciprocally inhibited by VTA, DRN) to avoid choosing and doing things leading to harm or loss, but also to make us feel worse, down when overstimulated. We propose that dopamine attenuates the output of the adversity processing circuit, thus decreasing inhibitory avoidance and self-control, while serotonin attenuates dACC, AI, clOFC, D1 loop of VS, LHb, amygdala and pain pathway. Thus, by reciprocal inhibition, by causing dopamine and serotonin suppression - and by being suppressed by them, the adversity processing circuit competes with reward processing circuit for control of choice behaviour and affective states. We propose stimulating effect of dopamine and calming inhibitory effect of serotonin on the active avoidance circuit involving amygdala, linked to threat processing, anger, fear, self-defense and violences. We describe causes and roles of dopamine and serotonin signaling, and mental dysfunctions. We add new idea on vACC role in signaling that we are doing well and in inducing serotonin, when we gain/reach safety, comfort, valuable resources, social/biological rewards, affection or goals.
|
2311.07168
|
No First Name Abdul Samad
|
Muhammad Hamza, Hafeez Ur Rehman Ali Khera, Muhammad Umair Waqas,
Ayesha Muazzam, Sania Tariq, Zain Kaleem, Waseem Akram, M Talha Mumtaz,
Shehroz Ahmad, and Abdul Samad
|
Misuse of Antibiotics in Poultry Threatens Pakistan Communitys Health
| null | null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
A survey was conducted from February 2022 to May 2022 on the usage of
antibiotics at a poultry farm in different areas of Multan, Punjab Pakistan. A
well-organized questionnaire was used for the collection of data. Sixty poultry
farms were surveyed randomly in the Multan district. All of these Farms were
using antibiotics. Antibiotics are commonly used for the treatment of diseases.
Some are used as preventive medicine and a few are used as growth promotors.
neomycin, erythromycin, oxytetracycline, streptomycin, and colistin are the
broad-spectrum antibiotics that are being used commercially. Enrofloxacin and
Furazolidone are the common antibiotics that are being used in Studies these
days. The class of Fluoroquinolones is commonly used in poultry farms.
Thirty-three patterns of antibiotic usage were observed at poultry farms.
multi-drug practices were also observed on various farms. In this study, 25% of
antibiotics are prescribed by the veterans while more than 90 % were acquired
from the veterinary store. This study provides information about the
antibiotics which are commonly being used in the study location district
Multan. It is expected that the finding of this survey will be helpful in the
development of new strategies against the misuse of antibiotics on farms.
|
[
{
"created": "Mon, 13 Nov 2023 09:02:57 GMT",
"version": "v1"
}
] |
2023-11-14
|
[
[
"Hamza",
"Muhammad",
""
],
[
"Khera",
"Hafeez Ur Rehman Ali",
""
],
[
"Waqas",
"Muhammad Umair",
""
],
[
"Muazzam",
"Ayesha",
""
],
[
"Tariq",
"Sania",
""
],
[
"Kaleem",
"Zain",
""
],
[
"Akram",
"Waseem",
""
],
[
"Mumtaz",
"M Talha",
""
],
[
"Ahmad",
"Shehroz",
""
],
[
"Samad",
"Abdul",
""
]
] |
A survey was conducted from February 2022 to May 2022 on the usage of antibiotics at a poultry farm in different areas of Multan, Punjab Pakistan. A well-organized questionnaire was used for the collection of data. Sixty poultry farms were surveyed randomly in the Multan district. All of these Farms were using antibiotics. Antibiotics are commonly used for the treatment of diseases. Some are used as preventive medicine and a few are used as growth promotors. neomycin, erythromycin, oxytetracycline, streptomycin, and colistin are the broad-spectrum antibiotics that are being used commercially. Enrofloxacin and Furazolidone are the common antibiotics that are being used in Studies these days. The class of Fluoroquinolones is commonly used in poultry farms. Thirty-three patterns of antibiotic usage were observed at poultry farms. multi-drug practices were also observed on various farms. In this study, 25% of antibiotics are prescribed by the veterans while more than 90 % were acquired from the veterinary store. This study provides information about the antibiotics which are commonly being used in the study location district Multan. It is expected that the finding of this survey will be helpful in the development of new strategies against the misuse of antibiotics on farms.
|
1604.02733
|
Thibaud Taillefumier
|
Thibaud Taillefumier, Anna Posfai, Yigal Meir and Ned S. Wingreen
|
Bacterial cartels at steady supply
| null | null | null | null |
q-bio.PE q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Metagenomics has revealed hundreds of bacterial species in almost all
microbiota. In a few well-studied cases, bacterial communities have been
observed to coordinate their metabolic fluxes. In principle, bacteria can
divide tasks to reap the benefits of specialization, as in human economies.
However, the benefits and stability of an economy of bacterial specialists are
far from obvious. Here, we physically model the population dynamics of bacteria
that compete for steadily supplied resources. Importantly, we explicitly model
the metabolic fluxes yielding cellular biomass production under the constraint
of a limited enzyme budget. In our framework, we find that population dynamics
generally leads to the coexistence of different metabolic types, which satisfy
an extended competitive exclusion principle (even allowing for adaptive
mutation). We establish that these consortia act as cartels, whereby population
dynamics pins down resource concentrations at values for which no other
strategy can invade. Finally, we propose that at steady supply, cartels of
competing strategies automatically yield maximum biomass, thereby achieving a
collective optimum.
|
[
{
"created": "Sun, 10 Apr 2016 21:01:53 GMT",
"version": "v1"
}
] |
2016-04-12
|
[
[
"Taillefumier",
"Thibaud",
""
],
[
"Posfai",
"Anna",
""
],
[
"Meir",
"Yigal",
""
],
[
"Wingreen",
"Ned S.",
""
]
] |
Metagenomics has revealed hundreds of bacterial species in almost all microbiota. In a few well-studied cases, bacterial communities have been observed to coordinate their metabolic fluxes. In principle, bacteria can divide tasks to reap the benefits of specialization, as in human economies. However, the benefits and stability of an economy of bacterial specialists are far from obvious. Here, we physically model the population dynamics of bacteria that compete for steadily supplied resources. Importantly, we explicitly model the metabolic fluxes yielding cellular biomass production under the constraint of a limited enzyme budget. In our framework, we find that population dynamics generally leads to the coexistence of different metabolic types, which satisfy an extended competitive exclusion principle (even allowing for adaptive mutation). We establish that these consortia act as cartels, whereby population dynamics pins down resource concentrations at values for which no other strategy can invade. Finally, we propose that at steady supply, cartels of competing strategies automatically yield maximum biomass, thereby achieving a collective optimum.
|
1201.0384
|
Victor Novikov PhD
|
Victor P. Novikov
|
Three-stage Origin of Life as a Result of Directional Darwinian
Evolution
|
10 pages, 3 figures
| null | null | null |
q-bio.OT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The original hypothesis about Three-stage origin of life (TOL) on the Earth
is developed and discussed. The role of the temperature factor in life origin
is considered. It is supposed, that three stages of abiogenesis (DNA world, RNA
world and the Protein world) consistently followed each other during Darwinian
evolution. At the same time, the natural directional selection of the most
stable macromolecules and effective catalytic reactions took place. The
direction of this selection is related to action of the principle of
{\guillemotleft}Increasing Independence from the Environment{\guillemotright}
(IIE) and is caused by temperature evolution of the atmosphere of the Earth.
The direction of Anagenesis and inevitability of occurrence of genetic
mechanisms is discussed.
|
[
{
"created": "Sun, 1 Jan 2012 20:55:58 GMT",
"version": "v1"
}
] |
2012-01-04
|
[
[
"Novikov",
"Victor P.",
""
]
] |
The original hypothesis about Three-stage origin of life (TOL) on the Earth is developed and discussed. The role of the temperature factor in life origin is considered. It is supposed, that three stages of abiogenesis (DNA world, RNA world and the Protein world) consistently followed each other during Darwinian evolution. At the same time, the natural directional selection of the most stable macromolecules and effective catalytic reactions took place. The direction of this selection is related to action of the principle of {\guillemotleft}Increasing Independence from the Environment{\guillemotright} (IIE) and is caused by temperature evolution of the atmosphere of the Earth. The direction of Anagenesis and inevitability of occurrence of genetic mechanisms is discussed.
|
1501.04078
|
Maxim Koroteev
|
M.V. Koroteev
|
On a chain of fragmentation equations for duplication-mutation dynamics
in DNA sequences
|
8 pages, 7 figures
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recent studies have revealed that for the majority of species the length
distributions of duplicated sequences in natural DNA follow a power-law tail.
We study duplication-mutation models for processes in natural DNA sequences and
the length distributions of exact matches computed from both synthetic and
natural sequences. Here we present a hierarchy of equations for various number
of exact matches for these models. The reduction of these equations to one
equation for pairs of exact repeats is found. Quantitative correspondence of
solutions of the equation to simulations is demonstrated.
|
[
{
"created": "Thu, 15 Jan 2015 11:02:08 GMT",
"version": "v1"
},
{
"created": "Mon, 9 Feb 2015 18:28:24 GMT",
"version": "v2"
},
{
"created": "Tue, 17 Feb 2015 22:04:17 GMT",
"version": "v3"
},
{
"created": "Wed, 3 Jun 2015 13:15:01 GMT",
"version": "v4"
}
] |
2015-06-04
|
[
[
"Koroteev",
"M. V.",
""
]
] |
Recent studies have revealed that for the majority of species the length distributions of duplicated sequences in natural DNA follow a power-law tail. We study duplication-mutation models for processes in natural DNA sequences and the length distributions of exact matches computed from both synthetic and natural sequences. Here we present a hierarchy of equations for various number of exact matches for these models. The reduction of these equations to one equation for pairs of exact repeats is found. Quantitative correspondence of solutions of the equation to simulations is demonstrated.
|
1401.7803
|
Ben Shirt-Ediss
|
Ben Shirt-Ediss, Kepa Ruiz-Mirazo, Fabio Mavelli and Ricard V. Sol\'e
|
Modelling Lipid Competition Dynamics in Heterogeneous Protocell
Populations
|
15 pages, 6 figures, 1 table
| null |
10.1038/srep05675
| null |
q-bio.QM q-bio.SC
|
http://creativecommons.org/licenses/by/3.0/
|
In addressing the origins of Darwinian evolution, recent experimental work
has been focussed on the discovery of simple physical effects which would
provide a relevant selective advantage to protocells competing with each other
for a limited supply of lipid. In particular, data coming from Szostak's lab
suggest that the transition from simple prebiotically plausible lipid membranes
to more complex and heterogeneous ones, closer to real biomembranes, may have
been driven by changes in the fluidity of the membrane and its affinity for the
available amphiphilic compound, which in turn would involve changes in vesicle
growth dynamics. Earlier work from the same group reported osmotically-driven
competition effects, whereby swelled vesicles grow at the expense of isotonic
ones. In this paper, we try to expand on these experimental studies by
providing a simple mathematical model of a population of competing vesicles,
studied at the level of lipid kinetics. In silico simulations of the model are
able to reproduce qualitatively and often quantitatively the experimentally
reported competition effects in both scenarios. We also develop a method for
numerically solving the equilibrium of a population of competing model
vesicles, which is quite general and applicable to different vesicle kinetics
schemes.
|
[
{
"created": "Thu, 30 Jan 2014 11:31:11 GMT",
"version": "v1"
}
] |
2014-07-15
|
[
[
"Shirt-Ediss",
"Ben",
""
],
[
"Ruiz-Mirazo",
"Kepa",
""
],
[
"Mavelli",
"Fabio",
""
],
[
"Solé",
"Ricard V.",
""
]
] |
In addressing the origins of Darwinian evolution, recent experimental work has been focussed on the discovery of simple physical effects which would provide a relevant selective advantage to protocells competing with each other for a limited supply of lipid. In particular, data coming from Szostak's lab suggest that the transition from simple prebiotically plausible lipid membranes to more complex and heterogeneous ones, closer to real biomembranes, may have been driven by changes in the fluidity of the membrane and its affinity for the available amphiphilic compound, which in turn would involve changes in vesicle growth dynamics. Earlier work from the same group reported osmotically-driven competition effects, whereby swelled vesicles grow at the expense of isotonic ones. In this paper, we try to expand on these experimental studies by providing a simple mathematical model of a population of competing vesicles, studied at the level of lipid kinetics. In silico simulations of the model are able to reproduce qualitatively and often quantitatively the experimentally reported competition effects in both scenarios. We also develop a method for numerically solving the equilibrium of a population of competing model vesicles, which is quite general and applicable to different vesicle kinetics schemes.
|
1201.6320
|
Michael B\"orsch
|
Stefan Ernst, Monika G. Dueser, Nawid Zarrabi, Michael Boersch
|
Monitoring transient elastic energy storage within the rotary motors of
single FoF1-ATP synthase by DCO-ALEX FRET
|
14 pages, 7 figures
| null |
10.1117/12.907086
| null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The enzyme FoF1-ATP synthase provides the 'chemical energy currency'
adenosine triphosphate (ATP) for living cells. Catalysis is driven by
mechanochemical coupling of subunit rotation within the enzyme with
conformational changes in the three ATP binding sites. Proton translocation
through the membrane-bound Fo part of ATP synthase powers a 10-step rotary
motion of the ring of c subunits. This rotation is transmitted to the gamma and
epsilon subunits of the F1 part. Because gamma and epsilon subunits rotate in
120 deg steps, we aim to unravel this symmetry mismatch by real time monitoring
subunit rotation using single-molecule Forster resonance energy transfer
(FRET). One fluorophore is attached specifically to the F1 motor, another one
to the Fo motor of the liposome-reconstituted enzyme. Photophysical artifacts
due to spectral fluctuations of the single fluorophores are minimized by a
previously developed duty cycle-optimized alternating laser excitation scheme
(DCO-ALEX). We report the detection of reversible elastic deformations between
the rotor parts of Fo and F1 and estimate the maximum angular displacement
during the load-free rotation using Monte Carlo simulations
|
[
{
"created": "Mon, 30 Jan 2012 18:54:14 GMT",
"version": "v1"
}
] |
2015-06-04
|
[
[
"Ernst",
"Stefan",
""
],
[
"Dueser",
"Monika G.",
""
],
[
"Zarrabi",
"Nawid",
""
],
[
"Boersch",
"Michael",
""
]
] |
The enzyme FoF1-ATP synthase provides the 'chemical energy currency' adenosine triphosphate (ATP) for living cells. Catalysis is driven by mechanochemical coupling of subunit rotation within the enzyme with conformational changes in the three ATP binding sites. Proton translocation through the membrane-bound Fo part of ATP synthase powers a 10-step rotary motion of the ring of c subunits. This rotation is transmitted to the gamma and epsilon subunits of the F1 part. Because gamma and epsilon subunits rotate in 120 deg steps, we aim to unravel this symmetry mismatch by real time monitoring subunit rotation using single-molecule Forster resonance energy transfer (FRET). One fluorophore is attached specifically to the F1 motor, another one to the Fo motor of the liposome-reconstituted enzyme. Photophysical artifacts due to spectral fluctuations of the single fluorophores are minimized by a previously developed duty cycle-optimized alternating laser excitation scheme (DCO-ALEX). We report the detection of reversible elastic deformations between the rotor parts of Fo and F1 and estimate the maximum angular displacement during the load-free rotation using Monte Carlo simulations
|
1707.05636
|
Valerey Grytsay Dr
|
V.I. Grytsay
|
Self-Organization and Fractality in the Metabolic Process of Glycolysis
|
13 pages, 5 figures
|
Ukr. J. Phys., Vol. 59, N 12, p.1251-1262 (2015)
|
10.15407/ujpe60.12.1251
| null |
q-bio.OT nlin.AO nlin.CD
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Within a mathematical model, the metabolic process of glycolysis is studied.
The general scheme of glycolysis is considered as a natural result of the
biochemical evolution. By using the theory of dissipative structures, the
conditions of self-organization of the given process are sought. The
autocatalytic processes resulting in the conservation of cyclicity in the
dynamics of the process are determined. The conditions of breaking of the
synchronization of the process, increase in the multiplicity of a cyclicity,
and appearance of chaotic modes are studied. The phase-parametric diagrams of a
cascade of bifurcations, which characterize the transition to chaotic modes
according to the Feigenbaum scenario and the intermittence, are constructed.
The strange attractors formed as a result of the funnel effect are found. The
complete spectra of Lyapunov indices and divergences for the obtained modes are
calculated. The values of KS-entropy, horizons of predictability, and Lyapunov
dimensions of strange attractors are determined. Some conclusions concerning
the structural-functional connections in glycolysis and their influence on the
stability of the metabolic process in a cell are presented.
|
[
{
"created": "Fri, 14 Jul 2017 10:08:18 GMT",
"version": "v1"
}
] |
2017-07-19
|
[
[
"Grytsay",
"V. I.",
""
]
] |
Within a mathematical model, the metabolic process of glycolysis is studied. The general scheme of glycolysis is considered as a natural result of the biochemical evolution. By using the theory of dissipative structures, the conditions of self-organization of the given process are sought. The autocatalytic processes resulting in the conservation of cyclicity in the dynamics of the process are determined. The conditions of breaking of the synchronization of the process, increase in the multiplicity of a cyclicity, and appearance of chaotic modes are studied. The phase-parametric diagrams of a cascade of bifurcations, which characterize the transition to chaotic modes according to the Feigenbaum scenario and the intermittence, are constructed. The strange attractors formed as a result of the funnel effect are found. The complete spectra of Lyapunov indices and divergences for the obtained modes are calculated. The values of KS-entropy, horizons of predictability, and Lyapunov dimensions of strange attractors are determined. Some conclusions concerning the structural-functional connections in glycolysis and their influence on the stability of the metabolic process in a cell are presented.
|
q-bio/0410023
|
Sheng Li
|
Fangping Wei, Sheng Li and Hongru Ma
|
Network of tRNA Gene Sequences
|
Latex, 18 pages, 17 figures
| null | null | null |
q-bio.MN cond-mat.stat-mech q-bio.PE
| null |
We showed in this paper that similarity network can be used as an powerful
tools to study the relationship of tRNA genes. We constructed a network of 3719
tRNA gene sequences using simplest alignment and studied its topology, degree
distribution and clustering coefficient. It is found that the behavior of the
network shift from fluctuated distribution to scale-free distribution when the
similarity degree of the tRNA gene sequences increase. tRNA gene sequences with
the same anticodon identity are more self-organized than the tRNA gene
sequences with different anticodon identities and form local clusters in the
network. An interesting finding in our studied is some vertices of the local
cluster have a high connection with other local clusters, the probable reason
is given. Moreover, a network constructed by the same number of random tRNA
sequences is used to make comparisons. The relationships between properties of
the tRNA similarity network and the characters of tRNA evolutionary history are
discussed.
|
[
{
"created": "Wed, 20 Oct 2004 06:36:29 GMT",
"version": "v1"
},
{
"created": "Sat, 23 Oct 2004 12:22:21 GMT",
"version": "v2"
},
{
"created": "Tue, 14 Dec 2004 12:52:57 GMT",
"version": "v3"
}
] |
2009-09-29
|
[
[
"Wei",
"Fangping",
""
],
[
"Li",
"Sheng",
""
],
[
"Ma",
"Hongru",
""
]
] |
We showed in this paper that similarity network can be used as an powerful tools to study the relationship of tRNA genes. We constructed a network of 3719 tRNA gene sequences using simplest alignment and studied its topology, degree distribution and clustering coefficient. It is found that the behavior of the network shift from fluctuated distribution to scale-free distribution when the similarity degree of the tRNA gene sequences increase. tRNA gene sequences with the same anticodon identity are more self-organized than the tRNA gene sequences with different anticodon identities and form local clusters in the network. An interesting finding in our studied is some vertices of the local cluster have a high connection with other local clusters, the probable reason is given. Moreover, a network constructed by the same number of random tRNA sequences is used to make comparisons. The relationships between properties of the tRNA similarity network and the characters of tRNA evolutionary history are discussed.
|
1911.01988
|
Laura Schaposnik
|
Yuyuan Luo and Laura P. Schaposnik
|
Minimal percolating sets for mutating infectious diseases
|
11 pages, 10 figures
|
Phys. Rev. Research 2, 023001 (2020)
|
10.1103/PhysRevResearch.2.023001
| null |
q-bio.PE cs.SI math.CO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper is dedicated to the study of the interaction between dynamical
systems and percolation models, with views towards the study of viral
infections whose virus mutate with time. Recall that r-bootstrap percolation
describes a deterministic process where vertices of a graph are infected once r
neighbors of it are infected. We generalize this by introducing F(t)-bootstrap
percolation, a time-dependent process where the number of neighbouring vertices
which need to be infected for a disease to be transmitted is determined by a
percolation function F(t) at each time t. After studying some of the basic
properties of the model, we consider smallest percolating sets and construct a
polynomial-timed algorithm to find one smallest minimal percolating set on
finite trees for certain F(t)-bootstrap percolation models.
|
[
{
"created": "Tue, 5 Nov 2019 18:27:03 GMT",
"version": "v1"
}
] |
2020-04-08
|
[
[
"Luo",
"Yuyuan",
""
],
[
"Schaposnik",
"Laura P.",
""
]
] |
This paper is dedicated to the study of the interaction between dynamical systems and percolation models, with views towards the study of viral infections whose virus mutate with time. Recall that r-bootstrap percolation describes a deterministic process where vertices of a graph are infected once r neighbors of it are infected. We generalize this by introducing F(t)-bootstrap percolation, a time-dependent process where the number of neighbouring vertices which need to be infected for a disease to be transmitted is determined by a percolation function F(t) at each time t. After studying some of the basic properties of the model, we consider smallest percolating sets and construct a polynomial-timed algorithm to find one smallest minimal percolating set on finite trees for certain F(t)-bootstrap percolation models.
|
2210.05269
|
Liam Maher
|
Katharina T. Huber and Liam J. Maher
|
Autopolyploidy, allopolyploidy, and phylogenetic networks with
horizontal arcs
|
26 pages, 9 figures, 38 citations
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
Polyploidization is an evolutionary process by which a species acquires
multiple copies of its complete set of chromosomes. The reticulate nature of
the signal left behind by it means that phylogenetic networks offer themselves
as a framework to reconstruct the evolutionary past of species affected by it.
The main strategy for doing this is to first construct a so called
multiple-labelled tree and to then somehow derive such a network from it. The
following question therefore arises: How much can be said about that past if
such a tree is not readily available? By viewing a polyploid dataset as a
certain vector which we call a ploidy (level) profile we show that, among other
results, there always exists a phylogenetic network in the form of a beaded
phylogenetic tree with additional arcs that realizes a given ploidy profile.
