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3.75k
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1604.06089
|
Richard Mann
|
Richard P. Mann
|
Towards a fully predictive model of flight paths in pigeons navigating
in the familiar area: prediction across differing individuals
|
8 pages, 2 figures, Royal Institute of Navigation Conference on
Animal Navigation 2016
| null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This paper will detail the basis of our previously developed predictive model
for pigeon flight paths based on observations of the specific individual being
predicted. We will then describe how this model can be adapted to predict the
flight of a new, unobserved bird, based on observations of other individuals
from the same release site. We will test the accuracy of these predictions
relative to naive models with no previous flight information and those trained
on the focal bird's own previous flights, and discuss the implications of these
results for the nature of navigational cue use in the familiar area. Finally we
will discuss how visual cues may be explicitly encoded in the model in future
work.
|
[
{
"created": "Wed, 20 Apr 2016 18:58:13 GMT",
"version": "v1"
}
] |
2016-04-22
|
[
[
"Mann",
"Richard P.",
""
]
] |
This paper will detail the basis of our previously developed predictive model for pigeon flight paths based on observations of the specific individual being predicted. We will then describe how this model can be adapted to predict the flight of a new, unobserved bird, based on observations of other individuals from the same release site. We will test the accuracy of these predictions relative to naive models with no previous flight information and those trained on the focal bird's own previous flights, and discuss the implications of these results for the nature of navigational cue use in the familiar area. Finally we will discuss how visual cues may be explicitly encoded in the model in future work.
|
1906.03314
|
Jiawei Zhang
|
Jiawei Zhang
|
Secrets of the Brain: An Introduction to the Brain Anatomical Structure
and Biological Function
|
34 pages, 19 figures
| null | null | null |
q-bio.NC cs.NE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In this paper, we will provide an introduction to the brain structure and
function. Brain is an astonishing living organ inside our heads, weighing about
1.5kg, consisting of billions of tiny cells. The brain enables us to sense the
world around us (to touch, to smell, to see and to hear, etc.), to think and to
respond to the world as well. The main obstacles that prevent us from creating
a machine which can behavior like real-world creatures are due to our limited
knowledge about the brain in both its structure and its function. In this
paper, we will focus introducing the brain anatomical structure and biological
function, as well as its surrounding sensory systems. Many of the materials
used in this paper are from wikipedia and several other neuroscience
introductory articles, which will be properly cited in this article. This is
the first of the three tutorial articles about the brain (the other two are
[26] and [27]). In the follow-up two articles, we will further introduce the
low-level composition basis structures (e.g., neuron, synapse and action
potential) and the high-level cognitive functions (e.g., consciousness,
attention, learning and memory) of the brain, respectively.
|
[
{
"created": "Fri, 31 May 2019 03:07:33 GMT",
"version": "v1"
}
] |
2019-06-11
|
[
[
"Zhang",
"Jiawei",
""
]
] |
In this paper, we will provide an introduction to the brain structure and function. Brain is an astonishing living organ inside our heads, weighing about 1.5kg, consisting of billions of tiny cells. The brain enables us to sense the world around us (to touch, to smell, to see and to hear, etc.), to think and to respond to the world as well. The main obstacles that prevent us from creating a machine which can behavior like real-world creatures are due to our limited knowledge about the brain in both its structure and its function. In this paper, we will focus introducing the brain anatomical structure and biological function, as well as its surrounding sensory systems. Many of the materials used in this paper are from wikipedia and several other neuroscience introductory articles, which will be properly cited in this article. This is the first of the three tutorial articles about the brain (the other two are [26] and [27]). In the follow-up two articles, we will further introduce the low-level composition basis structures (e.g., neuron, synapse and action potential) and the high-level cognitive functions (e.g., consciousness, attention, learning and memory) of the brain, respectively.
|
1702.00329
|
Hon-Cheong So
|
Hon-Cheong So
|
Epigenome-wide association study and integrative analysis with the
transcriptome based on GWAS summary statistics
| null | null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The past decade has seen a rapid growth in omics technologies. Genome-wide
association studies (GWAS) have uncovered susceptibility variants for a variety
of complex traits. However, the functional significance of most discovered
variants are still not fully understood. On the other hand, there is increasing
interest in exploring the role of epigenetic variations such as DNA methylation
in disease pathogenesis. In this work, we present a general framework for
epigenome-wide association study and integrative analysis with the
transcriptome based on GWAS summary statistics and data from methylation and
expression quantitative trait loci (QTL) studies. The framework is based on
Mendelian randomization, which is much less vulnerable to confounding and
reverse causation compared to conventional studies. The framework was applied
to five complex diseases. We first identified loci that are differentially
methylated due to genetic variations, and then developed several approaches for
joint testing with the GWAS-imputed transcriptome. We discovered a number of
novel candidate genes that are not implicated in the original GWAS studies. We
also observed strong evidence (lowest p = 2.01e-184) for differential
expression among the top genes mapped to methylation loci. The framework
proposed here opens a new way of analyzing GWAS summary data and will be useful
for gaining deeper insight into disease mechanisms.
|
[
{
"created": "Wed, 1 Feb 2017 15:59:30 GMT",
"version": "v1"
},
{
"created": "Tue, 21 Feb 2017 07:13:30 GMT",
"version": "v2"
}
] |
2017-02-22
|
[
[
"So",
"Hon-Cheong",
""
]
] |
The past decade has seen a rapid growth in omics technologies. Genome-wide association studies (GWAS) have uncovered susceptibility variants for a variety of complex traits. However, the functional significance of most discovered variants are still not fully understood. On the other hand, there is increasing interest in exploring the role of epigenetic variations such as DNA methylation in disease pathogenesis. In this work, we present a general framework for epigenome-wide association study and integrative analysis with the transcriptome based on GWAS summary statistics and data from methylation and expression quantitative trait loci (QTL) studies. The framework is based on Mendelian randomization, which is much less vulnerable to confounding and reverse causation compared to conventional studies. The framework was applied to five complex diseases. We first identified loci that are differentially methylated due to genetic variations, and then developed several approaches for joint testing with the GWAS-imputed transcriptome. We discovered a number of novel candidate genes that are not implicated in the original GWAS studies. We also observed strong evidence (lowest p = 2.01e-184) for differential expression among the top genes mapped to methylation loci. The framework proposed here opens a new way of analyzing GWAS summary data and will be useful for gaining deeper insight into disease mechanisms.
|
1601.00891
|
Iddo Friedberg
|
Yuxiang Jiang, Tal Ronnen Oron, Wyatt T Clark, Asma R Bankapur, Daniel
D'Andrea, Rosalba Lepore, Christopher S Funk, Indika Kahanda, Karin M
Verspoor, Asa Ben-Hur, Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah
Youngs, Richard Bonneau, Alexandra Lin, Sayed ME Sahraeian, Pier Luigi
Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin
Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai
Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai
Fang, Ben Smithers, Matt Oates, Julian Gough, Petri T\"or\"onen, Patrik
Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico
Cozzetto, Federico Minneci, David T Jones, Samuel Chapman, Dukka B K.C.,
Ishita K Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena
Cibrian-Uhalte, Paul Denny, Rebecca E Foulger, Reija Hieta, Duncan Legge,
Ruth C Lovering, Michele Magrane, Anna N Melidoni, Prudence Mutowo-Meullenet,
Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal,
L\'eon-Charles Tranchevent, Sayoni Das, Natalie L Dawson, David Lee, Jonathan
G Lees, Ian Sillitoe, Prajwal Bhat, Tam\'as Nepusz, Alfonso E Romero,
Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, Jesse Gillis, Adriana E
Sede\~no-Cort\'es, Paul Pavlidis, Shou Feng, Juan M Cejuela, Tatyana
Goldberg, Tobias Hamp, Lothar Richter, Asaf Salamov, Toni Gabaldon, Marina
Marcet-Houben, Fran Supek, Qingtian Gong, Wei Ning, Yuanpeng Zhou, Weidong
Tian, Marco Falda, Paolo Fontana, Enrico Lavezzo, Stefano Toppo, Carlo
Ferrari, Manuel Giollo, Damiano Piovesan, Silvio Tosatto, Angela del Pozo,
Jos\'e M Fern\'andez, Paolo Maietta, Alfonso Valencia, Michael L Tress,
Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino,
Hafeez Ur Rehman, Matteo Re, Marco Mesiti, Giorgio Valentini, Joachim W
Bargsten, Aalt DJ van Dijk, Branislava Gemovic, Sanja Glisic, Vladmir
Perovic, Veljko Veljkovic, Nevena Veljkovic, Danillo C Almeida-e-Silva,
Ricardo ZN Vencio, Malvika Sharan, J\"org Vogel, Lakesh Kansakar, Shanshan
Zhang, Slobodan Vucetic, Zheng Wang, Michael JE Sternberg, Mark N Wass,
Rachael P Huntley, Maria J Martin, Claire O'Donovan, Peter N Robinson, Yves
Moreau, Anna Tramontano, Patricia C Babbitt, Steven E Brenner, Michal Linial,
Christine A Orengo, Burkhard Rost, Casey S Greene, Sean D Mooney, Iddo
Friedberg, Predrag Radivojac
|
An expanded evaluation of protein function prediction methods shows an
improvement in accuracy
|
Submitted to Genome Biology
| null |
10.1186/s13059-016-1037-6
| null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Background: The increasing volume and variety of genotypic and phenotypic
data is a major defining characteristic of modern biomedical sciences. At the
same time, the limitations in technology for generating data and the inherently
stochastic nature of biomolecular events have led to the discrepancy between
the volume of data and the amount of knowledge gleaned from it. A major
bottleneck in our ability to understand the molecular underpinnings of life is
the assignment of function to biological macromolecules, especially proteins.
While molecular experiments provide the most reliable annotation of proteins,
their relatively low throughput and restricted purview have led to an
increasing role for computational function prediction. However, accurately
assessing methods for protein function prediction and tracking progress in the
field remain challenging. Methodology: We have conducted the second Critical
Assessment of Functional Annotation (CAFA), a timed challenge to assess
computational methods that automatically assign protein function. One hundred
twenty-six methods from 56 research groups were evaluated for their ability to
predict biological functions using the Gene Ontology and gene-disease
associations using the Human Phenotype Ontology on a set of 3,681 proteins from
18 species. CAFA2 featured significantly expanded analysis compared with CAFA1,
with regards to data set size, variety, and assessment metrics. To review
progress in the field, the analysis also compared the best methods
participating in CAFA1 to those of CAFA2. Conclusions: The top performing
methods in CAFA2 outperformed the best methods from CAFA1, demonstrating that
computational function prediction is improving. This increased accuracy can be
attributed to the combined effect of the growing number of experimental
annotations and improved methods for function prediction.
|
[
{
"created": "Sun, 3 Jan 2016 00:55:23 GMT",
"version": "v1"
}
] |
2016-12-07
|
[
[
"Jiang",
"Yuxiang",
""
],
[
"Oron",
"Tal Ronnen",
""
],
[
"Clark",
"Wyatt T",
""
],
[
"Bankapur",
"Asma R",
""
],
[
"D'Andrea",
"Daniel",
""
],
[
"Lepore",
"Rosalba",
""
],
[
"Funk",
"Christopher S",
""
],
[
"Kahanda",
"Indika",
""
],
[
"Verspoor",
"Karin M",
""
],
[
"Ben-Hur",
"Asa",
""
],
[
"Koo",
"Emily",
""
],
[
"Penfold-Brown",
"Duncan",
""
],
[
"Shasha",
"Dennis",
""
],
[
"Youngs",
"Noah",
""
],
[
"Bonneau",
"Richard",
""
],
[
"Lin",
"Alexandra",
""
],
[
"Sahraeian",
"Sayed ME",
""
],
[
"Martelli",
"Pier Luigi",
""
],
[
"Profiti",
"Giuseppe",
""
],
[
"Casadio",
"Rita",
""
],
[
"Cao",
"Renzhi",
""
],
[
"Zhong",
"Zhaolong",
""
],
[
"Cheng",
"Jianlin",
""
],
[
"Altenhoff",
"Adrian",
""
],
[
"Skunca",
"Nives",
""
],
[
"Dessimoz",
"Christophe",
""
],
[
"Dogan",
"Tunca",
""
],
[
"Hakala",
"Kai",
""
],
[
"Kaewphan",
"Suwisa",
""
],
[
"Mehryary",
"Farrokh",
""
],
[
"Salakoski",
"Tapio",
""
],
[
"Ginter",
"Filip",
""
],
[
"Fang",
"Hai",
""
],
[
"Smithers",
"Ben",
""
],
[
"Oates",
"Matt",
""
],
[
"Gough",
"Julian",
""
],
[
"Törönen",
"Petri",
""
],
[
"Koskinen",
"Patrik",
""
],
[
"Holm",
"Liisa",
""
],
[
"Chen",
"Ching-Tai",
""
],
[
"Hsu",
"Wen-Lian",
""
],
[
"Bryson",
"Kevin",
""
],
[
"Cozzetto",
"Domenico",
""
],
[
"Minneci",
"Federico",
""
],
[
"Jones",
"David T",
""
],
[
"Chapman",
"Samuel",
""
],
[
"C.",
"Dukka B K.",
""
],
[
"Khan",
"Ishita K",
""
],
[
"Kihara",
"Daisuke",
""
],
[
"Ofer",
"Dan",
""
],
[
"Rappoport",
"Nadav",
""
],
[
"Stern",
"Amos",
""
],
[
"Cibrian-Uhalte",
"Elena",
""
],
[
"Denny",
"Paul",
""
],
[
"Foulger",
"Rebecca E",
""
],
[
"Hieta",
"Reija",
""
],
[
"Legge",
"Duncan",
""
],
[
"Lovering",
"Ruth C",
""
],
[
"Magrane",
"Michele",
""
],
[
"Melidoni",
"Anna N",
""
],
[
"Mutowo-Meullenet",
"Prudence",
""
],
[
"Pichler",
"Klemens",
""
],
[
"Shypitsyna",
"Aleksandra",
""
],
[
"Li",
"Biao",
""
],
[
"Zakeri",
"Pooya",
""
],
[
"ElShal",
"Sarah",
""
],
[
"Tranchevent",
"Léon-Charles",
""
],
[
"Das",
"Sayoni",
""
],
[
"Dawson",
"Natalie L",
""
],
[
"Lee",
"David",
""
],
[
"Lees",
"Jonathan G",
""
],
[
"Sillitoe",
"Ian",
""
],
[
"Bhat",
"Prajwal",
""
],
[
"Nepusz",
"Tamás",
""
],
[
"Romero",
"Alfonso E",
""
],
[
"Sasidharan",
"Rajkumar",
""
],
[
"Yang",
"Haixuan",
""
],
[
"Paccanaro",
"Alberto",
""
],
[
"Gillis",
"Jesse",
""
],
[
"Sedeño-Cortés",
"Adriana E",
""
],
[
"Pavlidis",
"Paul",
""
],
[
"Feng",
"Shou",
""
],
[
"Cejuela",
"Juan M",
""
],
[
"Goldberg",
"Tatyana",
""
],
[
"Hamp",
"Tobias",
""
],
[
"Richter",
"Lothar",
""
],
[
"Salamov",
"Asaf",
""
],
[
"Gabaldon",
"Toni",
""
],
[
"Marcet-Houben",
"Marina",
""
],
[
"Supek",
"Fran",
""
],
[
"Gong",
"Qingtian",
""
],
[
"Ning",
"Wei",
""
],
[
"Zhou",
"Yuanpeng",
""
],
[
"Tian",
"Weidong",
""
],
[
"Falda",
"Marco",
""
],
[
"Fontana",
"Paolo",
""
],
[
"Lavezzo",
"Enrico",
""
],
[
"Toppo",
"Stefano",
""
],
[
"Ferrari",
"Carlo",
""
],
[
"Giollo",
"Manuel",
""
],
[
"Piovesan",
"Damiano",
""
],
[
"Tosatto",
"Silvio",
""
],
[
"del Pozo",
"Angela",
""
],
[
"Fernández",
"José M",
""
],
[
"Maietta",
"Paolo",
""
],
[
"Valencia",
"Alfonso",
""
],
[
"Tress",
"Michael L",
""
],
[
"Benso",
"Alfredo",
""
],
[
"Di Carlo",
"Stefano",
""
],
[
"Politano",
"Gianfranco",
""
],
[
"Savino",
"Alessandro",
""
],
[
"Rehman",
"Hafeez Ur",
""
],
[
"Re",
"Matteo",
""
],
[
"Mesiti",
"Marco",
""
],
[
"Valentini",
"Giorgio",
""
],
[
"Bargsten",
"Joachim W",
""
],
[
"van Dijk",
"Aalt DJ",
""
],
[
"Gemovic",
"Branislava",
""
],
[
"Glisic",
"Sanja",
""
],
[
"Perovic",
"Vladmir",
""
],
[
"Veljkovic",
"Veljko",
""
],
[
"Veljkovic",
"Nevena",
""
],
[
"Almeida-e-Silva",
"Danillo C",
""
],
[
"Vencio",
"Ricardo ZN",
""
],
[
"Sharan",
"Malvika",
""
],
[
"Vogel",
"Jörg",
""
],
[
"Kansakar",
"Lakesh",
""
],
[
"Zhang",
"Shanshan",
""
],
[
"Vucetic",
"Slobodan",
""
],
[
"Wang",
"Zheng",
""
],
[
"Sternberg",
"Michael JE",
""
],
[
"Wass",
"Mark N",
""
],
[
"Huntley",
"Rachael P",
""
],
[
"Martin",
"Maria J",
""
],
[
"O'Donovan",
"Claire",
""
],
[
"Robinson",
"Peter N",
""
],
[
"Moreau",
"Yves",
""
],
[
"Tramontano",
"Anna",
""
],
[
"Babbitt",
"Patricia C",
""
],
[
"Brenner",
"Steven E",
""
],
[
"Linial",
"Michal",
""
],
[
"Orengo",
"Christine A",
""
],
[
"Rost",
"Burkhard",
""
],
[
"Greene",
"Casey S",
""
],
[
"Mooney",
"Sean D",
""
],
[
"Friedberg",
"Iddo",
""
],
[
"Radivojac",
"Predrag",
""
]
] |
Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations in technology for generating data and the inherently stochastic nature of biomolecular events have led to the discrepancy between the volume of data and the amount of knowledge gleaned from it. A major bottleneck in our ability to understand the molecular underpinnings of life is the assignment of function to biological macromolecules, especially proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, accurately assessing methods for protein function prediction and tracking progress in the field remain challenging. Methodology: We have conducted the second Critical Assessment of Functional Annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. One hundred twenty-six methods from 56 research groups were evaluated for their ability to predict biological functions using the Gene Ontology and gene-disease associations using the Human Phenotype Ontology on a set of 3,681 proteins from 18 species. CAFA2 featured significantly expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2. Conclusions: The top performing methods in CAFA2 outperformed the best methods from CAFA1, demonstrating that computational function prediction is improving. This increased accuracy can be attributed to the combined effect of the growing number of experimental annotations and improved methods for function prediction.
|
2304.08299
|
Bingxin Zhou
|
Bingxin Zhou, Outongyi Lv, Kai Yi, Xinye Xiong, Pan Tan, Liang Hong,
Yu Guang Wang
|
Accurate and Definite Mutational Effect Prediction with Lightweight
Equivariant Graph Neural Networks
| null | null | null | null |
q-bio.QM cs.LG
|
http://creativecommons.org/licenses/by/4.0/
|
Directed evolution as a widely-used engineering strategy faces obstacles in
finding desired mutants from the massive size of candidate modifications. While
deep learning methods learn protein contexts to establish feasible searching
space, many existing models are computationally demanding and fail to predict
how specific mutational tests will affect a protein's sequence or function.
This research introduces a lightweight graph representation learning scheme
that efficiently analyzes the microenvironment of wild-type proteins and
recommends practical higher-order mutations exclusive to the user-specified
protein and function of interest. Our method enables continuous improvement of
the inference model by limited computational resources and a few hundred
mutational training samples, resulting in accurate prediction of variant
effects that exhibit near-perfect correlation with the ground truth across deep
mutational scanning assays of 19 proteins. With its affordability and
applicability to both computer scientists and biochemical laboratories, our
solution offers a wide range of benefits that make it an ideal choice for the
community.
|
[
{
"created": "Thu, 13 Apr 2023 09:51:49 GMT",
"version": "v1"
}
] |
2023-04-18
|
[
[
"Zhou",
"Bingxin",
""
],
[
"Lv",
"Outongyi",
""
],
[
"Yi",
"Kai",
""
],
[
"Xiong",
"Xinye",
""
],
[
"Tan",
"Pan",
""
],
[
"Hong",
"Liang",
""
],
[
"Wang",
"Yu Guang",
""
]
] |
Directed evolution as a widely-used engineering strategy faces obstacles in finding desired mutants from the massive size of candidate modifications. While deep learning methods learn protein contexts to establish feasible searching space, many existing models are computationally demanding and fail to predict how specific mutational tests will affect a protein's sequence or function. This research introduces a lightweight graph representation learning scheme that efficiently analyzes the microenvironment of wild-type proteins and recommends practical higher-order mutations exclusive to the user-specified protein and function of interest. Our method enables continuous improvement of the inference model by limited computational resources and a few hundred mutational training samples, resulting in accurate prediction of variant effects that exhibit near-perfect correlation with the ground truth across deep mutational scanning assays of 19 proteins. With its affordability and applicability to both computer scientists and biochemical laboratories, our solution offers a wide range of benefits that make it an ideal choice for the community.
|
2207.12367
|
Simona Vulpe
|
Cosima Rughinis, Mihai Dima, Simona-Nicoleta Vulpe, Razvan Rughinis,
Sorina Vasile
|
Patterns of protection, infection, and detection: Country-level
effectiveness of COVID 19 vaccination in reducing mortality worldwide
|
43 pages, 4 figures, 3 tables, 2 supplementary materials
| null | null | null |
q-bio.QM
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
We investigated the negative relationship between mortality and COVID-19
vaccination at ecological level, which has been established through clinical
trials and other investigations at the individual level. We conducted an
exploratory, correlational, country-level analysis of open data centralized by
Our World in Data concerning the cumulative COVID-19 mortality for the winter
wave of the pandemic as function of the vaccination rate in October 2021. In
order to disentangle the protective relationship from confounding processes, we
controlled variables that capture country-level social development and level of
testing. We also deployed three segmentation tactics, distinguishing among
countries based on their level of COVID-19 testing, age structure, and types of
vaccines used. Controlling for confounding factors did not highlight a
statistically significant global relationship between vaccination and
cumulative mortality in the total country sample. As suggested by previous
estimates at country level, a strong, significant, negative relationship
between cumulative mortality and vaccination was highlighted through
segmentation analysis for countries positioned at the higher end of the social
development spectrum. The strongest estimate for vaccine effectiveness at
ecological level was obtained for countries that use Western-only vaccines.
This may partly reflect the higher effectiveness of Western vaccines in
comparison with the average of all vaccines in use; it may also derive from the
lower social heterogeneity of countries included in this segment. COVID-19
testing has a significant and positive relationship with cumulative mortality
for all subsamples. This indicates that testing intensity should be controlled
as a potential confounder in future ecological analyses of COVID-19 mortality.
|
[
{
"created": "Fri, 8 Jul 2022 11:41:42 GMT",
"version": "v1"
}
] |
2022-07-26
|
[
[
"Rughinis",
"Cosima",
""
],
[
"Dima",
"Mihai",
""
],
[
"Vulpe",
"Simona-Nicoleta",
""
],
[
"Rughinis",
"Razvan",
""
],
[
"Vasile",
"Sorina",
""
]
] |
We investigated the negative relationship between mortality and COVID-19 vaccination at ecological level, which has been established through clinical trials and other investigations at the individual level. We conducted an exploratory, correlational, country-level analysis of open data centralized by Our World in Data concerning the cumulative COVID-19 mortality for the winter wave of the pandemic as function of the vaccination rate in October 2021. In order to disentangle the protective relationship from confounding processes, we controlled variables that capture country-level social development and level of testing. We also deployed three segmentation tactics, distinguishing among countries based on their level of COVID-19 testing, age structure, and types of vaccines used. Controlling for confounding factors did not highlight a statistically significant global relationship between vaccination and cumulative mortality in the total country sample. As suggested by previous estimates at country level, a strong, significant, negative relationship between cumulative mortality and vaccination was highlighted through segmentation analysis for countries positioned at the higher end of the social development spectrum. The strongest estimate for vaccine effectiveness at ecological level was obtained for countries that use Western-only vaccines. This may partly reflect the higher effectiveness of Western vaccines in comparison with the average of all vaccines in use; it may also derive from the lower social heterogeneity of countries included in this segment. COVID-19 testing has a significant and positive relationship with cumulative mortality for all subsamples. This indicates that testing intensity should be controlled as a potential confounder in future ecological analyses of COVID-19 mortality.
|
2405.05864
|
Alireza Soleimani
|
Alireza Soleimani and Herre Jelger Risselada
|
SMARTINI3: Systematic Parametrization of Realistic Multi-Scale Membrane
Models via Unsupervised Learning and Multi-Objective Evolutionary Algorithms
| null | null | null | null |
q-bio.BM
|
http://creativecommons.org/licenses/by/4.0/
|
In this study, we utilize genetic algorithms to develop a realistic implicit
solvent ultra-coarse-grained (PC) membrane model comprising only three
interaction sites. The key philosophy of the ultra-CG membrane model SMARTINI3
is its compatibility with realistic membrane proteins, for example, modeled
within the Martini coarse-grained (CG) model, as well as with the widely used
GROMACS software for molecular simulations. Our objective is to parameterize
this ultra-CG model to accurately reproduce the experimentally observed
structural and thermodynamic properties of PC membranes in real units,
including properties such as area per lipid, area compressibility, bending
modulus, line tension, phase transition temperature, density profile, and
radial distribution function. In our example, we specifically focus on the
properties of a POPC membrane, although the developed membrane model could be
perceived as a generic model of lipid membranes. To optimize the performance of
the model (the fitness), we conduct a series of evolutionary runs with diverse
random initial population sizes (ranging from 96 to 384). We demonstrate that
the ultra-CG membrane model we developed exhibits authentic lipid membrane
behaviors, encompassing self-assembly into bilayers, vesicle formation,
membrane fusion, and gel phase formation. Moreover, we demonstrate
compatibility with the Martini coarse-grained model by successfully reproducing
the behavior of a transmembrane domain embedded within a lipid bilayer. This
facilitates the simulation of realistic membrane proteins within an ultra-CG
bilayer membrane, enhancing the accuracy and applicability of our model in
biophysical studies.
|
[
{
"created": "Thu, 9 May 2024 15:52:40 GMT",
"version": "v1"
}
] |
2024-05-10
|
[
[
"Soleimani",
"Alireza",
""
],
[
"Risselada",
"Herre Jelger",
""
]
] |
In this study, we utilize genetic algorithms to develop a realistic implicit solvent ultra-coarse-grained (PC) membrane model comprising only three interaction sites. The key philosophy of the ultra-CG membrane model SMARTINI3 is its compatibility with realistic membrane proteins, for example, modeled within the Martini coarse-grained (CG) model, as well as with the widely used GROMACS software for molecular simulations. Our objective is to parameterize this ultra-CG model to accurately reproduce the experimentally observed structural and thermodynamic properties of PC membranes in real units, including properties such as area per lipid, area compressibility, bending modulus, line tension, phase transition temperature, density profile, and radial distribution function. In our example, we specifically focus on the properties of a POPC membrane, although the developed membrane model could be perceived as a generic model of lipid membranes. To optimize the performance of the model (the fitness), we conduct a series of evolutionary runs with diverse random initial population sizes (ranging from 96 to 384). We demonstrate that the ultra-CG membrane model we developed exhibits authentic lipid membrane behaviors, encompassing self-assembly into bilayers, vesicle formation, membrane fusion, and gel phase formation. Moreover, we demonstrate compatibility with the Martini coarse-grained model by successfully reproducing the behavior of a transmembrane domain embedded within a lipid bilayer. This facilitates the simulation of realistic membrane proteins within an ultra-CG bilayer membrane, enhancing the accuracy and applicability of our model in biophysical studies.
|
0904.3535
|
Thierry Rabilloud
|
C\'ecile Lelong (BBSI), Mireille Chevallet (BBSI), Sylvie Luche
(BBSI), Thierry Rabilloud (BBSI)
|
Silver Staining of Proteins in 2DE Gels
| null |
Methods in molecular biology (Clifton, N.J.) 519 (2009) 339-350
|
10.1007/978-1-59745-281-6_21
| null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Silver staining detects proteins after electrophoretic separation on
polyacrylamide gels. Its main positive features are its excellent sensitivity
(in the low nanogram range) and the use of very simple and cheap equipment and
chemicals. The sequential phases of silver staining are protein fixation, then
sensitization, then silver impregnation, and finally image development. Several
variants of silver staining are described here, which can be completed in a
time range from 2 h to 1 day after the end of the electrophoretic separation.