Intriguingly, the two end vertices of almost all of these additional arcs can
be interpreted as having co-existed in time thereby adding biological realism
to our network, a feature that is, in general, not enjoyed by phylogenetic
networks. In addition, we show that our network may be viewed as a generator of
ploidy profile space, a novel concept similar to phylogenetic tree space that
we introduce to be able to compare phylogenetic networks that realize one and
the same ploidy profile. We illustrate our findings in terms of a publicly
available Viola dataset.
|
[
{
"created": "Tue, 11 Oct 2022 09:11:23 GMT",
"version": "v1"
},
{
"created": "Sun, 19 Feb 2023 13:19:42 GMT",
"version": "v2"
}
] |
2023-02-21
|
[
[
"Huber",
"Katharina T.",
""
],
[
"Maher",
"Liam J.",
""
]
] |
Polyploidization is an evolutionary process by which a species acquires multiple copies of its complete set of chromosomes. The reticulate nature of the signal left behind by it means that phylogenetic networks offer themselves as a framework to reconstruct the evolutionary past of species affected by it. The main strategy for doing this is to first construct a so called multiple-labelled tree and to then somehow derive such a network from it. The following question therefore arises: How much can be said about that past if such a tree is not readily available? By viewing a polyploid dataset as a certain vector which we call a ploidy (level) profile we show that, among other results, there always exists a phylogenetic network in the form of a beaded phylogenetic tree with additional arcs that realizes a given ploidy profile. Intriguingly, the two end vertices of almost all of these additional arcs can be interpreted as having co-existed in time thereby adding biological realism to our network, a feature that is, in general, not enjoyed by phylogenetic networks. In addition, we show that our network may be viewed as a generator of ploidy profile space, a novel concept similar to phylogenetic tree space that we introduce to be able to compare phylogenetic networks that realize one and the same ploidy profile. We illustrate our findings in terms of a publicly available Viola dataset.
|
2003.10073
|
Hideyoshi Yanagisawa
|
Hideyoshi Yanagisawa
|
Information-Theoretic Free Energy as Emotion Potential: Emotional
Valence as a Function of Complexity and Novelty
| null |
Frontiers in Computational Neuroscience, 15, 107 (2021)
|
10.3389/fncom.2021.698252
| null |
q-bio.NC cs.AI cs.IT math.IT
|
http://creativecommons.org/licenses/by/4.0/
|
This study extends the mathematical model of emotion dimensions that we
previously proposed (Yanagisawa, et al. 2019, Front Comput Neurosci) to
consider perceived complexity as well as novelty, as a source of arousal
potential. Berlyne's hedonic function of arousal potential (or the inverse
U-shaped curve, the so-called Wundt curve) is assumed. We modeled the arousal
potential as information contents to be processed in the brain after sensory
stimuli are perceived (or recognized), which we termed sensory surprisal. We
mathematically demonstrated that sensory surprisal represents free energy, and
it is equivalent to a summation of information gain (or information from
novelty) and perceived complexity (or information from complexity), which are
the collative variables forming the arousal potential. We demonstrated
empirical evidence with visual stimuli (profile shapes of butterfly) supporting
the hypothesis that the summation of perceived novelty and complexity shapes
the inverse U-shaped beauty function. We discussed the potential of free energy
as a mathematical principle explaining emotion initiators.
|
[
{
"created": "Mon, 23 Mar 2020 04:10:23 GMT",
"version": "v1"
}
] |
2021-11-23
|
[
[
"Yanagisawa",
"Hideyoshi",
""
]
] |
This study extends the mathematical model of emotion dimensions that we previously proposed (Yanagisawa, et al. 2019, Front Comput Neurosci) to consider perceived complexity as well as novelty, as a source of arousal potential. Berlyne's hedonic function of arousal potential (or the inverse U-shaped curve, the so-called Wundt curve) is assumed. We modeled the arousal potential as information contents to be processed in the brain after sensory stimuli are perceived (or recognized), which we termed sensory surprisal. We mathematically demonstrated that sensory surprisal represents free energy, and it is equivalent to a summation of information gain (or information from novelty) and perceived complexity (or information from complexity), which are the collative variables forming the arousal potential. We demonstrated empirical evidence with visual stimuli (profile shapes of butterfly) supporting the hypothesis that the summation of perceived novelty and complexity shapes the inverse U-shaped beauty function. We discussed the potential of free energy as a mathematical principle explaining emotion initiators.
|
2303.08158
|
Sayantan Nag Chowdhury
|
Sayantan Nag Chowdhury, Jeet Banerjee, Matja\v{z} Perc, Dibakar Ghosh
|
Eco-evolutionary cyclic dominance among predators, prey, and parasites
|
14 pages, 6 figures, Supplementary material related to this article
can be found online at https://doi.org/10.1016/j.jtbi.2023.111446
|
J. Theor. Biol. 564, 111446 (2023)
|
10.1016/j.jtbi.2023.111446
| null |
q-bio.PE nlin.AO
|
http://creativecommons.org/licenses/by/4.0/
|
Predator prey interactions are one of ecology's central research themes, but
with many interdisciplinary implications across the social and natural
sciences. Here we consider an often-overlooked species in these interactions,
namely parasites. We first show that a simple predator prey parasite model,
inspired by the classical Lotka Volterra equations, fails to produce a stable
coexistence of all three species, thus failing to provide a biologically
realistic outcome. To improve this, we introduce free space as a relevant
eco-evolutionary component in a new mathematical model that uses a
game-theoretical payoff matrix to describe a more realistic setup. We then show
that the consideration of free space stabilizes the dynamics by means of cyclic
dominance that emerges between the three species. We determine the parameter
regions of coexistence as well as the types of bifurcations leading to it by
means of analytical derivations as well as by means of numerical simulations.
We conclude that the consideration of free space as a finite resource reveals
the limits of biodiversity in predator prey parasite interactions, and it may
also help us in the determination of factors that promote a healthy biota.
|
[
{
"created": "Tue, 14 Mar 2023 18:14:53 GMT",
"version": "v1"
}
] |
2024-07-16
|
[
[
"Chowdhury",
"Sayantan Nag",
""
],
[
"Banerjee",
"Jeet",
""
],
[
"Perc",
"Matjaž",
""
],
[
"Ghosh",
"Dibakar",
""
]
] |
Predator prey interactions are one of ecology's central research themes, but with many interdisciplinary implications across the social and natural sciences. Here we consider an often-overlooked species in these interactions, namely parasites. We first show that a simple predator prey parasite model, inspired by the classical Lotka Volterra equations, fails to produce a stable coexistence of all three species, thus failing to provide a biologically realistic outcome. To improve this, we introduce free space as a relevant eco-evolutionary component in a new mathematical model that uses a game-theoretical payoff matrix to describe a more realistic setup. We then show that the consideration of free space stabilizes the dynamics by means of cyclic dominance that emerges between the three species. We determine the parameter regions of coexistence as well as the types of bifurcations leading to it by means of analytical derivations as well as by means of numerical simulations. We conclude that the consideration of free space as a finite resource reveals the limits of biodiversity in predator prey parasite interactions, and it may also help us in the determination of factors that promote a healthy biota.
|
2307.15083
|
Mircea Andrecut Dr
|
M. Andrecut
|
Reaction Diffusion TAP
|
11 pages, 4 figures, revised version accepted for publication in Int.
J. Mod. Phys. C
| null | null | null |
q-bio.PE physics.data-an
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The recently introduced Theory of the Adjacent Possible (TAP) is a model of
combinatorial innovation aiming to explain the "hockey-stick" upward trend of
human technological evolution, where an explosion in the number of produced
items with increasing complexity suddenly occurs. In addition, the TAP model
was also used to explain the rapidly emerging biological complexity. Inspired
by TAP here we propose a reaction-diffusion system aiming to extend the model
in both space and time. We show that the new model exhibits similar
characteristics to the TAP model, like the sudden increase in the production of
items, after a longer period of slow growth. The new model also exhibits wave
propagation of "innovation", resulting in self-sustained complex interference
patterns.
|
[
{
"created": "Tue, 25 Jul 2023 20:52:07 GMT",
"version": "v1"
},
{
"created": "Mon, 31 Jul 2023 03:40:57 GMT",
"version": "v2"
},
{
"created": "Wed, 6 Sep 2023 16:08:11 GMT",
"version": "v3"
}
] |
2023-09-07
|
[
[
"Andrecut",
"M.",
""
]
] |
The recently introduced Theory of the Adjacent Possible (TAP) is a model of combinatorial innovation aiming to explain the "hockey-stick" upward trend of human technological evolution, where an explosion in the number of produced items with increasing complexity suddenly occurs. In addition, the TAP model was also used to explain the rapidly emerging biological complexity. Inspired by TAP here we propose a reaction-diffusion system aiming to extend the model in both space and time. We show that the new model exhibits similar characteristics to the TAP model, like the sudden increase in the production of items, after a longer period of slow growth. The new model also exhibits wave propagation of "innovation", resulting in self-sustained complex interference patterns.
|
2007.14762
|
Peter Gawthrop
|
Peter J Gawthrop
|
Energy-based Modelling of the Feedback Control of Biomolecular Systems
with Cyclic Flow Modulation
| null |
IEEE Transactions on NanoBioscience, 2021
|
10.1109/TNB.2021.3058440
| null |
q-bio.MN
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Energy-based modelling brings engineering insight to the understanding of
biomolecular systems. It is shown how well-established control engineering
concepts, such as loop-gain, arise from energy feedback loops and are therefore
amenable to control engineering insight. In particular, a novel method is
introduced to allow the transfer function based approach of classical linear
control to be utilised in the analysis of feedback systems modelled by network
thermodynamics and thus amalgamate energy-based modelling with control systems
analysis. The approach is illustrated using a class of metabolic cycles with
activation and inhibition leading the concept of Cyclic Flow Modulation.
|
[
{
"created": "Wed, 29 Jul 2020 12:00:21 GMT",
"version": "v1"
},
{
"created": "Fri, 11 Dec 2020 11:57:15 GMT",
"version": "v2"
},
{
"created": "Thu, 28 Jan 2021 11:04:30 GMT",
"version": "v3"
}
] |
2021-03-30
|
[
[
"Gawthrop",
"Peter J",
""
]
] |
Energy-based modelling brings engineering insight to the understanding of biomolecular systems. It is shown how well-established control engineering concepts, such as loop-gain, arise from energy feedback loops and are therefore amenable to control engineering insight. In particular, a novel method is introduced to allow the transfer function based approach of classical linear control to be utilised in the analysis of feedback systems modelled by network thermodynamics and thus amalgamate energy-based modelling with control systems analysis. The approach is illustrated using a class of metabolic cycles with activation and inhibition leading the concept of Cyclic Flow Modulation.
|
0902.0313
|
Benzi Roberto
|
Roberto Benzi and David R. Nelson
|
Fisher equation with turbulence in one dimension
|
15 pages
| null |
10.1016/j.physd.2009.07.015
| null |
q-bio.PE cond-mat.stat-mech nlin.CD
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We investigate the dynamics of the Fisher equation for the spreading of
micro-organisms in one dimension subject to both turbulent convection and
diffusion. We show that for strong enough turbulence, bacteria, for example,
track in a quasilocalized fashion (with remakably long persistance times) sinks
in the turbulent field. An important consequence is a large reduction in the
carrying capacity of the fluid medium. We determine analytically the regimes
where this quasi-localized behavior occurs and test our predictions by
numerical simulations.
|
[
{
"created": "Mon, 2 Feb 2009 16:49:54 GMT",
"version": "v1"
}
] |
2015-05-13
|
[
[
"Benzi",
"Roberto",
""
],
[
"Nelson",
"David R.",
""
]
] |
We investigate the dynamics of the Fisher equation for the spreading of micro-organisms in one dimension subject to both turbulent convection and diffusion. We show that for strong enough turbulence, bacteria, for example, track in a quasilocalized fashion (with remakably long persistance times) sinks in the turbulent field. An important consequence is a large reduction in the carrying capacity of the fluid medium. We determine analytically the regimes where this quasi-localized behavior occurs and test our predictions by numerical simulations.
|
2311.16686
|
Rim Adenane
|
Florin Avram, Rim Adenane, Lasko Basnarkov, Matthew Johnston
|
Algorithmic approach for an unique definition of the next generation
matrix
| null | null | null | null |
q-bio.PE math.DS
|
http://creativecommons.org/licenses/by/4.0/
|
The basic reproduction number R0 is a concept which originated in population
dynamics, mathematical epidemiology, and ecology and is closely related to the
mean number of children in branching processes.We offer below three new
contributions to the literature: 1) We order a universal algorithmic definition
of a (F, V) gradient decomposition (and hence of the resulting R0), which
requires a minimal input from the user, namely the specification of an
admissible set of disease/infection variables. We also present examples where
other choices may be more reasonable, with more terms in F, or more terms in V .
2) We glean out from the works of Bacaer a fixed point equation (8) for the
extinction probabilities of a stochastic model associated to a deterministic
ODE model, which may be expressed in terms of the (F, V ) decomposition. The
fact that both R0 and the extinction probabilities are functions of (F, V )
underlines the centrality of this pair, which may be viewed as more fundamental
than the famous next generation matrix FV^{-1}.
3) We suggest introducing a new concept of sufficient/minimal
disease/infection set (sufficient for determining R0). More precisely, our
universal recipe of choosing "new infections" once the "infections" are
specified suggests focusing on the choice of the latter, which is also not
unique. The maximal choice of choosing all compartments which become 0 at the
given boundary point seems to always work, but is the least useful for analytic
computations, therefore we propose to investigate the minimal one. As a bonus,
this idea seems useful for understanding the Jacobian factorization approach
for computing R0 . Last but not least, we offer Mathematica scripts and
implement them for a large variety of examples, which illustrate that our
recipe others always reasonable results, but that sometimes other reasonable
(F, V ) decompositions are available as well.
|
[
{
"created": "Tue, 28 Nov 2023 10:56:21 GMT",
"version": "v1"
},
{
"created": "Wed, 29 Nov 2023 13:48:51 GMT",
"version": "v2"
}
] |
2023-11-30
|
[
[
"Avram",
"Florin",
""
],
[
"Adenane",
"Rim",
""
],
[
"Basnarkov",
"Lasko",
""
],
[
"Johnston",
"Matthew",
""
]
] |
The basic reproduction number R0 is a concept which originated in population dynamics, mathematical epidemiology, and ecology and is closely related to the mean number of children in branching processes.We offer below three new contributions to the literature: 1) We order a universal algorithmic definition of a (F, V) gradient decomposition (and hence of the resulting R0), which requires a minimal input from the user, namely the specification of an admissible set of disease/infection variables. We also present examples where other choices may be more reasonable, with more terms in F, or more terms in V . 2) We glean out from the works of Bacaer a fixed point equation (8) for the extinction probabilities of a stochastic model associated to a deterministic ODE model, which may be expressed in terms of the (F, V ) decomposition. The fact that both R0 and the extinction probabilities are functions of (F, V ) underlines the centrality of this pair, which may be viewed as more fundamental than the famous next generation matrix FV^{-1}. 3) We suggest introducing a new concept of sufficient/minimal disease/infection set (sufficient for determining R0). More precisely, our universal recipe of choosing "new infections" once the "infections" are specified suggests focusing on the choice of the latter, which is also not unique. The maximal choice of choosing all compartments which become 0 at the given boundary point seems to always work, but is the least useful for analytic computations, therefore we propose to investigate the minimal one. As a bonus, this idea seems useful for understanding the Jacobian factorization approach for computing R0 . Last but not least, we offer Mathematica scripts and implement them for a large variety of examples, which illustrate that our recipe others always reasonable results, but that sometimes other reasonable (F, V ) decompositions are available as well.
|
1911.02893
|
Tatiana Yakushkina S.
|
Sergei Drozhzhin, Tatiana Yakushkina, Alexander Bratus
|
Fitness Optimization and Evolution of Permanent Replicator Systems
|
31 page, 32 figures
| null | null | null |
q-bio.PE nlin.AO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we discuss the fitness landscape evolution of permanent
replicator systems using a hypothesis that the specific time of evolutionary
adaptation of the system parameters is much slower than the time of internal
evolutionary dynamics. In other words, we suppose that the extreme principle of
Darwinian evolution based the Fisher's fundamental theorem of natural selection
is valid for the steady-states. Various cases of the evolutionary adaptation
for permanent replicator system are considered.
|
[
{
"created": "Thu, 7 Nov 2019 13:28:21 GMT",
"version": "v1"
}
] |
2019-11-11
|
[
[
"Drozhzhin",
"Sergei",
""
],
[
"Yakushkina",
"Tatiana",
""
],
[
"Bratus",
"Alexander",
""
]
] |
In this paper, we discuss the fitness landscape evolution of permanent replicator systems using a hypothesis that the specific time of evolutionary adaptation of the system parameters is much slower than the time of internal evolutionary dynamics. In other words, we suppose that the extreme principle of Darwinian evolution based the Fisher's fundamental theorem of natural selection is valid for the steady-states. Various cases of the evolutionary adaptation for permanent replicator system are considered.
|
1411.1658
|
Peter Thomas PhD
|
Peter J. Thomas and Benjamin Lindner
|
Asymptotic Phase for Stochastic Oscillators
|
5 pages, 3 figures
|
Phys. Rev. Lett. 113(25):254101, Dec. 2014
|
10.1103/PhysRevLett.113.254101
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Oscillations and noise are ubiquitous in physical and biological systems.
When oscillations arise from a deterministic limit cycle, entrainment and
synchronization may be analyzed in terms of the asymptotic phase function. In
the presence of noise, the asymptotic phase is no longer well defined. We
introduce a new definition of asymptotic phase in terms of the slowest decaying
modes of the Kolmogorov backward operator. Our stochastic asymptotic phase is
well defined for noisy oscillators, even when the oscillations are noise
dependent. It reduces to the classical asymptotic phase in the limit of
vanishing noise. The phase can be obtained either by solving an eigenvalue
problem, or by empirical observation of an oscillating density's approach to
its steady state.
|
[
{
"created": "Thu, 6 Nov 2014 16:41:46 GMT",
"version": "v1"
},
{
"created": "Sun, 18 Jan 2015 21:17:02 GMT",
"version": "v2"
}
] |
2015-01-20
|
[
[
"Thomas",
"Peter J.",
""
],
[
"Lindner",
"Benjamin",
""
]
] |
Oscillations and noise are ubiquitous in physical and biological systems. When oscillations arise from a deterministic limit cycle, entrainment and synchronization may be analyzed in terms of the asymptotic phase function. In the presence of noise, the asymptotic phase is no longer well defined. We introduce a new definition of asymptotic phase in terms of the slowest decaying modes of the Kolmogorov backward operator. Our stochastic asymptotic phase is well defined for noisy oscillators, even when the oscillations are noise dependent. It reduces to the classical asymptotic phase in the limit of vanishing noise. The phase can be obtained either by solving an eigenvalue problem, or by empirical observation of an oscillating density's approach to its steady state.
|
2005.13607
|
Hehuan Ma
|
Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang
Xie, Geyan Ye, Junzhou Huang
|
Multi-View Graph Neural Networks for Molecular Property Prediction
| null | null | null | null |
q-bio.QM cs.LG stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The crux of molecular property prediction is to generate meaningful
representations of the molecules. One promising route is to exploit the
molecular graph structure through Graph Neural Networks (GNNs). It is well
known that both atoms and bonds significantly affect the chemical properties of
a molecule, so an expressive model shall be able to exploit both node (atom)
and edge (bond) information simultaneously. Guided by this observation, we
present Multi-View Graph Neural Network (MV-GNN), a multi-view message passing
architecture to enable more accurate predictions of molecular properties. In
MV-GNN, we introduce a shared self-attentive readout component and disagreement
loss to stabilize the training process. This readout component also renders the
whole architecture interpretable. We further boost the expressive power of
MV-GNN by proposing a cross-dependent message passing scheme that enhances
information communication of the two views, which results in the MV-GNN^cross
variant. Lastly, we theoretically justify the expressiveness of the two
proposed models in terms of distinguishing non-isomorphism graphs. Extensive
experiments demonstrate that MV-GNN models achieve remarkably superior
performance over the state-of-the-art models on a variety of challenging
benchmarks. Meanwhile, visualization results of the node importance are
consistent with prior knowledge, which confirms the interpretability power of
MV-GNN models.
|
[
{
"created": "Sun, 17 May 2020 04:46:07 GMT",
"version": "v1"
},
{
"created": "Fri, 29 May 2020 08:57:04 GMT",
"version": "v2"
},
{
"created": "Fri, 12 Jun 2020 06:09:52 GMT",
"version": "v3"
}
] |
2020-06-15
|
[
[
"Ma",
"Hehuan",
""
],
[
"Bian",
"Yatao",
""
],
[
"Rong",
"Yu",
""
],
[
"Huang",
"Wenbing",
""
],
[
"Xu",
"Tingyang",
""
],
[
"Xie",
"Weiyang",
""
],
[
"Ye",
"Geyan",
""
],
[
"Huang",
"Junzhou",
""
]
] |
The crux of molecular property prediction is to generate meaningful representations of the molecules. One promising route is to exploit the molecular graph structure through Graph Neural Networks (GNNs). It is well known that both atoms and bonds significantly affect the chemical properties of a molecule, so an expressive model shall be able to exploit both node (atom) and edge (bond) information simultaneously. Guided by this observation, we present Multi-View Graph Neural Network (MV-GNN), a multi-view message passing architecture to enable more accurate predictions of molecular properties. In MV-GNN, we introduce a shared self-attentive readout component and disagreement loss to stabilize the training process. This readout component also renders the whole architecture interpretable. We further boost the expressive power of MV-GNN by proposing a cross-dependent message passing scheme that enhances information communication of the two views, which results in the MV-GNN^cross variant. Lastly, we theoretically justify the expressiveness of the two proposed models in terms of distinguishing non-isomorphism graphs. Extensive experiments demonstrate that MV-GNN models achieve remarkably superior performance over the state-of-the-art models on a variety of challenging benchmarks. Meanwhile, visualization results of the node importance are consistent with prior knowledge, which confirms the interpretability power of MV-GNN models.
|
1201.5557
|
Shuhei Mano
|
Shuhei Mano
|
Duality between the two-locus Wright-Fisher Diffusion Model and the
Ancestral Process with Recombination
|
25 pages, no figures
|
J. Appl. Probab. 50 (2013) 256-271
| null | null |
q-bio.PE math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Known results on the moments of the distribution generated by the two-locus
Wright-Fisher diffusion model and a duality between the diffusion process and
the ancestral process with recombination are briefly summarized. A numerical
methods for computing moments by a Markov chain Monte Carlo and a method to
compute closed-form expressions of the moments are presented. By using the
duality argument properties of the ancestral recombination graph are studied in
terms of the moments.
|
[
{
"created": "Thu, 26 Jan 2012 15:38:01 GMT",
"version": "v1"
},
{
"created": "Sat, 18 Feb 2012 03:17:14 GMT",
"version": "v2"
}
] |
2013-04-08
|
[
[
"Mano",
"Shuhei",
""
]
] |
Known results on the moments of the distribution generated by the two-locus Wright-Fisher diffusion model and a duality between the diffusion process and the ancestral process with recombination are briefly summarized. A numerical methods for computing moments by a Markov chain Monte Carlo and a method to compute closed-form expressions of the moments are presented. By using the duality argument properties of the ancestral recombination graph are studied in terms of the moments.
|
1311.4206
|
Moritz Deger
|
Moritz Deger, Tilo Schwalger, Richard Naud, Wulfram Gerstner
|
Fluctuations and information filtering in coupled populations of spiking
neurons with adaptation
| null |
Phys. Rev. E 90, 062704 (2014)
|
10.1103/PhysRevE.90.062704
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Finite-sized populations of spiking elements are fundamental to brain
function, but also used in many areas of physics. Here we present a theory of
the dynamics of finite-sized populations of spiking units, based on a
quasi-renewal description of neurons with adaptation. We derive an integral
equation with colored noise that governs the stochastic dynamics of the
population activity in response to time-dependent stimulation and calculate the
spectral density in the asynchronous state. We show that systems of coupled
populations with adaptation can generate a frequency band in which sensory
information is preferentially encoded. The theory is applicable to fully as
well as randomly connected networks, and to leaky integrate-and-fire as well as
to generalized spiking neurons with adaptation on multiple time scales.
|
[
{
"created": "Sun, 17 Nov 2013 19:27:41 GMT",
"version": "v1"
},
{
"created": "Tue, 3 Mar 2015 13:52:23 GMT",
"version": "v2"
}
] |
2015-03-04
|
[
[
"Deger",
"Moritz",
""
],
[
"Schwalger",
"Tilo",
""
],
[
"Naud",
"Richard",
""
],
[
"Gerstner",
"Wulfram",
""
]
] |
Finite-sized populations of spiking elements are fundamental to brain function, but also used in many areas of physics. Here we present a theory of the dynamics of finite-sized populations of spiking units, based on a quasi-renewal description of neurons with adaptation. We derive an integral equation with colored noise that governs the stochastic dynamics of the population activity in response to time-dependent stimulation and calculate the spectral density in the asynchronous state. We show that systems of coupled populations with adaptation can generate a frequency band in which sensory information is preferentially encoded. The theory is applicable to fully as well as randomly connected networks, and to leaky integrate-and-fire as well as to generalized spiking neurons with adaptation on multiple time scales.
|
1606.08629
|
Alexey Mazur K
|
Alexey K. Mazur
|
Weak Nanoscale Chaos And Anomalous Relaxation in DNA
|
8 pages, 4 figures
|
Phys. Rev. E 95, 062417 (2017)
|
10.1103/PhysRevE.95.062417
| null |
q-bio.BM cond-mat.soft physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Anomalous non-exponential relaxation in hydrated biomolecules is commonly
attributed to the complexity of the free-energy landscapes, similarly to
polymers and glasses. It was found recently that the hydrogen-bond breathing of
terminal DNA base pairs exhibits a slow power-law relaxation attributable to
weak Hamiltonian chaos, with parameters similar to experimental data. Here, the
relationship is studied between this motion and spectroscopic signals measured
in DNA with a small molecular photoprobe inserted into the base-pair stack. To
this end, the earlier computational approach in combination with an analytical
theory is applied to the experimental DNA fragment. It is found that the
intensity of breathing dynamics is strongly increased in the internal base
pairs that flank the photoprobe, with anomalous relaxation quantitatively close
to that in terminal base pairs. A physical mechanism is proposed to explain the
coupling between the relaxation of base-pair breathing and the experimental
response signal. It is concluded that the algebraic relaxation observed
experimentally is very likely a manifestation of weakly chaotic dynamics of
hydrogen-bond breathing in the base pairs stacked to the photoprobe, and that
the weak nanoscale chaos can represent an ubiquitous hidden source of
non-exponential relaxation in ultrafast spectroscopy.
|
[
{
"created": "Tue, 28 Jun 2016 09:49:55 GMT",
"version": "v1"
},
{
"created": "Fri, 23 Jun 2017 09:07:23 GMT",
"version": "v2"
}
] |
2017-07-05
|
[
[
"Mazur",
"Alexey K.",
""
]
] |
Anomalous non-exponential relaxation in hydrated biomolecules is commonly attributed to the complexity of the free-energy landscapes, similarly to polymers and glasses. It was found recently that the hydrogen-bond breathing of terminal DNA base pairs exhibits a slow power-law relaxation attributable to weak Hamiltonian chaos, with parameters similar to experimental data. Here, the relationship is studied between this motion and spectroscopic signals measured in DNA with a small molecular photoprobe inserted into the base-pair stack. To this end, the earlier computational approach in combination with an analytical theory is applied to the experimental DNA fragment. It is found that the intensity of breathing dynamics is strongly increased in the internal base pairs that flank the photoprobe, with anomalous relaxation quantitatively close to that in terminal base pairs. A physical mechanism is proposed to explain the coupling between the relaxation of base-pair breathing and the experimental response signal. It is concluded that the algebraic relaxation observed experimentally is very likely a manifestation of weakly chaotic dynamics of hydrogen-bond breathing in the base pairs stacked to the photoprobe, and that the weak nanoscale chaos can represent an ubiquitous hidden source of non-exponential relaxation in ultrafast spectroscopy.
|
1802.02546
|
Valeriy Grytsay Dr
|
V.I. Grytsay, I.V. Musatenko
|
A mathematical model of the metabolism of a cell. Self-organization and
chaos
|
11 pages, 9 figures
| null | null | null |
q-bio.OT nlin.CD
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Using the classical tools of nonlinear dynamics, we study the process of
self-organization and the appearance of the chaos in the metabolic process in a
cell with the help of a mathematical model of the transformation of steroids by
a cell Arthrobacter globiformis. We constructed the phase-parametric diagrams
obtained under a variation of the dissipation of the kinetic membrane
potential. The oscillatory modes obtained are classified as regular and strange
attractors. We calculated the bifurcations, by which the self-organization and
the chaos occur in the system, and the transitions "chaos-order",
"order-chaos", "order-order", and "chaos-chaos" arise. Feigenbaum's scenarios
and the intermittences are found. For some selected modes, the projections of
the phase portraits of attractors, Poincar\'e sections, and Poincar\'e maps are
constructed. The total spectra of Lyapunov indices for the modes under study
are calculated. The structural stability of the attractors is demonstrated. A
general scenario of the formation of regular and strange attractors in the
given metabolic process in a cell is found. The physical nature of their
appearance in the metabolic process is studied.
|
[
{
"created": "Wed, 31 Jan 2018 09:29:50 GMT",
"version": "v1"
},
{
"created": "Tue, 13 Mar 2018 18:40:21 GMT",
"version": "v2"
}
] |
2018-03-15
|
[
[
"Grytsay",
"V. I.",
""
],
[
"Musatenko",
"I. V.",
""
]
] |
Using the classical tools of nonlinear dynamics, we study the process of self-organization and the appearance of the chaos in the metabolic process in a cell with the help of a mathematical model of the transformation of steroids by a cell Arthrobacter globiformis. We constructed the phase-parametric diagrams obtained under a variation of the dissipation of the kinetic membrane potential. The oscillatory modes obtained are classified as regular and strange attractors. We calculated the bifurcations, by which the self-organization and the chaos occur in the system, and the transitions "chaos-order", "order-chaos", "order-order", and "chaos-chaos" arise. Feigenbaum's scenarios and the intermittences are found. For some selected modes, the projections of the phase portraits of attractors, Poincar\'e sections, and Poincar\'e maps are constructed. The total spectra of Lyapunov indices for the modes under study are calculated. The structural stability of the attractors is demonstrated. A general scenario of the formation of regular and strange attractors in the given metabolic process in a cell is found. The physical nature of their appearance in the metabolic process is studied.
|
1610.06240
|
Semid\'an Robaina-Est\'evez
|
Semid\'an Robaina-Est\'evez, Zoran Nikoloski
|
On the effects of alternative optima in context-specific metabolic model
predictions
| null |
PLoS Comput Biol 13(5): e1005568 (2017)
|
10.1371/journal.pcbi.1005568
| null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recent methodological developments have facilitated the integration of
high-throughput data into genome-scale models to obtain context-specific
metabolic reconstructions. A unique solution to this data integration problem
often may not be guaranteed, leading to a multitude of context-specific
predictions equally concordant with the integrated data. Yet, little attention
has been paid to the alternative optima resulting from the integration of
context-specific data. Here we present computational approaches to analyze
alternative optima for different context-specific data integration instances.
By using these approaches on metabolic reconstructions for the leaf of
Arabidopsis thaliana and the human liver, we show that the analysis of
alternative optima is key to adequately evaluating the specificity of the
predictions in particular cellular contexts. While we provide several ways to
reduce the ambiguity in the context-specific predictions, our findings indicate
that the existence of alternative optimal solutions warrant caution in detailed
context-specific analyses of metabolism.
|
[
{
"created": "Wed, 19 Oct 2016 22:08:44 GMT",
"version": "v1"
},
{
"created": "Thu, 15 Jun 2017 14:39:30 GMT",
"version": "v2"
}
] |
2017-06-16
|
[
[
"Robaina-Estévez",
"Semidán",
""
],
[
"Nikoloski",
"Zoran",
""
]
] |
Recent methodological developments have facilitated the integration of high-throughput data into genome-scale models to obtain context-specific metabolic reconstructions. A unique solution to this data integration problem often may not be guaranteed, leading to a multitude of context-specific predictions equally concordant with the integrated data. Yet, little attention has been paid to the alternative optima resulting from the integration of context-specific data. Here we present computational approaches to analyze alternative optima for different context-specific data integration instances. By using these approaches on metabolic reconstructions for the leaf of Arabidopsis thaliana and the human liver, we show that the analysis of alternative optima is key to adequately evaluating the specificity of the predictions in particular cellular contexts. While we provide several ways to reduce the ambiguity in the context-specific predictions, our findings indicate that the existence of alternative optimal solutions warrant caution in detailed context-specific analyses of metabolism.
|
q-bio/0309022
|
V. Krishnan Ramanujan
|
R.V.Krishnan, A.Masuda, V.E.Centoze and B.Herman
|
Quantitative Imaging of Protein-Protein Interactions by Multiphoton
Fluorescence Lifetime Imaging Microscopy using a Streak camera
|
Overview of FLIM techniques, StreakFLIM instrument, FRET applications
|
Journal of Biomedical Optics Vo.8, 362 (July 2003)
|
10.1117/1.1577574
| null |
q-bio.QM q-bio.CB
| null |
Fluorescence Lifetime Imaging Microscopy (FLIM) using multiphoton excitation
techniques is now finding an important place in quantitative imaging of
protein-protein interactions and intracellular physiology. We review here the
recent developments in multiphoton FLIM methods and also present a description
of a novel multiphoton FLIM system using a streak camera that was developed in
our laboratory. We provide an example of a typical application of the system in
which we measure the fluorescence resonance energy transfer between a
donor/acceptor pair of fluorescent proteins within a cellular specimen.
|
[
{
"created": "Tue, 30 Sep 2003 14:19:35 GMT",
"version": "v1"
}
] |
2009-11-10
|
[
[
"Krishnan",
"R. V.",
""
],
[
"Masuda",
"A.",
""
],
[
"Centoze",
"V. E.",
""
],
[
"Herman",
"B.",
""
]
] |
Fluorescence Lifetime Imaging Microscopy (FLIM) using multiphoton excitation techniques is now finding an important place in quantitative imaging of protein-protein interactions and intracellular physiology. We review here the recent developments in multiphoton FLIM methods and also present a description of a novel multiphoton FLIM system using a streak camera that was developed in our laboratory. We provide an example of a typical application of the system in which we measure the fluorescence resonance energy transfer between a donor/acceptor pair of fluorescent proteins within a cellular specimen.
|
1307.4954
|
Robert Kofler
|
Robert Kofler and Christian Schl\"otterer
|
Guidelines for the design of evolve and resequencing studies
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Standing genetic variation provides a rich reservoir of potentially useful
mutations facilitating the adaptation to novel environments. Experimental
evolution studies have demonstrated that rapid and strong phenotypic responses
to selection can also be obtained in the laboratory. When combined with the
Next Generation Sequencing technology, these experiments promise to identify
the individual loci contributing to adaption. Nevertheless, until now, very
little is known about the design of such evolve and resequencing (E&R) studies.
Here, we use forward simulations of entire genomes to evaluate different
experimental designs that aim to maximize the power to detect selected
variants. We show that low linkage disequilibrium in the starting population,
population size, duration of the experiment and the number of replicates are
the key factors in determining the power and accuracy of E&R studies.
Furthermore, replication of E&R is more important for detecting the targets of
selection than increasing the population size. Using an optimized design
beneficial loci with a selective advantage as low as s=0.005 can be identified
at the nucleotide level. Even when a large number of loci are selected
simultaneously, up to 56% can be reliably detected without incurring large
numbers of false positives. Our computer simulations suggest that, with an
adequate experimental design, E&R studies are a powerful tool to identify
adaptive mutations from standing genetic variation and thereby provide an
excellent means to analyze the trajectories of selected alleles in evolving
populations.
|
[
{
"created": "Thu, 18 Jul 2013 14:16:16 GMT",
"version": "v1"
}
] |
2013-07-19
|
[
[
"Kofler",
"Robert",
""
],
[
"Schlötterer",
"Christian",
""
]
] |
Standing genetic variation provides a rich reservoir of potentially useful mutations facilitating the adaptation to novel environments. Experimental evolution studies have demonstrated that rapid and strong phenotypic responses to selection can also be obtained in the laboratory. When combined with the Next Generation Sequencing technology, these experiments promise to identify the individual loci contributing to adaption. Nevertheless, until now, very little is known about the design of such evolve and resequencing (E&R) studies. Here, we use forward simulations of entire genomes to evaluate different experimental designs that aim to maximize the power to detect selected variants. We show that low linkage disequilibrium in the starting population, population size, duration of the experiment and the number of replicates are the key factors in determining the power and accuracy of E&R studies. Furthermore, replication of E&R is more important for detecting the targets of selection than increasing the population size. Using an optimized design beneficial loci with a selective advantage as low as s=0.005 can be identified at the nucleotide level. Even when a large number of loci are selected simultaneously, up to 56% can be reliably detected without incurring large numbers of false positives. Our computer simulations suggest that, with an adequate experimental design, E&R studies are a powerful tool to identify adaptive mutations from standing genetic variation and thereby provide an excellent means to analyze the trajectories of selected alleles in evolving populations.
|
2309.13319
|
Catherine Beauchemin
|
Jamie Porthiyas, Daniel Nussey, Catherine A. A. Beauchemin, Donald C.
Warren, Christian Quirouette, Kathleen P. Wilkie
|
A closer look at parameter identifiability, model selection and handling
of censored data with Bayesian Inference in mathematical models of tumour
growth
|
15 pages, 7 figures
|
NPJ Syst. Biol. Appl., 10:89 (2024)
|
10.1038/s41540-024-00409-6
|
RIKEN-iTHEMS-Report-23
|
q-bio.QM
|
http://creativecommons.org/licenses/by-sa/4.0/
|
Mathematical models (MMs) are a powerful tool to help us understand and
predict the dynamics of tumour growth under various conditions. In this work,
we use 5 MMs with an increasing number of parameters to explore how certain
(often overlooked) decisions in estimating parameters from data of experimental
tumour growth affect the outcome of the analysis. In particular, we propose a
framework for including tumour volume measurements that fall outside the upper
and lower limits of detection, which are normally discarded. We demonstrate how
excluding censored data results in an overestimation of the initial tumour
volume and the MM-predicted tumour volumes prior to the first measurements, and
an underestimation of the carrying capacity and the MM-predicted tumour volumes
beyond the latest measurable time points. We show in which way the choice of
prior for the MM parameters can impact the posterior distributions, and
illustrate that reporting the highest-likelihood parameters and their 95%
credible interval can lead to confusing or misleading interpretations. We hope
this work will encourage others to carefully consider choices made in parameter
estimation and to adopt the approaches we put forward herein.
|
[
{
"created": "Sat, 23 Sep 2023 09:27:38 GMT",
"version": "v1"
}
] |
2024-08-16
|
[
[
"Porthiyas",
"Jamie",
""
],
[
"Nussey",
"Daniel",
""
],
[
"Beauchemin",
"Catherine A. A.",
""
],
[
"Warren",
"Donald C.",
""
],
[
"Quirouette",
"Christian",
""
],
[
"Wilkie",
"Kathleen P.",
""
]
] |
Mathematical models (MMs) are a powerful tool to help us understand and predict the dynamics of tumour growth under various conditions. In this work, we use 5 MMs with an increasing number of parameters to explore how certain (often overlooked) decisions in estimating parameters from data of experimental tumour growth affect the outcome of the analysis. In particular, we propose a framework for including tumour volume measurements that fall outside the upper and lower limits of detection, which are normally discarded. We demonstrate how excluding censored data results in an overestimation of the initial tumour volume and the MM-predicted tumour volumes prior to the first measurements, and an underestimation of the carrying capacity and the MM-predicted tumour volumes beyond the latest measurable time points. We show in which way the choice of prior for the MM parameters can impact the posterior distributions, and illustrate that reporting the highest-likelihood parameters and their 95% credible interval can lead to confusing or misleading interpretations. We hope this work will encourage others to carefully consider choices made in parameter estimation and to adopt the approaches we put forward herein.
|
1610.07161
|
Mihai Alexandru Petrovici
|
Mihai A. Petrovici, Johannes Bill, Ilja Bytschok, Johannes Schemmel,
Karlheinz Meier
|
Stochastic inference with spiking neurons in the high-conductance state
| null |
Phys. Rev. E 94, 042312 (2016)
|
10.1103/PhysRevE.94.042312
| null |
q-bio.NC cond-mat.dis-nn cs.NE physics.bio-ph stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The highly variable dynamics of neocortical circuits observed in vivo have
been hypothesized to represent a signature of ongoing stochastic inference but
stand in apparent contrast to the deterministic response of neurons measured in
vitro. Based on a propagation of the membrane autocorrelation across spike
bursts, we provide an analytical derivation of the neural activation function
that holds for a large parameter space, including the high-conductance state.
On this basis, we show how an ensemble of leaky integrate-and-fire neurons with
conductance-based synapses embedded in a spiking environment can attain the
correct firing statistics for sampling from a well-defined target distribution.
For recurrent networks, we examine convergence toward stationarity in computer
simulations and demonstrate sample-based Bayesian inference in a mixed
graphical model. This points to a new computational role of high-conductance
states and establishes a rigorous link between deterministic neuron models and
functional stochastic dynamics on the network level.
|
[
{
"created": "Sun, 23 Oct 2016 12:27:05 GMT",
"version": "v1"
}
] |
2017-03-14
|
[
[
"Petrovici",
"Mihai A.",
""
],
[
"Bill",
"Johannes",
""
],
[
"Bytschok",
"Ilja",
""
],
[
"Schemmel",
"Johannes",
""
],
[
"Meier",
"Karlheinz",
""
]
] |
The highly variable dynamics of neocortical circuits observed in vivo have been hypothesized to represent a signature of ongoing stochastic inference but stand in apparent contrast to the deterministic response of neurons measured in vitro. Based on a propagation of the membrane autocorrelation across spike bursts, we provide an analytical derivation of the neural activation function that holds for a large parameter space, including the high-conductance state. On this basis, we show how an ensemble of leaky integrate-and-fire neurons with conductance-based synapses embedded in a spiking environment can attain the correct firing statistics for sampling from a well-defined target distribution. For recurrent networks, we examine convergence toward stationarity in computer simulations and demonstrate sample-based Bayesian inference in a mixed graphical model. This points to a new computational role of high-conductance states and establishes a rigorous link between deterministic neuron models and functional stochastic dynamics on the network level.
|
2312.03954
|
Rylan Schaeffer
|
Rylan Schaeffer, Mikail Khona, Sanmi Koyejo, and Ila Rani Fiete
|
Disentangling Fact from Grid Cell Fiction in Trained Deep Path
Integrators
|
arXiv admin note: text overlap with arXiv:2311.16295
| null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Work on deep learning-based models of grid cells suggests that grid cells
generically and robustly arise from optimizing networks to path integrate,
i.e., track one's spatial position by integrating self-velocity signals. In
previous work, we challenged this path integration hypothesis by showing that
deep neural networks trained to path integrate almost always do so, but almost
never learn grid-like tuning unless separately inserted by researchers via
mechanisms unrelated to path integration. In this work, we restate the key
evidence substantiating these insights, then address a response to by authors
of one of the path integration hypothesis papers. First, we show that the
response misinterprets our work, indirectly confirming our points. Second, we
evaluate the response's preferred "unified theory for the origin of grid cells"
in trained deep path integrators and show that it is at best "occasionally
suggestive," not exact or comprehensive. We finish by considering why assessing
model quality through prediction of biological neural activity by regression of
activity in deep networks can lead to the wrong conclusions.
|
[
{
"created": "Wed, 6 Dec 2023 23:44:43 GMT",
"version": "v1"
},
{
"created": "Fri, 8 Dec 2023 04:14:42 GMT",
"version": "v2"
},
{
"created": "Sat, 16 Dec 2023 15:01:17 GMT",
"version": "v3"
}
] |
2023-12-19
|
[
[
"Schaeffer",
"Rylan",
""
],
[
"Khona",
"Mikail",
""
],
[
"Koyejo",
"Sanmi",
""
],
[
"Fiete",
"Ila Rani",
""
]
] |
Work on deep learning-based models of grid cells suggests that grid cells generically and robustly arise from optimizing networks to path integrate, i.e., track one's spatial position by integrating self-velocity signals. In previous work, we challenged this path integration hypothesis by showing that deep neural networks trained to path integrate almost always do so, but almost never learn grid-like tuning unless separately inserted by researchers via mechanisms unrelated to path integration. In this work, we restate the key evidence substantiating these insights, then address a response to by authors of one of the path integration hypothesis papers. First, we show that the response misinterprets our work, indirectly confirming our points. Second, we evaluate the response's preferred "unified theory for the origin of grid cells" in trained deep path integrators and show that it is at best "occasionally suggestive," not exact or comprehensive. We finish by considering why assessing model quality through prediction of biological neural activity by regression of activity in deep networks can lead to the wrong conclusions.
|
1007.5235
|
Pietro Faccioli
|
S. a Beccara, P. Faccioli, G. Garberoglio, M. Sega, F. Pederiva and H.
Orland
|
Dominant folding pathways of a peptide chain, from ab-initio
quantum-mechanical simulations
|
9 pages, 5 figures
| null | null | null |
q-bio.BM cond-mat.soft cond-mat.str-el
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Using the Dominant Reaction Pathways method, we perform an ab-initio
quantum-mechanical simulation of a conformational transition of a peptide
chain. The method we propose makes it possible to investigate the
out-of-equilibrium dynamics of these systems, without resorting to an empirical
representation of the molecular force field. It also allows to study rare
transitions involving rearrangements in the electronic structure. By comparing
the results of the ab-initio simulation with those obtained employing a
standard force field, we discuss its capability to describe the non-equilibrium
dynamics of conformational transitions.
|
[
{
"created": "Thu, 29 Jul 2010 14:45:58 GMT",
"version": "v1"
}
] |
2010-07-30
|
[
[
"Beccara",
"S. a",
""
],
[
"Faccioli",
"P.",
""
],
[
"Garberoglio",
"G.",
""
],
[
"Sega",
"M.",
""
],
[
"Pederiva",
"F.",
""
],
[
"Orland",
"H.",
""
]
] |
Using the Dominant Reaction Pathways method, we perform an ab-initio quantum-mechanical simulation of a conformational transition of a peptide chain. The method we propose makes it possible to investigate the out-of-equilibrium dynamics of these systems, without resorting to an empirical representation of the molecular force field. It also allows to study rare transitions involving rearrangements in the electronic structure. By comparing the results of the ab-initio simulation with those obtained employing a standard force field, we discuss its capability to describe the non-equilibrium dynamics of conformational transitions.
|
0707.4487
|
Shimshon Jacobi
|
Jean-Pierre Eckmann, Shimshon Jacobi, Shimon Marom, Elisha Moses,
Cyrille Zbinden
|
Leadership in 2D living neural networks
| null | null | null |
New J. Phys. 10 (2008) 015011
|
q-bio.NC
| null |
Eytan and Marom recently showed that the spontaneous burst activity of rat
neuron cultures includes `first to fire' cells that consistently fire earlier
than others. Here we analyze the behavior of these neurons in long term
recordings of spontaneous activity of rat hippocampal and rat cortical neuron
cultures from three different laboratories. We identify precursor events that
may either subside (`small events') or can lead to a full-blown burst
(`pre-bursts'). We find that the activation in the pre-burst typically has a
first neuron (`leader'), followed by a localized response in its neighborhood.
Locality is diminished in the bursts themselves. The long term dynamics of the
leaders is relatively robust, evolving with a half-life of 23-34 hours.