Once completed, the stain is stable for several weeks.
|
[
{
"created": "Wed, 22 Apr 2009 19:27:23 GMT",
"version": "v1"
}
] |
2009-04-23
|
[
[
"Lelong",
"Cécile",
"",
"BBSI"
],
[
"Chevallet",
"Mireille",
"",
"BBSI"
],
[
"Luche",
"Sylvie",
"",
"BBSI"
],
[
"Rabilloud",
"Thierry",
"",
"BBSI"
]
] |
Silver staining detects proteins after electrophoretic separation on polyacrylamide gels. Its main positive features are its excellent sensitivity (in the low nanogram range) and the use of very simple and cheap equipment and chemicals. The sequential phases of silver staining are protein fixation, then sensitization, then silver impregnation, and finally image development. Several variants of silver staining are described here, which can be completed in a time range from 2 h to 1 day after the end of the electrophoretic separation. Once completed, the stain is stable for several weeks.
|
0709.4206
|
Ney Lemke
|
Joao Paulo Muller da Silva, Marcio Luis Acencio, Jose Carlos Merino
Mombach, Renata Vieira, Jose Guliherme Camargo da Silva, Ney Lemke, Marialva
Sinigaglia
|
In silico network topology-based prediction of gene essentiality
| null | null | null | null |
q-bio.GN physics.bio-ph
| null |
The identification of genes essential for survival is important for the
understanding of the minimal requirements for cellular life and for drug
design. As experimental studies with the purpose of building a catalog of
essential genes for a given organism are time-consuming and laborious, a
computational approach which could predict gene essentiality with high accuracy
would be of great value. We present here a novel computational approach, called
NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on
network topology features of a gene to estimate its essentiality. The first
step of NTPGE is to construct the integrated molecular network for a given
organism comprising protein physical, metabolic and transcriptional regulation
interactions. The second step consists in training a decision tree-based
machine learning algorithm on known essential and non-essential genes of the
organism of interest, considering as learning attributes the network topology
information for each of these genes. Finally, the decision tree classifier
generated is applied to the set of genes of this organism to estimate
essentiality for each gene. We applied the NTPGE approach for discovering
essential genes in Escherichia coli and then assessed its performance.
|
[
{
"created": "Wed, 26 Sep 2007 16:35:32 GMT",
"version": "v1"
}
] |
2007-09-27
|
[
[
"da Silva",
"Joao Paulo Muller",
""
],
[
"Acencio",
"Marcio Luis",
""
],
[
"Mombach",
"Jose Carlos Merino",
""
],
[
"Vieira",
"Renata",
""
],
[
"da Silva",
"Jose Guliherme Camargo",
""
],
[
"Lemke",
"Ney",
""
],
[
"Sinigaglia",
"Marialva",
""
]
] |
The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision tree-based machine learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering essential genes in Escherichia coli and then assessed its performance.
|
1112.5006
|
Gilles Guillot
|
Gilles Guillot, Sabrina Renaud, Ronan Ledevin, Joahn Michaux, Julien
Claude
|
A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic
Data
| null | null | null | null |
q-bio.PE q-bio.QM stat.AP stat.CO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Recognition of evolutionary units (species, populations) requires integrating
several kinds of data such as genetic or phenotypic markers or spatial
information, in order to get a comprehensive view concerning the
differentiation of the units. We propose a statistical model with a double
original advantage: (i) it incorporates information about the spatial
distribution of the samples, with the aim to increase inference power and to
relate more explicitly observed patterns to geography; and (ii) it allows one
to analyze genetic and phenotypic data within a unified model and inference
framework, thus opening the way to robust comparisons between markers and
possibly combined analyzes. We show from simulated data as well are real data
from the literature that our method estimates parameters accurately and
improves alternative approaches in many situations. The interest of this method
is exemplified using an intricate case of inter- and intra-species
differentiation based on an original data-set of georeferenced genetic and
morphometric markers obtained on {\em Myodes} voles from Sweden. A computer
program is made available as an extension of the R package Geneland.
|
[
{
"created": "Wed, 21 Dec 2011 12:34:40 GMT",
"version": "v1"
}
] |
2011-12-22
|
[
[
"Guillot",
"Gilles",
""
],
[
"Renaud",
"Sabrina",
""
],
[
"Ledevin",
"Ronan",
""
],
[
"Michaux",
"Joahn",
""
],
[
"Claude",
"Julien",
""
]
] |
Recognition of evolutionary units (species, populations) requires integrating several kinds of data such as genetic or phenotypic markers or spatial information, in order to get a comprehensive view concerning the differentiation of the units. We propose a statistical model with a double original advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography; and (ii) it allows one to analyze genetic and phenotypic data within a unified model and inference framework, thus opening the way to robust comparisons between markers and possibly combined analyzes. We show from simulated data as well are real data from the literature that our method estimates parameters accurately and improves alternative approaches in many situations. The interest of this method is exemplified using an intricate case of inter- and intra-species differentiation based on an original data-set of georeferenced genetic and morphometric markers obtained on {\em Myodes} voles from Sweden. A computer program is made available as an extension of the R package Geneland.
|
2311.05668
|
Philip Bourne
|
Terence R. Johnson and Philip E. Bourne
|
The Biological Data Sustainability Paradox
|
12 pages 5852 words 1 figure
| null | null | null |
q-bio.OT cs.DB
|
http://creativecommons.org/licenses/by/4.0/
|
Biological data in digital form has become a, if not the, driving force
behind innovations in biology, medicine, and the environment. No study and no
model would be complete without access to digital data (including text)
collected by others and available in public repositories. With this ascent in
the fundamental importance of data for reproducible scientific progress has
come a troubling paradox.
|
[
{
"created": "Thu, 9 Nov 2023 14:56:27 GMT",
"version": "v1"
}
] |
2023-11-13
|
[
[
"Johnson",
"Terence R.",
""
],
[
"Bourne",
"Philip E.",
""
]
] |
Biological data in digital form has become a, if not the, driving force behind innovations in biology, medicine, and the environment. No study and no model would be complete without access to digital data (including text) collected by others and available in public repositories. With this ascent in the fundamental importance of data for reproducible scientific progress has come a troubling paradox.
|
2307.00084
|
Milind Kunchur
|
Milind N. Kunchur
|
The Human Auditory System and Audio
|
32 pages, 22 figures, 19 equations, 218 cited references
|
Applied Acoustics (Elsevier), Volume 211, August 2023, 109507
|
10.1016/j.apacoust.2023.109507
| null |
q-bio.NC cs.SD eess.AS
|
http://creativecommons.org/licenses/by/4.0/
|
This work reviews the human auditory system, elucidating some of the
specialized mechanisms and non-linear pathways along the chain of events
between physical sound and its perception. Customary relationships between
frequency, time, and phase--such as the uncertainty principle--that hold for
linear systems, do not apply straightforwardly to the hearing process. Auditory
temporal resolution for certain processes can be a hundredth of the period of
the signal, and can extend down to the microseconds time scale. The
astonishingly large number of variations that correspond to the neural
excitation pattern of 30000 auditory nerve fibers, originating from 3500 inner
hair cells, explicates the vast capacity of the auditory system for the
resolution of sonic detail. And the ear is sensitive enough to detect a
basilar-membrane amplitude at the level of a picometer, or about a hundred
times smaller than an atom. This article surveys and provides new insights into
some of the impressive capabilities of the human auditory system and explores
their relationship to fidelity in reproduced sound.
|
[
{
"created": "Fri, 30 Jun 2023 18:41:49 GMT",
"version": "v1"
},
{
"created": "Fri, 28 Jul 2023 20:37:39 GMT",
"version": "v2"
}
] |
2023-08-01
|
[
[
"Kunchur",
"Milind N.",
""
]
] |
This work reviews the human auditory system, elucidating some of the specialized mechanisms and non-linear pathways along the chain of events between physical sound and its perception. Customary relationships between frequency, time, and phase--such as the uncertainty principle--that hold for linear systems, do not apply straightforwardly to the hearing process. Auditory temporal resolution for certain processes can be a hundredth of the period of the signal, and can extend down to the microseconds time scale. The astonishingly large number of variations that correspond to the neural excitation pattern of 30000 auditory nerve fibers, originating from 3500 inner hair cells, explicates the vast capacity of the auditory system for the resolution of sonic detail. And the ear is sensitive enough to detect a basilar-membrane amplitude at the level of a picometer, or about a hundred times smaller than an atom. This article surveys and provides new insights into some of the impressive capabilities of the human auditory system and explores their relationship to fidelity in reproduced sound.
|
1209.5242
|
Michael GB Blum
|
Nicolas Duforet-Frebourg, Michael G. B. Blum
|
Non-stationary patterns of isolation-by-distance: inferring measures of
local genetic differentiation with Bayesian kriging
|
In press, Evolution 2014
| null |
10.1111/evo.12342
| null |
q-bio.PE stat.AP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Patterns of isolation-by-distance arise when population differentiation
increases with increasing geographic distances. Patterns of
isolation-by-distance are usually caused by local spatial dispersal, which
explains why differences of allele frequencies between populations accumulate
with distance. However, spatial variations of demographic parameters such as
migration rate or population density can generate non-stationary patterns of
isolation-by-distance where the rate at which genetic differentiation
accumulates varies across space. To characterize non-stationary patterns of
isolation-by-distance, we infer local genetic differentiation based on Bayesian
kriging. Local genetic differentiation for a sampled population is defined as
the average genetic differentiation between the sampled population and fictive
neighboring populations. To avoid defining populations in advance, the method
can also be applied at the scale of individuals making it relevant for
landscape genetics. Inference of local genetic differentiation relies on a
matrix of pairwise similarity or dissimilarity between populations or
individuals such as matrices of FST between pairs of populations. Simulation
studies show that maps of local genetic differentiation can reveal barriers to
gene flow but also other patterns such as continuous variations of gene flow
across habitat. The potential of the method is illustrated with 2 data sets:
genome-wide SNP data for human Swedish populations and AFLP markers for alpine
plant species. The software LocalDiff implementing the method is available at
http://membres-timc.imag.fr/Michael.Blum/LocalDiff.html
|
[
{
"created": "Mon, 24 Sep 2012 12:17:15 GMT",
"version": "v1"
},
{
"created": "Tue, 25 Sep 2012 09:36:36 GMT",
"version": "v2"
},
{
"created": "Tue, 7 Jan 2014 08:44:31 GMT",
"version": "v3"
}
] |
2014-01-08
|
[
[
"Duforet-Frebourg",
"Nicolas",
""
],
[
"Blum",
"Michael G. B.",
""
]
] |
Patterns of isolation-by-distance arise when population differentiation increases with increasing geographic distances. Patterns of isolation-by-distance are usually caused by local spatial dispersal, which explains why differences of allele frequencies between populations accumulate with distance. However, spatial variations of demographic parameters such as migration rate or population density can generate non-stationary patterns of isolation-by-distance where the rate at which genetic differentiation accumulates varies across space. To characterize non-stationary patterns of isolation-by-distance, we infer local genetic differentiation based on Bayesian kriging. Local genetic differentiation for a sampled population is defined as the average genetic differentiation between the sampled population and fictive neighboring populations. To avoid defining populations in advance, the method can also be applied at the scale of individuals making it relevant for landscape genetics. Inference of local genetic differentiation relies on a matrix of pairwise similarity or dissimilarity between populations or individuals such as matrices of FST between pairs of populations. Simulation studies show that maps of local genetic differentiation can reveal barriers to gene flow but also other patterns such as continuous variations of gene flow across habitat. The potential of the method is illustrated with 2 data sets: genome-wide SNP data for human Swedish populations and AFLP markers for alpine plant species. The software LocalDiff implementing the method is available at http://membres-timc.imag.fr/Michael.Blum/LocalDiff.html
|
1012.3938
|
Natalja Strelkowa
|
Natalja Strelkowa and Mauricio Barahona
|
Transient dynamics around unstable periodic orbits in the generalized
repressilator model
|
24 pages, 8 figures
| null |
10.1063/1.3574387
| null |
q-bio.MN q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We study the spatio-temporal dynamics of the generalized repressilator, a
system of coupled repressing genes arranged in a directed ring topology, and
give analytical conditions for the emergence of a cascade of unstable periodic
orbits (UPOs) that lead to reachable long-lived oscillating transients. Such
transients dominate the finite time horizon dynamics that is relevant in
confined, noisy environments such as bacterial cells (see our previous work
[Strelkowa and Barahona, 2010]) and are therefore of interest for
bioengineering and synthetic biology. We show that the family of unstable
orbits possesses spatial symmetries and can also be understood in terms of
traveling wave solutions of kink-like topological defects. The long-lived
oscillatory transients correspond to the propagation of quasistable two-kink
configurations that unravel over a long time. We also assess the similarities
between the generalized repressilator model and other unidirectionally coupled
electronic systems, such as magnetic flux gates, which have been implemented
experimentally.
|
[
{
"created": "Fri, 17 Dec 2010 17:42:12 GMT",
"version": "v1"
}
] |
2015-05-20
|
[
[
"Strelkowa",
"Natalja",
""
],
[
"Barahona",
"Mauricio",
""
]
] |
We study the spatio-temporal dynamics of the generalized repressilator, a system of coupled repressing genes arranged in a directed ring topology, and give analytical conditions for the emergence of a cascade of unstable periodic orbits (UPOs) that lead to reachable long-lived oscillating transients. Such transients dominate the finite time horizon dynamics that is relevant in confined, noisy environments such as bacterial cells (see our previous work [Strelkowa and Barahona, 2010]) and are therefore of interest for bioengineering and synthetic biology. We show that the family of unstable orbits possesses spatial symmetries and can also be understood in terms of traveling wave solutions of kink-like topological defects. The long-lived oscillatory transients correspond to the propagation of quasistable two-kink configurations that unravel over a long time. We also assess the similarities between the generalized repressilator model and other unidirectionally coupled electronic systems, such as magnetic flux gates, which have been implemented experimentally.
|
1109.2650
|
Eder Zavala
|
Eder Zavala, Mois\'es Santill\'an
|
An analysis of overall network architecture reveals an infinite-period
bifurcation underlying oscillation arrest in the segmentation clock
|
11 pages, 5 figures, added references, added figures, extended
supporting material, revised arguments in the discussion, corrected typos
| null | null | null |
q-bio.CB physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Unveiling the mechanisms through which the somitogenesis regulatory network
exerts spatiotemporal control of the somitic patterning has required a
combination of experimental and mathematical modeling strategies. Significant
progress has been made for the zebrafish clockwork. However, due to its
complexity, the clockwork of the amniote segmentation regulatory network has
not been fully elucidated. Here, we address the question of how oscillations
are arrested in the amniote segmentation clock. We do this by constructing a
minimal model of the regulatory network, which privileges architectural
information over molecular details. With a suitable choice of parameters, our
model is able to reproduce the oscillatory behavior of the Wnt, Notch and FGF
signaling pathways in presomitic mesoderm (PSM) cells. By introducing
positional information via a single Wnt3a gradient, we show that oscillations
are arrested following an infinite-period bifurcation. Notably: the
oscillations increase their amplitude as cells approach the anterior PSM and
remain in an upregulated state when arrested; the transition from the
oscillatory regime to the upregulated state exhibits hysteresis; and an
opposing distribution of the Fgf8 and RA gradients in the PSM arises naturally
in our simulations. We hypothesize that the interaction between a limit cycle
(originated by the Notch delayed-negative feedback loop) and a bistable switch
(originated by the Wnt-Notch positive cross-regulation) is responsible for the
observed segmentation patterning. Our results agree with previously unexplained
experimental observations and suggest a simple plausible mechanism for
spatiotemporal control of somitogenesis in amniotes.
|
[
{
"created": "Tue, 13 Sep 2011 00:03:19 GMT",
"version": "v1"
},
{
"created": "Fri, 23 Mar 2012 02:36:56 GMT",
"version": "v2"
}
] |
2015-03-13
|
[
[
"Zavala",
"Eder",
""
],
[
"Santillán",
"Moisés",
""
]
] |
Unveiling the mechanisms through which the somitogenesis regulatory network exerts spatiotemporal control of the somitic patterning has required a combination of experimental and mathematical modeling strategies. Significant progress has been made for the zebrafish clockwork. However, due to its complexity, the clockwork of the amniote segmentation regulatory network has not been fully elucidated. Here, we address the question of how oscillations are arrested in the amniote segmentation clock. We do this by constructing a minimal model of the regulatory network, which privileges architectural information over molecular details. With a suitable choice of parameters, our model is able to reproduce the oscillatory behavior of the Wnt, Notch and FGF signaling pathways in presomitic mesoderm (PSM) cells. By introducing positional information via a single Wnt3a gradient, we show that oscillations are arrested following an infinite-period bifurcation. Notably: the oscillations increase their amplitude as cells approach the anterior PSM and remain in an upregulated state when arrested; the transition from the oscillatory regime to the upregulated state exhibits hysteresis; and an opposing distribution of the Fgf8 and RA gradients in the PSM arises naturally in our simulations. We hypothesize that the interaction between a limit cycle (originated by the Notch delayed-negative feedback loop) and a bistable switch (originated by the Wnt-Notch positive cross-regulation) is responsible for the observed segmentation patterning. Our results agree with previously unexplained experimental observations and suggest a simple plausible mechanism for spatiotemporal control of somitogenesis in amniotes.
|
2101.02947
|
Michael Grinfeld
|
Michael Grinfeld
|
An enzymatic hormesis box
|
7 pages, 2 figures
| null | null | null |
q-bio.BM q-bio.SC
|
http://creativecommons.org/licenses/by/4.0/
|
We present a simple enzymatic system that is capable of a biphasic response
under competitive inhibition. This is arguably the simplest system that can be
said to be hormetic
|
[
{
"created": "Fri, 8 Jan 2021 10:28:36 GMT",
"version": "v1"
}
] |
2021-01-11
|
[
[
"Grinfeld",
"Michael",
""
]
] |
We present a simple enzymatic system that is capable of a biphasic response under competitive inhibition. This is arguably the simplest system that can be said to be hormetic
|
1803.08573
|
Katherine Medina
|
Victor Flores and Katherine Medina
|
The effects of cyclical simulation on the axon hillock diameter of
murine intracortical neurons
|
12 pages; submitted to PlosOne
| null | null | null |
q-bio.NC
|
http://creativecommons.org/publicdomain/zero/1.0/
|
Changes to the axon hillock in frequently firing neurons are known to be
important predictors of early disease states. Studying this phenomenon is
critical to understanding the first insult implicated in multiple
neuro-degenerative disorders. To study these changes we used cyclical
stimulations using micro-electrodes to the axon hillock of mouse intracortical
neurons. Numerical simulation results indicate that axon hillock water
potential fluctuated sinusoidally on high voltage only. Fluctuations in the
amplitude and trend were caused by calcium flow and storage resistance,
respectively. The change in axon hillock-stored water was proportional to the
change rate in water potential. Axon hillock diameter increased with
fluctuations in calcium free media; moreover, it varied slightly under low
voltage conditions. Changes in axon hillock diameter were caused by changes in
water potential, which was determined by subcellular gated channels, media
calcium potential, and other baseline characteristics of neurons.
|
[
{
"created": "Thu, 22 Mar 2018 20:18:15 GMT",
"version": "v1"
}
] |
2018-03-26
|
[
[
"Flores",
"Victor",
""
],
[
"Medina",
"Katherine",
""
]
] |
Changes to the axon hillock in frequently firing neurons are known to be important predictors of early disease states. Studying this phenomenon is critical to understanding the first insult implicated in multiple neuro-degenerative disorders. To study these changes we used cyclical stimulations using micro-electrodes to the axon hillock of mouse intracortical neurons. Numerical simulation results indicate that axon hillock water potential fluctuated sinusoidally on high voltage only. Fluctuations in the amplitude and trend were caused by calcium flow and storage resistance, respectively. The change in axon hillock-stored water was proportional to the change rate in water potential. Axon hillock diameter increased with fluctuations in calcium free media; moreover, it varied slightly under low voltage conditions. Changes in axon hillock diameter were caused by changes in water potential, which was determined by subcellular gated channels, media calcium potential, and other baseline characteristics of neurons.
|
1707.04885
|
Min Xu
|
Chengqian Che, Ruogu Lin, Xiangrui Zeng, Karim Elmaaroufi, John
Galeotti, and Min Xu
|
Improved deep learning based macromolecules structure classification
from electron cryo tomograms
|
Preliminary working report
| null |
10.1007/s00138-018-0949-4
| null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Cellular processes are governed by macromolecular complexes inside the cell.
Study of the native structures of macromolecular complexes has been extremely
difficult due to lack of data. With recent breakthroughs in Cellular electron
cryo tomography (CECT) 3D imaging technology, it is now possible for
researchers to gain accesses to fully study and understand the macromolecular
structures single cells. However, systematic recovery of macromolecular
structures from CECT is very difficult due to high degree of structural
complexity and practical imaging limitations. Specifically, we proposed a deep
learning based image classification approach for large-scale systematic
macromolecular structure separation from CECT data. However, our previous work
was only a very initial step towards exploration of the full potential of deep
learning based macromolecule separation. In this paper, we focus on improving
classification performance by proposing three newly designed individual CNN
models: an extended version of (Deep Small Receptive Field) DSRF3D, donated as
DSRF3D-v2, a 3D residual block based neural network, named as RB3D and a
convolutional 3D(C3D) based model, CB3D. We compare them with our previously
developed model (DSRF3D) on 12 datasets with different SNRs and tilt angle
ranges. The experiments show that our new models achieved significantly higher
classification accuracies. The accuracies are not only higher than 0.9 on
normal datasets, but also demonstrate potentials to operate on datasets with
high levels of noises and missing wedge effects presented.
|
[
{
"created": "Sun, 16 Jul 2017 14:25:31 GMT",
"version": "v1"
}
] |
2018-06-12
|
[
[
"Che",
"Chengqian",
""
],
[
"Lin",
"Ruogu",
""
],
[
"Zeng",
"Xiangrui",
""
],
[
"Elmaaroufi",
"Karim",
""
],
[
"Galeotti",
"John",
""
],
[
"Xu",
"Min",
""
]
] |
Cellular processes are governed by macromolecular complexes inside the cell. Study of the native structures of macromolecular complexes has been extremely difficult due to lack of data. With recent breakthroughs in Cellular electron cryo tomography (CECT) 3D imaging technology, it is now possible for researchers to gain accesses to fully study and understand the macromolecular structures single cells. However, systematic recovery of macromolecular structures from CECT is very difficult due to high degree of structural complexity and practical imaging limitations. Specifically, we proposed a deep learning based image classification approach for large-scale systematic macromolecular structure separation from CECT data. However, our previous work was only a very initial step towards exploration of the full potential of deep learning based macromolecule separation. In this paper, we focus on improving classification performance by proposing three newly designed individual CNN models: an extended version of (Deep Small Receptive Field) DSRF3D, donated as DSRF3D-v2, a 3D residual block based neural network, named as RB3D and a convolutional 3D(C3D) based model, CB3D. We compare them with our previously developed model (DSRF3D) on 12 datasets with different SNRs and tilt angle ranges. The experiments show that our new models achieved significantly higher classification accuracies. The accuracies are not only higher than 0.9 on normal datasets, but also demonstrate potentials to operate on datasets with high levels of noises and missing wedge effects presented.
|
2406.01107
|
Yujiang Wang
|
Bethany Little, Nida Alyas, Alexander Surtees, Gavin P Winston, John S
Duncan, David A Cousins, John-Paul Taylor, Peter Taylor, Karoline Leiberg,
Yujiang Wang
|
Brain Morphology Normative modelling platform for abnormality and
Centile estimation: Brain MoNoCle
| null | null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Normative models of brain structure estimate the effects of covariates such
as age and sex using large samples of healthy controls. These models can then
be applied to smaller clinical cohorts to distinguish disease effects from
other covariates. However, these advanced statistical modelling approaches can
be difficult to access, and processing large healthy cohorts is computationally
demanding. Thus, accessible platforms with pre-trained normative models are
needed.
We present such a platform for brain morphology analysis as an open-source
web application https://cnnplab.shinyapps.io/normativemodelshiny/, with six key
features: (i) user-friendly web interface, (ii) individual and group outputs,
(iii) multi-site analysis, (iv) regional and whole-brain analysis, (v)
integration with existing tools, and (vi) featuring multiple morphology
metrics.
Using a diverse sample of 3,276 healthy controls across 21 sites, we
pre-trained normative models on various metrics. We validated the models with a
small clinical sample of individuals with bipolar disorder, showing outputs
that aligned closely with existing literature only after applying our normative
modelling. Further validation with a cohort of temporal lobe epilepsy showed
agreement with previous group-level findings and individual-level seizure
lateralisation. Finally, with the ability to investigate multiple morphology
measures in the same framework, we found that biological covariates are better
explained in specific morphology measures, and for clinical applications, only
some measures are sensitive to the disease process.
Our platform offers a comprehensive framework to analyse brain morphology in
clinical and research settings. Validations confirm the superiority of
normative models and the advantage of investigating a range of brain morphology
metrics together.
|
[
{
"created": "Mon, 3 Jun 2024 08:41:53 GMT",
"version": "v1"
},
{
"created": "Wed, 26 Jun 2024 20:10:43 GMT",
"version": "v2"
}
] |
2024-06-28
|
[
[
"Little",
"Bethany",
""
],
[
"Alyas",
"Nida",
""
],
[
"Surtees",
"Alexander",
""
],
[
"Winston",
"Gavin P",
""
],
[
"Duncan",
"John S",
""
],
[
"Cousins",
"David A",
""
],
[
"Taylor",
"John-Paul",
""
],
[
"Taylor",
"Peter",
""
],
[
"Leiberg",
"Karoline",
""
],
[
"Wang",
"Yujiang",
""
]
] |
Normative models of brain structure estimate the effects of covariates such as age and sex using large samples of healthy controls. These models can then be applied to smaller clinical cohorts to distinguish disease effects from other covariates. However, these advanced statistical modelling approaches can be difficult to access, and processing large healthy cohorts is computationally demanding. Thus, accessible platforms with pre-trained normative models are needed. We present such a platform for brain morphology analysis as an open-source web application https://cnnplab.shinyapps.io/normativemodelshiny/, with six key features: (i) user-friendly web interface, (ii) individual and group outputs, (iii) multi-site analysis, (iv) regional and whole-brain analysis, (v) integration with existing tools, and (vi) featuring multiple morphology metrics. Using a diverse sample of 3,276 healthy controls across 21 sites, we pre-trained normative models on various metrics. We validated the models with a small clinical sample of individuals with bipolar disorder, showing outputs that aligned closely with existing literature only after applying our normative modelling. Further validation with a cohort of temporal lobe epilepsy showed agreement with previous group-level findings and individual-level seizure lateralisation. Finally, with the ability to investigate multiple morphology measures in the same framework, we found that biological covariates are better explained in specific morphology measures, and for clinical applications, only some measures are sensitive to the disease process. Our platform offers a comprehensive framework to analyse brain morphology in clinical and research settings. Validations confirm the superiority of normative models and the advantage of investigating a range of brain morphology metrics together.
|
2304.05700
|
Enya Weidner
|
Enya M. Weidner, Stephan Moratti, Sebastian Schindler, Philip Grewe,
Christian G. Bien, Johanna Kissler
|
Amygdala and cortical gamma band responses to emotional faces depend on
the attended to valence
| null | null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
The amygdala is assumed to contribute to a bottom-up attentional bias during
visual processing of emotional faces. Still, how its response to emotion
interacts with top-down attention is not fully understood. It is also unclear
if amygdala activity and scalp EEG respond to emotion and attention in a
similar way. Therefore, we studied the interaction of emotion and attention
during face processing in oscillatory gamma-band activity (GBA) in the amygdala
and on the scalp. Amygdala signals were recorded via intracranial EEG (iEEG) in
10 patients with epilepsy. Scalp recordings were collected from 19 healthy
participants. Three randomized blocks of angry, neutral, and happy faces were
presented, and either negative, neutral, or positive expressions were denoted
as targets. Both groups detected happy faces fastest and most accurately.