Stimulation of the culture can temporarily alter the leader distribution, but
it returns to the previous distribution within about 1 hour. We show that the
leaders carry information about the identity of the burst, as measured by the
signature of the number of spikes per neuron in a burst. The number of spikes
from leaders in the first few spikes of a precursor event is furthermore shown
to be predictive with regard to the transition into a burst (pre-burst versus
small event). We conclude that the leaders play a r\^ole in the development of
the bursts, and conjecture that they are part of an underlying sub-network that
is excited first and then act as nucleation centers for the burst.
|
[
{
"created": "Mon, 30 Jul 2007 21:14:47 GMT",
"version": "v1"
}
] |
2010-04-19
|
[
[
"Eckmann",
"Jean-Pierre",
""
],
[
"Jacobi",
"Shimshon",
""
],
[
"Marom",
"Shimon",
""
],
[
"Moses",
"Elisha",
""
],
[
"Zbinden",
"Cyrille",
""
]
] |
Eytan and Marom recently showed that the spontaneous burst activity of rat neuron cultures includes `first to fire' cells that consistently fire earlier than others. Here we analyze the behavior of these neurons in long term recordings of spontaneous activity of rat hippocampal and rat cortical neuron cultures from three different laboratories. We identify precursor events that may either subside (`small events') or can lead to a full-blown burst (`pre-bursts'). We find that the activation in the pre-burst typically has a first neuron (`leader'), followed by a localized response in its neighborhood. Locality is diminished in the bursts themselves. The long term dynamics of the leaders is relatively robust, evolving with a half-life of 23-34 hours. Stimulation of the culture can temporarily alter the leader distribution, but it returns to the previous distribution within about 1 hour. We show that the leaders carry information about the identity of the burst, as measured by the signature of the number of spikes per neuron in a burst. The number of spikes from leaders in the first few spikes of a precursor event is furthermore shown to be predictive with regard to the transition into a burst (pre-burst versus small event). We conclude that the leaders play a r\^ole in the development of the bursts, and conjecture that they are part of an underlying sub-network that is excited first and then act as nucleation centers for the burst.
|
0908.1615
|
David Saakian
|
David B. Saakian, Olga Rozanova, Andrei Akmetzhanov
|
Exactly solvable dynamics of the Eigen and the Crow-Kimura models
|
7 pages
|
Physical Review E 78, 041908 (2008)
|
10.1103/PhysRevE.78.041908
| null |
q-bio.PE q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We introduce a new way to study molecular evolution within well-established
Hamilton-Jacobi formalism, showing that for a broad class of fitness landscapes
it is possible to derive dynamics analytically within the $1/N$-accuracy, where
$N$ is genome length. For smooth and monotonic fitness function this approach
gives two dynamical phases: smooth dynamics, and discontinuous dynamics. The
latter phase arises naturally with no explicit singular fitness function,
counter-intuitively. The Hamilton-Jacobi method yields straightforward
analytical results for the models that utilize fitness as a function of Hamming
distance from a reference genome sequence. We also show the way in which this
method gives dynamical phase structure for multi-peak fitness.
|
[
{
"created": "Wed, 12 Aug 2009 05:11:25 GMT",
"version": "v1"
}
] |
2015-05-13
|
[
[
"Saakian",
"David B.",
""
],
[
"Rozanova",
"Olga",
""
],
[
"Akmetzhanov",
"Andrei",
""
]
] |
We introduce a new way to study molecular evolution within well-established Hamilton-Jacobi formalism, showing that for a broad class of fitness landscapes it is possible to derive dynamics analytically within the $1/N$-accuracy, where $N$ is genome length. For smooth and monotonic fitness function this approach gives two dynamical phases: smooth dynamics, and discontinuous dynamics. The latter phase arises naturally with no explicit singular fitness function, counter-intuitively. The Hamilton-Jacobi method yields straightforward analytical results for the models that utilize fitness as a function of Hamming distance from a reference genome sequence. We also show the way in which this method gives dynamical phase structure for multi-peak fitness.
|
2303.06503
|
Iheanyi Okonko Okonko
|
Iheanyi Omezuruike Okonko, Chisom Chimbundum Adim, Blessing Jachinma
Okonko and Edith Ijeego Mba
|
Semi-Quantitative Analysis and Serological Evidence of Hepatitis A Virus
IgG Antibody among children in Rumuewhor, Emuoha, Rivers State, Nigeria
|
7 pages
| null | null | null |
q-bio.OT
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Hepatitis A virus (HAV) infection has been greatly reduced in most developed
countries through the use of vaccine and improved hygienic conditions. However,
the magnitude of the problem is underestimated and there are no
well-established Hepatitis A virus prevention and control strategies in
Nigeria. The aim of this study was to determine the prevalence of Hepatitis A
virus infection among children aged 2 to 9 years in Rumuewhor, Emuoha LGA,
Rivers State, Nigeria. Blood samples were collected from the 89 children
enrolled in this study, and analyzed for the presence of HAV IgG antibodies
using ELISA techniques. Of the 89 participants, 22 (24.7%) tested positive for
HAV IgG antibodies, while 67 (75.3%) were negative. The children within the
ages of 4 to 6 years had the highest seropositivity rate (33.3%) while those
less than 4 years had the least seropositivity rate (22.4%). The prevalence
rate ratio of the males to females was 1:1.3. There was no significant
difference (p between IgG seropositivity and age groups and gender. However,
there was a statistical association of IgG seropositivity rates with respect to
immunization. The seroprevalence rate recorded in this study was significant,
indicating that the virus is endemic in this study area. Proper awareness,
health education and vaccination are imperative to controlling and preventing
HAV infection in Rumuewhor, Emuoha, Rivers State, Nigeria.
|
[
{
"created": "Sat, 11 Mar 2023 22:06:44 GMT",
"version": "v1"
}
] |
2023-03-14
|
[
[
"Okonko",
"Iheanyi Omezuruike",
""
],
[
"Adim",
"Chisom Chimbundum",
""
],
[
"Okonko",
"Blessing Jachinma",
""
],
[
"Mba",
"Edith Ijeego",
""
]
] |
Hepatitis A virus (HAV) infection has been greatly reduced in most developed countries through the use of vaccine and improved hygienic conditions. However, the magnitude of the problem is underestimated and there are no well-established Hepatitis A virus prevention and control strategies in Nigeria. The aim of this study was to determine the prevalence of Hepatitis A virus infection among children aged 2 to 9 years in Rumuewhor, Emuoha LGA, Rivers State, Nigeria. Blood samples were collected from the 89 children enrolled in this study, and analyzed for the presence of HAV IgG antibodies using ELISA techniques. Of the 89 participants, 22 (24.7%) tested positive for HAV IgG antibodies, while 67 (75.3%) were negative. The children within the ages of 4 to 6 years had the highest seropositivity rate (33.3%) while those less than 4 years had the least seropositivity rate (22.4%). The prevalence rate ratio of the males to females was 1:1.3. There was no significant difference (p between IgG seropositivity and age groups and gender. However, there was a statistical association of IgG seropositivity rates with respect to immunization. The seroprevalence rate recorded in this study was significant, indicating that the virus is endemic in this study area. Proper awareness, health education and vaccination are imperative to controlling and preventing HAV infection in Rumuewhor, Emuoha, Rivers State, Nigeria.
|
2406.10739
|
Ananda Shikhara Bhat
|
Ananda Shikhara Bhat
|
A stochastic field theory for the evolution of quantitative traits in
finite populations
|
Main text is 36 pages long (with references) and contains two
figures; Supplementary material is 35 pages long (with references) and
contains one figure
| null | null | null |
q-bio.PE cond-mat.stat-mech math.PR physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Infinitely many distinct trait values may arise in populations bearing
quantitative traits, and modelling their population dynamics is thus a
formidable task. While classical models assume fixed or infinite population
size, models in which the total population size fluctuates due to demographic
noise in births and deaths can behave qualitatively differently from constant
or infinite population models due to density-dependent dynamics. In this paper,
I present a stochastic field theory for the eco-evolutionary dynamics of finite
populations bearing one-dimensional quantitative traits. I derive stochastic
field equations that describe the evolution of population densities, trait
frequencies, and the mean value of any trait in the population. These equations
recover well-known results such as the replicator-mutator equation, Price
equation, and gradient dynamics in the infinite population limit. For finite
populations, the equations describe the intricate interplay between natural
selection, noise-induced selection, eco-evolutionary feedback, and neutral
genetic drift in determining evolutionary trajectories. My methods use ideas
from statistical physics and present an alternative to some recently proposed
measure-theoretic frameworks.
|
[
{
"created": "Sat, 15 Jun 2024 20:58:02 GMT",
"version": "v1"
}
] |
2024-06-18
|
[
[
"Bhat",
"Ananda Shikhara",
""
]
] |
Infinitely many distinct trait values may arise in populations bearing quantitative traits, and modelling their population dynamics is thus a formidable task. While classical models assume fixed or infinite population size, models in which the total population size fluctuates due to demographic noise in births and deaths can behave qualitatively differently from constant or infinite population models due to density-dependent dynamics. In this paper, I present a stochastic field theory for the eco-evolutionary dynamics of finite populations bearing one-dimensional quantitative traits. I derive stochastic field equations that describe the evolution of population densities, trait frequencies, and the mean value of any trait in the population. These equations recover well-known results such as the replicator-mutator equation, Price equation, and gradient dynamics in the infinite population limit. For finite populations, the equations describe the intricate interplay between natural selection, noise-induced selection, eco-evolutionary feedback, and neutral genetic drift in determining evolutionary trajectories. My methods use ideas from statistical physics and present an alternative to some recently proposed measure-theoretic frameworks.
|
1911.00383
|
Homayoun Valafar
|
Rishi Mukhopadhyay, Paul Shealy, Homayoun Valafar
|
Protein Fold Family Recognition From Unassigned Residual Dipolar
Coupling Data
|
BioComp 2008, 7 pages
| null | null | null |
q-bio.BM cs.CV
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Despite many advances in computational modeling of protein structures, these
methods have not been widely utilized by experimental structural biologists.
Two major obstacles are preventing the transition from a purely-experimental to
a purely-computational mode of protein structure determination. The first
problem is that most computational methods need a large library of computed
structures that span a large variety of protein fold families, while structural
genomics initiatives have slowed in their ability to provide novel protein
folds in recent years. The second problem is an unwillingness to trust
computational models that have no experimental backing. In this paper we test a
potential solution to these problems that we have called Probability Density
Profile Analysis (PDPA) that utilizes unassigned residual dipolar coupling data
that are relatively cheap to acquire from NMR experiments.
|
[
{
"created": "Fri, 1 Nov 2019 14:01:25 GMT",
"version": "v1"
}
] |
2019-11-04
|
[
[
"Mukhopadhyay",
"Rishi",
""
],
[
"Shealy",
"Paul",
""
],
[
"Valafar",
"Homayoun",
""
]
] |
Despite many advances in computational modeling of protein structures, these methods have not been widely utilized by experimental structural biologists. Two major obstacles are preventing the transition from a purely-experimental to a purely-computational mode of protein structure determination. The first problem is that most computational methods need a large library of computed structures that span a large variety of protein fold families, while structural genomics initiatives have slowed in their ability to provide novel protein folds in recent years. The second problem is an unwillingness to trust computational models that have no experimental backing. In this paper we test a potential solution to these problems that we have called Probability Density Profile Analysis (PDPA) that utilizes unassigned residual dipolar coupling data that are relatively cheap to acquire from NMR experiments.
|
2004.11961
|
Alexey Ovchinnikov
|
Alexey Ovchinnikov, Isabel Cristina P\'erez Verona, Gleb Pogudin,
Mirco Tribastone
|
CLUE: Exact maximal reduction of kinetic models by constrained lumping
of differential equations
| null | null | null | null |
q-bio.MN cs.SC cs.SY eess.SY
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Motivation: Detailed mechanistic models of biological processes can pose
significant challenges for analysis and parameter estimations due to the large
number of equations used to track the dynamics of all distinct configurations
in which each involved biochemical species can be found. Model reduction can
help tame such complexity by providing a lower-dimensional model in which each
macro-variable can be directly related to the original variables.
Results: We present CLUE, an algorithm for exact model reduction of systems
of polynomial differential equations by constrained linear lumping. It computes
the smallest dimensional reduction as a linear mapping of the state space such
that the reduced model preserves the dynamics of user-specified linear
combinations of the original variables. Even though CLUE works with nonlinear
differential equations, it is based on linear algebra tools, which makes it
applicable to high-dimensional models. Using case studies from the literature,
we show how CLUE can substantially lower model dimensionality and help extract
biologically intelligible insights from the reduction.
Availability: An implementation of the algorithm and relevant resources to
replicate the experiments herein reported are freely available for download at
https://github.com/pogudingleb/CLUE.
Supplementary information: enclosed.
|
[
{
"created": "Fri, 24 Apr 2020 19:42:51 GMT",
"version": "v1"
},
{
"created": "Tue, 15 Dec 2020 02:09:43 GMT",
"version": "v2"
}
] |
2020-12-16
|
[
[
"Ovchinnikov",
"Alexey",
""
],
[
"Verona",
"Isabel Cristina Pérez",
""
],
[
"Pogudin",
"Gleb",
""
],
[
"Tribastone",
"Mirco",
""
]
] |
Motivation: Detailed mechanistic models of biological processes can pose significant challenges for analysis and parameter estimations due to the large number of equations used to track the dynamics of all distinct configurations in which each involved biochemical species can be found. Model reduction can help tame such complexity by providing a lower-dimensional model in which each macro-variable can be directly related to the original variables. Results: We present CLUE, an algorithm for exact model reduction of systems of polynomial differential equations by constrained linear lumping. It computes the smallest dimensional reduction as a linear mapping of the state space such that the reduced model preserves the dynamics of user-specified linear combinations of the original variables. Even though CLUE works with nonlinear differential equations, it is based on linear algebra tools, which makes it applicable to high-dimensional models. Using case studies from the literature, we show how CLUE can substantially lower model dimensionality and help extract biologically intelligible insights from the reduction. Availability: An implementation of the algorithm and relevant resources to replicate the experiments herein reported are freely available for download at https://github.com/pogudingleb/CLUE. Supplementary information: enclosed.
|
q-bio/0312026
|
Brandilyn Stigler
|
Reinhard Laubenbacher, Brandilyn Stigler
|
A Computational Algebra Approach to the Reverse Engineering of Gene
Regulatory Networks
|
28 pages, 5 EPS figures, uses elsart.cls
|
Journal of Theoretical Biology 229 (2004) 523-537
|
10.1016/j.jtbi.2004.04.037
| null |
q-bio.QM q-bio.MN
| null |
This paper proposes a new method to reverse engineer gene regulatory networks
from experimental data. The modeling framework used is time-discrete
deterministic dynamical systems, with a finite set of states for each of the
variables. The simplest examples of such models are Boolean networks, in which
variables have only two possible states. The use of a larger number of possible
states allows a finer discretization of experimental data and more than one
possible mode of action for the variables, depending on threshold values.
Furthermore, with a suitable choice of state set, one can employ powerful tools
from computational algebra, that underlie the reverse-engineering algorithm,
avoiding costly enumeration strategies. To perform well, the algorithm requires
wildtype together with perturbation time courses. This makes it suitable for
small to meso-scale networks rather than networks on a genome-wide scale. The
complexity of the algorithm is quadratic in the number of variables and cubic
in the number of time points. The algorithm is validated on a recently
published Boolean network model of segment polarity development in Drosophila
melanogaster.
|
[
{
"created": "Wed, 17 Dec 2003 22:12:11 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Laubenbacher",
"Reinhard",
""
],
[
"Stigler",
"Brandilyn",
""
]
] |
This paper proposes a new method to reverse engineer gene regulatory networks from experimental data. The modeling framework used is time-discrete deterministic dynamical systems, with a finite set of states for each of the variables. The simplest examples of such models are Boolean networks, in which variables have only two possible states. The use of a larger number of possible states allows a finer discretization of experimental data and more than one possible mode of action for the variables, depending on threshold values. Furthermore, with a suitable choice of state set, one can employ powerful tools from computational algebra, that underlie the reverse-engineering algorithm, avoiding costly enumeration strategies. To perform well, the algorithm requires wildtype together with perturbation time courses. This makes it suitable for small to meso-scale networks rather than networks on a genome-wide scale. The complexity of the algorithm is quadratic in the number of variables and cubic in the number of time points. The algorithm is validated on a recently published Boolean network model of segment polarity development in Drosophila melanogaster.
|
2011.07982
|
Ricardo Martinez-Garcia
|
Ricardo Martinez-Garcia, Crist\'obal L\'opez, Federico Vazquez
|
Species exclusion and coexistence in a noisy voter model with a
competition-colonization tradeoff
|
13 pages, 9 figures, 3 appendices
|
Phys. Rev. E 103, 032406 (2021)
|
10.1103/PhysRevE.103.032406
| null |
q-bio.PE cond-mat.stat-mech
|
http://creativecommons.org/licenses/by/4.0/
|
We introduce an asymmetric noisy voter model to study the joint effect of
immigration and a competition-dispersal tradeoff in the dynamics of two species
competing for space in regular lattices. Individuals of one species can invade
a nearest-neighbor site in the lattice, while individuals of the other species
are able to invade sites at any distance but are less competitive locally,
i.e., they establish with a probability $g \le 1$. The model also accounts for
immigration, modeled as an external noise that may spontaneously replace an
individual at a lattice site by another individual of the other species. This
combination of mechanisms gives rise to a rich variety of outcomes for species
competition, including exclusion of either species, mono-stable coexistence of
both species at different population proportions, and bi-stable coexistence
with proportions of populations that depend on the initial condition.
Remarkably, in the bi-stable phase, the system undergoes a discontinuous
transition as the intensity of immigration overcomes a threshold, leading to a
half loop dynamics associated to a cusp catastrophe, which causes the
irreversible loss of the species with the shortest dispersal range.
|
[
{
"created": "Mon, 16 Nov 2020 14:28:05 GMT",
"version": "v1"
},
{
"created": "Fri, 5 Feb 2021 13:12:05 GMT",
"version": "v2"
},
{
"created": "Tue, 16 Feb 2021 16:13:29 GMT",
"version": "v3"
}
] |
2021-03-17
|
[
[
"Martinez-Garcia",
"Ricardo",
""
],
[
"López",
"Cristóbal",
""
],
[
"Vazquez",
"Federico",
""
]
] |
We introduce an asymmetric noisy voter model to study the joint effect of immigration and a competition-dispersal tradeoff in the dynamics of two species competing for space in regular lattices. Individuals of one species can invade a nearest-neighbor site in the lattice, while individuals of the other species are able to invade sites at any distance but are less competitive locally, i.e., they establish with a probability $g \le 1$. The model also accounts for immigration, modeled as an external noise that may spontaneously replace an individual at a lattice site by another individual of the other species. This combination of mechanisms gives rise to a rich variety of outcomes for species competition, including exclusion of either species, mono-stable coexistence of both species at different population proportions, and bi-stable coexistence with proportions of populations that depend on the initial condition. Remarkably, in the bi-stable phase, the system undergoes a discontinuous transition as the intensity of immigration overcomes a threshold, leading to a half loop dynamics associated to a cusp catastrophe, which causes the irreversible loss of the species with the shortest dispersal range.
|
1905.01158
|
Gabriel Obed Fosu
|
Gabriel O. Fosu and Emmanuel K. Mintah
|
A Two-Dose Vaccine Epidemic Model with Power Incidence Rate
| null | null | null | null |
q-bio.PE physics.soc-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The dynamics of a SIVR model with power relationship incidence rates $(\beta
I^p S^q)$ is investigated. It is assumed an individual can be susceptible after
receiving the first dose of the vaccine, hence a second dose is required to
attain permanent immunity. The steady states conditions of the disease-free
equilibrium and the endemic equilibrium are critically presented. Numerical
simulations are carried out to determine the impact of the exponential
parameters $(p;q)$ on infection.
|
[
{
"created": "Thu, 2 May 2019 16:41:22 GMT",
"version": "v1"
}
] |
2019-05-06
|
[
[
"Fosu",
"Gabriel O.",
""
],
[
"Mintah",
"Emmanuel K.",
""
]
] |
The dynamics of a SIVR model with power relationship incidence rates $(\beta I^p S^q)$ is investigated. It is assumed an individual can be susceptible after receiving the first dose of the vaccine, hence a second dose is required to attain permanent immunity. The steady states conditions of the disease-free equilibrium and the endemic equilibrium are critically presented. Numerical simulations are carried out to determine the impact of the exponential parameters $(p;q)$ on infection.
|
q-bio/0412033
|
Robersy Sanchez
|
Robersy Sanchez, Eberto Morgado and Ricardo Grau
|
Gene Algebra from a Genetic Code Algebraic Structure
|
27 pages, without figures
|
Journal of Mathematical Biology. 2005 Oct;51(4):431-57.
|
10.1007/s00285-005-0332-8
| null |
q-bio.QM q-bio.GN
| null |
The biological distinction between the base positions in the codon, the
chemical types of bases (purine and pyrimidine) and their hydrogen bond number
have been the most relevant codon properties used in the genetic code analysis.
Now, these properties have allowed us to build a Genetic Code ring isomorphic
to the ring (Z64, +,*) of the integer module 64. On the Z64-algebra of the set
of 64^N codon sequences of length N, gene mutations are described by means of
endomorphisms F: (Z64)^N->(Z64)^N. Endomorphisms and automorphisms helped us
describe the gene mutation pathways. For instance, 77.7% mutations in 749 HIV
protease gene sequences correspond to unique diagonal endomorphisms of the wild
type strain HXB2. In particular, most of the reported mutations that confer
drug resistance to the HIV protease gene correspond to diagonal automorphisms
of the wild type. What is more, in the human beta-globin gene a similar
situation appears where most of the single codon mutations correspond to
automorphisms. Hence, in the analyses of molecular evolution process on the DNA
sequence set of length N, the Z64-algebra will help us explain the quantitative
relationships between genes.
|
[
{
"created": "Thu, 16 Dec 2004 16:49:14 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Sanchez",
"Robersy",
""
],
[
"Morgado",
"Eberto",
""
],
[
"Grau",
"Ricardo",
""
]
] |
The biological distinction between the base positions in the codon, the chemical types of bases (purine and pyrimidine) and their hydrogen bond number have been the most relevant codon properties used in the genetic code analysis. Now, these properties have allowed us to build a Genetic Code ring isomorphic to the ring (Z64, +,*) of the integer module 64. On the Z64-algebra of the set of 64^N codon sequences of length N, gene mutations are described by means of endomorphisms F: (Z64)^N->(Z64)^N. Endomorphisms and automorphisms helped us describe the gene mutation pathways. For instance, 77.7% mutations in 749 HIV protease gene sequences correspond to unique diagonal endomorphisms of the wild type strain HXB2. In particular, most of the reported mutations that confer drug resistance to the HIV protease gene correspond to diagonal automorphisms of the wild type. What is more, in the human beta-globin gene a similar situation appears where most of the single codon mutations correspond to automorphisms. Hence, in the analyses of molecular evolution process on the DNA sequence set of length N, the Z64-algebra will help us explain the quantitative relationships between genes.
|
1304.3720
|
Brian Williams Dr
|
Brian G. Williams and Eleanor Gouws
|
R0 and the elimination of HIV in Africa: Will 90-90-90 be sufficient?
|
We have updated the previous version for two reasons. First, we have
given a better approximation for the estimation of R0 from epidemic doubling
times. Second, we have added comments on the new UNAIDS '90-90-90' strategy
which puts the results into a broader context
| null | null | null |
q-bio.QM q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The Joint United Nations Programme on HIV and AIDS (UNAIDS) has set a new
90-90-90 global target for the coverage of anti-retroviral therapy (ART) to be
reached by 2020. This would mean that 90% of all people infected with HIV know
their status, 90% of them are on ART and 90% of them will have full viral load
suppression. Here we first estimate the case reproduction number, R0, for
countries in sub-Saharan Africa and for India using data on the rate at which
the prevalence of HIV increased at the start of the epidemic and the life
expectancy of people living with HIV who are not on ART. R0 determines the
magnitude of the control problem, that is to say, the extent to which
transmission must be reduced to eliminate HIV. We show that in sub-Saharan
Africa the median value of R0 is 4.6 and in all but five countries R0 is less
than 6.3. If the 90-90-90 target is reached, 73% of all those living with HIV
will have full viral load suppression. If this is maintained it should
guarantee elimination in 70% of all countries in sub-Saharan Africa and will
reduce R0 to less than 2 in the remaining 12 countries, making elimination easy
to achieve by increasing the availability of other high impact methods of
prevention.
|
[
{
"created": "Fri, 12 Apr 2013 15:48:41 GMT",
"version": "v1"
},
{
"created": "Mon, 14 Jul 2014 15:00:51 GMT",
"version": "v2"
}
] |
2014-07-15
|
[
[
"Williams",
"Brian G.",
""
],
[
"Gouws",
"Eleanor",
""
]
] |
The Joint United Nations Programme on HIV and AIDS (UNAIDS) has set a new 90-90-90 global target for the coverage of anti-retroviral therapy (ART) to be reached by 2020. This would mean that 90% of all people infected with HIV know their status, 90% of them are on ART and 90% of them will have full viral load suppression. Here we first estimate the case reproduction number, R0, for countries in sub-Saharan Africa and for India using data on the rate at which the prevalence of HIV increased at the start of the epidemic and the life expectancy of people living with HIV who are not on ART. R0 determines the magnitude of the control problem, that is to say, the extent to which transmission must be reduced to eliminate HIV. We show that in sub-Saharan Africa the median value of R0 is 4.6 and in all but five countries R0 is less than 6.3. If the 90-90-90 target is reached, 73% of all those living with HIV will have full viral load suppression. If this is maintained it should guarantee elimination in 70% of all countries in sub-Saharan Africa and will reduce R0 to less than 2 in the remaining 12 countries, making elimination easy to achieve by increasing the availability of other high impact methods of prevention.
|
q-bio/0604002
|
Martin Huber
|
Martin Tobias Huber and Hans Albert Braun
|
Conductance versus current noise in a neuronal model for noisy
subthreshold oscillations and related spike generation
|
accepted for publication in Biosystems; 10 pages, 2 figures
| null | null | null |
q-bio.NC q-bio.CB
| null |
Biological systems are notoriously noisy. Noise, therefore, also plays an
important role in many models of neural impulse generation. Noise is not only
introduced for more realistic simulations but also to account for cooperative
effects between noisy and nonlinear dynamics. Often, this is achieved by a
simple noise term in the membrane equation (current noise). However, there are
ongoing discussions whether such current noise is justified or whether rather
conductance noise should be introduced because it is closer to the natural
origin of noise. Therefore, we have compared the effects of current and
conductance noise in a neuronal model for subthreshold oscillations and action
potential generation. We did not see any significant differences in the model
behavior with respect to voltage traces, tuning curves of interspike-intervals,
interval distributions or frequency responses when the noise strength is
adjusted. These findings indicate that simple current noise can give reasonable
results in neuronal simulations with regard to physiological relevant noise
effects.
|
[
{
"created": "Mon, 3 Apr 2006 13:22:07 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Huber",
"Martin Tobias",
""
],
[
"Braun",
"Hans Albert",
""
]
] |
Biological systems are notoriously noisy. Noise, therefore, also plays an important role in many models of neural impulse generation. Noise is not only introduced for more realistic simulations but also to account for cooperative effects between noisy and nonlinear dynamics. Often, this is achieved by a simple noise term in the membrane equation (current noise). However, there are ongoing discussions whether such current noise is justified or whether rather conductance noise should be introduced because it is closer to the natural origin of noise. Therefore, we have compared the effects of current and conductance noise in a neuronal model for subthreshold oscillations and action potential generation. We did not see any significant differences in the model behavior with respect to voltage traces, tuning curves of interspike-intervals, interval distributions or frequency responses when the noise strength is adjusted. These findings indicate that simple current noise can give reasonable results in neuronal simulations with regard to physiological relevant noise effects.
|
2405.06663
|
Eunji Ko
|
Eunji Ko, Seul Lee, Minseon Kim, Dongki Kim
|
Protein Representation Learning by Capturing Protein
Sequence-Structure-Function Relationship
|
ICLR 2024 MLGenX Workshop (Spotlight)
| null | null | null |
q-bio.BM cs.AI cs.LG
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
The goal of protein representation learning is to extract knowledge from
protein databases that can be applied to various protein-related downstream
tasks. Although protein sequence, structure, and function are the three key
modalities for a comprehensive understanding of proteins, existing methods for
protein representation learning have utilized only one or two of these
modalities due to the difficulty of capturing the asymmetric interrelationships
between them. To account for this asymmetry, we introduce our novel asymmetric
multi-modal masked autoencoder (AMMA). AMMA adopts (1) a unified multi-modal
encoder to integrate all three modalities into a unified representation space
and (2) asymmetric decoders to ensure that sequence latent features reflect
structural and functional information. The experiments demonstrate that the
proposed AMMA is highly effective in learning protein representations that
exhibit well-aligned inter-modal relationships, which in turn makes it
effective for various downstream protein-related tasks.
|
[
{
"created": "Mon, 29 Apr 2024 05:42:29 GMT",
"version": "v1"
}
] |
2024-05-14
|
[
[
"Ko",
"Eunji",
""
],
[
"Lee",
"Seul",
""
],
[
"Kim",
"Minseon",
""
],
[
"Kim",
"Dongki",
""
]
] |
The goal of protein representation learning is to extract knowledge from protein databases that can be applied to various protein-related downstream tasks. Although protein sequence, structure, and function are the three key modalities for a comprehensive understanding of proteins, existing methods for protein representation learning have utilized only one or two of these modalities due to the difficulty of capturing the asymmetric interrelationships between them. To account for this asymmetry, we introduce our novel asymmetric multi-modal masked autoencoder (AMMA). AMMA adopts (1) a unified multi-modal encoder to integrate all three modalities into a unified representation space and (2) asymmetric decoders to ensure that sequence latent features reflect structural and functional information. The experiments demonstrate that the proposed AMMA is highly effective in learning protein representations that exhibit well-aligned inter-modal relationships, which in turn makes it effective for various downstream protein-related tasks.
|
1307.5565
|
Giovanni Bussi
|
Trang N. Do, Paolo Carloni, Gabriele Varani, and Giovanni Bussi
|
RNA/peptide binding driven by electrostatics -- Insight from
bi-directional pulling simulations
|
Reprinted (adapted) with permission from J. Chem. Theory Comput.,
2013, 9 (3) 1720 (2013). Copyright (2013) American Chemical Society
|
J. Chem. Theory Comput. 9, 1720 (2013)
|
10.1021/ct3009914
| null |
q-bio.BM cond-mat.soft physics.bio-ph physics.chem-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
RNA/protein interactions play crucial roles in controlling gene expression.
They are becoming important targets for pharmaceutical applications. Due to RNA
flexibility and to the strength of electrostatic interactions, standard docking
methods are insufficient. We here present a computational method which allows
studying the binding of RNA molecules and charged peptides with atomistic,
explicit-solvent molecular dynamics. In our method, a suitable estimate of the
electrostatic interaction is used as an order parameter (collective variable)
which is then accelerated using bi-directional pulling simulations. Since the
electrostatic interaction is only used to enhance the sampling, the
approximations used to compute it do not affect the final accuracy. The method
is employed to characterize the binding of TAR RNA from HIV-1 and a small
cyclic peptide. Our simulation protocol allows blindly predicting the binding
pocket and pose as well as the binding affinity. The method is general and
could be applied to study other electrostatics-driven binding events.
|
[
{
"created": "Sun, 21 Jul 2013 20:12:24 GMT",
"version": "v1"
}
] |
2013-07-23
|
[
[
"Do",
"Trang N.",
""
],
[
"Carloni",
"Paolo",
""
],
[
"Varani",
"Gabriele",
""
],
[
"Bussi",
"Giovanni",
""
]
] |
RNA/protein interactions play crucial roles in controlling gene expression. They are becoming important targets for pharmaceutical applications. Due to RNA flexibility and to the strength of electrostatic interactions, standard docking methods are insufficient. We here present a computational method which allows studying the binding of RNA molecules and charged peptides with atomistic, explicit-solvent molecular dynamics. In our method, a suitable estimate of the electrostatic interaction is used as an order parameter (collective variable) which is then accelerated using bi-directional pulling simulations. Since the electrostatic interaction is only used to enhance the sampling, the approximations used to compute it do not affect the final accuracy. The method is employed to characterize the binding of TAR RNA from HIV-1 and a small cyclic peptide. Our simulation protocol allows blindly predicting the binding pocket and pose as well as the binding affinity. The method is general and could be applied to study other electrostatics-driven binding events.
|
2102.09124
|
Dietmar Plenz Dr
|
Dietmar Plenz, Tiago L. Ribeiro, Stephanie R. Miller, Patrick A.
Kells, Ali Vakili, Elliott L. Capek (Section on Critical Brain Dynamics,
National Institute of Mental Health, National Institutes of Health, USA)
|
Self-Organized Criticality in the Brain
|
40 pages, 14 figures
| null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Self-organized criticality (SOC) refers to the ability of complex systems to
evolve towards a 2nd-order phase transition at which interactions between
system components lead to scale-invariant events beneficial for system
performance. For the last two decades, considerable experimental evidence
accumulated that the mammalian cortex with its diversity in cell types and
connections might exhibit SOC. Here we review experimental findings of
isolated, layered cortex preparations to self-organize towards four dynamical
motifs identified in the cortex in vivo: up-states, oscillations, neuronal
avalanches, and coherence potentials. During up-states, the synchronization
observed for nested theta/gamma-oscillations embeds scale-invariant neuronal
avalanches that exhibit robust power law scaling in size with a slope of -3/2
and a critical branching parameter of 1. This dynamical coordination, tracked
in the local field potential (nLFP) and pyramidal neuron activity using
2-photon imaging, emerges autonomously in superficial layers of organotypic
cortex cultures and acute cortex slices, is homeostatically regulated, displays
separation of time scales, and reveals unique size vs. quiet time dependencies.
A threshold operation identifies coherence potentials; avalanches that in
addition maintain the precise time course of propagated synchrony. Avalanches
emerge under conditions of external driving. Control parameters are established
by the balance of excitation and inhibition (E/I) and the neuromodulator
dopamine. This rich dynamical repertoire is not observed in dissociated cortex
cultures, which lack cortical layers and exhibit dynamics similar to a
1st-order phase transition. The precise interactions between up-states, nested
oscillations, avalanches, and coherence potentials in superficial cortical
layers provide compelling evidence for SOC in the brain.
|
[
{
"created": "Thu, 18 Feb 2021 02:53:23 GMT",
"version": "v1"
},
{
"created": "Sat, 15 May 2021 13:37:14 GMT",
"version": "v2"
}
] |
2021-05-18
|
[
[
"Plenz",
"Dietmar",
"",
"Section on Critical Brain Dynamics,\n National Institute of Mental Health, National Institutes of Health, USA"
],
[
"Ribeiro",
"Tiago L.",
"",
"Section on Critical Brain Dynamics,\n National Institute of Mental Health, National Institutes of Health, USA"
],
[
"Miller",
"Stephanie R.",
"",
"Section on Critical Brain Dynamics,\n National Institute of Mental Health, National Institutes of Health, USA"
],
[
"Kells",
"Patrick A.",
"",
"Section on Critical Brain Dynamics,\n National Institute of Mental Health, National Institutes of Health, USA"
],
[
"Vakili",
"Ali",
"",
"Section on Critical Brain Dynamics,\n National Institute of Mental Health, National Institutes of Health, USA"
],
[
"Capek",
"Elliott L.",
"",
"Section on Critical Brain Dynamics,\n National Institute of Mental Health, National Institutes of Health, USA"
]
] |
Self-organized criticality (SOC) refers to the ability of complex systems to evolve towards a 2nd-order phase transition at which interactions between system components lead to scale-invariant events beneficial for system performance. For the last two decades, considerable experimental evidence accumulated that the mammalian cortex with its diversity in cell types and connections might exhibit SOC. Here we review experimental findings of isolated, layered cortex preparations to self-organize towards four dynamical motifs identified in the cortex in vivo: up-states, oscillations, neuronal avalanches, and coherence potentials. During up-states, the synchronization observed for nested theta/gamma-oscillations embeds scale-invariant neuronal avalanches that exhibit robust power law scaling in size with a slope of -3/2 and a critical branching parameter of 1. This dynamical coordination, tracked in the local field potential (nLFP) and pyramidal neuron activity using 2-photon imaging, emerges autonomously in superficial layers of organotypic cortex cultures and acute cortex slices, is homeostatically regulated, displays separation of time scales, and reveals unique size vs. quiet time dependencies. A threshold operation identifies coherence potentials; avalanches that in addition maintain the precise time course of propagated synchrony. Avalanches emerge under conditions of external driving. Control parameters are established by the balance of excitation and inhibition (E/I) and the neuromodulator dopamine. This rich dynamical repertoire is not observed in dissociated cortex cultures, which lack cortical layers and exhibit dynamics similar to a 1st-order phase transition. The precise interactions between up-states, nested oscillations, avalanches, and coherence potentials in superficial cortical layers provide compelling evidence for SOC in the brain.
|
2407.16013
|
Murat Okatan
|
Murat Okatan
|
A statistical significance test for spatio-temporal receptive field
estimates obtained using spike-triggered averaging of binary pseudo-random
sequences
|
This is a replacement of the article "Okatan, M. A statistical
significance test for spatio-temporal receptive field estimates obtained
using spike-triggered averaging of binary pseudo-random sequences. SIViP 17,
3759-3766 (2023). https://doi.org/10.1007/s11760-023-02603-1". The current
manuscript corrects an error in the lower right panel of Fig. 2 of the
original article
|
SIViP 17, 3759-3766 (2023)
|
10.1007/s11760-023-02603-1
| null |
q-bio.QM q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Spatio-temporal receptive fields (STRF) of visual neurons are often estimated
using spike-triggered averaging of binary pseudo-random stimulus sequences. The
spike train of a visual neuron is recorded simultaneously with the stimulus
presentation. The neuron's STRF is estimated by averaging the stimulus frames
that coincide with spikes at fixed latencies. Although this is a widely used
technique, an analytical method for determining the statistical significance of
the estimated value of the STRF pixels seems to be lacking. Such a significance
test would be useful for identifying the significant features of the STRF and
investigating their relationship with experimental variables. Here, the
distribution of the estimated STRF pixel values is derived for given spike
trains, under the null hypothesis that spike occurrences and stimulus values
are statistically independent. This distribution is then used for computing
amplitude thresholds to determine the STRF pixels where the null hypothesis can
be rejected at a desired two-tailed significance level. It is also proposed
that the size of the receptive field may be inferred from the significant
pixels. The application of the proposed method is illustrated on spike trains
collected from individual mouse retinal ganglion cells.
|
[
{
"created": "Mon, 22 Jul 2024 19:42:42 GMT",
"version": "v1"
}
] |
2024-07-24
|
[
[
"Okatan",
"Murat",
""
]
] |
Spatio-temporal receptive fields (STRF) of visual neurons are often estimated using spike-triggered averaging of binary pseudo-random stimulus sequences. The spike train of a visual neuron is recorded simultaneously with the stimulus presentation. The neuron's STRF is estimated by averaging the stimulus frames that coincide with spikes at fixed latencies. Although this is a widely used technique, an analytical method for determining the statistical significance of the estimated value of the STRF pixels seems to be lacking. Such a significance test would be useful for identifying the significant features of the STRF and investigating their relationship with experimental variables. Here, the distribution of the estimated STRF pixel values is derived for given spike trains, under the null hypothesis that spike occurrences and stimulus values are statistically independent. This distribution is then used for computing amplitude thresholds to determine the STRF pixels where the null hypothesis can be rejected at a desired two-tailed significance level. It is also proposed that the size of the receptive field may be inferred from the significant pixels. The application of the proposed method is illustrated on spike trains collected from individual mouse retinal ganglion cells.
|
1511.03150
|
Mazza
|
Micha\"el Dougoud, Christian Mazza and Laura Vinckenbosch
|
Ultrasensitivity and sharp threshold theorems for multisite systems
| null | null | null | null |
q-bio.SC math.PR
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study the ultrasensitivity of multisite binding processes where ligand
molecules can bind to several binding sites, considering more particularly
recent models involving complex chemical reactions in phosphorylation systems
such as allosteric phosphorylation processes, or substrate-catalyst chain
reactions and nucleosome mediated cooperativity. New statistics based formulas
for the Hill coefficient and the effective Hill coefficient are provided and
necessary conditions for a system to be ultrasensitive are exhibited. We then
assume that the binding process is described by a density dependent birth and
death process. We provide precise large deviation results for the steady state
distribution of the process, and show that switch-like ultrasensitive responses
are strongly related to the multi-stability of the associated dynamical system.
Ultrasensitivity occurs if and only if the entropy of the dynamical system has
more than one global minimum for some critical ligand concentration. In this
case, the Hill coefficient is proportional to the number of binding sites, and
the systems is highly ultrasensitive. We also discuss the interpretation of an
extension $I_q$ of the effective Hill coefficient $I_{0.9}$ for which we
recommend the computation of a broad range of values of $q$ instead of just the
standard one corresponding to the 10% to 90% variation in the dose-response. It
is shown that this single choice can sometimes mislead the conclusion by not
detecting ultrasensitivity. This new approach allows a better understanding of
multisite ultrasensitive systems and provides new tools for the design of such
systems.
|
[
{
"created": "Tue, 10 Nov 2015 15:44:25 GMT",
"version": "v1"
},
{
"created": "Wed, 11 Nov 2015 14:44:29 GMT",
"version": "v2"
},
{
"created": "Fri, 29 Apr 2016 13:29:58 GMT",
"version": "v3"
}
] |
2016-05-02
|
[
[
"Dougoud",
"Michaël",
""
],
[
"Mazza",
"Christian",
""
],
[
"Vinckenbosch",
"Laura",
""
]
] |
We study the ultrasensitivity of multisite binding processes where ligand molecules can bind to several binding sites, considering more particularly recent models involving complex chemical reactions in phosphorylation systems such as allosteric phosphorylation processes, or substrate-catalyst chain reactions and nucleosome mediated cooperativity. New statistics based formulas for the Hill coefficient and the effective Hill coefficient are provided and necessary conditions for a system to be ultrasensitive are exhibited. We then assume that the binding process is described by a density dependent birth and death process. We provide precise large deviation results for the steady state distribution of the process, and show that switch-like ultrasensitive responses are strongly related to the multi-stability of the associated dynamical system. Ultrasensitivity occurs if and only if the entropy of the dynamical system has more than one global minimum for some critical ligand concentration. In this case, the Hill coefficient is proportional to the number of binding sites, and the systems is highly ultrasensitive. We also discuss the interpretation of an extension $I_q$ of the effective Hill coefficient $I_{0.9}$ for which we recommend the computation of a broad range of values of $q$ instead of just the standard one corresponding to the 10% to 90% variation in the dose-response. It is shown that this single choice can sometimes mislead the conclusion by not detecting ultrasensitivity. This new approach allows a better understanding of multisite ultrasensitive systems and provides new tools for the design of such systems.
|
1503.00669
|
Cengiz Pehlevan
|
Cengiz Pehlevan, Tao Hu, Dmitri B. Chklovskii
|
A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A
Derivation from Multidimensional Scaling of Streaming Data
|
Accepted for publication in Neural Computation
| null |
10.1162/NECO_a_00745
| null |
q-bio.NC cs.NE stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Neural network models of early sensory processing typically reduce the
dimensionality of streaming input data. Such networks learn the principal
subspace, in the sense of principal component analysis (PCA), by adjusting
synaptic weights according to activity-dependent learning rules. When derived
from a principled cost function these rules are nonlocal and hence biologically
implausible. At the same time, biologically plausible local rules have been
postulated rather than derived from a principled cost function. Here, to bridge
this gap, we derive a biologically plausible network for subspace learning on
streaming data by minimizing a principled cost function. In a departure from
previous work, where cost was quantified by the representation, or
reconstruction, error, we adopt a multidimensional scaling (MDS) cost function
for streaming data. The resulting algorithm relies only on biologically
plausible Hebbian and anti-Hebbian local learning rules. In a stochastic
setting, synaptic weights converge to a stationary state which projects the
input data onto the principal subspace. If the data are generated by a
nonstationary distribution, the network can track the principal subspace. Thus,
our result makes a step towards an algorithmic theory of neural computation.
|
[
{
"created": "Mon, 2 Mar 2015 19:39:33 GMT",
"version": "v1"
}
] |
2015-05-18
|
[
[
"Pehlevan",
"Cengiz",
""
],
[
"Hu",
"Tao",
""
],
[
"Chklovskii",
"Dmitri B.",
""
]
] |
Neural network models of early sensory processing typically reduce the dimensionality of streaming input data. Such networks learn the principal subspace, in the sense of principal component analysis (PCA), by adjusting synaptic weights according to activity-dependent learning rules. When derived from a principled cost function these rules are nonlocal and hence biologically implausible. At the same time, biologically plausible local rules have been postulated rather than derived from a principled cost function. Here, to bridge this gap, we derive a biologically plausible network for subspace learning on streaming data by minimizing a principled cost function. In a departure from previous work, where cost was quantified by the representation, or reconstruction, error, we adopt a multidimensional scaling (MDS) cost function for streaming data. The resulting algorithm relies only on biologically plausible Hebbian and anti-Hebbian local learning rules. In a stochastic setting, synaptic weights converge to a stationary state which projects the input data onto the principal subspace. If the data are generated by a nonstationary distribution, the network can track the principal subspace. Thus, our result makes a step towards an algorithmic theory of neural computation.
|
2104.01554
|
Hoang Ngan Nguyen
|
Ngan Nguyen, Ciril Bohak, Dominik Engel, Peter Mindek, Ond\v{r}ej
Strnad, Peter Wonka, Sai Li, Timo Ropinski, Ivan Viola
|
Finding Nano-\"Otzi: Semi-Supervised Volume Visualization for
Cryo-Electron Tomography
| null |
IEEE Transactions on Visualization and Computer Graphics, 2022
|
10.1109/TVCG.2022.3186146
| null |
q-bio.QM
|
http://creativecommons.org/licenses/by-sa/4.0/
|
Cryo-Electron Tomography (cryo-ET) is a new 3D imaging technique with
unprecedented potential for resolving submicron structural detail. Existing
volume visualization methods, however, cannot cope with its very low
signal-to-noise ratio. In order to design more powerful transfer functions, we
propose to leverage soft segmentation as an explicit component of visualization
for noisy volumes. Our technical realization is based on semi-supervised
learning where we combine the advantages of two segmentation algorithms. A
first weak segmentation algorithm provides good results for propagating sparse
user provided labels to other voxels in the same volume. This weak segmentation
algorithm is used to generate dense pseudo labels. A second powerful
deep-learning based segmentation algorithm can learn from these pseudo labels
to generalize the segmentation to other unseen volumes, a task that the weak
segmentation algorithm fails at completely. The proposed volume visualization
uses the deep-learning based segmentation as a component for segmentation-aware
transfer function design. Appropriate ramp parameters can be suggested
automatically through histogram analysis. Finally, our visualization uses
gradient-free ambient occlusion shading to further suppress visual presence of
noise, and to give structural detail desired prominence. The cryo-ET data
studied throughout our technical experiments is based on the highest-quality
tilted series of intact SARS-CoV-2 virions. Our technique shows the high impact
in target sciences for visual data analysis of very noisy volumes that cannot
be visualized with existing techniques.
|
[
{
"created": "Sun, 4 Apr 2021 07:45:48 GMT",
"version": "v1"
}
] |
2022-06-28
|
[
[
"Nguyen",
"Ngan",
""
],
[
"Bohak",
"Ciril",
""
],
[
"Engel",
"Dominik",
""
],
[
"Mindek",
"Peter",
""
],
[
"Strnad",
"Ondřej",
""
],
[
"Wonka",
"Peter",
""
],
[
"Li",
"Sai",
""
],
[
"Ropinski",
"Timo",
""
],
[
"Viola",
"Ivan",
""
]
] |
Cryo-Electron Tomography (cryo-ET) is a new 3D imaging technique with unprecedented potential for resolving submicron structural detail. Existing volume visualization methods, however, cannot cope with its very low signal-to-noise ratio. In order to design more powerful transfer functions, we propose to leverage soft segmentation as an explicit component of visualization for noisy volumes. Our technical realization is based on semi-supervised learning where we combine the advantages of two segmentation algorithms. A first weak segmentation algorithm provides good results for propagating sparse user provided labels to other voxels in the same volume. This weak segmentation algorithm is used to generate dense pseudo labels. A second powerful deep-learning based segmentation algorithm can learn from these pseudo labels to generalize the segmentation to other unseen volumes, a task that the weak segmentation algorithm fails at completely. The proposed volume visualization uses the deep-learning based segmentation as a component for segmentation-aware transfer function design. Appropriate ramp parameters can be suggested automatically through histogram analysis. Finally, our visualization uses gradient-free ambient occlusion shading to further suppress visual presence of noise, and to give structural detail desired prominence. The cryo-ET data studied throughout our technical experiments is based on the highest-quality tilted series of intact SARS-CoV-2 virions. Our technique shows the high impact in target sciences for visual data analysis of very noisy volumes that cannot be visualized with existing techniques.
|
1905.11800
|
Kelin Xia
|
Kelin Xia, D Vijay Anand, Shikhar Saxena, Yuguang Mu
|
Persistent homology analysis of osmolyte molecular aggregation and their
hydrogen-bonding networks
|
19 pages; 9 figures; 1 table
| null |
10.1039/C9CP03009C
| null |
q-bio.QM q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Two types of osmolytes, i.e., trimethylamin N-oxide (TMAO) and urea,
demonstrate dramatically different properties in a protein folding process.