During attention to negative faces, low GBA (< 90 Hz) increased specifically
for angry faces both in the amygdala and over posterior scalp regions, albeit
earlier on the scalp (60 ms) than in the amygdala (130 ms). From 220 ms,
amygdala high GBA (117.5-145 Hz) was additionally persistently increased for
both angry and neutral compared to happy faces. When neutral faces served as
targets, amygdala high GBA (105-122.5 Hz) was higher for emotional than neutral
faces from 160-320 ms. Attention to positive faces did not result in a
differentiation between facial expressions. Present data reveal that
attention-independent emotion detection in amygdala high GBA may only occur
during a neutral focus of attention. Top-down threat vigilance coordinates
widespread GBA, biasing stimulus processing in favor of negative faces. These
results are in line with a multi-pathway model of emotion processing and help
specify the role of GBA in this process by revealing how attentional focus can
tune timing and amplitude of emotional GBA responses.
|
[
{
"created": "Wed, 12 Apr 2023 08:42:32 GMT",
"version": "v1"
},
{
"created": "Tue, 16 May 2023 11:11:34 GMT",
"version": "v2"
}
] |
2023-05-17
|
[
[
"Weidner",
"Enya M.",
""
],
[
"Moratti",
"Stephan",
""
],
[
"Schindler",
"Sebastian",
""
],
[
"Grewe",
"Philip",
""
],
[
"Bien",
"Christian G.",
""
],
[
"Kissler",
"Johanna",
""
]
] |
The amygdala is assumed to contribute to a bottom-up attentional bias during visual processing of emotional faces. Still, how its response to emotion interacts with top-down attention is not fully understood. It is also unclear if amygdala activity and scalp EEG respond to emotion and attention in a similar way. Therefore, we studied the interaction of emotion and attention during face processing in oscillatory gamma-band activity (GBA) in the amygdala and on the scalp. Amygdala signals were recorded via intracranial EEG (iEEG) in 10 patients with epilepsy. Scalp recordings were collected from 19 healthy participants. Three randomized blocks of angry, neutral, and happy faces were presented, and either negative, neutral, or positive expressions were denoted as targets. Both groups detected happy faces fastest and most accurately. During attention to negative faces, low GBA (< 90 Hz) increased specifically for angry faces both in the amygdala and over posterior scalp regions, albeit earlier on the scalp (60 ms) than in the amygdala (130 ms). From 220 ms, amygdala high GBA (117.5-145 Hz) was additionally persistently increased for both angry and neutral compared to happy faces. When neutral faces served as targets, amygdala high GBA (105-122.5 Hz) was higher for emotional than neutral faces from 160-320 ms. Attention to positive faces did not result in a differentiation between facial expressions. Present data reveal that attention-independent emotion detection in amygdala high GBA may only occur during a neutral focus of attention. Top-down threat vigilance coordinates widespread GBA, biasing stimulus processing in favor of negative faces. These results are in line with a multi-pathway model of emotion processing and help specify the role of GBA in this process by revealing how attentional focus can tune timing and amplitude of emotional GBA responses.
|
2009.08023
|
Shantanu Jain
|
Yisu Peng (1), Shantanu Jain (1), Yong Fuga Li (2), Michal Gregus (3
and 4), Alexander R. Ivanov (3 and 4), Olga Vitek (1 and 4) and Predrag
Radivojac (1) ((1) Khoury College of Computer Sciences, Northeastern
University, (2) Illumina Inc., (3) Department of Chemistry and Chemical
Biology, Northeastern University, (4) Barnett Institute of Chemical and
Biological Analysis, Northeastern University)
|
New mixture models for decoy-free false discovery rate estimation in
mass-spectrometry proteomics
| null | null | null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Motivation: Accurate estimation of false discovery rate (FDR) of spectral
identification is a central problem in mass spectrometry-based proteomics. Over
the past two decades, target decoy approaches (TDAs) and decoy-free approaches
(DFAs), have been widely used to estimate FDR. TDAs use a database of decoy
species to faithfully model score distributions of incorrect peptide-spectrum
matches (PSMs). DFAs, on the other hand, fit two-component mixture models to
learn the parameters of correct and incorrect PSM score distributions. While
conceptually straightforward, both approaches lead to problems in practice,
particularly in experiments that push instrumentation to the limit and generate
low fragmentation-efficiency and low signal-to-noise-ratio spectra. Results: We
introduce a new decoy-free framework for FDR estimation that generalizes
present DFAs while exploiting more search data in a manner similar to TDAs. Our
approach relies on multi-component mixtures, in which score distributions
corresponding to the correct PSMs, best incorrect PSMs, and second-best
incorrect PSMs are modeled by the skew normal family. We derive EM algorithms
to estimate parameters of these distributions from the scores of best and
second-best PSMs associated with each experimental spectrum. We evaluate our
models on multiple proteomics datasets and a HeLa cell digest case study
consisting of more than a million spectra in total. We provide evidence of
improved performance over existing DFAs and improved stability and speed over
TDAs without any performance degradation. We propose that the new strategy has
the potential to extend beyond peptide identification and reduce the need for
TDA on all analytical platforms.
|
[
{
"created": "Thu, 17 Sep 2020 02:22:15 GMT",
"version": "v1"
}
] |
2020-09-18
|
[
[
"Peng",
"Yisu",
"",
"3\n and 4"
],
[
"Jain",
"Shantanu",
"",
"3\n and 4"
],
[
"Li",
"Yong Fuga",
"",
"3\n and 4"
],
[
"Gregus",
"Michal",
"",
"3\n and 4"
],
[
"Ivanov",
"Alexander R.",
"",
"3 and 4"
],
[
"Vitek",
"Olga",
"",
"1 and 4"
],
[
"Radivojac",
"Predrag",
""
]
] |
Motivation: Accurate estimation of false discovery rate (FDR) of spectral identification is a central problem in mass spectrometry-based proteomics. Over the past two decades, target decoy approaches (TDAs) and decoy-free approaches (DFAs), have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra. Results: We introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs, and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms.
|
0805.0835
|
Masaki Sasai
|
Kohei Eguchi, Mitsumasa Yoda, Tomoki P. Terada, and Masaki Sasai
|
Mechanism of robust circadian oscillation of KaiC phosphorylation in
vitro
| null | null |
10.1529/biophysj.107.127555
| null |
q-bio.MN cond-mat.dis-nn q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
By incubating the mixture of three cyanobacterial proteins, KaiA, KaiB, and
KaiC, with ATP in vitro, Kondo and his colleagues reconstituted the robust
circadian rhythm of the phosphorylation level of KaiC (Science, 308; 414-415
(2005)). This finding indicates that protein-protein interactions and the
associated hydrolysis of ATP suffice to generate the circadian rhythm. Several
theoretical models have been proposed to explain the rhythm generated in this
"protein-only" system, but the clear criterion to discern different possible
mechanisms was not known. In this paper, we discuss a model based on the two
basic assumptions: The assumption of the allosteric transition of a KaiC
hexamer and the assumption of the monomer exchange between KaiC hexamers. The
model shows a stable rhythmic oscillation of the phosphorylation level of KaiC,
which is robust against changes in concentration of Kai proteins. We show that
this robustness gives a clue to distinguish different possible mechanisms. We
also discuss the robustness of oscillation against the change in the system
size. Behaviors of the system with the cellular or subcellular size should shed
light on the role of the protein-protein interactions in in vivo circadian
oscillation.
|
[
{
"created": "Wed, 7 May 2008 04:15:40 GMT",
"version": "v1"
}
] |
2009-11-13
|
[
[
"Eguchi",
"Kohei",
""
],
[
"Yoda",
"Mitsumasa",
""
],
[
"Terada",
"Tomoki P.",
""
],
[
"Sasai",
"Masaki",
""
]
] |
By incubating the mixture of three cyanobacterial proteins, KaiA, KaiB, and KaiC, with ATP in vitro, Kondo and his colleagues reconstituted the robust circadian rhythm of the phosphorylation level of KaiC (Science, 308; 414-415 (2005)). This finding indicates that protein-protein interactions and the associated hydrolysis of ATP suffice to generate the circadian rhythm. Several theoretical models have been proposed to explain the rhythm generated in this "protein-only" system, but the clear criterion to discern different possible mechanisms was not known. In this paper, we discuss a model based on the two basic assumptions: The assumption of the allosteric transition of a KaiC hexamer and the assumption of the monomer exchange between KaiC hexamers. The model shows a stable rhythmic oscillation of the phosphorylation level of KaiC, which is robust against changes in concentration of Kai proteins. We show that this robustness gives a clue to distinguish different possible mechanisms. We also discuss the robustness of oscillation against the change in the system size. Behaviors of the system with the cellular or subcellular size should shed light on the role of the protein-protein interactions in in vivo circadian oscillation.
|
1403.1562
|
Krzysztof Bartoszek
|
Krzysztof Bartoszek
|
The Laplace Motion in Phylogenetic Comparative Methods
|
http://kkzmbm.mimuw.edu.pl/?pageId=4&sprawId=18
|
Proceedings of the Eighteenth National Conference on Applications
of Mathematics in Biology and Medicine, 2012
| null | null |
q-bio.PE math.PR stat.AP stat.CO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The majority of current phylogenetic comparative methods assume that the
stochastic evolutionary process is homogeneous over the phylogeny or offer
relaxations of this in rather limited and usually parameter expensive ways.
Here we make a preliminary investigation, by means of a numerical experiment,
whether the Laplace motion process can offer an alternative approach.
|
[
{
"created": "Thu, 6 Mar 2014 20:24:38 GMT",
"version": "v1"
}
] |
2014-03-07
|
[
[
"Bartoszek",
"Krzysztof",
""
]
] |
The majority of current phylogenetic comparative methods assume that the stochastic evolutionary process is homogeneous over the phylogeny or offer relaxations of this in rather limited and usually parameter expensive ways. Here we make a preliminary investigation, by means of a numerical experiment, whether the Laplace motion process can offer an alternative approach.
|
1505.01066
|
Jayajit Das
|
Jayajit Das, Sayak Mukherjee, Susan E. Hodge
|
Maximum Entropy estimation of probability distribution of variables in
higher dimensions from lower dimensional data
|
in review
|
Entropy 2015, 17(7), 4986-4999
|
10.3390/e17074986
| null |
q-bio.QM cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A common statistical situation concerns inferring an unknown distribution
Q(x) from a known distribution P(y), where X (dimension n), and Y (dimension m)
have a known functional relationship. Most commonly, n<m, and the task is
relatively straightforward. For example, if Y1 and Y2 are independent random
variables, each uniform on [0, 1], one can determine the distribution of X = Y1
+ Y2; here m=2 and n=1. However, biological and physical situations can arise
where n>m. In general, in the absence of additional information, there is no
unique solution to Q in those cases. Nevertheless, one may still want to draw
some inferences about Q. To this end, we propose a novel maximum entropy
(MaxEnt) approach that estimates Q(x) based only on the available data, namely,
P(y). The method has the additional advantage that one does not need to
explicitly calculate the Lagrange multipliers. In this paper we develop the
approach, for both discrete and continuous probability distributions, and
demonstrate its validity. We give an intuitive justification as well, and we
illustrate with examples.
|
[
{
"created": "Tue, 5 May 2015 16:19:21 GMT",
"version": "v1"
}
] |
2016-02-01
|
[
[
"Das",
"Jayajit",
""
],
[
"Mukherjee",
"Sayak",
""
],
[
"Hodge",
"Susan E.",
""
]
] |
A common statistical situation concerns inferring an unknown distribution Q(x) from a known distribution P(y), where X (dimension n), and Y (dimension m) have a known functional relationship. Most commonly, n<m, and the task is relatively straightforward. For example, if Y1 and Y2 are independent random variables, each uniform on [0, 1], one can determine the distribution of X = Y1 + Y2; here m=2 and n=1. However, biological and physical situations can arise where n>m. In general, in the absence of additional information, there is no unique solution to Q in those cases. Nevertheless, one may still want to draw some inferences about Q. To this end, we propose a novel maximum entropy (MaxEnt) approach that estimates Q(x) based only on the available data, namely, P(y). The method has the additional advantage that one does not need to explicitly calculate the Lagrange multipliers. In this paper we develop the approach, for both discrete and continuous probability distributions, and demonstrate its validity. We give an intuitive justification as well, and we illustrate with examples.
|
2109.00123
|
Pik-Yin Lai
|
Mao-Xiang Wang, Arthur Lander, and Pik-Yin Lai
|
Regulatory Feedback Effects on Tissue Growth Dynamics in a Two-Stage
Cell Lineage Model
|
to be published in Physical Review E
| null |
10.1103/PhysRevE.104.034405
| null |
q-bio.TO physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Identifying the mechanism of intercellular feedback regulation is critical
for the basic understanding of tissue growth control in organisms. In this
paper, we analyze a tissue growth model consisting of a single lineage of two
cell types regulated by negative feedback signalling molecules that undergo
spatial diffusion. By deriving the fixed points for the uniform steady states
and carrying out linear stability analysis, phase diagrams are obtained
analytically for arbitrary parameters of the model. Two different generic
growth modes are found: blow-up growth and final-state controlled growth which
are governed by the non-trivial fixed point and the trivial fixed point
respectively, and can be sensitively switched by varying the negative feedback
regulation on the proliferation of the stem cells. Analytic expressions for the
characteristic time scales for these two growth modes are also derived.
Remarkably, the trivial and non-trivial uniform steady states can coexist and a
sharp transition occurs in the bistable regime as the relevant parameters are
varied. Furthermore, the bi-stable growth properties allows for the external
control to switch between these two growth modes. In addition, the condition
for an early accelerated growth followed by a retarded growth can be derived.
These analytical results are further verified by numerical simulations and
provide insights on the growth behavior of the tissue. Our results are also
discussed in the light of possible realistic biological experiments and tissue
growth control strategy. Furthermore, by external feedback control of the
concentration of regulatory molecules, it is possible to achieve a desired
growth mode, as demonstrated with an analysis of boosted growth, catch-up
growth and the design for the target of a linear growth dynamic.
|
[
{
"created": "Wed, 1 Sep 2021 00:14:31 GMT",
"version": "v1"
}
] |
2021-09-22
|
[
[
"Wang",
"Mao-Xiang",
""
],
[
"Lander",
"Arthur",
""
],
[
"Lai",
"Pik-Yin",
""
]
] |
Identifying the mechanism of intercellular feedback regulation is critical for the basic understanding of tissue growth control in organisms. In this paper, we analyze a tissue growth model consisting of a single lineage of two cell types regulated by negative feedback signalling molecules that undergo spatial diffusion. By deriving the fixed points for the uniform steady states and carrying out linear stability analysis, phase diagrams are obtained analytically for arbitrary parameters of the model. Two different generic growth modes are found: blow-up growth and final-state controlled growth which are governed by the non-trivial fixed point and the trivial fixed point respectively, and can be sensitively switched by varying the negative feedback regulation on the proliferation of the stem cells. Analytic expressions for the characteristic time scales for these two growth modes are also derived. Remarkably, the trivial and non-trivial uniform steady states can coexist and a sharp transition occurs in the bistable regime as the relevant parameters are varied. Furthermore, the bi-stable growth properties allows for the external control to switch between these two growth modes. In addition, the condition for an early accelerated growth followed by a retarded growth can be derived. These analytical results are further verified by numerical simulations and provide insights on the growth behavior of the tissue. Our results are also discussed in the light of possible realistic biological experiments and tissue growth control strategy. Furthermore, by external feedback control of the concentration of regulatory molecules, it is possible to achieve a desired growth mode, as demonstrated with an analysis of boosted growth, catch-up growth and the design for the target of a linear growth dynamic.
|
2211.02636
|
Zibin Zhao
|
Zibin Zhao
|
Towards Alzheimer's Disease Progression Assessment: A Review of Machine
Learning Methods
|
16 pages, 3 figures
| null | null | null |
q-bio.NC cs.LG q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Alzheimer's Disease (AD), as the most devastating neurodegenerative disease
worldwide, has reached nearly 10 million new cases annually. Current technology
provides unprecedented opportunities to study the progression and etiology of
this disease with the advanced in imaging techniques. With the recent emergence
of a society driven by big data and machine learning (ML), researchers have
exerted considerable effort to summarize recent advances in ML-based AD
diagnosis. Here, we outline some of the most prevalent and recent ML models for
assessing the progression of AD and provide insights on the challenges,
opportunities, and future directions that could be advantageous to future
research in AD using ML.
|
[
{
"created": "Tue, 1 Nov 2022 07:50:06 GMT",
"version": "v1"
},
{
"created": "Fri, 11 Nov 2022 06:35:45 GMT",
"version": "v2"
}
] |
2022-11-14
|
[
[
"Zhao",
"Zibin",
""
]
] |
Alzheimer's Disease (AD), as the most devastating neurodegenerative disease worldwide, has reached nearly 10 million new cases annually. Current technology provides unprecedented opportunities to study the progression and etiology of this disease with the advanced in imaging techniques. With the recent emergence of a society driven by big data and machine learning (ML), researchers have exerted considerable effort to summarize recent advances in ML-based AD diagnosis. Here, we outline some of the most prevalent and recent ML models for assessing the progression of AD and provide insights on the challenges, opportunities, and future directions that could be advantageous to future research in AD using ML.
|
2005.13074
|
Cecilia Jarne Dr
|
Cecilia Jarne
|
Different eigenvalue distributions encode the same temporal tasks in
recurrent neural networks
|
19 pages, 10 Figures
| null |
10.1007/s11571-022-09802-5
| null |
q-bio.NC cond-mat.dis-nn
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Different brain areas, such as the cortex and, more specifically, the
prefrontal cortex, show great recurrence in their connections, even in early
sensory areas. {Several approaches and methods based on trained networks have
been proposed to model and describe these regions. It is essential to
understand the dynamics behind the models because they are used to build
different hypotheses about the functioning of brain areas and to explain
experimental results. The main contribution here is the description of the
dynamics through the classification and interpretation carried out with a set
of numerical simulations. This study sheds light on the multiplicity of
solutions obtained for the same tasks and shows the link between the spectra of
linearized trained networks and the dynamics of the counterparts. The patterns
in the distribution of the eigenvalues of the recurrent weight matrix were
studied and properly related to the dynamics in each task.
|
[
{
"created": "Tue, 26 May 2020 22:41:32 GMT",
"version": "v1"
},
{
"created": "Tue, 23 Jun 2020 19:08:24 GMT",
"version": "v2"
},
{
"created": "Mon, 18 Oct 2021 14:39:01 GMT",
"version": "v3"
},
{
"created": "Mon, 24 Jan 2022 20:06:39 GMT",
"version": "v4"
},
{
"created": "Thu, 27 Jan 2022 17:42:44 GMT",
"version": "v5"
}
] |
2022-04-25
|
[
[
"Jarne",
"Cecilia",
""
]
] |
Different brain areas, such as the cortex and, more specifically, the prefrontal cortex, show great recurrence in their connections, even in early sensory areas. {Several approaches and methods based on trained networks have been proposed to model and describe these regions. It is essential to understand the dynamics behind the models because they are used to build different hypotheses about the functioning of brain areas and to explain experimental results. The main contribution here is the description of the dynamics through the classification and interpretation carried out with a set of numerical simulations. This study sheds light on the multiplicity of solutions obtained for the same tasks and shows the link between the spectra of linearized trained networks and the dynamics of the counterparts. The patterns in the distribution of the eigenvalues of the recurrent weight matrix were studied and properly related to the dynamics in each task.
|
2007.09671
|
Mariana Recamonde-Mendoza
|
Jo\~ao Schapke, Anderson Tavares, Mariana Recamonde-Mendoza
|
EPGAT: Gene Essentiality Prediction With Graph Attention Networks
|
Published in IEEE/ACM Transactions on Computational Biology and
Bioinformatics
| null |
10.1109/TCBB.2021.3054738
| null |
q-bio.MN cs.LG q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The identification of essential genes/proteins is a critical step towards a
better understanding of human biology and pathology. Computational approaches
helped to mitigate experimental constraints by exploring machine learning (ML)
methods and the correlation of essentiality with biological information,
especially protein-protein interaction (PPI) networks, to predict essential
genes. Nonetheless, their performance is still limited, as network-based
centralities are not exclusive proxies of essentiality, and traditional ML
methods are unable to learn from non-Euclidean domains such as graphs. Given
these limitations, we proposed EPGAT, an approach for essentiality prediction
based on Graph Attention Networks (GATs), which are attention-based Graph
Neural Networks (GNNs) that operate on graph-structured data. Our model
directly learns patterns of gene essentiality from PPI networks, integrating
additional evidence from multiomics data encoded as node attributes. We
benchmarked EPGAT for four organisms, including humans, accurately predicting
gene essentiality with AUC score ranging from 0.78 to 0.97. Our model
significantly outperformed network-based and shallow ML-based methods and
achieved a very competitive performance against the state-of-the-art node2vec
embedding method. Notably, EPGAT was the most robust approach in scenarios with
limited and imbalanced training data. Thus, the proposed approach offers a
powerful and effective way to identify essential genes and proteins.
|
[
{
"created": "Sun, 19 Jul 2020 13:47:15 GMT",
"version": "v1"
}
] |
2021-08-02
|
[
[
"Schapke",
"João",
""
],
[
"Tavares",
"Anderson",
""
],
[
"Recamonde-Mendoza",
"Mariana",
""
]
] |
The identification of essential genes/proteins is a critical step towards a better understanding of human biology and pathology. Computational approaches helped to mitigate experimental constraints by exploring machine learning (ML) methods and the correlation of essentiality with biological information, especially protein-protein interaction (PPI) networks, to predict essential genes. Nonetheless, their performance is still limited, as network-based centralities are not exclusive proxies of essentiality, and traditional ML methods are unable to learn from non-Euclidean domains such as graphs. Given these limitations, we proposed EPGAT, an approach for essentiality prediction based on Graph Attention Networks (GATs), which are attention-based Graph Neural Networks (GNNs) that operate on graph-structured data. Our model directly learns patterns of gene essentiality from PPI networks, integrating additional evidence from multiomics data encoded as node attributes. We benchmarked EPGAT for four organisms, including humans, accurately predicting gene essentiality with AUC score ranging from 0.78 to 0.97. Our model significantly outperformed network-based and shallow ML-based methods and achieved a very competitive performance against the state-of-the-art node2vec embedding method. Notably, EPGAT was the most robust approach in scenarios with limited and imbalanced training data. Thus, the proposed approach offers a powerful and effective way to identify essential genes and proteins.
|
q-bio/0601013
|
Gerhard Schmid
|
Gerhard Schmid, Igor Goychuk, Peter Hanggi
|
Effect of channel block on the spiking activity of excitable membranes
in a stochastic Hodgkin-Huxley model
|
10 pages, 3 figures, published 2004
|
PHYSICAL BIOLOGY 1, pp. 61-66 (2004)
|
10.1088/1478-3967/1/2/002
| null |
q-bio.SC
| null |
The influence of intrinsic channel noise on the spontaneous spiking activity
of poisoned excitable membrane patches is studied by use of a stochastic
generalization of the Hodgkin-Huxley model. Internal noise stemming from the
stochastic dynamics of individual ion channels is known to affect the
collective properties of the whole ion channel cluster. For example, there
exists an optimal size of the membrane patch for which the internal noise alone
causes a regular spontaneous generation of action potentials. In addition to
varying the size of ion channel clusters, living organisms may adapt the
densities of ion channels in order to optimally regulate the spontaneous
spiking activity. The influence of channel block on the excitability of a
membrane patch of certain size is twofold: First, a variation of ion channel
densities primarily yields a change of the conductance level. Second, a
down-regulation of working ion channels always increases the channel noise.
While the former effect dominates in the case of sodium channel block resulting
in a reduced spiking activity, the latter enhances the generation of
spontaneous action potentials in the case of a tailored potassium channel
blocking. Moreover, by blocking some portion of either potassium or sodium ion
channels, it is possible to either increase or to decrease the regularity of
the spike train.
|
[
{
"created": "Wed, 11 Jan 2006 13:53:12 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Schmid",
"Gerhard",
""
],
[
"Goychuk",
"Igor",
""
],
[
"Hanggi",
"Peter",
""
]
] |
The influence of intrinsic channel noise on the spontaneous spiking activity of poisoned excitable membrane patches is studied by use of a stochastic generalization of the Hodgkin-Huxley model. Internal noise stemming from the stochastic dynamics of individual ion channels is known to affect the collective properties of the whole ion channel cluster. For example, there exists an optimal size of the membrane patch for which the internal noise alone causes a regular spontaneous generation of action potentials. In addition to varying the size of ion channel clusters, living organisms may adapt the densities of ion channels in order to optimally regulate the spontaneous spiking activity. The influence of channel block on the excitability of a membrane patch of certain size is twofold: First, a variation of ion channel densities primarily yields a change of the conductance level. Second, a down-regulation of working ion channels always increases the channel noise. While the former effect dominates in the case of sodium channel block resulting in a reduced spiking activity, the latter enhances the generation of spontaneous action potentials in the case of a tailored potassium channel blocking. Moreover, by blocking some portion of either potassium or sodium ion channels, it is possible to either increase or to decrease the regularity of the spike train.
|
2110.09017
|
Thomas Bochynek
|
Thomas Bochynek, Florian Schiffers, Andr\'e Aichert, Oliver Cossairt,
Simon Garnier, Michael Rubenstein
|
Anatomy of a superorganism -- structure and growth dynamics of army ant
bivouacs
| null | null | null | null |
q-bio.QM
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Beyond unicellular and multicellular organisms, there is a third type of
structural complexity in living animals: that of the mechanical self-assembly
of groups of distinct multicellular organisms into dynamical, functional
structures. One of the most striking examples of such structures is the army
ant bivouac, a nest which self-assembles solely from the interconnected bodies
of hundreds of thousands of individuals. These bivouacs are difficult to study
because they rapidly disassemble when disturbed, and hence little is known
about the structure and rules that individuals follow during their formation.
Here we use a custom-built Computed Tomography scanner to investigate the
details of the internal structure and growth process of army ant bivouacs. We
show that bivouacs are heterogeneous structures, which throughout their growth
maintain a thick shell surrounding a less dense interior that contains empty
spaces akin to nest chambers. We find that ants within the bivouac do not carry
more than approximately eight times their weight regardless of the size of the
structure or their position within it. This observation suggests that bivouac
size is not limited by physical constraints of the ants' morphology. This study
brings us closer to understanding the rules used by individuals to govern the
formation of these exceptional superorganismal structures, and provides insight
into how to create engineered self-assembling systems with, for instance,
swarms of robots or active matter.
|
[
{
"created": "Mon, 18 Oct 2021 05:09:41 GMT",
"version": "v1"
}
] |
2021-10-19
|
[
[
"Bochynek",
"Thomas",
""
],
[
"Schiffers",
"Florian",
""
],
[
"Aichert",
"André",
""
],
[
"Cossairt",
"Oliver",
""
],
[
"Garnier",
"Simon",
""
],
[
"Rubenstein",
"Michael",
""
]
] |
Beyond unicellular and multicellular organisms, there is a third type of structural complexity in living animals: that of the mechanical self-assembly of groups of distinct multicellular organisms into dynamical, functional structures. One of the most striking examples of such structures is the army ant bivouac, a nest which self-assembles solely from the interconnected bodies of hundreds of thousands of individuals. These bivouacs are difficult to study because they rapidly disassemble when disturbed, and hence little is known about the structure and rules that individuals follow during their formation. Here we use a custom-built Computed Tomography scanner to investigate the details of the internal structure and growth process of army ant bivouacs. We show that bivouacs are heterogeneous structures, which throughout their growth maintain a thick shell surrounding a less dense interior that contains empty spaces akin to nest chambers. We find that ants within the bivouac do not carry more than approximately eight times their weight regardless of the size of the structure or their position within it. This observation suggests that bivouac size is not limited by physical constraints of the ants' morphology. This study brings us closer to understanding the rules used by individuals to govern the formation of these exceptional superorganismal structures, and provides insight into how to create engineered self-assembling systems with, for instance, swarms of robots or active matter.
|
2303.08822
|
Val\'erie Voorsluijs
|
Val\'erie Voorsluijs, Francesco Avanzini, Gianmaria Falasco,
Massimiliano Esposito, Alexander Skupin
|
Nonequilibrium calcium dynamics optimizes the energetic efficiency of
mitochondrial metabolism
| null | null | null | null |
q-bio.MN cond-mat.other cond-mat.stat-mech
|
http://creativecommons.org/licenses/by/4.0/
|
Living organisms continuously harness energy to perform complex functions for
their adaptation and survival while part of that energy is dissipated in the
form of heat or chemical waste. Determining the energetic cost and the
efficiency of specific cellular processes remains a largely open problem. Here,
we analyze the efficiency of mitochondrial adenosine triphosphate (ATP)
production through the tricarboxylic acid (TCA) cycle and oxidative
phosphorylation that generates most of the cellular chemical energy in
eukaryotes. The regulation of this pathway by calcium signaling represents a
well-characterized example of a regulatory cross-talk that can affect the
energetic output of a metabolic pathway, but its concrete energetic impact
remains elusive. On the one hand, calcium enhances ATP production by activating
key enzymes of the TCA cycle, but on the other hand calcium homeostasis depends
on ATP availability. To evaluate how calcium signaling impacts the efficiency
of mitochondrial metabolism, we propose a detailed kinetic model describing the
calcium-mitochondria cross-talk and we analyze it using a nonequilibrium
thermodynamic approach: after identifying the effective reactions driving
mitochondrial metabolism out of equilibrium, we quantify the thermodynamic
efficiency of the metabolic machinery for different physiological conditions.
We find that calcium oscillations increase the efficiency with a maximum close
to substrate-limited conditions, suggesting a compensatory effect of calcium
signaling on the energetics of mitochondrial metabolism.
|
[
{
"created": "Wed, 15 Mar 2023 13:24:39 GMT",
"version": "v1"
},
{
"created": "Wed, 29 Mar 2023 06:15:10 GMT",
"version": "v2"
},
{
"created": "Fri, 4 Aug 2023 16:28:23 GMT",
"version": "v3"
}
] |
2023-08-07
|
[
[
"Voorsluijs",
"Valérie",
""
],
[
"Avanzini",
"Francesco",
""
],
[
"Falasco",
"Gianmaria",
""
],
[
"Esposito",
"Massimiliano",
""
],
[
"Skupin",
"Alexander",
""
]
] |
Living organisms continuously harness energy to perform complex functions for their adaptation and survival while part of that energy is dissipated in the form of heat or chemical waste. Determining the energetic cost and the efficiency of specific cellular processes remains a largely open problem. Here, we analyze the efficiency of mitochondrial adenosine triphosphate (ATP) production through the tricarboxylic acid (TCA) cycle and oxidative phosphorylation that generates most of the cellular chemical energy in eukaryotes. The regulation of this pathway by calcium signaling represents a well-characterized example of a regulatory cross-talk that can affect the energetic output of a metabolic pathway, but its concrete energetic impact remains elusive. On the one hand, calcium enhances ATP production by activating key enzymes of the TCA cycle, but on the other hand calcium homeostasis depends on ATP availability. To evaluate how calcium signaling impacts the efficiency of mitochondrial metabolism, we propose a detailed kinetic model describing the calcium-mitochondria cross-talk and we analyze it using a nonequilibrium thermodynamic approach: after identifying the effective reactions driving mitochondrial metabolism out of equilibrium, we quantify the thermodynamic efficiency of the metabolic machinery for different physiological conditions. We find that calcium oscillations increase the efficiency with a maximum close to substrate-limited conditions, suggesting a compensatory effect of calcium signaling on the energetics of mitochondrial metabolism.
|
1703.04022
|
Christian Temp Kerskens
|
Christian Kerskens
|
Comments on the arterial spin labelling quantification recommended by
the ISMRM perfusion study group and the European consortium for ASL in
dementia
|
not relevant anymore
| null | null | null |
q-bio.OT
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
A petition for more careful considerations towards the usage of a
quantification approach for ASL which has been recommended by the ISMRM
perfusion study group and the European consortium for ASL in dementia.
|
[
{
"created": "Sat, 11 Mar 2017 19:47:45 GMT",
"version": "v1"
},
{
"created": "Fri, 2 Jun 2017 18:12:29 GMT",
"version": "v2"
}
] |
2017-06-06
|
[
[
"Kerskens",
"Christian",
""
]
] |
A petition for more careful considerations towards the usage of a quantification approach for ASL which has been recommended by the ISMRM perfusion study group and the European consortium for ASL in dementia.
|
2311.10443
|
Matthew Hartley
|
Teresa Zulueta-Coarasa, Florian Jug, Aastha Mathur, Josh Moore, Arrate
Mu\~noz-Barrutia, Liviu Anita, Kola Babalola, Pete Bankhead, Perrine
Gilloteaux, Nodar Gogoberidze, Martin Jones, Gerard J. Kleywegt, Paul Korir,
Anna Kreshuk, Ayb\"uke K\"upc\"u Yolda\c{s}, Luca Marconato, Kedar Narayan,
Nils Norlin, Bugra Oezdemir, Jessica Riesterer, Norman Rzepka, Ugis Sarkans,
Beatriz Serrano, Christian Tischer, Virginie Uhlmann, Vladim\'ir Ulman,
Matthew Hartley
|
MIFA: Metadata, Incentives, Formats, and Accessibility guidelines to
improve the reuse of AI datasets for bioimage analysis
|
16 pages, 3 figures
| null | null | null |
q-bio.OT eess.IV
|
http://creativecommons.org/licenses/by/4.0/
|
Artificial Intelligence methods are powerful tools for biological image
analysis and processing. High-quality annotated images are key to training and
developing new methods, but access to such data is often hindered by the lack
of standards for sharing datasets. We brought together community experts in a
workshop to develop guidelines to improve the reuse of bioimages and
annotations for AI applications. These include standards on data formats,
metadata, data presentation and sharing, and incentives to generate new
datasets. We are positive that the MIFA (Metadata, Incentives, Formats, and
Accessibility) recommendations will accelerate the development of AI tools for
bioimage analysis by facilitating access to high quality training data.
|
[
{
"created": "Fri, 17 Nov 2023 10:49:58 GMT",
"version": "v1"
},
{
"created": "Wed, 22 Nov 2023 09:31:32 GMT",
"version": "v2"
}
] |
2023-11-23
|
[
[
"Zulueta-Coarasa",
"Teresa",
""
],
[
"Jug",
"Florian",
""
],
[
"Mathur",
"Aastha",
""
],
[
"Moore",
"Josh",
""
],
[
"Muñoz-Barrutia",
"Arrate",
""
],
[
"Anita",
"Liviu",
""
],
[
"Babalola",
"Kola",
""
],
[
"Bankhead",
"Pete",
""
],
[
"Gilloteaux",
"Perrine",
""
],
[
"Gogoberidze",
"Nodar",
""
],
[
"Jones",
"Martin",
""
],
[
"Kleywegt",
"Gerard J.",
""
],
[
"Korir",
"Paul",
""
],
[
"Kreshuk",
"Anna",
""
],
[
"Yoldaş",
"Aybüke Küpcü",
""
],
[
"Marconato",
"Luca",
""
],
[
"Narayan",
"Kedar",
""
],
[
"Norlin",
"Nils",
""
],
[
"Oezdemir",
"Bugra",
""
],
[
"Riesterer",
"Jessica",
""
],
[
"Rzepka",
"Norman",
""
],
[
"Sarkans",
"Ugis",
""
],
[
"Serrano",
"Beatriz",
""
],
[
"Tischer",
"Christian",
""
],
[
"Uhlmann",
"Virginie",
""
],
[
"Ulman",
"Vladimír",
""
],
[
"Hartley",
"Matthew",
""
]
] |
Artificial Intelligence methods are powerful tools for biological image analysis and processing. High-quality annotated images are key to training and developing new methods, but access to such data is often hindered by the lack of standards for sharing datasets. We brought together community experts in a workshop to develop guidelines to improve the reuse of bioimages and annotations for AI applications. These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets. We are positive that the MIFA (Metadata, Incentives, Formats, and Accessibility) recommendations will accelerate the development of AI tools for bioimage analysis by facilitating access to high quality training data.
|
q-bio/0611058
|
Tilo Beyer
|
Tilo Beyer and Michael Meyer-Hermann
|
Mechanisms of organogenesis of primary lymphoid follicles
|
31 pages, 2 figures
| null | null | null |
q-bio.TO q-bio.CB
| null |
Primary lymphoid follicles in secondary lymphoid tissue of mammals are the
backbone for the formation of follicular dendritic cell networks. These are
important for germinal center reactions. In the context of organogenesis
molecular requirements for the formation of follicles have been identified. The
present study complements this work with a simulation of the dynamics of the
primary lymphoid follicle formation. In contrast to other problems of pattern
formation, here, the homeostasis of the cell population is not governed by a
growth-death balance but by a flow equilibrium of migrating cells. The influx
of cells into secondary lymphoid tissue was extensively studied while less
information is available about the efflux of lymphocytes from secondary
lymphoid tissues. This study formulates the minimal requirements for cell
efflux that guarantee a flow equilibrium and, thus, a stable primary lymphoid
follicle. The model predicts that in addition to already identified mechanisms
a negative regulation of the generation of follicular dendritic cells is
required. Furthermore, a comparison with data concerning the microanatomy of
secondary lymphoid tissues yields the conclusion that dynamical changes during
the formation of FDC networks of the lymphatic endothelium are necessary to
understand the genesis and maintenance of follicles.
|
[
{
"created": "Fri, 17 Nov 2006 16:05:03 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Beyer",
"Tilo",
""
],
[
"Meyer-Hermann",
"Michael",
""
]
] |
Primary lymphoid follicles in secondary lymphoid tissue of mammals are the backbone for the formation of follicular dendritic cell networks. These are important for germinal center reactions. In the context of organogenesis molecular requirements for the formation of follicles have been identified. The present study complements this work with a simulation of the dynamics of the primary lymphoid follicle formation. In contrast to other problems of pattern formation, here, the homeostasis of the cell population is not governed by a growth-death balance but by a flow equilibrium of migrating cells. The influx of cells into secondary lymphoid tissue was extensively studied while less information is available about the efflux of lymphocytes from secondary lymphoid tissues. This study formulates the minimal requirements for cell efflux that guarantee a flow equilibrium and, thus, a stable primary lymphoid follicle. The model predicts that in addition to already identified mechanisms a negative regulation of the generation of follicular dendritic cells is required. Furthermore, a comparison with data concerning the microanatomy of secondary lymphoid tissues yields the conclusion that dynamical changes during the formation of FDC networks of the lymphatic endothelium are necessary to understand the genesis and maintenance of follicles.
|
2401.04862
|
William Cannon
|
William R. Cannon, Ethan King, Katherine A. Huening and Justin A.
North
|
Redox Poise during Rhodospirillum rubrum Phototrophic Growth Drives
Large-scale Changes in Macromolecular Synthesis Pathways
| null | null | null | null |
q-bio.MN q-bio.CB q-bio.SC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
During photoheterotrophic growth on organic substrates, purple nonsulfur
photosynthetic bacteria like Rhodospirillum rubrum can acquire electrons by
multiple means, including oxidation of organic substrates, oxidation of
inorganic electron donors (e.g. H$_2$), and by reverse electron flow from the
photosynthetic electron transport chain. These electrons are stored in the form
of reduced electron-carrying cofactors (e.g. NAD(P)H and ferredoxin). The ratio
of oxidized to reduced redox cofactors (e.g. ratio of NAD(P)+:NAD(P)H), or
'redox poise` is difficult to understand or predict, as are the the cellular
processes for dissipating these reducing equivalents. Using physics-based
models that capture mass action kinetics consistent with the thermodynamics of
reactions and pathways, a range of redox conditions for heterophototrophic
growth are evaluated, from conditions in which the NADP+/NADPH levels
approached thermodynamic equilibrium to conditions in which the NADP+/NADPH
ratio is far above the typical physiological values. Modeling results together
with experimental measurements of macro molecule levels (DNA, RNA, proteins and
fatty acids) indicate that the redox poise of the cell results in large-scale
changes in the activity of biosynthetic pathways. Phototrophic growth is less
coupled than expected to producing reductant, NAD(P)H, by reverse electron flow
from the quinone pool. Instead, it primarily functions for ATP production
(photophosphorylation), which drives reduction even when NADPH levels are
relatively low compared to NADP+. The model, in agreement with experimental
measurements of macromolecule ratios of cells growing on different carbon
substrates, indicate that the dynamics of nucleotide versus lipid and protein
production is likely a significant mechanism of balancing oxidation and
reduction in the cell.
|
[
{
"created": "Wed, 10 Jan 2024 00:40:22 GMT",
"version": "v1"
}
] |
2024-01-11
|
[
[
"Cannon",
"William R.",
""
],
[
"King",
"Ethan",
""
],
[
"Huening",
"Katherine A.",
""
],
[
"North",
"Justin A.",
""
]
] |
During photoheterotrophic growth on organic substrates, purple nonsulfur photosynthetic bacteria like Rhodospirillum rubrum can acquire electrons by multiple means, including oxidation of organic substrates, oxidation of inorganic electron donors (e.g. H$_2$), and by reverse electron flow from the photosynthetic electron transport chain. These electrons are stored in the form of reduced electron-carrying cofactors (e.g. NAD(P)H and ferredoxin). The ratio of oxidized to reduced redox cofactors (e.g. ratio of NAD(P)+:NAD(P)H), or 'redox poise` is difficult to understand or predict, as are the the cellular processes for dissipating these reducing equivalents. Using physics-based models that capture mass action kinetics consistent with the thermodynamics of reactions and pathways, a range of redox conditions for heterophototrophic growth are evaluated, from conditions in which the NADP+/NADPH levels approached thermodynamic equilibrium to conditions in which the NADP+/NADPH ratio is far above the typical physiological values. Modeling results together with experimental measurements of macro molecule levels (DNA, RNA, proteins and fatty acids) indicate that the redox poise of the cell results in large-scale changes in the activity of biosynthetic pathways. Phototrophic growth is less coupled than expected to producing reductant, NAD(P)H, by reverse electron flow from the quinone pool. Instead, it primarily functions for ATP production (photophosphorylation), which drives reduction even when NADPH levels are relatively low compared to NADP+. The model, in agreement with experimental measurements of macromolecule ratios of cells growing on different carbon substrates, indicate that the dynamics of nucleotide versus lipid and protein production is likely a significant mechanism of balancing oxidation and reduction in the cell.
|
1808.08948
|
Tom Chou
|
Song Xu and Tom Chou
|
Immigration-induced phase transition in a regulated multispecies
birth-death process
|
22 pages, 8 figures, accepted to J. Phys. A
| null |
10.1088/1751-8121/aadcb4
| null |
q-bio.PE cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Power-law-distributed species counts or clone counts arise in many biological
settings such as multispecies cell populations, population genetics, and
ecology. This empirical observation that the number of species $c_{k}$
represented by $k$ individuals scales as negative powers of $k$ is also
supported by a series of theoretical birth-death-immigration (BDI) models that
consistently predict many low-population species, a few intermediate-population
species, and very high-population species. However, we show how a simple global
population-dependent regulation in a neutral BDI model destroys the power law
distributions. Simulation of the regulated BDI model shows a high probability
of observing a high-population species that dominates the total population.
Further analysis reveals that the origin of this breakdown is associated with
the failure of a mean-field approximation for the expected species abundance
distribution. We find an accurate estimate for the expected distribution
$\langle c_k \rangle$ by mapping the problem to a lower-dimensional Moran
process, allowing us to also straightforwardly calculate the covariances
$\langle c_k c_\ell \rangle$. Finally, we exploit the concepts associated with
energy landscapes to explain the failure of the mean-field assumption by
identifying a phase transition in the quasi-steady-state species counts
triggered by a decreasing immigration rate.
|
[
{
"created": "Mon, 27 Aug 2018 17:54:22 GMT",
"version": "v1"
}
] |
2018-09-26
|
[
[
"Xu",
"Song",
""
],
[
"Chou",
"Tom",
""
]
] |
Power-law-distributed species counts or clone counts arise in many biological settings such as multispecies cell populations, population genetics, and ecology. This empirical observation that the number of species $c_{k}$ represented by $k$ individuals scales as negative powers of $k$ is also supported by a series of theoretical birth-death-immigration (BDI) models that consistently predict many low-population species, a few intermediate-population species, and very high-population species. However, we show how a simple global population-dependent regulation in a neutral BDI model destroys the power law distributions. Simulation of the regulated BDI model shows a high probability of observing a high-population species that dominates the total population. Further analysis reveals that the origin of this breakdown is associated with the failure of a mean-field approximation for the expected species abundance distribution. We find an accurate estimate for the expected distribution $\langle c_k \rangle$ by mapping the problem to a lower-dimensional Moran process, allowing us to also straightforwardly calculate the covariances $\langle c_k c_\ell \rangle$. Finally, we exploit the concepts associated with energy landscapes to explain the failure of the mean-field assumption by identifying a phase transition in the quasi-steady-state species counts triggered by a decreasing immigration rate.
|
2302.07820
|
Walid Hachem
|
Imane Akjouj, Walid Hachem, Myl\`ene Ma\"ida, Jamal Najim
|
Equilibria of large random Lotka-Volterra systems with vanishing
species: a mathematical approach
| null | null | null | null |
q-bio.PE math.PR
|
http://creativecommons.org/licenses/by/4.0/
|
Ecosystems with a large number of species are often modelled as
Lotka-Volterra dynamical systems built around a large random interaction
matrix. Under some known conditions, a global equilibrium exists and is unique.
In this article, we rigorously study its statistical properties in the large
dimensional regime. Such an equilibrium vector is known to be the solution of a
so-called Linear Complementarity Problem (LCP). We describe its statistical
properties by designing an Approximate Message Passing (AMP) algorithm, a
technique that has recently aroused an intense research effort in the fields of
statistical physics, Machine Learning, or communication theory. Interaction
matrices taken from the Gaussian Orthogonal Ensemble, or following a Wishart
distribution are considered. Beyond these models, the AMP approach developed in
this article has the potential to describe the statistical properties of
equilibria associated to more involved interaction matrix models.
|
[
{
"created": "Wed, 15 Feb 2023 18:01:48 GMT",
"version": "v1"
},
{
"created": "Mon, 31 Jul 2023 12:45:41 GMT",
"version": "v2"
}
] |
2023-08-01
|
[
[
"Akjouj",
"Imane",
""
],
[
"Hachem",
"Walid",
""
],
[
"Maïda",
"Mylène",
""
],
[
"Najim",
"Jamal",
""
]
] |
Ecosystems with a large number of species are often modelled as Lotka-Volterra dynamical systems built around a large random interaction matrix. Under some known conditions, a global equilibrium exists and is unique. In this article, we rigorously study its statistical properties in the large dimensional regime. Such an equilibrium vector is known to be the solution of a so-called Linear Complementarity Problem (LCP). We describe its statistical properties by designing an Approximate Message Passing (AMP) algorithm, a technique that has recently aroused an intense research effort in the fields of statistical physics, Machine Learning, or communication theory. Interaction matrices taken from the Gaussian Orthogonal Ensemble, or following a Wishart distribution are considered. Beyond these models, the AMP approach developed in this article has the potential to describe the statistical properties of equilibria associated to more involved interaction matrix models.
|
1908.02316
|
Matthias Fischer
|
Matthias M. Fischer
|
A mechanistic model of disjunctive metabolic symbioses in microbes
|
19 pages, 4 figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Lately, experimental research on microbial symbioses based on nutrient
exchange and interdependence has yielded a number of interesting findings,
however an in-depth mathematical description of the exact underlying dynamics
of such symbiotic associations is still missing. Here, we derive and analyse a
mechanistic mathematical model of such a relationship in a continuous chemostat
culture based on five coupled differential equations. The influence of the
biological traits of the involved organisms on the position and stability of
the equilibrium states of the system is examined. We also demonstrate how
manipulating the external metabolite concentrations of the system can shift the
species interaction on a continuous spectrum ranging from mutualism over
commensalism to parasitism.
|
[
{
"created": "Tue, 6 Aug 2019 18:32:49 GMT",
"version": "v1"
}
] |
2019-08-08
|
[
[
"Fischer",
"Matthias M.",
""
]
] |
Lately, experimental research on microbial symbioses based on nutrient exchange and interdependence has yielded a number of interesting findings, however an in-depth mathematical description of the exact underlying dynamics of such symbiotic associations is still missing. Here, we derive and analyse a mechanistic mathematical model of such a relationship in a continuous chemostat culture based on five coupled differential equations. The influence of the biological traits of the involved organisms on the position and stability of the equilibrium states of the system is examined. We also demonstrate how manipulating the external metabolite concentrations of the system can shift the species interaction on a continuous spectrum ranging from mutualism over commensalism to parasitism.
|
1601.01788
|
Taoyang Wu
|
Katharina T. Huber and Vincent Moulton and Taoyang Wu
|
Transforming phylogenetic networks: Moving beyond tree space
|
27 pages, 13 figures
| null | null | null |
q-bio.PE math.CO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Phylogenetic networks are a generalization of phylogenetic trees that are
used to represent reticulate evolution. Unrooted phylogenetic networks form a
special class of such networks, which naturally generalize unrooted
phylogenetic trees. In this paper we define two operations on unrooted
phylogenetic networks, one of which is a generalization of the well-known
nearest-neighbor interchange (NNI) operation on phylogenetic trees. We show
that any unrooted phylogenetic network can be transformed into any other such
network using only these operations. This generalizes the well-known fact that
any phylogenetic tree can be transformed into any other such tree using only
NNI operations. It also allows us to define a generalization of tree space and
to define some new metrics on unrooted phylogenetic networks. To prove our main
results, we employ some fascinating new connections between phylogenetic
networks and cubic graphs that we have recently discovered. Our results should
be useful in developing new strategies to search for optimal phylogenetic
networks, a topic that has recently generated some interest in the literature,
as well as for providing new ways to compare networks.
|
[
{
"created": "Fri, 8 Jan 2016 08:10:24 GMT",
"version": "v1"
}
] |
2016-01-11
|
[
[
"Huber",
"Katharina T.",
""
],
[
"Moulton",
"Vincent",
""
],
[
"Wu",
"Taoyang",
""
]
] |
Phylogenetic networks are a generalization of phylogenetic trees that are used to represent reticulate evolution. Unrooted phylogenetic networks form a special class of such networks, which naturally generalize unrooted phylogenetic trees. In this paper we define two operations on unrooted phylogenetic networks, one of which is a generalization of the well-known nearest-neighbor interchange (NNI) operation on phylogenetic trees. We show that any unrooted phylogenetic network can be transformed into any other such network using only these operations. This generalizes the well-known fact that any phylogenetic tree can be transformed into any other such tree using only NNI operations. It also allows us to define a generalization of tree space and to define some new metrics on unrooted phylogenetic networks. To prove our main results, we employ some fascinating new connections between phylogenetic networks and cubic graphs that we have recently discovered. Our results should be useful in developing new strategies to search for optimal phylogenetic networks, a topic that has recently generated some interest in the literature, as well as for providing new ways to compare networks.
|
2102.12374
|
Kasey Laurent
|
Kasey M. Laurent, Bob Fogg, Tobias Ginsburg, Casey Halverson, Michael
Lanzone, Tricia A. Miller, David W. Winkler, Gregory P. Bewley
|
Turbulence explains the accelerations of an eagle in natural flight
|
21 pages, 4 figures
| null |
10.1073/pnas.2102588118
| null |
q-bio.QM physics.bio-ph physics.flu-dyn
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Turbulent winds and gusts fluctuate on a wide range of timescales from
milliseconds to minutes and longer, a range that overlaps the timescales of
avian flight behavior, yet the importance of turbulence to avian behavior is
unclear. By combining wind speed data with the measured accelerations of a
golden eagle (Aquila chrysaetos) flying in the wild, we show that the eagle's
accelerations can be explained by a linear interaction with turbulence for
timescales between about 1/2 and 10 s. These timescales are comparable to those
of typical eagle behaviors, corresponding to between about 1 and 25 wingbeats,
and to those of turbulent gusts both larger than the eagle's wingspan and
smaller than large-scale atmospheric phenomena such as convection cells. The
eagle's accelerations exhibit power spectra and intermittent activity
characteristic of turbulence, and increase in proportion to the turbulence
intensity. Intermittency results in accelerations that are occasionally several
times stronger than gravity, and much larger than the ones we experience while
driving, for instance. These imprints of turbulence on the bird's movements
need to be further explored to understand the energetics of birds and other
volant lifeforms, to improve our own methods of flying through ceaselessly
turbulent environments, and to engage airborne wildlife as distributed probes
of the changing conditions in the atmosphere.
|
[
{
"created": "Fri, 19 Feb 2021 15:56:34 GMT",
"version": "v1"
},
{
"created": "Tue, 2 Mar 2021 17:13:17 GMT",
"version": "v2"
},
{
"created": "Tue, 4 May 2021 13:51:03 GMT",
"version": "v3"
},
{
"created": "Wed, 19 May 2021 16:46:15 GMT",
"version": "v4"
}
] |
2021-07-07
|
[
[
"Laurent",
"Kasey M.",
""
],
[
"Fogg",
"Bob",
""
],
[
"Ginsburg",
"Tobias",
""
],
[
"Halverson",
"Casey",
""
],
[
"Lanzone",
"Michael",
""
],
[
"Miller",
"Tricia A.",
""
],
[
"Winkler",
"David W.",
""
],
[
"Bewley",
"Gregory P.",
""
]
] |
Turbulent winds and gusts fluctuate on a wide range of timescales from milliseconds to minutes and longer, a range that overlaps the timescales of avian flight behavior, yet the importance of turbulence to avian behavior is unclear. By combining wind speed data with the measured accelerations of a golden eagle (Aquila chrysaetos) flying in the wild, we show that the eagle's accelerations can be explained by a linear interaction with turbulence for timescales between about 1/2 and 10 s. These timescales are comparable to those of typical eagle behaviors, corresponding to between about 1 and 25 wingbeats, and to those of turbulent gusts both larger than the eagle's wingspan and smaller than large-scale atmospheric phenomena such as convection cells. The eagle's accelerations exhibit power spectra and intermittent activity characteristic of turbulence, and increase in proportion to the turbulence intensity. Intermittency results in accelerations that are occasionally several times stronger than gravity, and much larger than the ones we experience while driving, for instance. These imprints of turbulence on the bird's movements need to be further explored to understand the energetics of birds and other volant lifeforms, to improve our own methods of flying through ceaselessly turbulent environments, and to engage airborne wildlife as distributed probes of the changing conditions in the atmosphere.
|
2310.13866
|
Grzegorz A Rempala
|
Grzegorz A. Rempala
|
Equivalence of Mass Action and Poisson Network SIR Epidemic Models
|
2 figures
| null | null | null |
q-bio.PE math.DS
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
This brief note highlights a largely overlooked similarity between the SIR
ordinary differential equations used for epidemics on the configuration model
of a Poisson network and the classical mass-action SIR equations introduced
nearly a century ago by Kermack and McKendrick. We demonstrate that the decline
pattern in susceptibles is identical for both models. This equivalence carries
practical implications: the susceptibles decay curve, often referred to as the
epidemic or incidence curve, is frequently used in empirical studies to
forecast epidemic dynamics. Although the curves for susceptibles align
perfectly, those for infections do differ. Yet, the infection curves tend to
converge and become almost indistinguishable in high-degree networks. In
summary, our analysis suggests that under many practical scenarios, it is
acceptable to use the classical SIR model as a close approximation to the
Poisson SIR network model.
|
[
{
"created": "Sat, 21 Oct 2023 00:07:48 GMT",
"version": "v1"
}
] |
2023-10-24
|
[
[
"Rempala",
"Grzegorz A.",
""
]
] |
This brief note highlights a largely overlooked similarity between the SIR ordinary differential equations used for epidemics on the configuration model of a Poisson network and the classical mass-action SIR equations introduced nearly a century ago by Kermack and McKendrick. We demonstrate that the decline pattern in susceptibles is identical for both models. This equivalence carries practical implications: the susceptibles decay curve, often referred to as the epidemic or incidence curve, is frequently used in empirical studies to forecast epidemic dynamics. Although the curves for susceptibles align perfectly, those for infections do differ. Yet, the infection curves tend to converge and become almost indistinguishable in high-degree networks. In summary, our analysis suggests that under many practical scenarios, it is acceptable to use the classical SIR model as a close approximation to the Poisson SIR network model.
|
2003.08684
|
Silvia Licciardi
|
Giuseppe Dattoli, Emanuele Di Palma, Silvia Licciardi, Elio Sabia
|
A Note on the Evolution of Covid-19 in Italy
|
10 pages, 11 figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We employ methods largely exploited in Physics, in the analysis of the
evolution of dynamical systems, to study the pattern of the Covid-19 infection
in Italy. The techniques we employ are based on the use of logistic function
and of its derivative, namely the Hubbert function. The latter is exploited to
give a prediction on the number of infected per day. We also mention the
possibility of taking advantage from other mathematical tools based e.g. on the
Gompertz equation and make some comparison on the different predictive
capabilities.
|
[
{
"created": "Thu, 19 Mar 2020 11:05:07 GMT",
"version": "v1"
}
] |
2020-03-20
|
[
[
"Dattoli",
"Giuseppe",
""
],
[
"Di Palma",
"Emanuele",
""
],
[
"Licciardi",
"Silvia",
""
],
[
"Sabia",
"Elio",
""
]
] |
We employ methods largely exploited in Physics, in the analysis of the evolution of dynamical systems, to study the pattern of the Covid-19 infection in Italy. The techniques we employ are based on the use of logistic function and of its derivative, namely the Hubbert function. The latter is exploited to give a prediction on the number of infected per day. We also mention the possibility of taking advantage from other mathematical tools based e.g. on the Gompertz equation and make some comparison on the different predictive capabilities.
|
1003.4756
|
Douady Stephane
|
Etienne Couturier, Sylvain Courrech du Pont, St\'ephane Douady
|
The filling law: a general framework for leaf shape diversity and its
consequences on folded leaves
|
27 p., 28 fig., article
| null | null | null |
q-bio.TO nlin.AO
|
http://creativecommons.org/licenses/by-nc-sa/3.0/
|
Leaves are packed in a bud in different ways, being flat, enrolled, or
folded, but always filling the whole bud volume. This {\guillemotleft} filling
law {\guillemotright} has many consequences, in particular on the shape of
growing folded leaves. This is shown here for different types of folding and
packing. The folded volume is always part of an ellipsoid, with the veins on
the outside rounded face, and the lamina margin on an adaxial plane or axis.
The veins on the abaxial side protect the more fragile lamina. The first
general consequence of the folds is the presence of symmetries on the leaf
shape, but also quantitative relationships between lobes and sinus sizes. For
particular geometries, the leaf lamina can be limited by lateral veins,
creating spoon-like lobes, or transverse cuts, creating asymmetrical wavy
perimeters. A change in the packing between cultivars induces the corresponding
change in the leaf shape. Each particular case shows how pervasive are the
geometrical consequences of the filling law.
|
[
{
"created": "Wed, 24 Mar 2010 21:26:25 GMT",
"version": "v1"
},
{
"created": "Thu, 7 Oct 2010 20:06:13 GMT",
"version": "v2"
}
] |
2010-10-11
|
[
[
"Couturier",
"Etienne",
""
],
[
"Pont",
"Sylvain Courrech du",
""
],
[
"Douady",
"Stéphane",
""
]
] |
Leaves are packed in a bud in different ways, being flat, enrolled, or folded, but always filling the whole bud volume. This {\guillemotleft} filling law {\guillemotright} has many consequences, in particular on the shape of growing folded leaves. This is shown here for different types of folding and packing. The folded volume is always part of an ellipsoid, with the veins on the outside rounded face, and the lamina margin on an adaxial plane or axis. The veins on the abaxial side protect the more fragile lamina. The first general consequence of the folds is the presence of symmetries on the leaf shape, but also quantitative relationships between lobes and sinus sizes. For particular geometries, the leaf lamina can be limited by lateral veins, creating spoon-like lobes, or transverse cuts, creating asymmetrical wavy perimeters. A change in the packing between cultivars induces the corresponding change in the leaf shape. Each particular case shows how pervasive are the geometrical consequences of the filling law.
|
q-bio/0701038
|
Vittoria Colizza
|
Vittoria Colizza, Alain Barrat, Marc Barthelemy, Alain-Jacques
Valleron, Alessandro Vespignani
|
Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and
Containment Interventions
|
16 pages
|
PLoS Med 4(1): e13. (2007)
|
10.1371/journal.pmed.0040013
| null |
q-bio.OT cond-mat.stat-mech physics.soc-ph
| null |
We present a study of the worldwide spread of a pandemic influenza and its
possible containment at a global level taking into account all available
information on air travel. We studied a metapopulation stochastic epidemic
model on a global scale that considers airline travel flow data among urban
areas. We provided a temporal and spatial evolution of the pandemic with a
sensitivity analysis of different levels of infectiousness of the virus and
initial outbreak conditions (both geographical and seasonal). For each
spreading scenario we provided the timeline and the geographical impact of the
pandemic in 3,100 urban areas, located in 220 different countries. We compared
the baseline cases with different containment strategies, including travel
restrictions and the therapeutic use of antiviral (AV) drugs. We show that the
inclusion of air transportation is crucial in the assessment of the occurrence
probability of global outbreaks. The large-scale therapeutic usage of AV drugs
in all hit countries would be able to mitigate a pandemic effect with a
reproductive rate as high as 1.9 during the first year; with AV supply use
sufficient to treat approximately 2% to 6% of the population, in conjunction
with efficient case detection and timely drug distribution. For highly
contagious viruses (i.e., a reproductive rate as high as 2.3), even the
unrealistic use of supplies corresponding to the treatment of approximately 20%
of the population leaves 30%-50% of the population infected. In the case of
limited AV supplies and pandemics with a reproductive rate as high as 1.9, we
demonstrate that the more cooperative the strategy, the more effective are the
containment results in all regions of the world, including those countries that
made part of their resources available for global use.
|
[
{
"created": "Wed, 24 Jan 2007 18:32:50 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Colizza",
"Vittoria",
""
],
[
"Barrat",
"Alain",
""
],
[
"Barthelemy",
"Marc",
""
],
[
"Valleron",
"Alain-Jacques",
""
],
[
"Vespignani",
"Alessandro",
""
]
] |
We present a study of the worldwide spread of a pandemic influenza and its possible containment at a global level taking into account all available information on air travel. We studied a metapopulation stochastic epidemic model on a global scale that considers airline travel flow data among urban areas. We provided a temporal and spatial evolution of the pandemic with a sensitivity analysis of different levels of infectiousness of the virus and initial outbreak conditions (both geographical and seasonal). For each spreading scenario we provided the timeline and the geographical impact of the pandemic in 3,100 urban areas, located in 220 different countries. We compared the baseline cases with different containment strategies, including travel restrictions and the therapeutic use of antiviral (AV) drugs. We show that the inclusion of air transportation is crucial in the assessment of the occurrence probability of global outbreaks. The large-scale therapeutic usage of AV drugs in all hit countries would be able to mitigate a pandemic effect with a reproductive rate as high as 1.9 during the first year; with AV supply use sufficient to treat approximately 2% to 6% of the population, in conjunction with efficient case detection and timely drug distribution. For highly contagious viruses (i.e., a reproductive rate as high as 2.3), even the unrealistic use of supplies corresponding to the treatment of approximately 20% of the population leaves 30%-50% of the population infected. In the case of limited AV supplies and pandemics with a reproductive rate as high as 1.9, we demonstrate that the more cooperative the strategy, the more effective are the containment results in all regions of the world, including those countries that made part of their resources available for global use.
|
1810.10894
|
Panteleimon Vafeidis
|
Panteleimon Vafeidis, Vasilios K. Kimiskidis, Dimitris Kugiumtzis
|
Evaluation of algorithms for correction of transcranial magnetic
stimulation induced artifacts in electroencephalograms
|
18 pages, 7 figures, 2 tables. Med Biol Eng Comput (2019)
| null |
10.1007/s11517-019-02053-3
| null |
q-bio.QM q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Transcranial magnetic stimulation combined with electroencephalography
(TMS-EEG) is widely used to study the reactivity and connectivity of brain
regions for clinical or research purposes. The electromagnetic pulse of the TMS
device generates at the instant of administration an artifact of large
amplitude and a duration up to tens of milliseconds that overlaps with brain
activity. Methods for TMS artifact correction have been developed to remove the
artifact and recover the underlying, immediate response of the cerebral cortex
to the magnetic stimulus. In this study, three such algorithms are evaluated.