Even with the great progresses in revealing the potential underlying mechanism
of these two osmolyte systems, many problems still remain unsolved. In this
paper, we propose to use the persistent homology, a newly-invented topological
method, to systematically study the osmolytes molecular aggregation and their
hydrogen-bonding network from a global topological perspective. It has been
found that, for the first time, TMAO and urea show two extremely different
topological behaviors, i.e., extensive network and local cluster. In general,
TMAO forms highly consistent large loop or circle structures in high
concentrations. In contrast, urea is more tightly aggregated locally. Moreover,
the resulting hydrogen-bonding networks also demonstrate distinguishable
features. With the concentration increase, TMAO hydrogen-bonding networks vary
greatly in their total number of loop structures and large-sized loop
structures consistently increase. In contrast, urea hydrogen-bonding networks
remain relatively stable with slight reduce of the total loop number. Moreover,
the persistent entropy (PE) is, for the first time, used in characterization of
the topological information of the aggregation and hydrogen-bonding networks.
The average PE systematically increases with the concentration for both TMAO
and urea, and decreases in their hydrogen-bonding networks. But their PE
variances have totally different behaviors. Finally, topological features of
the hydrogen-bonding networks are found to be highly consistent with those from
the ion aggregation systems, indicating that our topological invariants can
characterize intrinsic features of the "structure making" and "structure
breaking" systems.
|
[
{
"created": "Tue, 28 May 2019 13:26:43 GMT",
"version": "v1"
}
] |
2019-10-23
|
[
[
"Xia",
"Kelin",
""
],
[
"Anand",
"D Vijay",
""
],
[
"Saxena",
"Shikhar",
""
],
[
"Mu",
"Yuguang",
""
]
] |
Two types of osmolytes, i.e., trimethylamin N-oxide (TMAO) and urea, demonstrate dramatically different properties in a protein folding process. Even with the great progresses in revealing the potential underlying mechanism of these two osmolyte systems, many problems still remain unsolved. In this paper, we propose to use the persistent homology, a newly-invented topological method, to systematically study the osmolytes molecular aggregation and their hydrogen-bonding network from a global topological perspective. It has been found that, for the first time, TMAO and urea show two extremely different topological behaviors, i.e., extensive network and local cluster. In general, TMAO forms highly consistent large loop or circle structures in high concentrations. In contrast, urea is more tightly aggregated locally. Moreover, the resulting hydrogen-bonding networks also demonstrate distinguishable features. With the concentration increase, TMAO hydrogen-bonding networks vary greatly in their total number of loop structures and large-sized loop structures consistently increase. In contrast, urea hydrogen-bonding networks remain relatively stable with slight reduce of the total loop number. Moreover, the persistent entropy (PE) is, for the first time, used in characterization of the topological information of the aggregation and hydrogen-bonding networks. The average PE systematically increases with the concentration for both TMAO and urea, and decreases in their hydrogen-bonding networks. But their PE variances have totally different behaviors. Finally, topological features of the hydrogen-bonding networks are found to be highly consistent with those from the ion aggregation systems, indicating that our topological invariants can characterize intrinsic features of the "structure making" and "structure breaking" systems.
|
2408.07977
|
Kimberly Nestor
|
Kimberly Nestor, Javier Rasero, Richard Betzel, Peter J. Gianaros,
Timothy Verstynen
|
Cortical network reconfiguration aligns with shifts of basal ganglia and
cerebellar influence
| null | null | null | null |
q-bio.NC cs.SI
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Mammalian functional architecture flexibly adapts, transitioning from
integration where information is distributed across the cortex, to segregation
where information is focal in densely connected communities of brain regions.
This flexibility in cortical brain networks is hypothesized to be driven by
control signals originating from subcortical pathways, with the basal ganglia
shifting the cortex towards integrated processing states and the cerebellum
towards segregated states. In a sample of healthy human participants (N=242),
we used fMRI to measure temporal variation in global brain networks while
participants performed two tasks with similar cognitive demands (Stroop and
Multi-Source Inference Task (MSIT)). Using the modularity index, we determined
cortical networks shifted from integration (low modularity) at rest to high
modularity during easier i.e. congruent (segregation). Increased task
difficulty (incongruent) resulted in lower modularity in comparison to the
easier counterpart indicating more integration of the cortical network.
Influence of basal ganglia and cerebellum was measured using eigenvector
centrality. Results correlated with decreases and increases in cortical
modularity respectively, with only the basal ganglia influence preceding
cortical integration. Our results support the theory the basal ganglia shifts
cortical networks to integrated states due to environmental demand. Cerebellar
influence correlates with shifts to segregated cortical states, though may not
play a causal role.
|
[
{
"created": "Thu, 15 Aug 2024 06:43:52 GMT",
"version": "v1"
}
] |
2024-08-16
|
[
[
"Nestor",
"Kimberly",
""
],
[
"Rasero",
"Javier",
""
],
[
"Betzel",
"Richard",
""
],
[
"Gianaros",
"Peter J.",
""
],
[
"Verstynen",
"Timothy",
""
]
] |
Mammalian functional architecture flexibly adapts, transitioning from integration where information is distributed across the cortex, to segregation where information is focal in densely connected communities of brain regions. This flexibility in cortical brain networks is hypothesized to be driven by control signals originating from subcortical pathways, with the basal ganglia shifting the cortex towards integrated processing states and the cerebellum towards segregated states. In a sample of healthy human participants (N=242), we used fMRI to measure temporal variation in global brain networks while participants performed two tasks with similar cognitive demands (Stroop and Multi-Source Inference Task (MSIT)). Using the modularity index, we determined cortical networks shifted from integration (low modularity) at rest to high modularity during easier i.e. congruent (segregation). Increased task difficulty (incongruent) resulted in lower modularity in comparison to the easier counterpart indicating more integration of the cortical network. Influence of basal ganglia and cerebellum was measured using eigenvector centrality. Results correlated with decreases and increases in cortical modularity respectively, with only the basal ganglia influence preceding cortical integration. Our results support the theory the basal ganglia shifts cortical networks to integrated states due to environmental demand. Cerebellar influence correlates with shifts to segregated cortical states, though may not play a causal role.
|
1604.07667
|
Julien Cors
|
J. Autebert, J. F. Cors, David P. Taylor and G. V. Kaigala
|
Convection-Enhanced Biopatterning with Recirculation of Hydrodynamically
Confined Nanoliter Volumes of Reagents
| null | null |
10.1021/acs.analchem.5b04649
| null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We present a new methodology for efficient and high-quality patterning of
biological reagents for surface-based biological assays. The method relies on
hydrodynamically confined nanoliter volumes of reagents to interact with the
substrate at the micrometer-length scale. We study the interplay between
diffusion, advection, and surface chemistry and present the design of a
noncontact scanning microfluidic device to efficiently present reagents on
surfaces. By leveraging convective flows, recirculation, and mixing of a
processing liquid, this device overcomes limitations of existing biopatterning
approaches, such as passive diffusion of analytes, uncontrolled wetting, and
drying artifacts. We demonstrate the deposition of analytes, showing a 2- to
5-fold increase in deposition rate together with a 10-fold reduction in analyte
consumption while ensuring less than 6% variation in pattern homogeneity on a
standard biological substrate. In addition, we demonstrate the recirculation of
a processing liquid using a microfluidic probe (MFP) in the context of a
surface assay for (i) probing 12 independent areas with a single microliter of
processing liquid and (ii) processing a 2 mm2 surface to create 170 antibody
spots of 50 x 100 {\mu}m2 area using 1.6 {\mu}L of liquid. We observe high
pattern quality, conservative usage of reagents, micrometer precision of
localization and convection-enhanced fast deposition. Such a device and method
may facilitate quantitative biological assays and spur the development of the
next generation of protein microarrays.
|
[
{
"created": "Tue, 26 Apr 2016 13:18:22 GMT",
"version": "v1"
}
] |
2016-04-27
|
[
[
"Autebert",
"J.",
""
],
[
"Cors",
"J. F.",
""
],
[
"Taylor",
"David P.",
""
],
[
"Kaigala",
"G. V.",
""
]
] |
We present a new methodology for efficient and high-quality patterning of biological reagents for surface-based biological assays. The method relies on hydrodynamically confined nanoliter volumes of reagents to interact with the substrate at the micrometer-length scale. We study the interplay between diffusion, advection, and surface chemistry and present the design of a noncontact scanning microfluidic device to efficiently present reagents on surfaces. By leveraging convective flows, recirculation, and mixing of a processing liquid, this device overcomes limitations of existing biopatterning approaches, such as passive diffusion of analytes, uncontrolled wetting, and drying artifacts. We demonstrate the deposition of analytes, showing a 2- to 5-fold increase in deposition rate together with a 10-fold reduction in analyte consumption while ensuring less than 6% variation in pattern homogeneity on a standard biological substrate. In addition, we demonstrate the recirculation of a processing liquid using a microfluidic probe (MFP) in the context of a surface assay for (i) probing 12 independent areas with a single microliter of processing liquid and (ii) processing a 2 mm2 surface to create 170 antibody spots of 50 x 100 {\mu}m2 area using 1.6 {\mu}L of liquid. We observe high pattern quality, conservative usage of reagents, micrometer precision of localization and convection-enhanced fast deposition. Such a device and method may facilitate quantitative biological assays and spur the development of the next generation of protein microarrays.
|
2406.14516
|
Hermano Velten
|
Hermano Velten, Carlos Felipe Pinheiro and Alcides Castro e Silva
|
Extended error threshold mechanism in {\it quasispecies} theory via
population dynamics
|
5 pages, 1 figure
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
We investigate Eigen's model for the evolution of the genetic code of
microorganisms using a novel method based on population dynamics analysis. This
model, for a given number of offspring, determines long-term survival as a
function of the "genetic" information length and copy error probability. There
exists a maximum threshold for the quantity of information that can be
consistently preserved through the process of evolution within a population of
perfectly replicating sequences, meaning no errors are allowed. With our
formula, we expand upon the traditional error threshold formula of Eigen's
theory and introduce a new expression for general cases where the
self-reproduction process allows up to any integer number of copying errors per
digit per replication step.
|
[
{
"created": "Thu, 20 Jun 2024 17:26:08 GMT",
"version": "v1"
}
] |
2024-06-21
|
[
[
"Velten",
"Hermano",
""
],
[
"Pinheiro",
"Carlos Felipe",
""
],
[
"Silva",
"Alcides Castro e",
""
]
] |
We investigate Eigen's model for the evolution of the genetic code of microorganisms using a novel method based on population dynamics analysis. This model, for a given number of offspring, determines long-term survival as a function of the "genetic" information length and copy error probability. There exists a maximum threshold for the quantity of information that can be consistently preserved through the process of evolution within a population of perfectly replicating sequences, meaning no errors are allowed. With our formula, we expand upon the traditional error threshold formula of Eigen's theory and introduce a new expression for general cases where the self-reproduction process allows up to any integer number of copying errors per digit per replication step.
|
1011.1212
|
Jose Vilar
|
J. M. G. Vilar and L. Saiz
|
CplexA: a Mathematica package to study macromolecular-assembly control
of gene expression
|
28 pages. Includes Mathematica, Matlab, and Python implementation
tutorials. Software can be downloaded at http://cplexa.sourceforge.net/
| null |
10.1093/bioinformatics/btq328
| null |
q-bio.QM cond-mat.stat-mech cs.CE physics.bio-ph q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Summary: Macromolecular assembly vertebrates essential cellular processes,
such as gene regulation and signal transduction. A major challenge for
conventional computational methods to study these processes is tackling the
exponential increase of the number of configurational states with the number of
components. CplexA is a Mathematica package that uses functional programming to
efficiently compute probabilities and average properties over such
exponentially large number of states from the energetics of the interactions.
The package is particularly suited to study gene expression at complex
promoters controlled by multiple, local and distal, DNA binding sites for
transcription factors. Availability: CplexA is freely available together with
documentation at http://sourceforge.net/projects/cplexa/.
|
[
{
"created": "Thu, 4 Nov 2010 16:59:09 GMT",
"version": "v1"
},
{
"created": "Thu, 13 Dec 2012 16:31:45 GMT",
"version": "v2"
},
{
"created": "Sun, 6 Jan 2013 14:23:03 GMT",
"version": "v3"
}
] |
2013-01-08
|
[
[
"Vilar",
"J. M. G.",
""
],
[
"Saiz",
"L.",
""
]
] |
Summary: Macromolecular assembly vertebrates essential cellular processes, such as gene regulation and signal transduction. A major challenge for conventional computational methods to study these processes is tackling the exponential increase of the number of configurational states with the number of components. CplexA is a Mathematica package that uses functional programming to efficiently compute probabilities and average properties over such exponentially large number of states from the energetics of the interactions. The package is particularly suited to study gene expression at complex promoters controlled by multiple, local and distal, DNA binding sites for transcription factors. Availability: CplexA is freely available together with documentation at http://sourceforge.net/projects/cplexa/.
|
q-bio/0407001
|
Laxmidhar Behera Dr.
|
Laxmidhar Behera, Indrani Kar and Avshalom Elitzur
|
Quantum Brain: A Recurrent Quantum Neural Network Model to Describe Eye
Tracking of Moving Targets
|
7 pages, 7 figures submitted to Physical Review Letters
| null |
10.1007/s10702-005-7125-6
| null |
q-bio.NC q-bio.OT
| null |
A theoretical quantum brain model is proposed using a nonlinear Schroedinger
wave equation. The model proposes that there exists a quantum process that
mediates the collective response of a neural lattice (classical brain). The
model is used to explain eye movements when tracking moving targets. Using a
Recurrent Quantum Neural Network(RQNN) while simulating the quantum brain
model, two very interesting phenomena are observed. First, as eye sensor data
is processed in a classical brain, a wave packet is triggered in the quantum
brain. This wave packet moves like a particle. Second, when the eye tracks a
fixed target, this wave packet moves not in a continuous but rather in a
discrete mode. This result reminds one of the saccadic movements of the eye
consisting of 'jumps' and 'rests'. However, such a saccadic movement is
intertwined with smooth pursuit movements when the eye has to track a dynamic
trajectory. In a sense, this is the first theoretical model explaining the
experimental observation reported concerning eye movements in a static scene
situation. The resulting prediction is found to be very precise and efficient
in comparison to classical objective modeling schemes such as the Kalman
filter.
|
[
{
"created": "Fri, 2 Jul 2004 05:11:33 GMT",
"version": "v1"
}
] |
2009-11-10
|
[
[
"Behera",
"Laxmidhar",
""
],
[
"Kar",
"Indrani",
""
],
[
"Elitzur",
"Avshalom",
""
]
] |
A theoretical quantum brain model is proposed using a nonlinear Schroedinger wave equation. The model proposes that there exists a quantum process that mediates the collective response of a neural lattice (classical brain). The model is used to explain eye movements when tracking moving targets. Using a Recurrent Quantum Neural Network(RQNN) while simulating the quantum brain model, two very interesting phenomena are observed. First, as eye sensor data is processed in a classical brain, a wave packet is triggered in the quantum brain. This wave packet moves like a particle. Second, when the eye tracks a fixed target, this wave packet moves not in a continuous but rather in a discrete mode. This result reminds one of the saccadic movements of the eye consisting of 'jumps' and 'rests'. However, such a saccadic movement is intertwined with smooth pursuit movements when the eye has to track a dynamic trajectory. In a sense, this is the first theoretical model explaining the experimental observation reported concerning eye movements in a static scene situation. The resulting prediction is found to be very precise and efficient in comparison to classical objective modeling schemes such as the Kalman filter.
|
1909.02947
|
Carina Curto
|
Carina Curto, Jesse Geneson, Katherine Morrison
|
Stable fixed points of combinatorial threshold-linear networks
|
30 pages, 6 figures. Minor revisions, added references. To appear in
Advances in Applied Mathematics
| null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Combinatorial threshold-linear networks (CTLNs) are a special class of
recurrent neural networks whose dynamics are tightly controlled by an
underlying directed graph. Recurrent networks have long been used as models for
associative memory and pattern completion, with stable fixed points playing the
role of stored memory patterns in the network. In prior work, we showed that
target-free cliques of the graph correspond to stable fixed points of the
dynamics, and we conjectured that these are the only stable fixed points
possible. In this paper, we prove that the conjecture holds in a variety of
special cases, including for networks with very strong inhibition and graphs of
size $n \leq 4$. We also provide further evidence for the conjecture by showing
that sparse graphs and graphs that are nearly cliques can never support stable
fixed points. Finally, we translate some results from extremal combinatorics to
obtain an upper bound on the number of stable fixed points of CTLNs in cases
where the conjecture holds.
|
[
{
"created": "Tue, 27 Aug 2019 06:36:01 GMT",
"version": "v1"
},
{
"created": "Mon, 15 Aug 2022 02:08:10 GMT",
"version": "v2"
},
{
"created": "Sun, 19 Nov 2023 02:00:19 GMT",
"version": "v3"
}
] |
2023-11-21
|
[
[
"Curto",
"Carina",
""
],
[
"Geneson",
"Jesse",
""
],
[
"Morrison",
"Katherine",
""
]
] |
Combinatorial threshold-linear networks (CTLNs) are a special class of recurrent neural networks whose dynamics are tightly controlled by an underlying directed graph. Recurrent networks have long been used as models for associative memory and pattern completion, with stable fixed points playing the role of stored memory patterns in the network. In prior work, we showed that target-free cliques of the graph correspond to stable fixed points of the dynamics, and we conjectured that these are the only stable fixed points possible. In this paper, we prove that the conjecture holds in a variety of special cases, including for networks with very strong inhibition and graphs of size $n \leq 4$. We also provide further evidence for the conjecture by showing that sparse graphs and graphs that are nearly cliques can never support stable fixed points. Finally, we translate some results from extremal combinatorics to obtain an upper bound on the number of stable fixed points of CTLNs in cases where the conjecture holds.
|
2009.03187
|
Keith Dillon
|
Keith Dillon
|
The Resolution Matrix for Visualizing Functional Network Connectivity
| null | null | null | null |
q-bio.NC cs.SI
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The resolution matrix is a mathematical tool for analyzing inverse problems
such as computational imaging systems. When treating network connectivity
estimation as an inverse problem, the resolution matrix describes the degree to
which network nodes and edges can be resolved. This is useful both for
quantifying robustness of the network estimate, as well as identifying
correlated activity. In this report we analyze the resolution matrix for
functional MRI data from the Human Connectome project. We find that common
metrics of the resolution metric can be used to identify networked activity,
though with a new twist on the relationship between default mode network and
the frontoparietal attention network.
|
[
{
"created": "Fri, 4 Sep 2020 13:10:19 GMT",
"version": "v1"
}
] |
2020-09-08
|
[
[
"Dillon",
"Keith",
""
]
] |
The resolution matrix is a mathematical tool for analyzing inverse problems such as computational imaging systems. When treating network connectivity estimation as an inverse problem, the resolution matrix describes the degree to which network nodes and edges can be resolved. This is useful both for quantifying robustness of the network estimate, as well as identifying correlated activity. In this report we analyze the resolution matrix for functional MRI data from the Human Connectome project. We find that common metrics of the resolution metric can be used to identify networked activity, though with a new twist on the relationship between default mode network and the frontoparietal attention network.
|
2304.13796
|
Mason A. Porter
|
Elisa C. Baek, Ryan Hyon, Karina L\'opez, Mason A. Porter, and Carolyn
Parkinson
|
Perceived community alignment increases information sharing
|
44 pages, including main text + supplementary information
| null | null | null |
q-bio.NC cs.SI physics.soc-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Information sharing is a ubiquitous and consequential behavior that has been
proposed to play a critical role in cultivating and maintaining a sense of
shared reality. Across three studies, we tested this theory by investigating
whether or not people are especially likely to share information that they
believe will be interpreted similarly by others in their social circles. Using
neuroimaging while members of the same community viewed brief film clips, we
found that more similar neural responding of participants was associated with a
greater likelihood to share content. We then tested this relationship using
behavioral studies and found (1) that people were particularly likely to share
content about which they believed others in their social circles would share
their viewpoints and (2) that this relationship is causal. In concert, our
findings support the idea that people are driven to share information to create
and reinforce shared understanding, which is critical to social connection.
|
[
{
"created": "Wed, 26 Apr 2023 19:28:49 GMT",
"version": "v1"
}
] |
2023-05-01
|
[
[
"Baek",
"Elisa C.",
""
],
[
"Hyon",
"Ryan",
""
],
[
"López",
"Karina",
""
],
[
"Porter",
"Mason A.",
""
],
[
"Parkinson",
"Carolyn",
""
]
] |
Information sharing is a ubiquitous and consequential behavior that has been proposed to play a critical role in cultivating and maintaining a sense of shared reality. Across three studies, we tested this theory by investigating whether or not people are especially likely to share information that they believe will be interpreted similarly by others in their social circles. Using neuroimaging while members of the same community viewed brief film clips, we found that more similar neural responding of participants was associated with a greater likelihood to share content. We then tested this relationship using behavioral studies and found (1) that people were particularly likely to share content about which they believed others in their social circles would share their viewpoints and (2) that this relationship is causal. In concert, our findings support the idea that people are driven to share information to create and reinforce shared understanding, which is critical to social connection.
|
1803.03475
|
Anna Doizy
|
Anna Doizy, Edmund Barter, Jane Memmott, Karen Varnham, Thilo Gross
|
Impact of cyber-invasive species on a large ecological network
|
10 pages, 2 figures, 1 table
| null |
10.1038/s41598-018-31423-4
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
As impacts of introduced species cascade through trophic levels, they can
cause indirect and counter-intuitive effects. To investigate the impact of
invasive species at the network scale, we use a generalized food web model,
capable of propagating changes through networks with a series of ecologically
realistic criteria. Using data from a small British offshore island, we
quantify the impacts of four virtual invasive species (an insectivore, a
herbivore, a carnivore and an omnivore whose diet is based on a rat) and
explore which clusters of species react in similar ways. We find that the
predictions for the impacts of invasive species are ecologically plausible,
even for large networks robust predictions for the impacts of invasive species
can be obtained. Species in the same taxonomic group are similarly impacted by
a virtual invasive species. However, interesting differences within a given
taxonomic group can occur. The results suggest that some native species may be
at risk from a wider range of invasives than previously believed. The
implications of these results for ecologists and land managers are discussed.
|
[
{
"created": "Fri, 9 Mar 2018 11:33:05 GMT",
"version": "v1"
},
{
"created": "Mon, 6 Aug 2018 09:57:33 GMT",
"version": "v2"
}
] |
2019-07-23
|
[
[
"Doizy",
"Anna",
""
],
[
"Barter",
"Edmund",
""
],
[
"Memmott",
"Jane",
""
],
[
"Varnham",
"Karen",
""
],
[
"Gross",
"Thilo",
""
]
] |
As impacts of introduced species cascade through trophic levels, they can cause indirect and counter-intuitive effects. To investigate the impact of invasive species at the network scale, we use a generalized food web model, capable of propagating changes through networks with a series of ecologically realistic criteria. Using data from a small British offshore island, we quantify the impacts of four virtual invasive species (an insectivore, a herbivore, a carnivore and an omnivore whose diet is based on a rat) and explore which clusters of species react in similar ways. We find that the predictions for the impacts of invasive species are ecologically plausible, even for large networks robust predictions for the impacts of invasive species can be obtained. Species in the same taxonomic group are similarly impacted by a virtual invasive species. However, interesting differences within a given taxonomic group can occur. The results suggest that some native species may be at risk from a wider range of invasives than previously believed. The implications of these results for ecologists and land managers are discussed.
|
1307.4137
|
Michael DeGiorgio
|
Michael DeGiorgio, Kirk E. Lohmueller, Rasmus Nielsen
|
A model-based approach for identifying signatures of balancing selection
in genetic data
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
While much effort has focused on detecting positive and negative directional
selection in the human genome, relatively little work has been devoted to
balancing selection. This lack of attention is likely due to the paucity of
sophisticated methods for identifying sites under balancing selection. Here we
develop two composite likelihood ratio tests for detecting balancing selection.