Since there is no ground truth for the masked brain activity, pilot data formed
from the superposition of the isolated TMS artifact on the EEG brain activity
are used to evaluate the performance of the algorithms. Different scenarios of
TMS-EEG experiments are considered for the evaluation: TMS at resting state,
TMS inducing epileptiform discharges and TMS administered during epileptiform
discharges. We show that a proposed gap filling method is able to reproduce
qualitative characteristics and in many cases closely resemble the hidden EEG
signal. Finally, shortcomings of the TMS correction algorithms as well as the
pilot data approach are discussed.
|
[
{
"created": "Thu, 25 Oct 2018 14:27:26 GMT",
"version": "v1"
}
] |
2019-10-30
|
[
[
"Vafeidis",
"Panteleimon",
""
],
[
"Kimiskidis",
"Vasilios K.",
""
],
[
"Kugiumtzis",
"Dimitris",
""
]
] |
Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is widely used to study the reactivity and connectivity of brain regions for clinical or research purposes. The electromagnetic pulse of the TMS device generates at the instant of administration an artifact of large amplitude and a duration up to tens of milliseconds that overlaps with brain activity. Methods for TMS artifact correction have been developed to remove the artifact and recover the underlying, immediate response of the cerebral cortex to the magnetic stimulus. In this study, three such algorithms are evaluated. Since there is no ground truth for the masked brain activity, pilot data formed from the superposition of the isolated TMS artifact on the EEG brain activity are used to evaluate the performance of the algorithms. Different scenarios of TMS-EEG experiments are considered for the evaluation: TMS at resting state, TMS inducing epileptiform discharges and TMS administered during epileptiform discharges. We show that a proposed gap filling method is able to reproduce qualitative characteristics and in many cases closely resemble the hidden EEG signal. Finally, shortcomings of the TMS correction algorithms as well as the pilot data approach are discussed.
|
2405.00838
|
Jayoung Ryu
|
Jayoung Ryu, Romain Lopez, Charlotte Bunne, Aviv Regev
|
Cross-modality Matching and Prediction of Perturbation Responses with
Labeled Gromov-Wasserstein Optimal Transport
|
16 pages, 4 figures, correspondence to Aviv Regev and Romain Lopez
| null | null | null |
q-bio.GN math.OC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
It is now possible to conduct large scale perturbation screens with complex
readout modalities, such as different molecular profiles or high content cell
images. While these open the way for systematic dissection of causal cell
circuits, integrated such data across screens to maximize our ability to
predict circuits poses substantial computational challenges, which have not
been addressed. Here, we extend two Gromov-Wasserstein Optimal Transport
methods to incorporate the perturbation label for cross-modality alignment. The
obtained alignment is then employed to train a predictive model that estimates
cellular responses to perturbations observed with only one measurement
modality. We validate our method for the tasks of cross-modality alignment and
cross-modality prediction in a recent multi-modal single-cell perturbation
dataset. Our approach opens the way to unified causal models of cell biology.
|
[
{
"created": "Wed, 1 May 2024 19:59:45 GMT",
"version": "v1"
}
] |
2024-05-03
|
[
[
"Ryu",
"Jayoung",
""
],
[
"Lopez",
"Romain",
""
],
[
"Bunne",
"Charlotte",
""
],
[
"Regev",
"Aviv",
""
]
] |
It is now possible to conduct large scale perturbation screens with complex readout modalities, such as different molecular profiles or high content cell images. While these open the way for systematic dissection of causal cell circuits, integrated such data across screens to maximize our ability to predict circuits poses substantial computational challenges, which have not been addressed. Here, we extend two Gromov-Wasserstein Optimal Transport methods to incorporate the perturbation label for cross-modality alignment. The obtained alignment is then employed to train a predictive model that estimates cellular responses to perturbations observed with only one measurement modality. We validate our method for the tasks of cross-modality alignment and cross-modality prediction in a recent multi-modal single-cell perturbation dataset. Our approach opens the way to unified causal models of cell biology.
|
1807.11654
|
Akram Yazdani PhD
|
Akram Yazdani, Raul Mendez Giraldez, Ahmad Samiei
|
Insights into Complex Brain Functions Related to Schizophrenia Disorder
through Causal Network Analysis
| null | null | null | null |
q-bio.GN q-bio.MN q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Gene expression represents a fundamental interface between genes and
environment in the development and ongoing plasticity of the human organism.
Individual differences in gene expression are likely to underpin much of human
diversity, including psychiatric illness. Gene expression shows a distinct
regulatory pattern in different tissues. Therefore, brain tissue analysis
provides insights into brain disorder mechanisms. Furthermore, mechanistic
understanding of gene regulatory pattern can be provided through studying the
underlying relationships as a complex network. Identification of brain specific
gene relationships provides a complementary framework in which to tackle the
complex dysregulations that occur in neuropsychiatric and other neurological
disorders. Using a systems approach established in Mendelian randomization and
Bayesian Network, we integrated genetic and transcriptomic data from the
common-mind consortium and identified transcriptomic causal networks in
observational studies. Focusing on Schizophrenia disorder, we identified high
impact genes and revealed their underlying pathways in brain tissue. In
addition, we generated novel hypotheses including genes as causes of the
schizophrenia-associated genes and new genes associated with Schizophrenia.
This approach may facilitate a better understanding of the disease mechanism
that is complementary to molecular experimental studies especially for complex
systems and large-scale data sets.
|
[
{
"created": "Tue, 31 Jul 2018 04:18:22 GMT",
"version": "v1"
},
{
"created": "Tue, 28 May 2019 14:02:50 GMT",
"version": "v2"
}
] |
2019-05-31
|
[
[
"Yazdani",
"Akram",
""
],
[
"Giraldez",
"Raul Mendez",
""
],
[
"Samiei",
"Ahmad",
""
]
] |
Gene expression represents a fundamental interface between genes and environment in the development and ongoing plasticity of the human organism. Individual differences in gene expression are likely to underpin much of human diversity, including psychiatric illness. Gene expression shows a distinct regulatory pattern in different tissues. Therefore, brain tissue analysis provides insights into brain disorder mechanisms. Furthermore, mechanistic understanding of gene regulatory pattern can be provided through studying the underlying relationships as a complex network. Identification of brain specific gene relationships provides a complementary framework in which to tackle the complex dysregulations that occur in neuropsychiatric and other neurological disorders. Using a systems approach established in Mendelian randomization and Bayesian Network, we integrated genetic and transcriptomic data from the common-mind consortium and identified transcriptomic causal networks in observational studies. Focusing on Schizophrenia disorder, we identified high impact genes and revealed their underlying pathways in brain tissue. In addition, we generated novel hypotheses including genes as causes of the schizophrenia-associated genes and new genes associated with Schizophrenia. This approach may facilitate a better understanding of the disease mechanism that is complementary to molecular experimental studies especially for complex systems and large-scale data sets.
|
2405.01664
|
Dilawar Ahmad Mir
|
Dilawar Ahmad Mir, Zhengxin Ma, Jordan Horrocks, Aric N Rogers
|
Stress-induced Eukaryotic Translational Regulatory Mechanisms
|
37 Pages, Figures 7, Review Article
| null | null | null |
q-bio.MN
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
The eukaryotic protein synthesis process entails intricate stages governed by
diverse mechanisms to tightly regulate translation. Translational regulation
during stress is pivotal for maintaining cellular homeostasis, ensuring the
accurate expression of essential proteins crucial for survival. This selective
translational control mechanism is integral to cellular adaptation and
resilience under adverse conditions. This review manuscript explores various
mechanisms involved in selective translational regulation, focusing on
mRNA-specific and global regulatory processes. Key aspects of translational
control include translation initiation, which is often a rate-limiting step,
and involves the formation of the eIF4F complex and recruitment of mRNA to
ribosomes. Regulation of translation initiation factors, such as eIF4E, eIF4E2,
and eIF2, through phosphorylation and interactions with binding proteins,
modulates translation efficiency under stress conditions. This review also
highlights the control of translation initiation through factors like the eIF4F
complex and the ternary complex and also underscores the importance of
eIF2{\alpha} phosphorylation in stress granule formation and cellular stress
responses. Additionally, the impact of amino acid deprivation, mTOR signaling,
and ribosome biogenesis on translation regulation and cellular adaptation to
stress is also discussed. Understanding the intricate mechanisms of
translational regulation during stress provides insights into cellular
adaptation mechanisms and potential therapeutic targets for various diseases,
offering valuable avenues for addressing conditions associated with
dysregulated protein synthesis.
|
[
{
"created": "Thu, 2 May 2024 18:34:53 GMT",
"version": "v1"
}
] |
2024-05-06
|
[
[
"Mir",
"Dilawar Ahmad",
""
],
[
"Ma",
"Zhengxin",
""
],
[
"Horrocks",
"Jordan",
""
],
[
"Rogers",
"Aric N",
""
]
] |
The eukaryotic protein synthesis process entails intricate stages governed by diverse mechanisms to tightly regulate translation. Translational regulation during stress is pivotal for maintaining cellular homeostasis, ensuring the accurate expression of essential proteins crucial for survival. This selective translational control mechanism is integral to cellular adaptation and resilience under adverse conditions. This review manuscript explores various mechanisms involved in selective translational regulation, focusing on mRNA-specific and global regulatory processes. Key aspects of translational control include translation initiation, which is often a rate-limiting step, and involves the formation of the eIF4F complex and recruitment of mRNA to ribosomes. Regulation of translation initiation factors, such as eIF4E, eIF4E2, and eIF2, through phosphorylation and interactions with binding proteins, modulates translation efficiency under stress conditions. This review also highlights the control of translation initiation through factors like the eIF4F complex and the ternary complex and also underscores the importance of eIF2{\alpha} phosphorylation in stress granule formation and cellular stress responses. Additionally, the impact of amino acid deprivation, mTOR signaling, and ribosome biogenesis on translation regulation and cellular adaptation to stress is also discussed. Understanding the intricate mechanisms of translational regulation during stress provides insights into cellular adaptation mechanisms and potential therapeutic targets for various diseases, offering valuable avenues for addressing conditions associated with dysregulated protein synthesis.
|
2202.13282
|
Vijay Rajagopal
|
Vijay Rajagopal, Senthil Arumugam, Peter Hunter, Afshin Khadangi,
Joshua Chung, Michael Pan
|
The Cell Physiome: What do we need in a computational physiology
framework for predicting single cell biology?
|
Minor text edits to fix minor grammatical errors and figure reference
| null | null | null |
q-bio.CB physics.bio-ph q-bio.QM q-bio.SC
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Modern biology and biomedicine are undergoing a big-data explosion needing
advanced computational algorithms to extract mechanistic insights on the
physiological state of living cells. We present the motivation for the Cell
Physiome: a framework and approach for creating, sharing, and using
biophysics-based computational models of single cell physiology. Using examples
in calcium signaling, bioenergetics, and endosomal trafficking, we highlight
the need for spatially detailed, biophysics-based computational models to
uncover new mechanisms underlying cell biology. We review progress and
challenges to date towards creating cell physiome models. We then introduce
bond graphs as an efficient way to create cell physiome models that integrate
chemical, mechanical, electromagnetic, and thermal processes while maintaining
mass and energy balance. Bond graphs enhance modularization and re-usability of
computational models of cells at scale. We conclude with a look forward into
steps that will help fully realize this exciting new field of mechanistic
biomedical data science.
|
[
{
"created": "Sun, 27 Feb 2022 03:36:45 GMT",
"version": "v1"
},
{
"created": "Sat, 5 Mar 2022 05:02:27 GMT",
"version": "v2"
}
] |
2022-03-08
|
[
[
"Rajagopal",
"Vijay",
""
],
[
"Arumugam",
"Senthil",
""
],
[
"Hunter",
"Peter",
""
],
[
"Khadangi",
"Afshin",
""
],
[
"Chung",
"Joshua",
""
],
[
"Pan",
"Michael",
""
]
] |
Modern biology and biomedicine are undergoing a big-data explosion needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome: a framework and approach for creating, sharing, and using biophysics-based computational models of single cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date towards creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and re-usability of computational models of cells at scale. We conclude with a look forward into steps that will help fully realize this exciting new field of mechanistic biomedical data science.
|
2005.02188
|
Guo-Wei Wei
|
Rui Wang, Yuta Hozumi, Changchuan Yin and Guo-Wei Wei
|
Mutations on COVID-19 diagnostic targets
|
3 tables and 6 pages, and 48 tables in the Supporting Material
| null | null | null |
q-bio.GN q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Effective, sensitive, and reliable diagnostic reagents are of paramount
importance for combating the ongoing coronavirus disease 2019 (COVID-19)
pandemic at a time there is no preventive vaccine nor specific drug available
for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It would be
an absolute tragedy if currently used diagnostic reagents are undermined in any
manner. Based on the genotyping of 7818 SARS-CoV-2 genome samples collected up
to May 1, 2020, we reveal that essentially all of the current COVID-19
diagnostic targets have had mutations. We further show that SARS-CoV-2 has the
most devastating mutations on the targets of various nucleocapsid (N) gene
primers and probes, which have been unfortunately used by countries around the
world to diagnose COVID-19. Our findings explain what has seriously gone wrong
with a specific diagnostic reagent made in China. To understand whether
SARS-CoV-2 genes have mutated unevenly, we have computed the mutation ratio and
mutation $h$-index of all SARS-CoV genes, indicating that the N gene is the
most non-conservative gene in the SARS-CoV-2 genome. Our findings enable
researchers to target the most conservative SARS-CoV-2 genes and proteins for
the design and development of COVID-19 diagnostic reagents, preventive
vaccines, and therapeutic medicines.
|
[
{
"created": "Tue, 5 May 2020 13:57:25 GMT",
"version": "v1"
}
] |
2020-05-06
|
[
[
"Wang",
"Rui",
""
],
[
"Hozumi",
"Yuta",
""
],
[
"Yin",
"Changchuan",
""
],
[
"Wei",
"Guo-Wei",
""
]
] |
Effective, sensitive, and reliable diagnostic reagents are of paramount importance for combating the ongoing coronavirus disease 2019 (COVID-19) pandemic at a time there is no preventive vaccine nor specific drug available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It would be an absolute tragedy if currently used diagnostic reagents are undermined in any manner. Based on the genotyping of 7818 SARS-CoV-2 genome samples collected up to May 1, 2020, we reveal that essentially all of the current COVID-19 diagnostic targets have had mutations. We further show that SARS-CoV-2 has the most devastating mutations on the targets of various nucleocapsid (N) gene primers and probes, which have been unfortunately used by countries around the world to diagnose COVID-19. Our findings explain what has seriously gone wrong with a specific diagnostic reagent made in China. To understand whether SARS-CoV-2 genes have mutated unevenly, we have computed the mutation ratio and mutation $h$-index of all SARS-CoV genes, indicating that the N gene is the most non-conservative gene in the SARS-CoV-2 genome. Our findings enable researchers to target the most conservative SARS-CoV-2 genes and proteins for the design and development of COVID-19 diagnostic reagents, preventive vaccines, and therapeutic medicines.
|
1911.04638
|
David Abramov
|
David Abramov, Jasmine Otto, Mahika Dubey, Cassia Artanegara, Pierre
Boutillier, Walter Fontana, Angus G. Forbes
|
RuleVis: Constructing Patterns and Rules for Rule-Based Models
|
4 pages, 6 figures, presented at IEEE VIS 2019
| null | null | null |
q-bio.QM cs.HC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We introduce RuleVis, a web-based application for defining and editing
"correct-by-construction" executable rules that model biochemical
functionality, which can be used to simulate the behavior of protein-protein
interaction networks and other complex systems. Rule-based models involve
emergent effects based on the interactions between rules, which can vary
considerably with regard to the scale of a model, requiring the user to inspect
and edit individual rules. RuleVis bridges the graph rewriting and systems
biology research communities by providing an external visual representation of
salient patterns that experts can use to determine the appropriate level of
detail for a particular modeling context. We describe the visualization and
interaction features available in RuleVisand provide a detailed example
demonstrating how RuleVis can be used to reason about intracellular
interactions.
|
[
{
"created": "Tue, 12 Nov 2019 02:24:58 GMT",
"version": "v1"
}
] |
2019-11-13
|
[
[
"Abramov",
"David",
""
],
[
"Otto",
"Jasmine",
""
],
[
"Dubey",
"Mahika",
""
],
[
"Artanegara",
"Cassia",
""
],
[
"Boutillier",
"Pierre",
""
],
[
"Fontana",
"Walter",
""
],
[
"Forbes",
"Angus G.",
""
]
] |
We introduce RuleVis, a web-based application for defining and editing "correct-by-construction" executable rules that model biochemical functionality, which can be used to simulate the behavior of protein-protein interaction networks and other complex systems. Rule-based models involve emergent effects based on the interactions between rules, which can vary considerably with regard to the scale of a model, requiring the user to inspect and edit individual rules. RuleVis bridges the graph rewriting and systems biology research communities by providing an external visual representation of salient patterns that experts can use to determine the appropriate level of detail for a particular modeling context. We describe the visualization and interaction features available in RuleVisand provide a detailed example demonstrating how RuleVis can be used to reason about intracellular interactions.
|
1907.12045
|
Lisa Buchauer
|
Lisa Buchauer, Hedda Wardemann
|
Calculating Germinal Centre Reactions
| null |
Current Opinion in Systems Biology 18:1-8 (2019)
|
10.1016/j.coisb.2019.10.004
| null |
q-bio.QM q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
Germinal centres are anatomically defined lymphoid organ structures that
mediate B cell affinity maturation and affect the quality of humoral immune
responses. Mathematical models based on differential equations or agent-based
simulations have been widely used to deepen our understanding of the cellular
and molecular processes characterizing these complex dynamic systems. Along
with experimental studies, these tools have provided insights into the
spatio-temporal behavior of B cells in germinal center reactions and the
mechanisms underlying their clonal selection and cellular differentiation. More
recently, mathematical models have been used to define key parameters that
influence the quality of humoral vaccine responses such as vaccine composition
and vaccination schedule. Here, we review current mathematical and
computational models of the GC response, highlight interesting model features
and discuss how they helped to improve our understanding of B cell responses
specifically in immunization settings.
|
[
{
"created": "Sun, 28 Jul 2019 08:49:33 GMT",
"version": "v1"
}
] |
2019-11-22
|
[
[
"Buchauer",
"Lisa",
""
],
[
"Wardemann",
"Hedda",
""
]
] |
Germinal centres are anatomically defined lymphoid organ structures that mediate B cell affinity maturation and affect the quality of humoral immune responses. Mathematical models based on differential equations or agent-based simulations have been widely used to deepen our understanding of the cellular and molecular processes characterizing these complex dynamic systems. Along with experimental studies, these tools have provided insights into the spatio-temporal behavior of B cells in germinal center reactions and the mechanisms underlying their clonal selection and cellular differentiation. More recently, mathematical models have been used to define key parameters that influence the quality of humoral vaccine responses such as vaccine composition and vaccination schedule. Here, we review current mathematical and computational models of the GC response, highlight interesting model features and discuss how they helped to improve our understanding of B cell responses specifically in immunization settings.
|
1407.4137
|
Eric Jonas
|
Eric Jonas and Konrad Kording
|
Automatic discovery of cell types and microcircuitry from neural
connectomics
| null | null | null | null |
q-bio.NC stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Neural connectomics has begun producing massive amounts of data,
necessitating new analysis methods to discover the biological and computational
structure. It has long been assumed that discovering neuron types and their
relation to microcircuitry is crucial to understanding neural function. Here we
developed a nonparametric Bayesian technique that identifies neuron types and
microcircuitry patterns in connectomics data. It combines the information
traditionally used by biologists, including connectivity, cell body location
and the spatial distribution of synapses, in a principled and
probabilistically-coherent manner. We show that the approach recovers known
neuron types in the retina and enables predictions of connectivity, better than
simpler algorithms. It also can reveal interesting structure in the nervous
system of C. elegans, and automatically discovers the structure of a
microprocessor. Our approach extracts structural meaning from connectomics,
enabling new approaches of automatically deriving anatomical insights from
these emerging datasets.
|
[
{
"created": "Tue, 15 Jul 2014 20:14:05 GMT",
"version": "v1"
}
] |
2014-07-17
|
[
[
"Jonas",
"Eric",
""
],
[
"Kording",
"Konrad",
""
]
] |
Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a nonparametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists, including connectivity, cell body location and the spatial distribution of synapses, in a principled and probabilistically-coherent manner. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity, better than simpler algorithms. It also can reveal interesting structure in the nervous system of C. elegans, and automatically discovers the structure of a microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets.
|
2002.08294
|
Anders Ledberg
|
Anders Ledberg
|
Exponential increase in mortality with age is a generic property of a
simple model system of damage accumulation and death
| null | null |
10.1371/journal.pone.0233384
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The risk of dying increases exponentially with age, in humans as well as in
many other species. This increase is often attributed to the "accumulation of
damage" known to occur in many biological structures and systems. The aim of
this paper is to describe a generic model of damage accumulation and death in
which mortality increases exponentially with age. The damage-accumulation
process is modeled by a stochastic process know as a queue, and risk of dying
is a function of the accumulated damage, i.e. length of the queue. The model
has four parameters and the main characteristics of the model are: (i) damage
occurs at random times with a constant high rate; (ii) the damage is repaired
at a limited rate, and consequently damage can accumulate; (iii) the efficiency
of the repair mechanism decays linearly with age; (iv) the risk of dying is a
function of the accumulated damage. Using standard results from the
mathematical theory of queues it is shown that there is an exponential
dependence between risk of dying and age in these models, and that this
dependency holds irrespective of how the damage-accumulation process is
modeled. Furthermore, the ways in which this exponential dependence is shaped
by the model parameters are also independent of the details of the damage
accumulation process. These generic features suggest that the model could be
useful when interpreting changes in the relation between age and mortality in
real data. To examplify, historical mortality data from Sweden are interpreted
in the light of the model. The decrease in mortality seen between cohorts born
in 1905, compared to those born in 1885, can be accounted for by higher
threshold to damage. This fits well with the many advances made in public
health during the 20th century.
|
[
{
"created": "Wed, 19 Feb 2020 17:11:10 GMT",
"version": "v1"
}
] |
2020-07-01
|
[
[
"Ledberg",
"Anders",
""
]
] |
The risk of dying increases exponentially with age, in humans as well as in many other species. This increase is often attributed to the "accumulation of damage" known to occur in many biological structures and systems. The aim of this paper is to describe a generic model of damage accumulation and death in which mortality increases exponentially with age. The damage-accumulation process is modeled by a stochastic process know as a queue, and risk of dying is a function of the accumulated damage, i.e. length of the queue. The model has four parameters and the main characteristics of the model are: (i) damage occurs at random times with a constant high rate; (ii) the damage is repaired at a limited rate, and consequently damage can accumulate; (iii) the efficiency of the repair mechanism decays linearly with age; (iv) the risk of dying is a function of the accumulated damage. Using standard results from the mathematical theory of queues it is shown that there is an exponential dependence between risk of dying and age in these models, and that this dependency holds irrespective of how the damage-accumulation process is modeled. Furthermore, the ways in which this exponential dependence is shaped by the model parameters are also independent of the details of the damage accumulation process. These generic features suggest that the model could be useful when interpreting changes in the relation between age and mortality in real data. To examplify, historical mortality data from Sweden are interpreted in the light of the model. The decrease in mortality seen between cohorts born in 1905, compared to those born in 1885, can be accounted for by higher threshold to damage. This fits well with the many advances made in public health during the 20th century.
|
1708.04025
|
Etienne Thevenot
|
Alexis Delabri\`ere (CEA), Ulli Hohenester, Benoit Colsch, Christophe
Junot, Fran\c{c}ois Fenaille, Etienne Th\'evenot (CEA)
|
proFIA: A data preprocessing workflow for Flow Injection Analysis
coupled to High-Resolution Mass Spectrometry
|
Bioinformatics, Oxford University Press (OUP), 2017
| null |
10.1093/bioinformatics/btx458
| null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Motivation: Flow Injection Analysis coupled to High-Resolution Mass
Spectrometry (FIA-HRMS) is a promising approach for high-throughput
metabolomics. FIA-HRMS data, however, cannot be preprocessed with current
software tools which rely on liquid chromatography separation, or handle low
resolution data only. Results: We thus developed the proFIA package, which
implements a suite of innovative algorithms to preprocess FIA-HRMS raw files,
and generates the table of peak intensities. The workflow consists of 3 steps:
i) noise estimation, peak detection and quantification, ii) peak grouping
across samples, and iii) missing value imputation. In addition, we have
implemented a new indicator to quantify the potential alteration of the feature
peak shape due to matrix effect. The preprocessing is fast (less than 15 s per
file), and the value of the main parameters (ppm and dmz) can be easily
inferred from the mass resolution of the instrument. Application to two
metabolomics datasets (including spiked serum samples) showed high precision
(96%) and recall (98%) compared with manual integration. These results
demonstrate that proFIA achieves very efficient and robust detection and
quantification of FIA-HRMS data, and opens new opportunities for
high-throughput phenotyping. Availability: The proFIA software (as well as the
plasFIA data set) is available as an R package on the Bioconductor repository
(http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main
Toolshed (https://toolshed.g2.bx.psu.edu/) and on the Workflow4Metabolomics
online infrastructure (http://workflow4metabolomics.org). Contacts:
alexis.delabriere@cea.fr and etienne.thevenot@cea.fr.
|
[
{
"created": "Mon, 14 Aug 2017 07:37:18 GMT",
"version": "v1"
}
] |
2017-08-15
|
[
[
"Delabrière",
"Alexis",
"",
"CEA"
],
[
"Hohenester",
"Ulli",
"",
"CEA"
],
[
"Colsch",
"Benoit",
"",
"CEA"
],
[
"Junot",
"Christophe",
"",
"CEA"
],
[
"Fenaille",
"François",
"",
"CEA"
],
[
"Thévenot",
"Etienne",
"",
"CEA"
]
] |
Motivation: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. Results: We thus developed the proFIA package, which implements a suite of innovative algorithms to preprocess FIA-HRMS raw files, and generates the table of peak intensities. The workflow consists of 3 steps: i) noise estimation, peak detection and quantification, ii) peak grouping across samples, and iii) missing value imputation. In addition, we have implemented a new indicator to quantify the potential alteration of the feature peak shape due to matrix effect. The preprocessing is fast (less than 15 s per file), and the value of the main parameters (ppm and dmz) can be easily inferred from the mass resolution of the instrument. Application to two metabolomics datasets (including spiked serum samples) showed high precision (96%) and recall (98%) compared with manual integration. These results demonstrate that proFIA achieves very efficient and robust detection and quantification of FIA-HRMS data, and opens new opportunities for high-throughput phenotyping. Availability: The proFIA software (as well as the plasFIA data set) is available as an R package on the Bioconductor repository (http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main Toolshed (https://toolshed.g2.bx.psu.edu/) and on the Workflow4Metabolomics online infrastructure (http://workflow4metabolomics.org). Contacts: alexis.delabriere@cea.fr and etienne.thevenot@cea.fr.
|
2206.10370
|
In\^es Guerreiro
|
In\^es C. Guerreiro, Matteo di Volo, Boris Gutkin
|
A new generation of reduction methods for networks of neurons with
complex dynamic phenotypes
|
reduction method for bursting neurons added
| null | null | null |
q-bio.NC cond-mat.stat-mech
|
http://creativecommons.org/licenses/by/4.0/
|
Collective dynamics of spiking networks of neurons has been of central
interest to both computation neuroscience and network science. Over the past
years a new generation of neural population models based on exact reductions
(ER) of spiking networks have been developed. However, most of these efforts
have been limited to networks of neurons with simple dynamics (e.g. the
quadratic integrate and fire models). Here, we present an extension of ER to
conductance-based networks of two-dimensional Izhikevich neuron models. We
employ an adiabatic approximation, which allows us to analytically solve the
continuity equation describing the evolution of the state of the neural
population and thus to reduce model dimensionality. We validate our results by
showing that the reduced mean-field description we derived can qualitatively
and quantitatively describe the macroscopic behaviour of populations of
two-dimensional QIF neurons with different electrophysiological profiles
(regular firing, adapting, resonator and type III excitable). Most notably, we
apply this technique to develop an ER for networks of neurons with bursting
dynamics.
|
[
{
"created": "Tue, 21 Jun 2022 13:20:02 GMT",
"version": "v1"
},
{
"created": "Mon, 23 Oct 2023 11:55:09 GMT",
"version": "v2"
}
] |
2023-10-24
|
[
[
"Guerreiro",
"Inês C.",
""
],
[
"di Volo",
"Matteo",
""
],
[
"Gutkin",
"Boris",
""
]
] |
Collective dynamics of spiking networks of neurons has been of central interest to both computation neuroscience and network science. Over the past years a new generation of neural population models based on exact reductions (ER) of spiking networks have been developed. However, most of these efforts have been limited to networks of neurons with simple dynamics (e.g. the quadratic integrate and fire models). Here, we present an extension of ER to conductance-based networks of two-dimensional Izhikevich neuron models. We employ an adiabatic approximation, which allows us to analytically solve the continuity equation describing the evolution of the state of the neural population and thus to reduce model dimensionality. We validate our results by showing that the reduced mean-field description we derived can qualitatively and quantitatively describe the macroscopic behaviour of populations of two-dimensional QIF neurons with different electrophysiological profiles (regular firing, adapting, resonator and type III excitable). Most notably, we apply this technique to develop an ER for networks of neurons with bursting dynamics.
|
2107.11458
|
Sanna Gudmundsson
|
Sanna Gudmundsson, Moriel Singer-Berk, Nicholas A. Watts, William Phu,
Julia K. Goodrich, Matthew Solomonson, Genome Aggregation Database
Consortium, Heidi L. Rehm, Daniel G. MacArthur, Anne ODonnell-Luria
|
Variant interpretation using population databases: lessons from gnomAD
|
Version 3: Includes updates to mirror the latest features and layouts
available on the gnomAD browser and general improvements to text and figures
(clarifications, typos, additional references etc.) as well as the addition
of Table S1, S2, Figure S1, S2 and S5
| null |
10.1002/humu.24309
| null |
q-bio.GN
|
http://creativecommons.org/licenses/by/4.0/
|
Reference population databases are an essential tool in variant and gene
interpretation. Their use guides the identification of pathogenic variants
amidst the sea of benign variation present in every human genome, and supports
the discovery of new disease-gene relationships. The Genome Aggregation
Database (gnomAD) is currently the largest and most widely used publicly
available collection of population variation from harmonized sequencing data.