Using simulations, we show that these methods outperform competing methods
under a variety of assumptions and demographic models. We apply the new methods
to whole-genome human data, and find a number of previously-identified loci
with strong evidence of balancing selection, including several HLA genes.
Additionally, we find evidence for many novel candidates, the strongest of
which is FANK1, an imprinted gene that suppresses apoptosis, is expressed
during meiosis in males, and displays marginal signs of segregation distortion.
We hypothesize that balancing selection acts on this locus to stabilize the
segregation distortion and negative fitness effects of the distorter allele.
Thus, our methods are able to reproduce many previously-hypothesized signals of
balancing selection, as well as discover novel interesting candidates.
|
[
{
"created": "Tue, 16 Jul 2013 00:55:29 GMT",
"version": "v1"
}
] |
2013-07-17
|
[
[
"DeGiorgio",
"Michael",
""
],
[
"Lohmueller",
"Kirk E.",
""
],
[
"Nielsen",
"Rasmus",
""
]
] |
While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.
|
1003.1895
|
Dietrich Stauffer
|
D. Stauffer and S. Cebrat
|
Review of haplotype complementarity under mutational pressure
|
13 pages including 8 figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
No abstract; review only
|
[
{
"created": "Tue, 9 Mar 2010 15:10:07 GMT",
"version": "v1"
}
] |
2010-03-10
|
[
[
"Stauffer",
"D.",
""
],
[
"Cebrat",
"S.",
""
]
] |
No abstract; review only
|
2212.05184
|
Mehrdad Zandigohar
|
Mehrdad Zandigohar and Yang Dai
|
Information retrieval in single cell chromatin analysis using TF-IDF
transformation methods
|
6 pages, 4 figures, 3 tables. Accepted to the 2022 IEEE International
Conference on Bioinformatics and Biomedicine (BIBM)
| null | null | null |
q-bio.GN cs.IR cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Single-cell sequencing assay for transposase-accessible chromatin
(scATAC-seq) assesses genome-wide chromatin accessibility in thousands of cells
to reveal regulatory landscapes in high resolutions. However, the analysis
presents challenges due to the high dimensionality and sparsity of the data.
Several methods have been developed, including transformation techniques of
term-frequency inverse-document frequency (TF-IDF), dimension reduction methods
such as singular value decomposition (SVD), factor analysis, and autoencoders.
Yet, a comprehensive study on the mentioned methods has not been fully
performed. It is not clear what is the best practice when analyzing scATAC-seq
data. We compared several scenarios for transformation and dimension reduction
as well as the SVD-based feature analysis to investigate potential enhancements
in scATAC-seq information retrieval. Additionally, we investigate if
autoencoders benefit from the TF-IDF transformation. Our results reveal that
the TF-IDF transformation generally leads to improved clustering and
biologically relevant feature extraction.
|
[
{
"created": "Sat, 10 Dec 2022 02:50:01 GMT",
"version": "v1"
}
] |
2022-12-13
|
[
[
"Zandigohar",
"Mehrdad",
""
],
[
"Dai",
"Yang",
""
]
] |
Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) assesses genome-wide chromatin accessibility in thousands of cells to reveal regulatory landscapes in high resolutions. However, the analysis presents challenges due to the high dimensionality and sparsity of the data. Several methods have been developed, including transformation techniques of term-frequency inverse-document frequency (TF-IDF), dimension reduction methods such as singular value decomposition (SVD), factor analysis, and autoencoders. Yet, a comprehensive study on the mentioned methods has not been fully performed. It is not clear what is the best practice when analyzing scATAC-seq data. We compared several scenarios for transformation and dimension reduction as well as the SVD-based feature analysis to investigate potential enhancements in scATAC-seq information retrieval. Additionally, we investigate if autoencoders benefit from the TF-IDF transformation. Our results reveal that the TF-IDF transformation generally leads to improved clustering and biologically relevant feature extraction.
|
1110.1413
|
Yuriy Mileyko
|
Yuriy Mileyko, Herbert Edelsbrunner, Charles A. Price, Joshua S. Weitz
|
Hierarchical ordering of reticular networks
|
9 pages, 5 figures, During preparation of this manuscript the authors
became aware of a related work by Katifori and Magnasco, concurrently
submitted for publication
| null |
10.1371/journal.pone.0036715
| null |
q-bio.QM cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The structure of hierarchical networks in biological and physical systems has
long been characterized using the Horton-Strahler ordering scheme. The scheme
assigns an integer order to each edge in the network based on the topology of
branching such that the order increases from distal parts of the network (e.g.,
mountain streams or capillaries) to the "root" of the network (e.g., the river
outlet or the aorta). However, Horton-Strahler ordering cannot be applied to
networks with loops because they they create a contradiction in the edge
ordering in terms of which edge precedes another in the hierarchy. Here, we
present a generalization of the Horton-Strahler order to weighted planar
reticular networks, where weights are assumed to correlate with the importance
of network edges, e.g., weights estimated from edge widths may correlate to
flow capacity. Our method assigns hierarchical levels not only to edges of the
network, but also to its loops, and classifies the edges into reticular edges,
which are responsible for loop formation, and tree edges. In addition, we
perform a detailed and rigorous theoretical analysis of the sensitivity of the
hierarchical levels to weight perturbations. We discuss applications of this
generalized Horton-Strahler ordering to the study of leaf venation and other
biological networks.
|
[
{
"created": "Thu, 6 Oct 2011 23:27:01 GMT",
"version": "v1"
}
] |
2015-05-30
|
[
[
"Mileyko",
"Yuriy",
""
],
[
"Edelsbrunner",
"Herbert",
""
],
[
"Price",
"Charles A.",
""
],
[
"Weitz",
"Joshua S.",
""
]
] |
The structure of hierarchical networks in biological and physical systems has long been characterized using the Horton-Strahler ordering scheme. The scheme assigns an integer order to each edge in the network based on the topology of branching such that the order increases from distal parts of the network (e.g., mountain streams or capillaries) to the "root" of the network (e.g., the river outlet or the aorta). However, Horton-Strahler ordering cannot be applied to networks with loops because they they create a contradiction in the edge ordering in terms of which edge precedes another in the hierarchy. Here, we present a generalization of the Horton-Strahler order to weighted planar reticular networks, where weights are assumed to correlate with the importance of network edges, e.g., weights estimated from edge widths may correlate to flow capacity. Our method assigns hierarchical levels not only to edges of the network, but also to its loops, and classifies the edges into reticular edges, which are responsible for loop formation, and tree edges. In addition, we perform a detailed and rigorous theoretical analysis of the sensitivity of the hierarchical levels to weight perturbations. We discuss applications of this generalized Horton-Strahler ordering to the study of leaf venation and other biological networks.
|
q-bio/0309033
|
Alexander Volkovskii
|
M. I. Rabinovich, R. Huerta, A. Volkovskii, Henry D. I. Abarbanel, and
G. Laurent
|
Sensory Coding with Dynamically Competitive Networks
|
19 pages, 16 figures. Originally submitted to the neuro-sys archive
which was never publicly announced (was 9905002)
| null | null | null |
q-bio.NC
| null |
Studies of insect olfactory processing indicate that odors are represented by
rich spatio-temporal patterns of neural activity. These patterns are very
difficult to predict a priori, yet they are stimulus specific and reliable upon
repeated stimulation with the same input. We formulate here a theoretical
framework in which we can interpret these experimental results. We propose a
paradigm of ``dynamic competition'' in which inputs (odors) are represented by
internally competing neural assemblies. Each pattern is the result of dynamical
motion within the network and does not involve a ``winner'' among competing
possibilities. The model produces spatio-temporal patterns with strong
resemblance to those observed experimentally and possesses many of the general
features one desires for pattern classifiers: large information capacity,
reliability, specific responses to specific inputs, and reduced sensitivity to
initial conditions or influence of noise. This form of neural processing may
thus describe the organizational principles of neural information processing in
sensory systems and go well beyond the observations on insect olfactory
processing which motivated its development.
|
[
{
"created": "Fri, 21 May 1999 23:21:02 GMT",
"version": "v1"
},
{
"created": "Mon, 24 May 1999 01:18:27 GMT",
"version": "v2"
}
] |
2007-05-23
|
[
[
"Rabinovich",
"M. I.",
""
],
[
"Huerta",
"R.",
""
],
[
"Volkovskii",
"A.",
""
],
[
"Abarbanel",
"Henry D. I.",
""
],
[
"Laurent",
"G.",
""
]
] |
Studies of insect olfactory processing indicate that odors are represented by rich spatio-temporal patterns of neural activity. These patterns are very difficult to predict a priori, yet they are stimulus specific and reliable upon repeated stimulation with the same input. We formulate here a theoretical framework in which we can interpret these experimental results. We propose a paradigm of ``dynamic competition'' in which inputs (odors) are represented by internally competing neural assemblies. Each pattern is the result of dynamical motion within the network and does not involve a ``winner'' among competing possibilities. The model produces spatio-temporal patterns with strong resemblance to those observed experimentally and possesses many of the general features one desires for pattern classifiers: large information capacity, reliability, specific responses to specific inputs, and reduced sensitivity to initial conditions or influence of noise. This form of neural processing may thus describe the organizational principles of neural information processing in sensory systems and go well beyond the observations on insect olfactory processing which motivated its development.
|
1204.1324
|
Marc Emanuel
|
Marc Emanuel, Giovanni Lanzani, Helmut Schiessel
|
Multi-plectoneme phase of double-stranded DNA under torsion
|
4 pages, 6 figures, submitted, 2 typo's corrected, one reference
added
| null | null | null |
q-bio.BM cond-mat.soft
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We use the worm-like chain model to study supercoiling of DNA under tension
and torque. The model reproduces experimental data for a much broader range of
forces, salt concentrations and contour lengths than previous approaches. Our
theory shows, for the first time, how the behavior of the system is controlled
by a multi-plectoneme phase in a wide range of parameters. This phase does not
only affect turn-extension curves but also leads to a non-constant torque in
the plectonemic phase. Shortcomings from previous models and inconsistencies
between experimental data are resolved in our theory without the need of
adjustable parameters.
|
[
{
"created": "Thu, 5 Apr 2012 19:42:17 GMT",
"version": "v1"
},
{
"created": "Mon, 9 Apr 2012 09:57:28 GMT",
"version": "v2"
}
] |
2012-04-10
|
[
[
"Emanuel",
"Marc",
""
],
[
"Lanzani",
"Giovanni",
""
],
[
"Schiessel",
"Helmut",
""
]
] |
We use the worm-like chain model to study supercoiling of DNA under tension and torque. The model reproduces experimental data for a much broader range of forces, salt concentrations and contour lengths than previous approaches. Our theory shows, for the first time, how the behavior of the system is controlled by a multi-plectoneme phase in a wide range of parameters. This phase does not only affect turn-extension curves but also leads to a non-constant torque in the plectonemic phase. Shortcomings from previous models and inconsistencies between experimental data are resolved in our theory without the need of adjustable parameters.
|
2402.06748
|
Peter Mikhael
|
Peter G. Mikhael, Itamar Chinn, Regina Barzilay
|
CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes
| null | null | null | null |
q-bio.QM
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Computational screening of naturally occurring proteins has the potential to
identify efficient catalysts among the hundreds of millions of sequences that
remain uncharacterized. Current experimental methods remain time, cost and
labor intensive, limiting the number of enzymes they can reasonably screen. In
this work, we propose a computational framework for in-silico enzyme screening.
Through a contrastive objective, we train CLIPZyme to encode and align
representations of enzyme structures and reaction pairs. With no standard
computational baseline, we compare CLIPZyme to existing EC (enzyme commission)
predictors applied to virtual enzyme screening and show improved performance in
scenarios where limited information on the reaction is available (BEDROC$_{85}$
of 44.69%). Additionally, we evaluate combining EC predictors with CLIPZyme and
show its generalization capacity on both unseen reactions and protein clusters.
|
[
{
"created": "Fri, 9 Feb 2024 19:23:26 GMT",
"version": "v1"
}
] |
2024-02-13
|
[
[
"Mikhael",
"Peter G.",
""
],
[
"Chinn",
"Itamar",
""
],
[
"Barzilay",
"Regina",
""
]
] |
Computational screening of naturally occurring proteins has the potential to identify efficient catalysts among the hundreds of millions of sequences that remain uncharacterized. Current experimental methods remain time, cost and labor intensive, limiting the number of enzymes they can reasonably screen. In this work, we propose a computational framework for in-silico enzyme screening. Through a contrastive objective, we train CLIPZyme to encode and align representations of enzyme structures and reaction pairs. With no standard computational baseline, we compare CLIPZyme to existing EC (enzyme commission) predictors applied to virtual enzyme screening and show improved performance in scenarios where limited information on the reaction is available (BEDROC$_{85}$ of 44.69%). Additionally, we evaluate combining EC predictors with CLIPZyme and show its generalization capacity on both unseen reactions and protein clusters.
|
1903.07855
|
Axel Brandenburg
|
Axel Brandenburg
|
The limited roles of autocatalysis and enantiomeric cross inhibition in
achieving homochirality in dilute systems
|
14 pages, 5 figures, 2 tables, Orig. Life Evol. Biosph., in press
|
Orig. Life Evol. Biosph. 49, 49-60 (2019)
|
10.1007/s11084-019-09579-4
|
Nordita-2019-023
|
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
To understand the effects of fluctuations on achieving homochirality, we
employ a Monte-Carlo method where autocatalysis and enantiomeric
cross-inhibition, as well as racemization and deracemization reactions are
included. The results of earlier work either without autocatalysis or without
cross-inhibition are reproduced. Bifurcation diagrams and the dependencies of
the number of reaction steps on parameters are studied. In systems with 30,000
molecules, for example, up to a billion reaction steps may be needed to achieve
homochirality without autocatalysis.
|
[
{
"created": "Tue, 19 Mar 2019 06:28:19 GMT",
"version": "v1"
},
{
"created": "Wed, 5 Jun 2019 11:57:56 GMT",
"version": "v2"
}
] |
2019-08-26
|
[
[
"Brandenburg",
"Axel",
""
]
] |
To understand the effects of fluctuations on achieving homochirality, we employ a Monte-Carlo method where autocatalysis and enantiomeric cross-inhibition, as well as racemization and deracemization reactions are included. The results of earlier work either without autocatalysis or without cross-inhibition are reproduced. Bifurcation diagrams and the dependencies of the number of reaction steps on parameters are studied. In systems with 30,000 molecules, for example, up to a billion reaction steps may be needed to achieve homochirality without autocatalysis.
|
2207.13212
|
Alicia Shin
|
Alicia Shin
|
The History, Current Status, Benefits, and Challenges of 3D Printed
Organs
|
7 pages
| null | null | null |
q-bio.TO
|
http://creativecommons.org/publicdomain/zero/1.0/
|
There is an increase in demand for organs as transplantation is becoming a
common practice to elongate human life. To reach this demand, three-dimensional
bioprinting is developing from prior knowledge of scaffolds, growth factors,
etc. This review paper aims to determine the current status and future
possibilities of three-dimensional bioprinting of organs and evaluate the
benefits and challenges, along with the history of its development. Prior
research has viewed three-dimensional bioprinting as a technology that will
enable safer transplantation without graft rejection and provide demand-based
production. However, it faces challenges such as the need to improve
biocompatibility and biofunctionality, legal and ethical issues, and the need
to improve the technology itself. While the development of three-dimensional
printing organs is not yet completed, we are seeing improvements and expecting
it to be clinically applied soon.
|
[
{
"created": "Tue, 26 Jul 2022 23:21:30 GMT",
"version": "v1"
},
{
"created": "Mon, 12 Sep 2022 02:17:31 GMT",
"version": "v2"
},
{
"created": "Tue, 27 Dec 2022 20:31:43 GMT",
"version": "v3"
}
] |
2022-12-29
|
[
[
"Shin",
"Alicia",
""
]
] |
There is an increase in demand for organs as transplantation is becoming a common practice to elongate human life. To reach this demand, three-dimensional bioprinting is developing from prior knowledge of scaffolds, growth factors, etc. This review paper aims to determine the current status and future possibilities of three-dimensional bioprinting of organs and evaluate the benefits and challenges, along with the history of its development. Prior research has viewed three-dimensional bioprinting as a technology that will enable safer transplantation without graft rejection and provide demand-based production. However, it faces challenges such as the need to improve biocompatibility and biofunctionality, legal and ethical issues, and the need to improve the technology itself. While the development of three-dimensional printing organs is not yet completed, we are seeing improvements and expecting it to be clinically applied soon.
|
1903.02594
|
Pavel Kraikivski
|
Pavel Kraikivski
|
Systems of Oscillators Designed for a Specific Conscious Percept
|
submitted to New Mathematics and Natural Computation journal on July
2017
| null |
10.1142/S1793005720500052
| null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
As put forward by neuroscientists, the mechanisms of consciousness can be
elucidated by revealing correlations between neural dynamics and specific
conscious percepts. Recently, I have elaborated on the mathematical formulation
for a system of processes that are mutually connected to be isomorphic to a
conscious percept of a point in space. Importantly, in such a system, any
process can be derived through all other processes that form its complement, or
interpretation. To generate such a solution, I am proposing a dynamical system
of oscillators coupled in a manner to preserve the properties of a percept.
Specifically, I crafted a dynamical system that retains the mutual
relationships among processes, forming an operational map isomorphic to a
distance matrix that mimics a percept of space-like properties. The study and
results pave a novel way to analyze the dynamics of neural-like (oscillatory)
processes with a purpose of extracting the information relevant to specific
conscious percepts, which will facilitate the search for neural correlates of
consciousness.
|
[
{
"created": "Tue, 5 Mar 2019 15:34:55 GMT",
"version": "v1"
}
] |
2019-09-10
|
[
[
"Kraikivski",
"Pavel",
""
]
] |
As put forward by neuroscientists, the mechanisms of consciousness can be elucidated by revealing correlations between neural dynamics and specific conscious percepts. Recently, I have elaborated on the mathematical formulation for a system of processes that are mutually connected to be isomorphic to a conscious percept of a point in space. Importantly, in such a system, any process can be derived through all other processes that form its complement, or interpretation. To generate such a solution, I am proposing a dynamical system of oscillators coupled in a manner to preserve the properties of a percept. Specifically, I crafted a dynamical system that retains the mutual relationships among processes, forming an operational map isomorphic to a distance matrix that mimics a percept of space-like properties. The study and results pave a novel way to analyze the dynamics of neural-like (oscillatory) processes with a purpose of extracting the information relevant to specific conscious percepts, which will facilitate the search for neural correlates of consciousness.
|
2403.10993
|
Ryota Kobayashi
|
Ryota Kobayashi and Shigeru Shinomoto
|
Inference of Monosynaptic Connections from Parallel Spike Trains: A
Review
|
11 pages, 3 figures
| null | null | null |
q-bio.NC q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This article presents a mini-review about the progress in inferring
monosynaptic connections from spike trains of multiple neurons over the past
twenty years. First, we explain a variety of meanings of ``neuronal
connectivity'' in different research areas of neuroscience, such as structural
connectivity, monosynaptic connectivity, and functional connectivity. Among
these, we focus on the methods used to infer the monosynaptic connectivity from
spike data. We then summarize the inference methods based on two main
approaches, i.e., correlation-based and model-based approaches. Finally, we
describe available source codes for connectivity inference and future
challenges. Although inference will never be perfect, the accuracy of
identifying the monosynaptic connections has improved dramatically in recent
years due to continuous efforts.
|
[
{
"created": "Sat, 16 Mar 2024 18:42:13 GMT",
"version": "v1"
}
] |
2024-03-19
|
[
[
"Kobayashi",
"Ryota",
""
],
[
"Shinomoto",
"Shigeru",
""
]
] |
This article presents a mini-review about the progress in inferring monosynaptic connections from spike trains of multiple neurons over the past twenty years. First, we explain a variety of meanings of ``neuronal connectivity'' in different research areas of neuroscience, such as structural connectivity, monosynaptic connectivity, and functional connectivity. Among these, we focus on the methods used to infer the monosynaptic connectivity from spike data. We then summarize the inference methods based on two main approaches, i.e., correlation-based and model-based approaches. Finally, we describe available source codes for connectivity inference and future challenges. Although inference will never be perfect, the accuracy of identifying the monosynaptic connections has improved dramatically in recent years due to continuous efforts.
|
2401.01489
|
Dmitri Chklovskii
|
Jason Moore, Alexander Genkin, Magnus Tournoy, Joshua Pughe-Sanford,
Rob R. de Ruyter van Steveninck, and Dmitri B. Chklovskii
|
The Neuron as a Direct Data-Driven Controller
| null | null | null | null |
q-bio.NC cs.AI cs.SY eess.SY
|
http://creativecommons.org/licenses/by/4.0/
|
In the quest to model neuronal function amidst gaps in physiological data, a
promising strategy is to develop a normative theory that interprets neuronal
physiology as optimizing a computational objective. This study extends the
current normative models, which primarily optimize prediction, by
conceptualizing neurons as optimal feedback controllers. We posit that neurons,
especially those beyond early sensory areas, act as controllers, steering their
environment towards a specific desired state through their output. This
environment comprises both synaptically interlinked neurons and external motor
sensory feedback loops, enabling neurons to evaluate the effectiveness of their
control via synaptic feedback. Utilizing the novel Direct Data-Driven Control
(DD-DC) framework, we model neurons as biologically feasible controllers which
implicitly identify loop dynamics, infer latent states and optimize control.