The data is available through the online gnomAD browser
(https://gnomad.broadinstitute.org/) that enables rapid and intuitive variant
analysis. This review provides guidance on the content of the gnomAD browser,
and its usage for variant and gene interpretation. We introduce key features
including allele frequency, per-base expression levels, constraint scores, and
variant co-occurrence, alongside guidance on how to use these in analysis, with
a focus on the interpretation of candidate variants and novel genes in rare
disease.
|
[
{
"created": "Fri, 23 Jul 2021 20:56:50 GMT",
"version": "v1"
},
{
"created": "Thu, 4 Nov 2021 15:01:14 GMT",
"version": "v2"
},
{
"created": "Sun, 16 Jan 2022 18:36:52 GMT",
"version": "v3"
}
] |
2022-01-19
|
[
[
"Gudmundsson",
"Sanna",
""
],
[
"Singer-Berk",
"Moriel",
""
],
[
"Watts",
"Nicholas A.",
""
],
[
"Phu",
"William",
""
],
[
"Goodrich",
"Julia K.",
""
],
[
"Solomonson",
"Matthew",
""
],
[
"Consortium",
"Genome Aggregation Database",
""
],
[
"Rehm",
"Heidi L.",
""
],
[
"MacArthur",
"Daniel G.",
""
],
[
"ODonnell-Luria",
"Anne",
""
]
] |
Reference population databases are an essential tool in variant and gene interpretation. Their use guides the identification of pathogenic variants amidst the sea of benign variation present in every human genome, and supports the discovery of new disease-gene relationships. The Genome Aggregation Database (gnomAD) is currently the largest and most widely used publicly available collection of population variation from harmonized sequencing data. The data is available through the online gnomAD browser (https://gnomad.broadinstitute.org/) that enables rapid and intuitive variant analysis. This review provides guidance on the content of the gnomAD browser, and its usage for variant and gene interpretation. We introduce key features including allele frequency, per-base expression levels, constraint scores, and variant co-occurrence, alongside guidance on how to use these in analysis, with a focus on the interpretation of candidate variants and novel genes in rare disease.
|
1505.03827
|
Daniel Korytowski
|
Daniel A. Korytowski and Hal L. Smith
|
Persistence in Phage-Bacteria Communities with Nested and One-to-One
Infection Networks
|
15 pages. arXiv admin note: substantial text overlap with
arXiv:1406.5461
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We show that a bacteria and bacteriophage system with either a perfectly
nested or a one-to-one infection network is permanent, a.k.a uniformly
persistent, provided that bacteria that are superior competitors for nutrient
devote the least to defence against infection and the virus that are the most
efficient at infecting host have the smallest host range. By ensuring that the
density-dependent reduction in bacterial growth rates are independent of
bacterial strain, we are able to arrive at the permanence conclusion sought by
Jover et al (J. Theor. Biol. 332:65-77, 2013). The same permanence results hold
for the one-to-one infection network considered by Thingstad (Limnol Oceanogr
45:1320-1328, 2000) but without virus efficiency ordering. Additionally we show
the global stability for the nested infection network, and the global dynamics
for the one-to-one network.
|
[
{
"created": "Thu, 14 May 2015 18:32:28 GMT",
"version": "v1"
},
{
"created": "Thu, 28 May 2015 04:10:37 GMT",
"version": "v2"
}
] |
2015-05-29
|
[
[
"Korytowski",
"Daniel A.",
""
],
[
"Smith",
"Hal L.",
""
]
] |
We show that a bacteria and bacteriophage system with either a perfectly nested or a one-to-one infection network is permanent, a.k.a uniformly persistent, provided that bacteria that are superior competitors for nutrient devote the least to defence against infection and the virus that are the most efficient at infecting host have the smallest host range. By ensuring that the density-dependent reduction in bacterial growth rates are independent of bacterial strain, we are able to arrive at the permanence conclusion sought by Jover et al (J. Theor. Biol. 332:65-77, 2013). The same permanence results hold for the one-to-one infection network considered by Thingstad (Limnol Oceanogr 45:1320-1328, 2000) but without virus efficiency ordering. Additionally we show the global stability for the nested infection network, and the global dynamics for the one-to-one network.
|
1807.02985
|
Bartlomiej Waclaw Dr
|
Craig Watson, Paul Hush, Joshua Williams, Angela Dawson, Nikola Ojkic,
Simon Titmuss, and Bartlomiej Waclaw
|
Reduced adhesion between cells and substrate confers selective advantage
in bacterial colonies
|
7 pages, 7 figures, submitted to the EPL Special Issue "Evolutionary
modeling and experimental evolution"
| null |
10.1209/0295-5075/123/68001
| null |
q-bio.PE physics.bio-ph
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Microbial colonies cultured on agar Petri dishes have become a model system
to study biological evolution in populations expanding in space. Processes such
as clonal segregation and gene surfing have been shown to be affected by
interactions between microbial cells and their environment. In this work we
investigate the role of mechanical interactions such as cell-surface adhesion.
We compare two strains of the bacterium E. coli: a wild-type strain and a
"shaved" strain that adheres less to agar. We show that the shaved strain has a
selective advantage over the wild type: although both strains grow with the
same rate in liquid media, the shaved strain produces colonies that expand
faster on agar. This allows the shaved strain outgrow the wild type when both
strains compete for space. We hypothesise that, in contrast to a more common
scenario in which selective advantage results from increased growth rate, the
higher fitness of the shaved strain is caused by reduced adhesion and friction
with the agar surface.
|
[
{
"created": "Mon, 9 Jul 2018 08:18:06 GMT",
"version": "v1"
}
] |
2018-10-17
|
[
[
"Watson",
"Craig",
""
],
[
"Hush",
"Paul",
""
],
[
"Williams",
"Joshua",
""
],
[
"Dawson",
"Angela",
""
],
[
"Ojkic",
"Nikola",
""
],
[
"Titmuss",
"Simon",
""
],
[
"Waclaw",
"Bartlomiej",
""
]
] |
Microbial colonies cultured on agar Petri dishes have become a model system to study biological evolution in populations expanding in space. Processes such as clonal segregation and gene surfing have been shown to be affected by interactions between microbial cells and their environment. In this work we investigate the role of mechanical interactions such as cell-surface adhesion. We compare two strains of the bacterium E. coli: a wild-type strain and a "shaved" strain that adheres less to agar. We show that the shaved strain has a selective advantage over the wild type: although both strains grow with the same rate in liquid media, the shaved strain produces colonies that expand faster on agar. This allows the shaved strain outgrow the wild type when both strains compete for space. We hypothesise that, in contrast to a more common scenario in which selective advantage results from increased growth rate, the higher fitness of the shaved strain is caused by reduced adhesion and friction with the agar surface.
|
1409.0761
|
Tom Nye
|
Tom M. W. Nye
|
An algorithm for constructing principal geodesics in phylogenetic
treespace
|
6 figures, IEEE/ACM Transactions on Computational Biology and
Bioinformatics, Vol. 11, No. 2, 2014
| null |
10.1109/TCBB.2014.2309599
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Most phylogenetic analyses result in a sample of trees, but summarizing and
visualizing these samples can be challenging. Consensus trees often provide
limited information about a sample, and so methods such as consensus networks,
clustering and multidimensional scaling have been developed and applied to tree
samples. This paper describes a stochastic algorithm for constructing a
principal geodesic or line through treespace which is analogous to the first
principal component in standard Principal Components Analysis. A principal
geodesic summarizes the most variable features of a sample of trees, in terms
of both tree topology and branch lengths, and it can be visualized as an
animation of smoothly changing trees. The algorithm performs a stochastic
search through parameter space for a geodesic which minimises the sum of
squared projected distances of the data points. This procedure aims to identify
the globally optimal principal geodesic, though convergence to locally optimal
geodesics is possible. The methodology is illustrated by constructing principal
geodesics for experimental and simulated data sets, demonstrating the insight
into samples of trees that can be gained and how the method improves on a
previously published approach. A java package called GeoPhytter for
constructing and visualising principal geodesics is freely available from
www.ncl.ac.uk/~ntmwn/geophytter.
|
[
{
"created": "Tue, 2 Sep 2014 15:41:13 GMT",
"version": "v1"
}
] |
2014-09-03
|
[
[
"Nye",
"Tom M. W.",
""
]
] |
Most phylogenetic analyses result in a sample of trees, but summarizing and visualizing these samples can be challenging. Consensus trees often provide limited information about a sample, and so methods such as consensus networks, clustering and multidimensional scaling have been developed and applied to tree samples. This paper describes a stochastic algorithm for constructing a principal geodesic or line through treespace which is analogous to the first principal component in standard Principal Components Analysis. A principal geodesic summarizes the most variable features of a sample of trees, in terms of both tree topology and branch lengths, and it can be visualized as an animation of smoothly changing trees. The algorithm performs a stochastic search through parameter space for a geodesic which minimises the sum of squared projected distances of the data points. This procedure aims to identify the globally optimal principal geodesic, though convergence to locally optimal geodesics is possible. The methodology is illustrated by constructing principal geodesics for experimental and simulated data sets, demonstrating the insight into samples of trees that can be gained and how the method improves on a previously published approach. A java package called GeoPhytter for constructing and visualising principal geodesics is freely available from www.ncl.ac.uk/~ntmwn/geophytter.
|
0910.1916
|
Iain Johnston
|
Iain G. Johnston, Ard A. Louis, Jonathan P. K. Doye
|
Modelling the Self-Assembly of Virus Capsids
|
16 pages, 11 figures
|
J. Phys.: Condens. Matter 22 104101 (2010)
|
10.1088/0953-8984/22/10/104101
| null |
q-bio.BM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We use computer simulations to study a model, first proposed by Wales [1],
for the reversible and monodisperse self-assembly of simple icosahedral virus
capsid structures. The success and efficiency of assembly as a function of
thermodynamic and geometric factors can be qualitatively related to the
potential energy landscape structure of the assembling system. Even though the
model is strongly coarse-grained, it exhibits a number of features also
observed in experiments, such as sigmoidal assembly dynamics, hysteresis in
capsid formation and numerous kinetic traps. We also investigate the effect of
macromolecular crowding on the assembly dynamics. Crowding agents generally
reduce capsid yields at optimal conditions for non-crowded assembly, but may
increase yields for parameter regimes away from the optimum. Finally, we
generalize the model to a larger triangulation number T = 3, and observe more
complex assembly dynamics than that seen for the original T = 1 model.
|
[
{
"created": "Sat, 10 Oct 2009 12:15:06 GMT",
"version": "v1"
}
] |
2010-02-24
|
[
[
"Johnston",
"Iain G.",
""
],
[
"Louis",
"Ard A.",
""
],
[
"Doye",
"Jonathan P. K.",
""
]
] |
We use computer simulations to study a model, first proposed by Wales [1], for the reversible and monodisperse self-assembly of simple icosahedral virus capsid structures. The success and efficiency of assembly as a function of thermodynamic and geometric factors can be qualitatively related to the potential energy landscape structure of the assembling system. Even though the model is strongly coarse-grained, it exhibits a number of features also observed in experiments, such as sigmoidal assembly dynamics, hysteresis in capsid formation and numerous kinetic traps. We also investigate the effect of macromolecular crowding on the assembly dynamics. Crowding agents generally reduce capsid yields at optimal conditions for non-crowded assembly, but may increase yields for parameter regimes away from the optimum. Finally, we generalize the model to a larger triangulation number T = 3, and observe more complex assembly dynamics than that seen for the original T = 1 model.
|
q-bio/0506021
|
Eli Eisenberg
|
Moshe Havilio, Erez Y. Levanon, Galia Lerman, Martin Kupiec and Eli
Eisenberg
|
Evidence for abundant transcription of non-coding regions in the
Saccharomyces cerevisiae genome
|
Journal version available at
http://www.biomedcentral.com/1471-2164/6/93/abstract
|
BMC Genomics 6:93 (2005)
|
10.1186/1471-2164-6-93
| null |
q-bio.GN
| null |
Background: Recent studies in a growing number of organisms have yielded
accumulating evidence that a significant portion of the non-coding region in
the genome is transcribed. We address this issue in the yeast Saccharomyces
cerevisiae.
Results: Taking into account the absence of a significantly large yeast EST
database, we use microarray expression data collected for genomic regions
erroneously believed to be coding to study the expression pattern of non-coding
regions in the Saccharomyces cerevisiae genome. We find that at least 164 out
of 589 (28%) such regions are expressed under specific biological conditions.
In particular, looking at the probes that are located opposing other known
genes at the same genomic locus, we find that 88 out of 341 (26%) of these
genes support antisense transcription. The expression patterns of these
antisense genes are positively correlated. We validate these results using
RT-PCR on a sample of 6 non-coding transcripts.
Conclusions: 1. The yeast genome is transcribed on a scale larger than
previously assumed. 2. Correlated transcription of antisense genes is abundant
in the yeast genome. 3. Antisense genes in yeast are non-coding.
|
[
{
"created": "Thu, 16 Jun 2005 13:28:40 GMT",
"version": "v1"
}
] |
2007-05-23
|
[
[
"Havilio",
"Moshe",
""
],
[
"Levanon",
"Erez Y.",
""
],
[
"Lerman",
"Galia",
""
],
[
"Kupiec",
"Martin",
""
],
[
"Eisenberg",
"Eli",
""
]
] |
Background: Recent studies in a growing number of organisms have yielded accumulating evidence that a significant portion of the non-coding region in the genome is transcribed. We address this issue in the yeast Saccharomyces cerevisiae. Results: Taking into account the absence of a significantly large yeast EST database, we use microarray expression data collected for genomic regions erroneously believed to be coding to study the expression pattern of non-coding regions in the Saccharomyces cerevisiae genome. We find that at least 164 out of 589 (28%) such regions are expressed under specific biological conditions. In particular, looking at the probes that are located opposing other known genes at the same genomic locus, we find that 88 out of 341 (26%) of these genes support antisense transcription. The expression patterns of these antisense genes are positively correlated. We validate these results using RT-PCR on a sample of 6 non-coding transcripts. Conclusions: 1. The yeast genome is transcribed on a scale larger than previously assumed. 2. Correlated transcription of antisense genes is abundant in the yeast genome. 3. Antisense genes in yeast are non-coding.
|
1912.12762
|
Andrey Kuznetsov
|
I. A. Kuznetsov and A. V. Kuznetsov
|
How old are dense core vesicles residing in en passant boutons:
Simulation of the mean age of dense core vesicles in axonal arbors accounting
for resident and transiting vesicle populations
|
Final, accepted manuscript version
|
Proc. R. Soc. A, vol. 476: 20200454, 2020
|
10.1098/rspa.2020.0454
| null |
q-bio.SC q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
In neurons, neuropeptides are synthesized in the soma and are then
transported along the axon in dense core vesicles (DCVs). DCVs are captured in
varicosities located along the axon terminal called en passant boutons, which
are active terminal sites that accumulate and release neurotransmitters.
Recently developed experimental techniques allow for the estimation of the age
of DCVs in various locations in the axon terminal. Accurate simulation of the
mean age of DCVs in boutons requires the development of a model that would
account for resident, transiting-anterograde, and transiting-retrograde DCV
populations. In this paper, such a model is developed. The model is applied to
simulating DCV transport in Drosophila type II motoneurons. The model simulates
DCV transport and capture in the axon terminals and makes it possible to
predict the age density distribution of DCVs in en passant boutons as well as
DCV's mean age in boutons. The predicted prevalence of older organelles in
distal boutons may explain the "dying back" pattern of axonal degeneration
observed in dopaminergic neurons in Parkinson's disease. The predicted
difference of two hours between the age of older DCVs residing in distal
boutons and the age of younger DCVs residing in proximal boutons is consistent
with an approximate estimate of age difference deduced from experimental
observations. The age density of resident DCVs is found to be bimodal, which is
because DCVs are captured from two transiting states: the anterograde
transiting state that contains younger DCVs and the retrograde transiting state
that contains older DCVs.
|
[
{
"created": "Mon, 30 Dec 2019 00:07:33 GMT",
"version": "v1"
},
{
"created": "Sat, 1 Feb 2020 16:39:11 GMT",
"version": "v2"
},
{
"created": "Wed, 6 May 2020 17:00:06 GMT",
"version": "v3"
},
{
"created": "Fri, 16 Oct 2020 18:25:00 GMT",
"version": "v4"
}
] |
2020-10-20
|
[
[
"Kuznetsov",
"I. A.",
""
],
[
"Kuznetsov",
"A. V.",
""
]
] |
In neurons, neuropeptides are synthesized in the soma and are then transported along the axon in dense core vesicles (DCVs). DCVs are captured in varicosities located along the axon terminal called en passant boutons, which are active terminal sites that accumulate and release neurotransmitters. Recently developed experimental techniques allow for the estimation of the age of DCVs in various locations in the axon terminal. Accurate simulation of the mean age of DCVs in boutons requires the development of a model that would account for resident, transiting-anterograde, and transiting-retrograde DCV populations. In this paper, such a model is developed. The model is applied to simulating DCV transport in Drosophila type II motoneurons. The model simulates DCV transport and capture in the axon terminals and makes it possible to predict the age density distribution of DCVs in en passant boutons as well as DCV's mean age in boutons. The predicted prevalence of older organelles in distal boutons may explain the "dying back" pattern of axonal degeneration observed in dopaminergic neurons in Parkinson's disease. The predicted difference of two hours between the age of older DCVs residing in distal boutons and the age of younger DCVs residing in proximal boutons is consistent with an approximate estimate of age difference deduced from experimental observations. The age density of resident DCVs is found to be bimodal, which is because DCVs are captured from two transiting states: the anterograde transiting state that contains younger DCVs and the retrograde transiting state that contains older DCVs.
|
0712.3383
|
Thibault Lagache
|
Thibault Lagache and David Holcman
|
Effective Motion of a Virus Trafficking Inside a Biological Cell
|
22 pages, 6 figures, accepted in SIAM Journal of Applied Mathematics
| null | null | null |
q-bio.QM q-bio.SC
| null |
Virus trafficking is fundamental for infection success and plasmid cytosolic
trafficking is a key step of gene delivery. Based on the main physical
properties of the cellular transport machinery such as microtubules, motor
proteins, our goal here is to derive a mathematical model to study cytoplasmic
trafficking. Because experimental results reveal that both active and passive
movement are necessary for a virus to reach the cell nucleus, by taking into
account the complex interactions of the virus with the microtubules, we derive
here an estimate of the mean time a virus reaches the nucleus. In particular,
we present a mathematical procedure in which the complex viral movement,
oscillating between pure diffusion and a deterministic movement along
microtubules, can be approximated by a steady state stochastic equation with a
constant effective drift. An explicit expression for the drift amplitude is
given as a function of the real drift, the density of microtubules and other
physical parameters. The present approach can be used to model viral
trafficking inside the cytoplasm, which is a fundamental step of viral
infection, leading to viral replication and in some cases to cell damage.
|
[
{
"created": "Thu, 20 Dec 2007 12:05:35 GMT",
"version": "v1"
}
] |
2007-12-21
|
[
[
"Lagache",
"Thibault",
""
],
[
"Holcman",
"David",
""
]
] |
Virus trafficking is fundamental for infection success and plasmid cytosolic trafficking is a key step of gene delivery. Based on the main physical properties of the cellular transport machinery such as microtubules, motor proteins, our goal here is to derive a mathematical model to study cytoplasmic trafficking. Because experimental results reveal that both active and passive movement are necessary for a virus to reach the cell nucleus, by taking into account the complex interactions of the virus with the microtubules, we derive here an estimate of the mean time a virus reaches the nucleus. In particular, we present a mathematical procedure in which the complex viral movement, oscillating between pure diffusion and a deterministic movement along microtubules, can be approximated by a steady state stochastic equation with a constant effective drift. An explicit expression for the drift amplitude is given as a function of the real drift, the density of microtubules and other physical parameters. The present approach can be used to model viral trafficking inside the cytoplasm, which is a fundamental step of viral infection, leading to viral replication and in some cases to cell damage.
|
2305.19654
|
Polina Turishcheva
|
Polina Turishcheva, Paul G. Fahey, Laura Hansel, Rachel Froebe, Kayla
Ponder, Michaela Vystr\v{c}ilov\'a, Konstantin F. Willeke, Mohammad Bashiri,
Eric Wang, Zhiwei Ding, Andreas S. Tolias, Fabian H. Sinz, Alexander S. Ecker
|
The Dynamic Sensorium competition for predicting large-scale mouse
visual cortex activity from videos
|
arXiv admin note: substantial text overlap with arXiv:2206.08666
| null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
Understanding how biological visual systems process information is
challenging due to the complex nonlinear relationship between neuronal
responses and high-dimensional visual input. Artificial neural networks have
already improved our understanding of this system by allowing computational
neuroscientists to create predictive models and bridge biological and machine
vision. During the Sensorium 2022, we introduced benchmarks for vision models
with static input. However, animals operate and excel in dynamic environments,
making it crucial to study and understand how the brain functions under these
conditions. Moreover, many biological theories, such as predictive coding,
suggest that previous input is crucial for current input processing. Currently,
there is no standardized benchmark to identify state-of-the-art dynamic models
of the mouse visual system. To address this gap, we propose the Sensorium 2023
Benchmark Competition with dynamic input. It includes the collection of a new
large-scale dataset from the primary visual cortex of ten mice, containing
responses from over 78,000 neurons to over 2 hours of dynamic stimuli per
neuron. Participants in the main benchmark track will compete to identify the
best predictive models of neuronal responses for dynamic input. We will also
host a bonus track in which submission performance will be evaluated on
out-of-domain input, using withheld neuronal responses to dynamic input stimuli
whose statistics differ from the training set. Both tracks will offer
behavioral data along with video stimuli. As before, we will provide code,
tutorials, and strong pre-trained baseline models to encourage participation.
We hope this competition will continue to strengthen the accompanying Sensorium
benchmarks collection as a standard tool to measure progress in large-scale
neural system identification models of the entire mouse visual hierarchy and
beyond.
|
[
{
"created": "Wed, 31 May 2023 08:40:12 GMT",
"version": "v1"
},
{
"created": "Fri, 12 Jul 2024 08:53:07 GMT",
"version": "v2"
}
] |
2024-07-15
|
[
[
"Turishcheva",
"Polina",
""
],
[
"Fahey",
"Paul G.",
""
],
[
"Hansel",
"Laura",
""
],
[
"Froebe",
"Rachel",
""
],
[
"Ponder",
"Kayla",
""
],
[
"Vystrčilová",
"Michaela",
""
],
[
"Willeke",
"Konstantin F.",
""
],
[
"Bashiri",
"Mohammad",
""
],
[
"Wang",
"Eric",
""
],
[
"Ding",
"Zhiwei",
""
],
[
"Tolias",
"Andreas S.",
""
],
[
"Sinz",
"Fabian H.",
""
],
[
"Ecker",
"Alexander S.",
""
]
] |
Understanding how biological visual systems process information is challenging due to the complex nonlinear relationship between neuronal responses and high-dimensional visual input. Artificial neural networks have already improved our understanding of this system by allowing computational neuroscientists to create predictive models and bridge biological and machine vision. During the Sensorium 2022, we introduced benchmarks for vision models with static input. However, animals operate and excel in dynamic environments, making it crucial to study and understand how the brain functions under these conditions. Moreover, many biological theories, such as predictive coding, suggest that previous input is crucial for current input processing. Currently, there is no standardized benchmark to identify state-of-the-art dynamic models of the mouse visual system. To address this gap, we propose the Sensorium 2023 Benchmark Competition with dynamic input. It includes the collection of a new large-scale dataset from the primary visual cortex of ten mice, containing responses from over 78,000 neurons to over 2 hours of dynamic stimuli per neuron. Participants in the main benchmark track will compete to identify the best predictive models of neuronal responses for dynamic input. We will also host a bonus track in which submission performance will be evaluated on out-of-domain input, using withheld neuronal responses to dynamic input stimuli whose statistics differ from the training set. Both tracks will offer behavioral data along with video stimuli. As before, we will provide code, tutorials, and strong pre-trained baseline models to encourage participation. We hope this competition will continue to strengthen the accompanying Sensorium benchmarks collection as a standard tool to measure progress in large-scale neural system identification models of the entire mouse visual hierarchy and beyond.
|
1508.05317
|
David Murrugarra
|
David Murrugarra and Alan Veliz-Cuba and Boris Aguilar and Reinhard
Laubenbacher
|
Identification of control targets in Boolean molecular network models
via computational algebra
|
12 pages, 4 figures, 2 tables
|
BMC Systems Biology, 10:94, 2016
|
10.1186/s12918-016-0332-x
| null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Motivation: Many problems in biomedicine and other areas of the life sciences
can be characterized as control problems, with the goal of finding strategies
to change a disease or otherwise undesirable state of a biological system into
another, more desirable, state through an intervention, such as a drug or other
therapeutic treatment. The identification of such strategies is typically based
on a mathematical model of the process to be altered through targeted control
inputs. This paper focuses on processes at the molecular level that determine
the state of an individual cell, involving signaling or gene regulation. The
mathematical model type considered is that of Boolean networks. The potential
control targets can be represented by a set of nodes and edges that can be
manipulated to produce a desired effect on the system. Experimentally, node
manipulation requires technology to completely repress or fully activate a
particular gene product while edge manipulations only require a drug that
inactivates the interaction between two gene products. Results: This paper
presents a method for the identification of potential intervention targets in
Boolean molecular network models using algebraic techniques. The approach
exploits an algebraic representation of Boolean networks to encode the control
candidates in the network wiring diagram as the solutions of a system of
polynomials equations, and then uses computational algebra techniques to find
such controllers. The control methods in this paper are validated through the
identification of combinatorial interventions in the signaling pathways of
previously reported control targets in two well studied systems, a p53-mdm2
network and a blood T cell lymphocyte granular leukemia survival signaling
network.
|
[
{
"created": "Fri, 21 Aug 2015 15:46:34 GMT",
"version": "v1"
},
{
"created": "Thu, 3 Sep 2015 21:38:12 GMT",
"version": "v2"
},
{
"created": "Mon, 1 Aug 2016 17:49:21 GMT",
"version": "v3"
},
{
"created": "Mon, 3 Oct 2016 17:54:39 GMT",
"version": "v4"
}
] |
2016-10-04
|
[
[
"Murrugarra",
"David",
""
],
[
"Veliz-Cuba",
"Alan",
""
],
[
"Aguilar",
"Boris",
""
],
[
"Laubenbacher",
"Reinhard",
""
]
] |
Motivation: Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. Experimentally, node manipulation requires technology to completely repress or fully activate a particular gene product while edge manipulations only require a drug that inactivates the interaction between two gene products. Results: This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network.
|
1909.05215
|
Ellen Zhong
|
Ellen D. Zhong, Tristan Bepler, Joseph H. Davis, Bonnie Berger
|
Reconstructing continuous distributions of 3D protein structure from
cryo-EM images
| null |
International Conference on Learning Representations (ICLR), 2020
| null | null |
q-bio.QM cs.CV cs.LG eess.IV stat.ML
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Cryo-electron microscopy (cryo-EM) is a powerful technique for determining
the structure of proteins and other macromolecular complexes at near-atomic
resolution. In single particle cryo-EM, the central problem is to reconstruct
the three-dimensional structure of a macromolecule from $10^{4-7}$ noisy and
randomly oriented two-dimensional projections. However, the imaged protein
complexes may exhibit structural variability, which complicates reconstruction
and is typically addressed using discrete clustering approaches that fail to
capture the full range of protein dynamics. Here, we introduce a novel method
for cryo-EM reconstruction that extends naturally to modeling continuous
generative factors of structural heterogeneity. This method encodes structures
in Fourier space using coordinate-based deep neural networks, and trains these
networks from unlabeled 2D cryo-EM images by combining exact inference over
image orientation with variational inference for structural heterogeneity. We
demonstrate that the proposed method, termed cryoDRGN, can perform ab initio
reconstruction of 3D protein complexes from simulated and real 2D cryo-EM image
data. To our knowledge, cryoDRGN is the first neural network-based approach for
cryo-EM reconstruction and the first end-to-end method for directly
reconstructing continuous ensembles of protein structures from cryo-EM images.
|
[
{
"created": "Wed, 11 Sep 2019 17:13:06 GMT",
"version": "v1"
},
{
"created": "Thu, 12 Dec 2019 23:45:23 GMT",
"version": "v2"
},
{
"created": "Sat, 15 Feb 2020 04:31:46 GMT",
"version": "v3"
}
] |
2020-02-18
|
[
[
"Zhong",
"Ellen D.",
""
],
[
"Bepler",
"Tristan",
""
],
[
"Davis",
"Joseph H.",
""
],
[
"Berger",
"Bonnie",
""
]
] |
Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structure of proteins and other macromolecular complexes at near-atomic resolution. In single particle cryo-EM, the central problem is to reconstruct the three-dimensional structure of a macromolecule from $10^{4-7}$ noisy and randomly oriented two-dimensional projections. However, the imaged protein complexes may exhibit structural variability, which complicates reconstruction and is typically addressed using discrete clustering approaches that fail to capture the full range of protein dynamics. Here, we introduce a novel method for cryo-EM reconstruction that extends naturally to modeling continuous generative factors of structural heterogeneity. This method encodes structures in Fourier space using coordinate-based deep neural networks, and trains these networks from unlabeled 2D cryo-EM images by combining exact inference over image orientation with variational inference for structural heterogeneity. We demonstrate that the proposed method, termed cryoDRGN, can perform ab initio reconstruction of 3D protein complexes from simulated and real 2D cryo-EM image data. To our knowledge, cryoDRGN is the first neural network-based approach for cryo-EM reconstruction and the first end-to-end method for directly reconstructing continuous ensembles of protein structures from cryo-EM images.
|
1406.1028
|
Rui Vilela-Mendes
|
Hugo C. Mendes, Alberto Murta and R. Vilela Mendes
|
Long range dependence and the dynamics of exploited fish populations
|
14 pages, 6 figures
|
Advances in Complex Systems 18 (2015) 1550017
|
10.1142/S0219525915500174
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Long range dependence or long memory is a feature of many processes in the
natural world, which provides important insights on the underlying mechanisms
that generate the observed data. The usual tools available to characterize the
phenomenon are mostly based on second order correlations. However, the long
memory effects may not be evident at the level of second order correlations and
may require a deeper analysis of the nature of the stochastic processes.
After a short review of the notions and tools used to characterize long range
dependence, we analyse data related to the abundance of exploited fish
populations which provides an example of higher order long range dependence.
|
[
{
"created": "Wed, 4 Jun 2014 12:50:52 GMT",
"version": "v1"
}
] |
2016-05-11
|
[
[
"Mendes",
"Hugo C.",
""
],
[
"Murta",
"Alberto",
""
],
[
"Mendes",
"R. Vilela",
""
]
] |
Long range dependence or long memory is a feature of many processes in the natural world, which provides important insights on the underlying mechanisms that generate the observed data. The usual tools available to characterize the phenomenon are mostly based on second order correlations. However, the long memory effects may not be evident at the level of second order correlations and may require a deeper analysis of the nature of the stochastic processes. After a short review of the notions and tools used to characterize long range dependence, we analyse data related to the abundance of exploited fish populations which provides an example of higher order long range dependence.
|
0901.3233
|
Bernhard Mehlig
|
A. Eriksson, B. Mehlig, M. Panova, C. Andre, and K. Johannesson
|
Multiple paternity: determining the minimum number of sires of a large
brood
|
16 pages, 5 figures, 3 tables
|
Molecular Ecology Resources 10, 282 (2010)
|
10.1111/j.1755-0998.2009.02753.x
| null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We describe an efficient algorithm for determining exactly the minimum number
of sires consistent with the multi-locus genotypes of a mother and her progeny.
We consider cases where a simple exhaustive search through all possible sets of
sires is impossible in practice (because it would take too long to complete).
Our algorithm for solving this combinatorial optimisation problem avoids
visiting large parts of search space which would not improve the solution found
so far (i.e., result in a solution with fewer number of sires). This is of
particular importance when the number of allelic types in the progeny array is
large and when the minimum number of sires is expected to be large. Precisely
in such cases it is important to know the minimum number of sires: this number
gives an exact bound on the most likely number of sires estimated by a random
search algorithm in a parameter region where it may be difficult to determine
whether it has converged. We apply our algorithm to data from the marine snail,
Littorina saxatilis.
|
[
{
"created": "Wed, 21 Jan 2009 10:58:14 GMT",
"version": "v1"
}
] |
2012-06-13
|
[
[
"Eriksson",
"A.",
""
],
[
"Mehlig",
"B.",
""
],
[
"Panova",
"M.",
""
],
[
"Andre",
"C.",
""
],
[
"Johannesson",
"K.",
""
]
] |
We describe an efficient algorithm for determining exactly the minimum number of sires consistent with the multi-locus genotypes of a mother and her progeny. We consider cases where a simple exhaustive search through all possible sets of sires is impossible in practice (because it would take too long to complete). Our algorithm for solving this combinatorial optimisation problem avoids visiting large parts of search space which would not improve the solution found so far (i.e., result in a solution with fewer number of sires). This is of particular importance when the number of allelic types in the progeny array is large and when the minimum number of sires is expected to be large. Precisely in such cases it is important to know the minimum number of sires: this number gives an exact bound on the most likely number of sires estimated by a random search algorithm in a parameter region where it may be difficult to determine whether it has converged. We apply our algorithm to data from the marine snail, Littorina saxatilis.
|
2105.03961
|
Thomas Schmidt
|
Thomas Schmidt
|
Is response priming based on surface color? Response to Skrzypulec
(2021)
|
7 pages, 1 figure
| null | null | null |
q-bio.NC
|
http://creativecommons.org/licenses/by/4.0/
|
Skrzypulec (2021) raises the question whether motor activation by masked
color primes is based on the same type of color representation as conscious
vision. He postulates that the literature on color processing without awareness
makes an implicit assumption that "conscious" and "unconscious" color
representations have the same properties, in which case priming by masked color
stimuli would indeed indicate that the same complex representation of surface
color can be conscious as well as unconscious. I review some evidence from
response priming by lightness stimuli in the context of a visual illusion that
alters the perceived lightness of the primes (Schmidt et al., 2010). Those
results clearly show that response priming is not driven by color-constant
information but instead by local image contrast, making it unlikely that rapid
response activation by color primes is based on a color-constant representation
of surface color.
|
[
{
"created": "Sun, 9 May 2021 15:36:57 GMT",
"version": "v1"
},
{
"created": "Tue, 11 May 2021 09:13:21 GMT",
"version": "v2"
}
] |
2021-05-12
|
[
[
"Schmidt",
"Thomas",
""
]
] |
Skrzypulec (2021) raises the question whether motor activation by masked color primes is based on the same type of color representation as conscious vision. He postulates that the literature on color processing without awareness makes an implicit assumption that "conscious" and "unconscious" color representations have the same properties, in which case priming by masked color stimuli would indeed indicate that the same complex representation of surface color can be conscious as well as unconscious. I review some evidence from response priming by lightness stimuli in the context of a visual illusion that alters the perceived lightness of the primes (Schmidt et al., 2010). Those results clearly show that response priming is not driven by color-constant information but instead by local image contrast, making it unlikely that rapid response activation by color primes is based on a color-constant representation of surface color.
|
1010.4459
|
Marco Zamparo
|
Marco Zamparo, Antonio Trovato and Amos Maritan
|
A simplified exactly solvable model for beta-amyloid aggregation
|
4 pages, 2 figures
|
Phys. Rev. Lett. 105, 108102 (2010)
|
10.1103/PhysRevLett.105.108102
| null |
q-bio.BM cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We propose an exactly solvable simplified statistical mechanical model for
the thermodynamics of beta-amyloid aggregation, generalizing a well-studied
model for protein folding. The monomer concentration is explicitly taken into
account as well as a non trivial dependence on the microscopic degrees of
freedom of the single peptide chain, both in the alpha-helix folded isolated
state and in the fibrillar one. The phase diagram of the model is studied and
compared to the outcome of fibril formation experiments which is qualitatively
reproduced.
|
[
{
"created": "Thu, 21 Oct 2010 12:54:31 GMT",
"version": "v1"
}
] |
2010-10-22
|
[
[
"Zamparo",
"Marco",
""
],
[
"Trovato",
"Antonio",
""
],
[
"Maritan",
"Amos",
""
]
] |
We propose an exactly solvable simplified statistical mechanical model for the thermodynamics of beta-amyloid aggregation, generalizing a well-studied model for protein folding. The monomer concentration is explicitly taken into account as well as a non trivial dependence on the microscopic degrees of freedom of the single peptide chain, both in the alpha-helix folded isolated state and in the fibrillar one. The phase diagram of the model is studied and compared to the outcome of fibril formation experiments which is qualitatively reproduced.
|
q-bio/0606017
|
Wentian Li
|
Wen Fury, Franak Batliwalla, Peter K. Gregersen, and Wentian Li
|
Overlapping Probabilities of Top Ranking Gene Lists, Hypergeometric
Distribution, and Stringency of Gene Selection Criterion
|
submitted to IEEE/EMBS Conference'06
|
Proceedings of 28th Annual International Conference of the
Engineering in Medicine and Biology Society, IEEE (2006), pages 5531-5534
|
10.1109/IEMBS.2006.260828
|
q-bio.QM/0606017
|
q-bio.QM
| null |
When the same set of genes appear in two top ranking gene lists in two
different studies, it is often of interest to estimate the probability for this
being a chance event. This overlapping probability is well known to follow the
hypergeometric distribution. Usually, the lengths of top-ranking gene lists are
assumed to be fixed, by using a pre-set criterion on, e.g., $p$-value for the
t-test. We investigate how overlapping probability changes with the gene
selection criterion, or simply, with the length of the top-ranking gene lists.
It is concluded that overlapping probability is indeed a function of the gene
list length, and its statistical significance should be quoted in the context
of gene selection criterion.
|
[
{
"created": "Wed, 14 Jun 2006 20:40:14 GMT",
"version": "v1"
}
] |
2009-11-09
|
[
[
"Fury",
"Wen",
""
],
[
"Batliwalla",
"Franak",
""
],
[
"Gregersen",
"Peter K.",
""
],
[
"Li",
"Wentian",
""
]
] |
When the same set of genes appear in two top ranking gene lists in two different studies, it is often of interest to estimate the probability for this being a chance event. This overlapping probability is well known to follow the hypergeometric distribution. Usually, the lengths of top-ranking gene lists are assumed to be fixed, by using a pre-set criterion on, e.g., $p$-value for the t-test. We investigate how overlapping probability changes with the gene selection criterion, or simply, with the length of the top-ranking gene lists. It is concluded that overlapping probability is indeed a function of the gene list length, and its statistical significance should be quoted in the context of gene selection criterion.
|
1903.04347
|
Ionut Barnoaiea
|
Ionut Barnoaiea
|
Using satellite image classification and digital terrain modelling to
assess forest species distribution on mountain slopes.A case study in Varatec
Forest District
| null |
Proceedings of the 4 th International Conference Integrated
Management of Environmental Resources, 2017
| null | null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The relation between ecological conditions and geomorphological factors is
considered the basis for species distribution in Romania. In this context, the
location of each species within parts of the mountain slopes is difficult on a
medium to brad scale level. The paper presents methodology to combine
vegetation data, obtained from IKONOS satellite images, and Digital Elevation
Model obtained from digitized topographic maps. The study area is a northern
slope of the Stanisoarei Mountains with a gradient of species from beech mixed
and coniferous stands.
|
[
{
"created": "Mon, 11 Mar 2019 15:02:14 GMT",
"version": "v1"
}
] |
2019-03-12
|
[
[
"Barnoaiea",
"Ionut",
""
]
] |
The relation between ecological conditions and geomorphological factors is considered the basis for species distribution in Romania. In this context, the location of each species within parts of the mountain slopes is difficult on a medium to brad scale level. The paper presents methodology to combine vegetation data, obtained from IKONOS satellite images, and Digital Elevation Model obtained from digitized topographic maps. The study area is a northern slope of the Stanisoarei Mountains with a gradient of species from beech mixed and coniferous stands.
|
2402.09330
|
Carlos Oliver Dr.
|
Carlos Oliver, Vincent Mallet, J\'er\^ome Waldisp\"uhl
|
3D-based RNA function prediction tools in rnaglib
| null | null | null | null |
q-bio.BM cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Understanding the connection between complex structural features of RNA and
biological function is a fundamental challenge in evolutionary studies and in
RNA design. However, building datasets of RNA 3D structures and making
appropriate modeling choices remains time-consuming and lacks standardization.
In this chapter, we describe the use of rnaglib, to train supervised and
unsupervised machine learning-based function prediction models on datasets of
RNA 3D structures.
|
[
{
"created": "Wed, 14 Feb 2024 17:22:03 GMT",
"version": "v1"
},
{
"created": "Fri, 3 May 2024 09:01:17 GMT",
"version": "v2"
}
] |
2024-05-06
|
[
[
"Oliver",
"Carlos",
""
],
[
"Mallet",
"Vincent",
""
],
[
"Waldispühl",
"Jérôme",
""
]
] |
Understanding the connection between complex structural features of RNA and biological function is a fundamental challenge in evolutionary studies and in RNA design. However, building datasets of RNA 3D structures and making appropriate modeling choices remains time-consuming and lacks standardization. In this chapter, we describe the use of rnaglib, to train supervised and unsupervised machine learning-based function prediction models on datasets of RNA 3D structures.
|
1711.07162
|
Matthew Simpson
|
Wang Jin, Kai-Yin Lo, Shih-En Chou, Scott W McCue, Matthew J Simpson
|
The role of initial geometry in experimental models of wound closing
| null |
Chemical Engineering Science 2018
|
10.1016/j.ces.2018.01.004
| null |
q-bio.CB
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Wound healing assays are commonly used to study how populations of cells,
initialised on a two-dimensional surface, act to close an artificial wound
space. While real wounds have different shapes, standard wound healing assays
often deal with just one simple wound shape, and it is unclear whether varying
the wound shape might impact how we interpret results from these experiments.
In this work, we describe a new kind of wound healing assay, called a sticker
assay, that allows us to examine the role of wound shape in a series of wound
healing assays performed with fibroblast cells. In particular, we show how to
use the sticker assay to examine wound healing with square, circular and
triangular shaped wounds. We take a standard approach and report measurements
of the size of the wound as a function of time. This shows that the rate of
wound closure depends on the initial wound shape. This result is interesting
because the only aspect of the assay that we change is the initial wound shape,
and the reason for the different rate of wound closure is unclear. To provide
more insight into the experimental observations we describe our results
quantitatively by calibrating a mathematical model, describing the relevant
transport phenomena, to match our experimental data. Overall, our results
suggest that the rates of cell motility and cell proliferation from different
initial wound shapes are approximately the same, implying that the differences
we observe in the wound closure rate are consistent with a fairly typical
mathematical model of wound healing. Our results imply that parameter estimates
obtained from an experiment performed with one particular wound shape could be
used to describe an experiment performed with a different shape. This
fundamental result is important because this assumption is often invoked, but
never tested.
|
[
{
"created": "Mon, 20 Nov 2017 05:58:39 GMT",
"version": "v1"
}
] |
2018-05-18
|
[
[
"Jin",
"Wang",
""
],
[
"Lo",
"Kai-Yin",
""
],
[
"Chou",
"Shih-En",
""
],
[
"McCue",
"Scott W",
""
],
[
"Simpson",
"Matthew J",
""
]
] |
Wound healing assays are commonly used to study how populations of cells, initialised on a two-dimensional surface, act to close an artificial wound space. While real wounds have different shapes, standard wound healing assays often deal with just one simple wound shape, and it is unclear whether varying the wound shape might impact how we interpret results from these experiments. In this work, we describe a new kind of wound healing assay, called a sticker assay, that allows us to examine the role of wound shape in a series of wound healing assays performed with fibroblast cells. In particular, we show how to use the sticker assay to examine wound healing with square, circular and triangular shaped wounds. We take a standard approach and report measurements of the size of the wound as a function of time. This shows that the rate of wound closure depends on the initial wound shape. This result is interesting because the only aspect of the assay that we change is the initial wound shape, and the reason for the different rate of wound closure is unclear. To provide more insight into the experimental observations we describe our results quantitatively by calibrating a mathematical model, describing the relevant transport phenomena, to match our experimental data. Overall, our results suggest that the rates of cell motility and cell proliferation from different initial wound shapes are approximately the same, implying that the differences we observe in the wound closure rate are consistent with a fairly typical mathematical model of wound healing. Our results imply that parameter estimates obtained from an experiment performed with one particular wound shape could be used to describe an experiment performed with a different shape. This fundamental result is important because this assumption is often invoked, but never tested.
|
2206.04206
|
Ruriko Yoshida
|
Ruriko Yoshida and David Barnhill and Keiji Miura and Daniel Howe
|
Tropical Density Estimation of Phylogenetic Trees
|
18 pages
| null | null | null |
q-bio.PE
|
http://creativecommons.org/licenses/by/4.0/
|
Much evidence from biological theory and empirical data indicates that, gene
tree, phylogenetic trees reconstructed from different genes (loci), do not have
to have exactly the same tree topologies. Such incongruence between gene trees
might be caused by some ``unusual'' evolutionary events, such as meiotic sexual
recombination in eukaryotes or horizontal transfers of genetic material in
prokaryotes. However, most of gene trees are constrained by the tree topology
of its species tree, that is, the phylogenetic tree of a given species
following their evolutionary history. In order to discover ``outlying'' gene
trees which do not follow the ``main distribution(s)'' of trees, we propose to
apply the ``tropical metric'' with the max-plus algebra from tropical geometry
to a non-parametric estimation of gene trees over the space of phylogenetic
trees. In this research we apply the ``tropical metric,'' a well-defined metric
over the space of phylogenetic trees under the max-plus algebra, to
non-parametric estimation of gene trees distribution over the tree space.
Kernel density estimator (KDE) is one of the most popular non-parametric
estimation of a distribution from a given sample, and we propose an analogue of
the classical KDE in the setting of tropical geometry with the tropical metric
which measures the length of an intrinsic geodesic between trees over the tree
space. We estimate the probability of an observed tree by empirical frequencies
of nearby trees, with the level of influence determined by the tropical metric.
Then, with simulated data generated from the multispecies coalescent model, we
show that the non-parametric estimation of gene tree distribution using the
tropical metric performs better than one using the Billera-Holmes-Vogtmann
(BHV) metric developed by Weyenberg et al. in terms of computational times and
accuracy. We then apply it to Apicomplexa data.
|
[
{
"created": "Thu, 9 Jun 2022 01:06:27 GMT",
"version": "v1"
},
{
"created": "Fri, 12 Aug 2022 01:12:04 GMT",
"version": "v2"
},
{
"created": "Tue, 11 Jul 2023 13:22:00 GMT",
"version": "v3"
}
] |
2023-07-13
|
[
[
"Yoshida",
"Ruriko",
""
],
[
"Barnhill",
"David",
""
],
[
"Miura",
"Keiji",
""
],
[
"Howe",
"Daniel",
""
]
] |
Much evidence from biological theory and empirical data indicates that, gene tree, phylogenetic trees reconstructed from different genes (loci), do not have to have exactly the same tree topologies. Such incongruence between gene trees might be caused by some ``unusual'' evolutionary events, such as meiotic sexual recombination in eukaryotes or horizontal transfers of genetic material in prokaryotes. However, most of gene trees are constrained by the tree topology of its species tree, that is, the phylogenetic tree of a given species following their evolutionary history. In order to discover ``outlying'' gene trees which do not follow the ``main distribution(s)'' of trees, we propose to apply the ``tropical metric'' with the max-plus algebra from tropical geometry to a non-parametric estimation of gene trees over the space of phylogenetic trees. In this research we apply the ``tropical metric,'' a well-defined metric over the space of phylogenetic trees under the max-plus algebra, to non-parametric estimation of gene trees distribution over the tree space. Kernel density estimator (KDE) is one of the most popular non-parametric estimation of a distribution from a given sample, and we propose an analogue of the classical KDE in the setting of tropical geometry with the tropical metric which measures the length of an intrinsic geodesic between trees over the tree space. We estimate the probability of an observed tree by empirical frequencies of nearby trees, with the level of influence determined by the tropical metric. Then, with simulated data generated from the multispecies coalescent model, we show that the non-parametric estimation of gene tree distribution using the tropical metric performs better than one using the Billera-Holmes-Vogtmann (BHV) metric developed by Weyenberg et al. in terms of computational times and accuracy. We then apply it to Apicomplexa data.
|
2103.03679
|
Lu Liu
|
Xiaohan Zhang, Lu Liu, Guodong Long, Jing Jiang, Shenquan Liu
|
Episodic memory governs choices: An RNN-based reinforcement learning
model for decision-making task
|
Accepted to Neural Networks, Volume 134, February 2021, Pages 1-10
| null |
10.1016/j.neunet.2020.11.003
| null |
q-bio.NC cs.LG
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Typical methods to study cognitive function are to record the electrical
activities of animal neurons during the training of animals performing
behavioral tasks. A key problem is that they fail to record all the relevant
neurons in the animal brain. To alleviate this problem, we develop an RNN-based
Actor-Critic framework, which is trained through reinforcement learning (RL) to
solve two tasks analogous to the monkeys' decision-making tasks. The trained
model is capable of reproducing some features of neural activities recorded
from animal brain, or some behavior properties exhibited in animal experiments,
suggesting that it can serve as a computational platform to explore other
cognitive functions. Furthermore, we conduct behavioral experiments on our
framework, trying to explore an open question in neuroscience: which episodic
memory in the hippocampus should be selected to ultimately govern future
decisions. We find that the retrieval of salient events sampled from episodic
memories can effectively shorten deliberation time than common events in the
decision-making process. The results indicate that salient events stored in the
hippocampus could be prioritized to propagate reward information, and thus
allow decision-makers to learn a strategy faster.
|
[
{
"created": "Sun, 24 Jan 2021 04:33:07 GMT",
"version": "v1"
}
] |
2021-03-08
|
[
[
"Zhang",
"Xiaohan",
""
],
[
"Liu",
"Lu",
""
],
[
"Long",
"Guodong",
""
],
[
"Jiang",
"Jing",
""
],
[
"Liu",
"Shenquan",
""
]
] |
Typical methods to study cognitive function are to record the electrical activities of animal neurons during the training of animals performing behavioral tasks. A key problem is that they fail to record all the relevant neurons in the animal brain. To alleviate this problem, we develop an RNN-based Actor-Critic framework, which is trained through reinforcement learning (RL) to solve two tasks analogous to the monkeys' decision-making tasks. The trained model is capable of reproducing some features of neural activities recorded from animal brain, or some behavior properties exhibited in animal experiments, suggesting that it can serve as a computational platform to explore other cognitive functions. Furthermore, we conduct behavioral experiments on our framework, trying to explore an open question in neuroscience: which episodic memory in the hippocampus should be selected to ultimately govern future decisions. We find that the retrieval of salient events sampled from episodic memories can effectively shorten deliberation time than common events in the decision-making process. The results indicate that salient events stored in the hippocampus could be prioritized to propagate reward information, and thus allow decision-makers to learn a strategy faster.
|
2310.11791
|
Shanjun Mao
|
Shanjun Mao, Xiao Huang, Runjiu Chen, Chenyang Zhang, Yizhu Diao,
Zongjin Li, Qingzhe Wang, Shan Tang, and Shuixia Guo
|
STW-MD: A Novel Spatio-Temporal Weighting and Multi-Step Decision Tree
Method for Considering Spatial Heterogeneity in Brain Gene Expression Data
|
11 pages, 6 figures
| null | null | null |
q-bio.QM q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Motivation: Gene expression during brain development or abnormal development
is a biological process that is highly dynamic in spatio and temporal. Due to
the lack of comprehensive integration of spatial and temporal dimensions of
brain gene expression data, previous studies have mainly focused on individual
brain regions or a certain developmental stage. Our motivation is to address
this gap by incorporating spatio-temporal information to gain a more complete
understanding of the mechanisms underlying brain development or disorders
associated with abnormal brain development, such as Alzheimer's disease (AD),
and to identify potential determinants of response.
Results: In this study, we propose a novel two-step framework based on
spatial-temporal information weighting and multi-step decision trees. This
framework can effectively exploit the spatial similarity and temporal
dependence between different stages and different brain regions, and facilitate
differential gene analysis in brain regions with high heterogeneity. We focus
on two datasets: the AD dataset, which includes gene expression data from
early, middle, and late stages, and the brain development dataset, spanning
fetal development to adulthood. Our findings highlight the advantages of the
proposed framework in discovering gene classes and elucidating their impact on
brain development and AD progression across diverse brain regions and stages.
These findings align with existing studies and provide insights into the
processes of normal and abnormal brain development.
Availability: The code of STW-MD is available at
https://github.com/tsnm1/STW-MD.
|
[
{
"created": "Wed, 18 Oct 2023 08:32:22 GMT",
"version": "v1"
}
] |
2023-10-19
|
[
[
"Mao",
"Shanjun",
""
],
[
"Huang",
"Xiao",
""
],
[
"Chen",
"Runjiu",
""
],
[
"Zhang",
"Chenyang",
""
],
[
"Diao",
"Yizhu",
""
],
[
"Li",
"Zongjin",
""
],
[
"Wang",
"Qingzhe",
""
],
[
"Tang",
"Shan",
""
],
[
"Guo",
"Shuixia",
""
]
] |
Motivation: Gene expression during brain development or abnormal development is a biological process that is highly dynamic in spatio and temporal. Due to the lack of comprehensive integration of spatial and temporal dimensions of brain gene expression data, previous studies have mainly focused on individual brain regions or a certain developmental stage. Our motivation is to address this gap by incorporating spatio-temporal information to gain a more complete understanding of the mechanisms underlying brain development or disorders associated with abnormal brain development, such as Alzheimer's disease (AD), and to identify potential determinants of response. Results: In this study, we propose a novel two-step framework based on spatial-temporal information weighting and multi-step decision trees. This framework can effectively exploit the spatial similarity and temporal dependence between different stages and different brain regions, and facilitate differential gene analysis in brain regions with high heterogeneity. We focus on two datasets: the AD dataset, which includes gene expression data from early, middle, and late stages, and the brain development dataset, spanning fetal development to adulthood. Our findings highlight the advantages of the proposed framework in discovering gene classes and elucidating their impact on brain development and AD progression across diverse brain regions and stages. These findings align with existing studies and provide insights into the processes of normal and abnormal brain development. Availability: The code of STW-MD is available at https://github.com/tsnm1/STW-MD.
|
q-bio/0410033
|
Alexander Gorban
|
A.N. Gorban, T.G. Popova, A.Yu. Zinovyev
|
Four basic symmetry types in the universal 7-cluster structure of 143
complete bacterial genomic sequences
|
13 pages, 4 figures
|
In Silico Biol. 5, 0025 (2005)
http://www.bioinfo.de/isb/2005/05/0025/
| null | null |
q-bio.GN math.ST stat.TH
| null |
Coding information is the main source of heterogeneity (non-randomness) in
the sequences of bacterial genomes. This information can be naturally modeled
by analysing cluster structures in the "in-phase" triplet distributions of
relatively short genomic fragments (200-400bp). We found a universal 7-cluster
structure in bacterial genomic sequences and explained its properties. We show
that codon usage of bacterial genomes is a multi-linear function of their
genomic G+C-content with high accuracy. Based on the analysis of 143 completely
sequenced bacterial genomes available in Genbank in August 2004, we show that
there are four "pure" types of the 7-cluster structure observed. All 143
cluster animated 3D-scatters are collected in a database and is made available
on our web-site: http://www.ihes.fr/~zinovyev/7clusters The finding can be
readily introduced into any software for gene prediction, sequence alignment or
bacterial genomes classification.
|
[
{
"created": "Wed, 27 Oct 2004 20:31:06 GMT",
"version": "v1"
}
] |
2011-11-09
|
[
[
"Gorban",
"A. N.",
""
],
[
"Popova",
"T. G.",
""
],
[
"Zinovyev",
"A. Yu.",
""
]
] |
Coding information is the main source of heterogeneity (non-randomness) in the sequences of bacterial genomes. This information can be naturally modeled by analysing cluster structures in the "in-phase" triplet distributions of relatively short genomic fragments (200-400bp). We found a universal 7-cluster structure in bacterial genomic sequences and explained its properties. We show that codon usage of bacterial genomes is a multi-linear function of their genomic G+C-content with high accuracy. Based on the analysis of 143 completely sequenced bacterial genomes available in Genbank in August 2004, we show that there are four "pure" types of the 7-cluster structure observed. All 143 cluster animated 3D-scatters are collected in a database and is made available on our web-site: http://www.ihes.fr/~zinovyev/7clusters The finding can be readily introduced into any software for gene prediction, sequence alignment or bacterial genomes classification.
|
1703.05099
|
Christophe Guyeux
|
Huda Al-Nayyef and Christophe Guyeux and Jacques M. Bahi
|
Taenia Biomolecular Phylogeny and the Impact of Mitochondrial Genes on
this Latter
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Variations in mitochondrial genes are usually considered to infer
phylogenies. However some of these genes are lesser constraint than other ones,
and thus may blur the phylogenetic signals shared by the majority of the
mitochondrial DNA sequences. To investigate such effects, in this research
work, the molecular phylogeny of the genus Taenia is studied using 14 coding
sequences extracted from mitochondrial genomes of 17 species. We constructed
16,384 trees, using a combination of 1 up to 14 genes. We obtained 131
topologies, and we showed that only four particular instances were relevant.