Our DD-DC neuron model explains various neurophysiological phenomena: the shift
from potentiation to depression in Spike-Timing-Dependent Plasticity (STDP)
with its asymmetry, the duration and adaptive nature of feedforward and
feedback neuronal filters, the imprecision in spike generation under constant
stimulation, and the characteristic operational variability and noise in the
brain. Our model presents a significant departure from the traditional,
feedforward, instant-response McCulloch-Pitts-Rosenblatt neuron, offering a
novel and biologically-informed fundamental unit for constructing neural
networks.
|
[
{
"created": "Wed, 3 Jan 2024 01:24:10 GMT",
"version": "v1"
}
] |
2024-01-04
|
[
[
"Moore",
"Jason",
""
],
[
"Genkin",
"Alexander",
""
],
[
"Tournoy",
"Magnus",
""
],
[
"Pughe-Sanford",
"Joshua",
""
],
[
"van Steveninck",
"Rob R. de Ruyter",
""
],
[
"Chklovskii",
"Dmitri B.",
""
]
] |
In the quest to model neuronal function amidst gaps in physiological data, a promising strategy is to develop a normative theory that interprets neuronal physiology as optimizing a computational objective. This study extends the current normative models, which primarily optimize prediction, by conceptualizing neurons as optimal feedback controllers. We posit that neurons, especially those beyond early sensory areas, act as controllers, steering their environment towards a specific desired state through their output. This environment comprises both synaptically interlinked neurons and external motor sensory feedback loops, enabling neurons to evaluate the effectiveness of their control via synaptic feedback. Utilizing the novel Direct Data-Driven Control (DD-DC) framework, we model neurons as biologically feasible controllers which implicitly identify loop dynamics, infer latent states and optimize control. Our DD-DC neuron model explains various neurophysiological phenomena: the shift from potentiation to depression in Spike-Timing-Dependent Plasticity (STDP) with its asymmetry, the duration and adaptive nature of feedforward and feedback neuronal filters, the imprecision in spike generation under constant stimulation, and the characteristic operational variability and noise in the brain. Our model presents a significant departure from the traditional, feedforward, instant-response McCulloch-Pitts-Rosenblatt neuron, offering a novel and biologically-informed fundamental unit for constructing neural networks.
|
2309.09900
|
Giulia Garcia Lorenzana
|
Giulia Garcia Lorenzana, Ada Altieri, Giulio Biroli
|
Interactions and migration rescuing ecological diversity
|
13 pages, 10 figures, + 14 pages, 6 figures in Appendix
| null |
10.1103/PRXLife.2.013014
| null |
q-bio.PE cond-mat.dis-nn cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
How diversity is maintained in natural ecosystems is a long-standing question
in Theoretical Ecology. By studying a system that combines ecological dynamics,
heterogeneous interactions and spatial structure, we uncover a new mechanism
for the survival of diversity-rich ecosystems in the presence of demographic
fluctuations. For a single species, one finds a continuous phase transition
between an extinction and a survival state, that falls into the universality
class of Directed Percolation. Here we show that the case of many species with
heterogeneous interactions is different and richer. By merging theory and
simulations, we demonstrate that with sufficiently strong demographic noise,
the system exhibits behavior akin to the single-species case, undergoing a
continuous transition. Conversely, at low demographic noise, we observe unique
features indicative of the ecosystem's complexity. The combined effects of the
heterogeneity in the interaction network and migration enable the community to
thrive, even in situations where demographic noise would lead to the extinction
of isolated species. The emergence of mutualism induces the development of
global bistability, accompanied by sudden tipping points. We present a way to
predict the catastrophic shift from high diversity to extinction by probing
responses to perturbations as an early warning signal.
|
[
{
"created": "Mon, 18 Sep 2023 16:05:03 GMT",
"version": "v1"
},
{
"created": "Mon, 5 Feb 2024 11:25:58 GMT",
"version": "v2"
}
] |
2024-03-21
|
[
[
"Lorenzana",
"Giulia Garcia",
""
],
[
"Altieri",
"Ada",
""
],
[
"Biroli",
"Giulio",
""
]
] |
How diversity is maintained in natural ecosystems is a long-standing question in Theoretical Ecology. By studying a system that combines ecological dynamics, heterogeneous interactions and spatial structure, we uncover a new mechanism for the survival of diversity-rich ecosystems in the presence of demographic fluctuations. For a single species, one finds a continuous phase transition between an extinction and a survival state, that falls into the universality class of Directed Percolation. Here we show that the case of many species with heterogeneous interactions is different and richer. By merging theory and simulations, we demonstrate that with sufficiently strong demographic noise, the system exhibits behavior akin to the single-species case, undergoing a continuous transition. Conversely, at low demographic noise, we observe unique features indicative of the ecosystem's complexity. The combined effects of the heterogeneity in the interaction network and migration enable the community to thrive, even in situations where demographic noise would lead to the extinction of isolated species. The emergence of mutualism induces the development of global bistability, accompanied by sudden tipping points. We present a way to predict the catastrophic shift from high diversity to extinction by probing responses to perturbations as an early warning signal.
|
1911.00072
|
Gurpreet Singh Matharoo
|
Gurpreet S. Matharoo and Javeria A. Hashmi
|
Spontaneous back-pain alters randomness in functional connections in
large scale brain networks: A random matrix perspective
|
18 Pages, 5 Figures
|
Physica A; 2019
|
10.1016/j.physa.2019.123321
| null |
q-bio.NC cond-mat.dis-nn
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We use randomness as a measure to assess the impact of evoked pain on brain
networks. Randomness is defined here as the intrinsic correlations that exist
between different brain regions when the brain is in a task-free state. We use
fMRI data of three brain states in a set of back pain patients monitored over a
period of 6 months. We find that randomness in the task-free state closely
follows the predictions of Gaussian orthogonal ensemble of random matrices.
However, the randomness decreases when the brain is engaged in attending to
painful inputs in patients suffering with early stages of back pain. A
persistence of this pattern is observed in the patients that develop chronic
back pain, while the patients who recover from pain after six months, the
randomness no longer varies with the pain task. The study demonstrates the
effectiveness of random matrix theory in differentiating between resting state
and two distinct task states within the same patient. Further, it demonstrates
that random matrix theory is effective in measuring systematic changes
occurring in functional connectivity and offers new insights on how acute and
chronic pain are processed in the brain at a network level.
|
[
{
"created": "Thu, 31 Oct 2019 19:37:32 GMT",
"version": "v1"
}
] |
2019-11-04
|
[
[
"Matharoo",
"Gurpreet S.",
""
],
[
"Hashmi",
"Javeria A.",
""
]
] |
We use randomness as a measure to assess the impact of evoked pain on brain networks. Randomness is defined here as the intrinsic correlations that exist between different brain regions when the brain is in a task-free state. We use fMRI data of three brain states in a set of back pain patients monitored over a period of 6 months. We find that randomness in the task-free state closely follows the predictions of Gaussian orthogonal ensemble of random matrices. However, the randomness decreases when the brain is engaged in attending to painful inputs in patients suffering with early stages of back pain. A persistence of this pattern is observed in the patients that develop chronic back pain, while the patients who recover from pain after six months, the randomness no longer varies with the pain task. The study demonstrates the effectiveness of random matrix theory in differentiating between resting state and two distinct task states within the same patient. Further, it demonstrates that random matrix theory is effective in measuring systematic changes occurring in functional connectivity and offers new insights on how acute and chronic pain are processed in the brain at a network level.
|
2306.01793
|
Giulia Chiari
|
Giulia Chiari, Giada Fiandaca, Marcello Edoardo Delitala
|
Hypoxia-resistance heterogeneity in tumours: the impact of geometrical
characterization of environmental niches and evolutionary trade-offs. A
mathematical approach
| null | null |
10.1051/mmnp/2023023
| null |
q-bio.PE cs.NA math.AP math.NA physics.med-ph
|
http://creativecommons.org/licenses/by-sa/4.0/
|
In the study of cancer evolution and therapeutic strategies, scientific
evidence shows that a key dynamics lies in the tumor-environment interaction.
In particular, oxygen concentration plays a central role in the determination
of the phenotypic heterogeneity of cancer cell populations, whose qualitative
and geometric characteristics are predominant factors in the occurrence of
relapses and failure of eradication. We propose a mathematical model able to
describe the eco-evolutionary spatial dynamics of tumour cells in their
adaptation to hypoxic microenvironments. As a main novelty with respect to the
existing literature, we combine a phenotypic indicator reflecting the
experimentally-observed metabolic trade-off between the hypoxia-resistance
ability and the proliferative potential with a 2d geometric domain, without the
constraint of radial symmetry. The model is settled in the mathematical
framework of phenotype-structured population dynamics and it is formulated in
terms of systems of coupled non-linear integro-differential equations. The
computational outcomes demonstrate that hypoxia-induced selection results in a
geometric characterization of phenotypic-defined tumour niches that impact on
tumour aggressiveness and invasive ability. Furthermore, results show how the
knowledge of environmental characteristics provides a predictive advantage on
tumour mass development in terms of size, shape, and composition.
|
[
{
"created": "Thu, 1 Jun 2023 09:03:58 GMT",
"version": "v1"
}
] |
2023-07-20
|
[
[
"Chiari",
"Giulia",
""
],
[
"Fiandaca",
"Giada",
""
],
[
"Delitala",
"Marcello Edoardo",
""
]
] |
In the study of cancer evolution and therapeutic strategies, scientific evidence shows that a key dynamics lies in the tumor-environment interaction. In particular, oxygen concentration plays a central role in the determination of the phenotypic heterogeneity of cancer cell populations, whose qualitative and geometric characteristics are predominant factors in the occurrence of relapses and failure of eradication. We propose a mathematical model able to describe the eco-evolutionary spatial dynamics of tumour cells in their adaptation to hypoxic microenvironments. As a main novelty with respect to the existing literature, we combine a phenotypic indicator reflecting the experimentally-observed metabolic trade-off between the hypoxia-resistance ability and the proliferative potential with a 2d geometric domain, without the constraint of radial symmetry. The model is settled in the mathematical framework of phenotype-structured population dynamics and it is formulated in terms of systems of coupled non-linear integro-differential equations. The computational outcomes demonstrate that hypoxia-induced selection results in a geometric characterization of phenotypic-defined tumour niches that impact on tumour aggressiveness and invasive ability. Furthermore, results show how the knowledge of environmental characteristics provides a predictive advantage on tumour mass development in terms of size, shape, and composition.
|
2210.05713
|
Ziyuan Ye
|
Ziyuan Ye, Youzhi Qu, Zhichao Liang, Mo Wang, Quanying Liu
|
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph
Convolutional Network
| null | null | null | null |
q-bio.NC cs.NE eess.SP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Brain decoding, aiming to identify the brain states using neural activity, is
important for cognitive neuroscience and neural engineering. However, existing
machine learning methods for fMRI-based brain decoding either suffer from low
classification performance or poor explainability. Here, we address this issue
by proposing a biologically inspired architecture, Spatial Temporal-pyramid
Graph Convolutional Network (STpGCN), to capture the spatial-temporal graph
representation of functional brain activities. By designing multi-scale
spatial-temporal pathways and bottom-up pathways that mimic the information
process and temporal integration in the brain, STpGCN is capable of explicitly
utilizing the multi-scale temporal dependency of brain activities via graph,
thereby achieving high brain decoding performance. Additionally, we propose a
sensitivity analysis method called BrainNetX to better explain the decoding
results by automatically annotating task-related brain regions from the
brain-network standpoint. We conduct extensive experiments on fMRI data under
23 cognitive tasks from Human Connectome Project (HCP) S1200. The results show
that STpGCN significantly improves brain decoding performance compared to
competing baseline models; BrainNetX successfully annotates task-relevant brain
regions. Post hoc analysis based on these regions further validates that the
hierarchical structure in STpGCN significantly contributes to the
explainability, robustness and generalization of the model. Our methods not
only provide insights into information representation in the brain under
multiple cognitive tasks but also indicate a bright future for fMRI-based brain
decoding.
|
[
{
"created": "Sat, 8 Oct 2022 12:14:33 GMT",
"version": "v1"
}
] |
2022-10-13
|
[
[
"Ye",
"Ziyuan",
""
],
[
"Qu",
"Youzhi",
""
],
[
"Liang",
"Zhichao",
""
],
[
"Wang",
"Mo",
""
],
[
"Liu",
"Quanying",
""
]
] |
Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and neural engineering. However, existing machine learning methods for fMRI-based brain decoding either suffer from low classification performance or poor explainability. Here, we address this issue by proposing a biologically inspired architecture, Spatial Temporal-pyramid Graph Convolutional Network (STpGCN), to capture the spatial-temporal graph representation of functional brain activities. By designing multi-scale spatial-temporal pathways and bottom-up pathways that mimic the information process and temporal integration in the brain, STpGCN is capable of explicitly utilizing the multi-scale temporal dependency of brain activities via graph, thereby achieving high brain decoding performance. Additionally, we propose a sensitivity analysis method called BrainNetX to better explain the decoding results by automatically annotating task-related brain regions from the brain-network standpoint. We conduct extensive experiments on fMRI data under 23 cognitive tasks from Human Connectome Project (HCP) S1200. The results show that STpGCN significantly improves brain decoding performance compared to competing baseline models; BrainNetX successfully annotates task-relevant brain regions. Post hoc analysis based on these regions further validates that the hierarchical structure in STpGCN significantly contributes to the explainability, robustness and generalization of the model. Our methods not only provide insights into information representation in the brain under multiple cognitive tasks but also indicate a bright future for fMRI-based brain decoding.
|
1611.07776
|
David Lukatsky
|
Matan Goldshtein and David B. Lukatsky
|
Specificity-determining DNA triplet code for positioning of human
pre-initiation complex
| null | null |
10.1016/j.bpj.2017.04.023
| null |
q-bio.BM q-bio.GN q-bio.MN q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The notion that transcription factors bind DNA only through specific,
consensus binding sites has been recently questioned. In a pioneering study by
Pugh and Venters no specific consensus motif for the positioning of the human
pre-initiation complex (PIC) has been identified. Here, we reveal that
nonconsensus, statistical, DNA triplet code provides specificity for the
positioning of the human PIC. In particular, we reveal a highly non-random,
statistical pattern of repetitive nucleotide triplets that correlates with the
genome-wide binding preferences of PIC measured by Chip-exo. We analyze the
triplet enrichment and depletion near the transcription start site (TSS) and
identify triplets that have the strongest effect on PIC-DNA nonconsensus
binding. Our results constitute a proof-of-concept for a new design principle
for protein-DNA recognition in the human genome, which can lead to a better
mechanistic understanding of transcriptional regulation.
|
[
{
"created": "Wed, 23 Nov 2016 13:07:49 GMT",
"version": "v1"
}
] |
2017-06-28
|
[
[
"Goldshtein",
"Matan",
""
],
[
"Lukatsky",
"David B.",
""
]
] |
The notion that transcription factors bind DNA only through specific, consensus binding sites has been recently questioned. In a pioneering study by Pugh and Venters no specific consensus motif for the positioning of the human pre-initiation complex (PIC) has been identified. Here, we reveal that nonconsensus, statistical, DNA triplet code provides specificity for the positioning of the human PIC. In particular, we reveal a highly non-random, statistical pattern of repetitive nucleotide triplets that correlates with the genome-wide binding preferences of PIC measured by Chip-exo. We analyze the triplet enrichment and depletion near the transcription start site (TSS) and identify triplets that have the strongest effect on PIC-DNA nonconsensus binding. Our results constitute a proof-of-concept for a new design principle for protein-DNA recognition in the human genome, which can lead to a better mechanistic understanding of transcriptional regulation.
|
2002.09631
|
Alfonso Vivanco Lira
|
A. Vivanco-Lira
|
Novel therapeutic targets in chronic myeloid leukaemia through a
discrete time discrete Markov chain model of BCR-ABL1 interactions
|
32 pages, 1 table, 6 figures
| null | null | null |
q-bio.CB q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Chronic Myeloid Leukaemia (CML) is a blood-derived proliferative disorder,
which is highly associated to a translocation of chromosomes 9 and 22 or the
creation of Philadelphia chromosome Ph(+) cases, inducing the synthesis of a
chimeric fusion protein, namely BCR-ABL1 (Breakpoint Cluster Region-Abelson 1
chimeric protein), which is known for driving the pathophysiology of the
disease, however variants of CML are also recognized as CML Ph(-), these
nonetheless account for a small percentage of the overall CML patients; posing
thus the question whether BCR-ABL1 fusion protein is required for the whole of
the pathophysiology of CML. Hereof, through a stochastic description, a
discrete time discrete Markov chain depicts the various protein-protein
interactions of BCR-ABL1 to better understand signalling pathways and
time-dependent evolution of these pathways, as well as to provide prospective
therapeutic protein targets to improve both the specificity of the treatment
and the life-expectancy of the patients.
|
[
{
"created": "Sat, 22 Feb 2020 05:29:04 GMT",
"version": "v1"
}
] |
2020-02-25
|
[
[
"Vivanco-Lira",
"A.",
""
]
] |
Chronic Myeloid Leukaemia (CML) is a blood-derived proliferative disorder, which is highly associated to a translocation of chromosomes 9 and 22 or the creation of Philadelphia chromosome Ph(+) cases, inducing the synthesis of a chimeric fusion protein, namely BCR-ABL1 (Breakpoint Cluster Region-Abelson 1 chimeric protein), which is known for driving the pathophysiology of the disease, however variants of CML are also recognized as CML Ph(-), these nonetheless account for a small percentage of the overall CML patients; posing thus the question whether BCR-ABL1 fusion protein is required for the whole of the pathophysiology of CML. Hereof, through a stochastic description, a discrete time discrete Markov chain depicts the various protein-protein interactions of BCR-ABL1 to better understand signalling pathways and time-dependent evolution of these pathways, as well as to provide prospective therapeutic protein targets to improve both the specificity of the treatment and the life-expectancy of the patients.
|
2006.08647
|
Andres Escala
|
Andres Escala
|
Universal Relation for Life-span Energy Consumption in Living Organisms:
Insights for the origin of ageing
|
Comments welcome aescala@das.uchile.cl
| null | null | null |
q-bio.OT physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Metabolic energy consumption has long been thought to play a major role in
the aging process ({\it 1}). Across species, a gram of tissue on average
expends about the same amount of energy during life-span ({\it 2}). Energy
restriction has also been shown that increases maximum life-span ({\it 3}) and
retards age-associated changes ({\it 4}). However, there are significant
exceptions to a universal energy consumption during life-span, mainly coming
from the inter-class comparison ({\it 5, 6}). Here we present a unique relation
for life-span energy consumption, valid for $\sim$300 species representing all
classes of living organisms, from unicellular ones to the largest mammals. The
relation has an average scatter of only 0.3 dex, with 95\% ($\rm 2-\sigma$) of
the organisms having departures less than a factor of $\pi$ from the relation,
despite the $\sim$20 orders of magnitude difference in body mass, reducing any
possible inter-class variation in the relation to only a geometrical factor.
This result can be interpreted as supporting evidence for the existence of an
approximately constant total number $\rm N_r \sim 10^8$ of respiration cycles
per lifetime for all organisms, effectively predetermining the extension of
life by the basic energetics of respiration, being an incentive for future
studies that investigate the relation of such constant $\rm N_r$ cycles per
lifetime with the production rates of free radicals and oxidants, which may
give definite constraints on the origin of ageing.
|
[
{
"created": "Mon, 15 Jun 2020 18:00:32 GMT",
"version": "v1"
}
] |
2020-06-17
|
[
[
"Escala",
"Andres",
""
]
] |
Metabolic energy consumption has long been thought to play a major role in the aging process ({\it 1}). Across species, a gram of tissue on average expends about the same amount of energy during life-span ({\it 2}). Energy restriction has also been shown that increases maximum life-span ({\it 3}) and retards age-associated changes ({\it 4}). However, there are significant exceptions to a universal energy consumption during life-span, mainly coming from the inter-class comparison ({\it 5, 6}). Here we present a unique relation for life-span energy consumption, valid for $\sim$300 species representing all classes of living organisms, from unicellular ones to the largest mammals. The relation has an average scatter of only 0.3 dex, with 95\% ($\rm 2-\sigma$) of the organisms having departures less than a factor of $\pi$ from the relation, despite the $\sim$20 orders of magnitude difference in body mass, reducing any possible inter-class variation in the relation to only a geometrical factor. This result can be interpreted as supporting evidence for the existence of an approximately constant total number $\rm N_r \sim 10^8$ of respiration cycles per lifetime for all organisms, effectively predetermining the extension of life by the basic energetics of respiration, being an incentive for future studies that investigate the relation of such constant $\rm N_r$ cycles per lifetime with the production rates of free radicals and oxidants, which may give definite constraints on the origin of ageing.
|
1308.3032
|
Fabio Pichierri
|
Fabio Pichierri
|
Dipole-dipole interactions in protein-protein complexes: a quantum
mechanical study of the ubiquitin-Dsk2 complex
|
8 pages, 2 figures
| null | null | null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Quantum mechanical calculations are performed on the proteins that constitute
the ubiquitin-Dsk2 complex whose atomic structure has been experimentally
determined by NMR spectroscopy (PDB id 1WR1). The results indicate that the
dipole moment vectors of the two proteins are aligned in a head-to-tail
orientation while forming and angle of ~130{\deg}. Hence, attractive
dipole-dipole interactions not only stabilize the protein-protein complex but
they are likely to favor the correct orientation of the proteins during the
formation of the complex.
|
[
{
"created": "Wed, 14 Aug 2013 04:53:31 GMT",
"version": "v1"
}
] |
2013-08-15
|
[
[
"Pichierri",
"Fabio",
""
]
] |
Quantum mechanical calculations are performed on the proteins that constitute the ubiquitin-Dsk2 complex whose atomic structure has been experimentally determined by NMR spectroscopy (PDB id 1WR1). The results indicate that the dipole moment vectors of the two proteins are aligned in a head-to-tail orientation while forming and angle of ~130{\deg}. Hence, attractive dipole-dipole interactions not only stabilize the protein-protein complex but they are likely to favor the correct orientation of the proteins during the formation of the complex.
|
0904.3584
|
Hu Chen
|
Hu Chen, Yanhui Liu, Zhen Zhou, Lin Hu, Zhong-Can Ou-Yang, and Jie Yan
|
Temperature dependence of circular DNA topological states
|
15 pages in preprint format, 4 figures
|
PHYSICAL REVIEW E 79, 041926 (2009)
|
10.1103/PhysRevE.79.041926
| null |
q-bio.BM q-bio.QM
|
http://creativecommons.org/licenses/by-nc-sa/3.0/
|
Circular double stranded DNA has different topological states which are
defined by their linking numbers. Equilibrium distribution of linking numbers
can be obtained by closing a linear DNA into a circle by ligase. Using Monte
Carlo simulation, we predict the temperature dependence of the linking number
distribution of small circular DNAs. Our predictions are based on flexible
defect excitations resulted from local melting or unstacking of DNA base pairs.
We found that the reduced bending rigidity alone can lead to measurable changes
of the variance of linking number distribution of short circular DNAs. If the
defect is accompanied by local unwinding, the effect becomes much more
prominent. The predictions can be easily investigated in experiments, providing
a new method to study the micromechanics of sharply bent DNAs and the thermal
stability of specific DNA sequences. Furthermore, the predictions are directly
applicable to the studies of binding of DNA distorting proteins that can
locally reduce DNA rigidity, form DNA kinks, or introduce local unwinding.
|
[
{
"created": "Thu, 23 Apr 2009 02:34:28 GMT",
"version": "v1"
}
] |
2009-05-04
|
[
[
"Chen",
"Hu",
""
],
[
"Liu",
"Yanhui",
""
],
[
"Zhou",
"Zhen",
""
],
[
"Hu",
"Lin",
""
],
[
"Ou-Yang",
"Zhong-Can",
""
],
[
"Yan",
"Jie",
""
]
] |
Circular double stranded DNA has different topological states which are defined by their linking numbers. Equilibrium distribution of linking numbers can be obtained by closing a linear DNA into a circle by ligase. Using Monte Carlo simulation, we predict the temperature dependence of the linking number distribution of small circular DNAs. Our predictions are based on flexible defect excitations resulted from local melting or unstacking of DNA base pairs. We found that the reduced bending rigidity alone can lead to measurable changes of the variance of linking number distribution of short circular DNAs. If the defect is accompanied by local unwinding, the effect becomes much more prominent. The predictions can be easily investigated in experiments, providing a new method to study the micromechanics of sharply bent DNAs and the thermal stability of specific DNA sequences. Furthermore, the predictions are directly applicable to the studies of binding of DNA distorting proteins that can locally reduce DNA rigidity, form DNA kinks, or introduce local unwinding.
|
2201.00850
|
Michael McCreesh
|
Michael McCreesh and Jorge Cort\'es
|
Selective Inhibition and Recruitment of Linear-Threshold Thalamocortical
Networks
|
13 pages, 5 figures
| null | null | null |
q-bio.NC cs.SY eess.SY
|
http://creativecommons.org/licenses/by/4.0/
|
Neuroscientific evidence shows that for most brain networks all pathways
between cortical regions either pass through the thalamus or a transthalamic
parallel route exists for any direct corticocortical connection. This paper
seeks to formally study the dynamical behavior of the resulting thalamocortical
brain networks with a view to characterizing the inhibitory role played by the
thalamus and its benefits. We employ a linear-threshold mesoscale model for
individual brain subnetworks and study both hierarchical and star-connected
thalamocortical networks. Using tools from singular perturbation theory and
switched systems, we show that selective inhibition and recruitment can be
achieved in such networks through a combination of feedback and feedforward
control. Various simulations throughout the exposition illustrate the benefits
resulting from the presence of the thalamus regarding failsafe mechanisms,
required control magnitude, and network performance.
|
[
{
"created": "Mon, 3 Jan 2022 19:38:10 GMT",
"version": "v1"
},
{
"created": "Fri, 8 Jul 2022 19:57:11 GMT",
"version": "v2"
}
] |
2022-07-12
|
[
[
"McCreesh",
"Michael",
""
],
[
"Cortés",
"Jorge",
""
]
] |
Neuroscientific evidence shows that for most brain networks all pathways between cortical regions either pass through the thalamus or a transthalamic parallel route exists for any direct corticocortical connection. This paper seeks to formally study the dynamical behavior of the resulting thalamocortical brain networks with a view to characterizing the inhibitory role played by the thalamus and its benefits. We employ a linear-threshold mesoscale model for individual brain subnetworks and study both hierarchical and star-connected thalamocortical networks. Using tools from singular perturbation theory and switched systems, we show that selective inhibition and recruitment can be achieved in such networks through a combination of feedback and feedforward control. Various simulations throughout the exposition illustrate the benefits resulting from the presence of the thalamus regarding failsafe mechanisms, required control magnitude, and network performance.
|
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