Using further statistical investigations, we then extracted a particular
topology, which displays more robustness properties.
|
[
{
"created": "Wed, 15 Mar 2017 12:01:24 GMT",
"version": "v1"
}
] |
2017-03-16
|
[
[
"Al-Nayyef",
"Huda",
""
],
[
"Guyeux",
"Christophe",
""
],
[
"Bahi",
"Jacques M.",
""
]
] |
Variations in mitochondrial genes are usually considered to infer phylogenies. However some of these genes are lesser constraint than other ones, and thus may blur the phylogenetic signals shared by the majority of the mitochondrial DNA sequences. To investigate such effects, in this research work, the molecular phylogeny of the genus Taenia is studied using 14 coding sequences extracted from mitochondrial genomes of 17 species. We constructed 16,384 trees, using a combination of 1 up to 14 genes. We obtained 131 topologies, and we showed that only four particular instances were relevant. Using further statistical investigations, we then extracted a particular topology, which displays more robustness properties.
|
1612.09595
|
Peter Waddell
|
Peter J. Waddell
|
Complimentary Phylogenetic Signals for Morphological Characters and
Quantitative 3D Shape Data within genus Homo
|
12 pages, 6 figures
| null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Estimating the phylogeny of the genus Homo is entering a new phase of vastly
improved data and methodology. There is increasing evidence of 6 to 10
competing species/lineages at any point in the last half million years, making
the elucidation of the relationships of individual specimens particularly
important. Recent estimates of the phylogeny of key specimens include Waddell
(2013, 2014, 2015, 2016), and Mounier et al. (2016). These are made with quite
different data (3D skull shapes and discrete morphological characters,
respectively) and methods of analysis (unweighted least squares fitting of
distances, OLS+, and reweighted maximum parsimony, respectively). Initial
inspection of the trees in these articles might leave the impression of a great
deal of disagreement and confused results. Here it is shown this need not be
the case, and that these two types of data and analysis may be indicating a
very similar tree, one that is in good agreement also with subjective current
wisdom/expert opinions on particular parts of the phylogeny. The precise
location of the African LH18 specimen arises as key to a better understanding
of the likely form of the last common ancestors of H. sapiens and Neanderthals.
A diverse approach seems to bring forth much more agreement of trees than
otherwise perceived, and argues against being dogmatic about methods of
phylogenetic analysis particularly when working with difficult problems.
|
[
{
"created": "Fri, 30 Dec 2016 20:51:22 GMT",
"version": "v1"
}
] |
2017-01-02
|
[
[
"Waddell",
"Peter J.",
""
]
] |
Estimating the phylogeny of the genus Homo is entering a new phase of vastly improved data and methodology. There is increasing evidence of 6 to 10 competing species/lineages at any point in the last half million years, making the elucidation of the relationships of individual specimens particularly important. Recent estimates of the phylogeny of key specimens include Waddell (2013, 2014, 2015, 2016), and Mounier et al. (2016). These are made with quite different data (3D skull shapes and discrete morphological characters, respectively) and methods of analysis (unweighted least squares fitting of distances, OLS+, and reweighted maximum parsimony, respectively). Initial inspection of the trees in these articles might leave the impression of a great deal of disagreement and confused results. Here it is shown this need not be the case, and that these two types of data and analysis may be indicating a very similar tree, one that is in good agreement also with subjective current wisdom/expert opinions on particular parts of the phylogeny. The precise location of the African LH18 specimen arises as key to a better understanding of the likely form of the last common ancestors of H. sapiens and Neanderthals. A diverse approach seems to bring forth much more agreement of trees than otherwise perceived, and argues against being dogmatic about methods of phylogenetic analysis particularly when working with difficult problems.
|
1606.09048
|
Daniele De Martino
|
Daniele De Martino and Davide Masoero
|
Asymptotic analysis of noisy fitness maximization, applied to metabolism
and growth
|
24 pages, 6 figures
|
JSTAT (2016), n 12
|
10.1088/1742-5468/aa4e8f
| null |
q-bio.PE cond-mat.stat-mech math-ph math.MP
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We consider a population dynamics model coupling cell growth to a diffusion
in the space of metabolic phenotypes as it can be obtained from realistic
constraints-based modelling. In the asymptotic regime of slow diffusion, that
coincides with the relevant experimental range, the resulting non-linear
Fokker-Planck equation is solved for the steady state in the WKB approximation
that maps it into the ground state of a quantum particle in an Airy potential
plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations
and time response with respect to the distance from the maximum growth rate
suggesting that suboptimal populations can have a faster response to
perturbations.
|
[
{
"created": "Wed, 29 Jun 2016 11:19:15 GMT",
"version": "v1"
},
{
"created": "Thu, 27 Oct 2016 08:08:30 GMT",
"version": "v2"
}
] |
2017-02-17
|
[
[
"De Martino",
"Daniele",
""
],
[
"Masoero",
"Davide",
""
]
] |
We consider a population dynamics model coupling cell growth to a diffusion in the space of metabolic phenotypes as it can be obtained from realistic constraints-based modelling. In the asymptotic regime of slow diffusion, that coincides with the relevant experimental range, the resulting non-linear Fokker-Planck equation is solved for the steady state in the WKB approximation that maps it into the ground state of a quantum particle in an Airy potential plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations and time response with respect to the distance from the maximum growth rate suggesting that suboptimal populations can have a faster response to perturbations.
|
2405.07238
|
Vasileios Alevizos
|
Vasileios Alevizos, Clark Xu, Sabrina Edralin, Akebu Simasiku, Dimitra
Malliarou, Zongliang Yue, Antonis Messinis
|
Handwriting Anomalies and Learning Disabilities through Recurrent Neural
Networks and Geometric Pattern Analysis
| null | null | null | null |
q-bio.QM
|
http://creativecommons.org/licenses/by/4.0/
|
Dyslexia and dysgraphia are learning disabilities that significantly impact
reading, writing, and language processing capabilities. Dyslexia primarily
affects reading, manifesting as difficulties in word recognition and
phonological processing, where individuals struggle to connect sounds with
corresponding letters. Dysgraphia, on the other side, affects writing
abilities, leading to problems with letter formation, spacing, and alignment.
Coexistence of these disorders complicates diagnosis. This necessitates a
nuanced approach that can adapt to these changes and still accurately identify
and differentiate between these disorders. This study utilizes advanced
geometrical patterns and recurrent neural networks (RNN) to identify
handwriting anomalies indicative of dyslexia and dysgraphia. Handwriting
standardized features followed by feature extraction that focuses on baseline
deviations, letter connectivity, stroke thickness and other anomalies into RNN
based autoencoder to identify irregularities. Initial results show the
challenge associated with complex pattern adaptation.
|
[
{
"created": "Sun, 12 May 2024 10:10:13 GMT",
"version": "v1"
}
] |
2024-05-14
|
[
[
"Alevizos",
"Vasileios",
""
],
[
"Xu",
"Clark",
""
],
[
"Edralin",
"Sabrina",
""
],
[
"Simasiku",
"Akebu",
""
],
[
"Malliarou",
"Dimitra",
""
],
[
"Yue",
"Zongliang",
""
],
[
"Messinis",
"Antonis",
""
]
] |
Dyslexia and dysgraphia are learning disabilities that significantly impact reading, writing, and language processing capabilities. Dyslexia primarily affects reading, manifesting as difficulties in word recognition and phonological processing, where individuals struggle to connect sounds with corresponding letters. Dysgraphia, on the other side, affects writing abilities, leading to problems with letter formation, spacing, and alignment. Coexistence of these disorders complicates diagnosis. This necessitates a nuanced approach that can adapt to these changes and still accurately identify and differentiate between these disorders. This study utilizes advanced geometrical patterns and recurrent neural networks (RNN) to identify handwriting anomalies indicative of dyslexia and dysgraphia. Handwriting standardized features followed by feature extraction that focuses on baseline deviations, letter connectivity, stroke thickness and other anomalies into RNN based autoencoder to identify irregularities. Initial results show the challenge associated with complex pattern adaptation.
|
1704.07184
|
Yana Safonova
|
Alexander Shlemov, Sergey Bankevich, Andrey Bzikadze, Maria A.
Turchaninova, Yana Safonova and Pavel A. Pevzner
|
Reconstructing antibody repertoires from error-prone immunosequencing
datasets
|
Short version was accepted to RECOMB 2017
| null | null | null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Transforming error-prone immunosequencing datasets into antibody repertoires
is a fundamental problem in immunogenomics, and a prerequisite for studies of
immune responses. Although various repertoire reconstruction algorithms were
released in the last three years, it remains unclear how to benchmark them and
how to assess the accuracy of the reconstructed repertoires. We describe a
novel IgReC algorithm for constructing antibody repertoires from
high-throughput immunosequencing datasets and a new framework for assessing the
quality of reconstructed repertoires. Benchmarking IgReC against the existing
antibody repertoire reconstruction tools has demonstrated that it results in
highly accurate repertoire reconstructions. Surprisingly, antibody repertoires
constructed by IgReC from barcoded immunosequencing datasets in blind mode
(without using unique molecular identifiers information) improved upon the
repertoires constructed by the state-of-the-art tools that use barcoding. This
finding suggests that IgReC may alleviate the need to generate repertoires
using the barcoding technology (the workhorse of current immunogenomics
efforts) because our computational approach to error correction of
immunosequencing data ends up being nearly as powerful as the experimental
approach based on barcoding.
|
[
{
"created": "Mon, 24 Apr 2017 12:46:40 GMT",
"version": "v1"
}
] |
2017-04-25
|
[
[
"Shlemov",
"Alexander",
""
],
[
"Bankevich",
"Sergey",
""
],
[
"Bzikadze",
"Andrey",
""
],
[
"Turchaninova",
"Maria A.",
""
],
[
"Safonova",
"Yana",
""
],
[
"Pevzner",
"Pavel A.",
""
]
] |
Transforming error-prone immunosequencing datasets into antibody repertoires is a fundamental problem in immunogenomics, and a prerequisite for studies of immune responses. Although various repertoire reconstruction algorithms were released in the last three years, it remains unclear how to benchmark them and how to assess the accuracy of the reconstructed repertoires. We describe a novel IgReC algorithm for constructing antibody repertoires from high-throughput immunosequencing datasets and a new framework for assessing the quality of reconstructed repertoires. Benchmarking IgReC against the existing antibody repertoire reconstruction tools has demonstrated that it results in highly accurate repertoire reconstructions. Surprisingly, antibody repertoires constructed by IgReC from barcoded immunosequencing datasets in blind mode (without using unique molecular identifiers information) improved upon the repertoires constructed by the state-of-the-art tools that use barcoding. This finding suggests that IgReC may alleviate the need to generate repertoires using the barcoding technology (the workhorse of current immunogenomics efforts) because our computational approach to error correction of immunosequencing data ends up being nearly as powerful as the experimental approach based on barcoding.
|
1509.01194
|
Andy Lewis-Pye
|
Andrew Lewis-Pye, Antonio Montalban
|
A mathematical analysis of the evolutionary benefits of sexual
reproduction
| null | null | null | null |
q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The question as to why most higher organisms reproduce sexually has remained
open despite extensive research, and has been called "the queen of problems in
evolutionary biology". Theories dating back to Weismann have suggested that the
key must lie in the creation of increased variability in offspring, causing
enhanced response to selection. Rigorously quantifying the effects of assorted
mechanisms which might lead to such increased variability, and establishing
that these beneficial effects outweigh the immediate costs of sexual
reproduction has, however, proved problematic. Here we introduce an approach
which does not focus on particular mechanisms influencing factors such as the
fixation of beneficial mutants or the ability of populations to deal with
deleterious mutations, but rather tracks the entire distribution of a
population of genotypes as it moves across vast fitness landscapes. In this
setting simulations now show sex robustly outperforming asex across a broad
spectrum of finite or infinite population models. Concentrating on the additive
infinite populations model, we are able to give a rigorous mathematical proof
establishing that sexual reproduction acts as a more efficient optimiser of
mean fitness, thereby solving the problem for this model. Some of the key
features of this analysis carry through to the finite populations case.
|
[
{
"created": "Wed, 2 Sep 2015 05:17:15 GMT",
"version": "v1"
}
] |
2015-09-04
|
[
[
"Lewis-Pye",
"Andrew",
""
],
[
"Montalban",
"Antonio",
""
]
] |
The question as to why most higher organisms reproduce sexually has remained open despite extensive research, and has been called "the queen of problems in evolutionary biology". Theories dating back to Weismann have suggested that the key must lie in the creation of increased variability in offspring, causing enhanced response to selection. Rigorously quantifying the effects of assorted mechanisms which might lead to such increased variability, and establishing that these beneficial effects outweigh the immediate costs of sexual reproduction has, however, proved problematic. Here we introduce an approach which does not focus on particular mechanisms influencing factors such as the fixation of beneficial mutants or the ability of populations to deal with deleterious mutations, but rather tracks the entire distribution of a population of genotypes as it moves across vast fitness landscapes. In this setting simulations now show sex robustly outperforming asex across a broad spectrum of finite or infinite population models. Concentrating on the additive infinite populations model, we are able to give a rigorous mathematical proof establishing that sexual reproduction acts as a more efficient optimiser of mean fitness, thereby solving the problem for this model. Some of the key features of this analysis carry through to the finite populations case.
|
1510.00660
|
Paolo Masulli
|
Paolo Masulli and Alessandro E. P. Villa
|
The topology of the directed clique complex as a network invariant
|
13 pages, 3 figures. Figures and captions improved, typographical
changes
|
SpringerPlus (2016) 5(1), 1-12
|
10.1186/s40064-016-2022-y
| null |
q-bio.NC math.AT nlin.AO
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
We introduce new algebro-topological invariants of directed networks, based
on the topological construction of the directed clique complex. The shape of
the underlying directed graph is encoded in a way that can be studied
mathematically to obtain network invariants such as the Euler characteristic
and the Betti numbers. Two different cases illustrate the application of the
Euler characteristic. We investigate how the evolution of a Boolean recurrent
artificial neural network is influenced by its topology in a dynamics involving
pruning and strengthening of the connections, and to show that the topological
features of the directed clique complex influence the dynamical evolution of
the network. The second application considers the directed clique complex in a
broader framework, to define an invariant of directed networks, the network
degree invariant, which is constructed by computing the topological invariant
on a sequence of sub-networks filtered by the minimum in- or out-degree of the
nodes. The application of the Euler characteristic presented here can be
extended to any directed network and provides a new method for the assessment
of specific functional features associated with the network topology.
|
[
{
"created": "Fri, 2 Oct 2015 17:49:02 GMT",
"version": "v1"
},
{
"created": "Wed, 4 Nov 2015 11:26:30 GMT",
"version": "v2"
},
{
"created": "Tue, 5 Apr 2016 15:07:31 GMT",
"version": "v3"
}
] |
2016-04-06
|
[
[
"Masulli",
"Paolo",
""
],
[
"Villa",
"Alessandro E. P.",
""
]
] |
We introduce new algebro-topological invariants of directed networks, based on the topological construction of the directed clique complex. The shape of the underlying directed graph is encoded in a way that can be studied mathematically to obtain network invariants such as the Euler characteristic and the Betti numbers. Two different cases illustrate the application of the Euler characteristic. We investigate how the evolution of a Boolean recurrent artificial neural network is influenced by its topology in a dynamics involving pruning and strengthening of the connections, and to show that the topological features of the directed clique complex influence the dynamical evolution of the network. The second application considers the directed clique complex in a broader framework, to define an invariant of directed networks, the network degree invariant, which is constructed by computing the topological invariant on a sequence of sub-networks filtered by the minimum in- or out-degree of the nodes. The application of the Euler characteristic presented here can be extended to any directed network and provides a new method for the assessment of specific functional features associated with the network topology.
|
2301.04849
|
Chen Shen
|
Chen Shen, Zhao Song, Lei Shi, Jun Tanimoto, and Zhen Wang
|
Exit options sustain altruistic punishment and decrease the second-order
free-riders, but it is not a panacea
|
15 pages, 8 figures
| null | null | null |
q-bio.PE physics.soc-ph
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Altruistic punishment, where individuals incur personal costs to punish
others who have harmed third parties, presents an evolutionary conundrum as it
undermines individual fitness. Resolving this puzzle is crucial for
understanding the emergence and maintenance of human cooperation. This study
investigates the role of an alternative strategy, the exit option, in
explaining altruistic punishment. We analyze a two-stage prisoner's dilemma
game in well-mixed and networked populations, considering both finite and
infinite scenarios. Our findings reveal that the exit option does not
significantly enhance altruistic punishment in well-mixed populations. However,
in networked populations, the exit option enables the existence of altruistic
punishment and gives rise to complex dynamics, including cyclic dominance and
bi-stable states. This research contributes to our understanding of costly
punishment and sheds light on the effectiveness of different voluntary
participation strategies in addressing the conundrum of punishment.
|
[
{
"created": "Thu, 12 Jan 2023 07:24:05 GMT",
"version": "v1"
},
{
"created": "Wed, 26 Jul 2023 04:20:59 GMT",
"version": "v2"
}
] |
2023-07-27
|
[
[
"Shen",
"Chen",
""
],
[
"Song",
"Zhao",
""
],
[
"Shi",
"Lei",
""
],
[
"Tanimoto",
"Jun",
""
],
[
"Wang",
"Zhen",
""
]
] |
Altruistic punishment, where individuals incur personal costs to punish others who have harmed third parties, presents an evolutionary conundrum as it undermines individual fitness. Resolving this puzzle is crucial for understanding the emergence and maintenance of human cooperation. This study investigates the role of an alternative strategy, the exit option, in explaining altruistic punishment. We analyze a two-stage prisoner's dilemma game in well-mixed and networked populations, considering both finite and infinite scenarios. Our findings reveal that the exit option does not significantly enhance altruistic punishment in well-mixed populations. However, in networked populations, the exit option enables the existence of altruistic punishment and gives rise to complex dynamics, including cyclic dominance and bi-stable states. This research contributes to our understanding of costly punishment and sheds light on the effectiveness of different voluntary participation strategies in addressing the conundrum of punishment.
|
2106.06029
|
Pedro F da Costa
|
Pedro F. da Costa, Rianne Haartsen, Elena Throm, Luke Mason, Anna Gui,
Robert Leech, Emily J.H. Jones
|
Neuroadaptive electroencephalography: a proof-of-principle study in
infants
|
25 pages, 4 figures
| null | null | null |
q-bio.NC q-bio.QM
|
http://creativecommons.org/licenses/by-nc-nd/4.0/
|
A core goal of functional neuroimaging is to study how the environment is
processed in the brain. The mainstream paradigm involves concurrently measuring
a broad spectrum of brain responses to a small set of environmental features
preselected with reference to previous studies or a theoretical framework. As a
complement, we invert this approach by allowing the investigator to record the
modulation of a preselected brain response by a broad spectrum of environmental
features. Our approach is optimal when theoretical frameworks or previous
empirical data are impoverished. By using a prespecified closed-loop design,
the approach addresses fundamental challenges of reproducibility and
generalisability in brain research. These conditions are particularly acute
when studying the developing brain, where our theories based on adult brain
function may fundamentally misrepresent the topography of infant cognition and
where there are substantial practical challenges to data acquisition. Our
methodology employs machine learning to map modulation of a neural feature
across a space of experimental stimuli. Our method collects, processes and
analyses EEG brain data in real-time; and uses a neuro-adaptive Bayesian
optimisation algorithm to adjust the stimulus presented depending on the prior
samples of a given participant. Unsampled stimuli can be interpolated by
fitting a Gaussian process regression along the dataset. We show that our
method can automatically identify the face of the infant's mother through
online recording of their Nc brain response to a face continuum. We can
retrieve model statistics of individualised responses for each participant,
opening the door for early identification of atypical development. This
approach has substantial potential in infancy research and beyond for improving
power and generalisability of mapping the individual cognitive topography of
brain function.
|
[
{
"created": "Thu, 10 Jun 2021 20:13:04 GMT",
"version": "v1"
}
] |
2021-06-14
|
[
[
"da Costa",
"Pedro F.",
""
],
[
"Haartsen",
"Rianne",
""
],
[
"Throm",
"Elena",
""
],
[
"Mason",
"Luke",
""
],
[
"Gui",
"Anna",
""
],
[
"Leech",
"Robert",
""
],
[
"Jones",
"Emily J. H.",
""
]
] |
A core goal of functional neuroimaging is to study how the environment is processed in the brain. The mainstream paradigm involves concurrently measuring a broad spectrum of brain responses to a small set of environmental features preselected with reference to previous studies or a theoretical framework. As a complement, we invert this approach by allowing the investigator to record the modulation of a preselected brain response by a broad spectrum of environmental features. Our approach is optimal when theoretical frameworks or previous empirical data are impoverished. By using a prespecified closed-loop design, the approach addresses fundamental challenges of reproducibility and generalisability in brain research. These conditions are particularly acute when studying the developing brain, where our theories based on adult brain function may fundamentally misrepresent the topography of infant cognition and where there are substantial practical challenges to data acquisition. Our methodology employs machine learning to map modulation of a neural feature across a space of experimental stimuli. Our method collects, processes and analyses EEG brain data in real-time; and uses a neuro-adaptive Bayesian optimisation algorithm to adjust the stimulus presented depending on the prior samples of a given participant. Unsampled stimuli can be interpolated by fitting a Gaussian process regression along the dataset. We show that our method can automatically identify the face of the infant's mother through online recording of their Nc brain response to a face continuum. We can retrieve model statistics of individualised responses for each participant, opening the door for early identification of atypical development. This approach has substantial potential in infancy research and beyond for improving power and generalisability of mapping the individual cognitive topography of brain function.
|
0807.1869
|
Antonio Deiana
|
Antonio Deiana, Andrea Giansanti
|
Number of natively unfolded proteins scales with genome size
|
Submitted to Biophysics and Bioengineering Letters
http://padis2.uniroma1.it:81/ojs/index.php/CISB-BBL
| null | null | null |
q-bio.GN q-bio.PE
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Natively unfolded proteins exist as an ensemble of flexible conformations
lacking a well defined tertiary structure along a large portion of their
polypeptide chain. Despite the absence of a stable configuration, they are
involved in important cellular processes. In this work we used from three
indicators of folding status, derived from the analysis of mean packing and
mean contact energy of a protein sequence as well as from VSL2, a disorder
predictor, and we combined them into a consensus score to identify natively
unfolded proteins in several genomes from Archaea, Bacteria and Eukarya. We
found a high correlation among the number of predicted natively unfolded
proteins and the number of proteins in the genomes. More specifically, the
number of natively unfolded proteins scaled with the number of proteins in the
genomes, with exponent 1.81 +- 0.10. This scaling law may be important to
understand the relation between the number of natively unfolded proteins and
their roles in cellular processes.
|
[
{
"created": "Fri, 11 Jul 2008 15:22:48 GMT",
"version": "v1"
}
] |
2008-07-14
|
[
[
"Deiana",
"Antonio",
""
],
[
"Giansanti",
"Andrea",
""
]
] |
Natively unfolded proteins exist as an ensemble of flexible conformations lacking a well defined tertiary structure along a large portion of their polypeptide chain. Despite the absence of a stable configuration, they are involved in important cellular processes. In this work we used from three indicators of folding status, derived from the analysis of mean packing and mean contact energy of a protein sequence as well as from VSL2, a disorder predictor, and we combined them into a consensus score to identify natively unfolded proteins in several genomes from Archaea, Bacteria and Eukarya. We found a high correlation among the number of predicted natively unfolded proteins and the number of proteins in the genomes. More specifically, the number of natively unfolded proteins scaled with the number of proteins in the genomes, with exponent 1.81 +- 0.10. This scaling law may be important to understand the relation between the number of natively unfolded proteins and their roles in cellular processes.
|
2108.00371
|
Eduardo Cocca Padovani
|
Eduardo C. Padovani
|
Macaque's Cortical Functional Connectivity Dynamics at the Onset of
Propofol-Induced Anesthesia
|
20 pages, 5 figures
| null | null | null |
q-bio.NC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Propofol, when administered for general anesthesia, induces oscillatory
dynamic brain states that are thought to underlie the drug's pharmacological
effects. Despite the elucidation of propofol's mechanisms of action at the
molecular level, its effects on neural circuits and overall cortical
functioning, which eventually lead to unconsciousness, are still unclear. To
identify possible mechanisms, the spatial-temporal patterns of functional
connectivity established among specialized cortical areas in anesthetized
subjects need to be described. Within this context, the present research
involved the analysis of dense sub-dural ECoG electrode array recordings from
macaques under propofol anesthetic induction. Granger causality methodology was
used to infer functional connectivity interactions in five physiological
frequency bands serially over time, every five seconds throughout the
experiment. The time-resolved networks obtained permitted us to observe the
unfolding of the anesthetic induction and compare the networks obtained under
different experimental conditions. About one minute after administering
propofol, functional connectivity started to increase for 4-5 minutes, then
decreased until the LOC was achieved. A predominant Granger causality flow from
the occipital and temporal areas towards the frontal and parietal regions was
also evidenced during the transition. During general anesthesia, the local
connectivity of the occipital lobe increased, as did the interactions between
the occipital and temporal lobes. Conversely, the functional connectivity from
the frontal and parietal lobes toward the temporal and occipital regions was
mainly impaired. The research is one of the first studies to describe the
dynamics of the functional connectivity during the transitional state that
precedes the LOC.
|
[
{
"created": "Sun, 1 Aug 2021 06:08:26 GMT",
"version": "v1"
},
{
"created": "Tue, 5 Sep 2023 12:34:25 GMT",
"version": "v2"
}
] |
2023-09-06
|
[
[
"Padovani",
"Eduardo C.",
""
]
] |
Propofol, when administered for general anesthesia, induces oscillatory dynamic brain states that are thought to underlie the drug's pharmacological effects. Despite the elucidation of propofol's mechanisms of action at the molecular level, its effects on neural circuits and overall cortical functioning, which eventually lead to unconsciousness, are still unclear. To identify possible mechanisms, the spatial-temporal patterns of functional connectivity established among specialized cortical areas in anesthetized subjects need to be described. Within this context, the present research involved the analysis of dense sub-dural ECoG electrode array recordings from macaques under propofol anesthetic induction. Granger causality methodology was used to infer functional connectivity interactions in five physiological frequency bands serially over time, every five seconds throughout the experiment. The time-resolved networks obtained permitted us to observe the unfolding of the anesthetic induction and compare the networks obtained under different experimental conditions. About one minute after administering propofol, functional connectivity started to increase for 4-5 minutes, then decreased until the LOC was achieved. A predominant Granger causality flow from the occipital and temporal areas towards the frontal and parietal regions was also evidenced during the transition. During general anesthesia, the local connectivity of the occipital lobe increased, as did the interactions between the occipital and temporal lobes. Conversely, the functional connectivity from the frontal and parietal lobes toward the temporal and occipital regions was mainly impaired. The research is one of the first studies to describe the dynamics of the functional connectivity during the transitional state that precedes the LOC.
|
q-bio/0612035
|
Andras Czirok
|
Andras Szabo, Erica D. Perryn, Andras Czirok
|
Network formation of tissue cells via preferential attraction to
elongated structures
| null | null |
10.1103/PhysRevLett.98.038102
| null |
q-bio.CB
| null |
Vascular and non-vascular cells often form an interconnected network in
vitro, similar to the early vascular bed of warm blooded embryos. Our
time-lapse recordings show that the network forms by extending sprouts, i.e.,
multicellular linear segments. To explain the emergence of such structures, we
propose a simple model of preferential attraction to stretched cells. Numerical
simulations reveal that the model evolves into a quasi-stationary pattern
containing linear segments, which interconnect above the critical volume
fraction of 0.2. In the quasi-stationary state the generation of new branches
offset the coarsening driven by surface tension. In agreement with empirical
data, the characteristic size of the resulting polygonal pattern is
density-independent within a wide range of volume fractions.
|
[
{
"created": "Mon, 18 Dec 2006 12:38:52 GMT",
"version": "v1"
}
] |
2009-11-13
|
[
[
"Szabo",
"Andras",
""
],
[
"Perryn",
"Erica D.",
""
],
[
"Czirok",
"Andras",
""
]
] |
Vascular and non-vascular cells often form an interconnected network in vitro, similar to the early vascular bed of warm blooded embryos. Our time-lapse recordings show that the network forms by extending sprouts, i.e., multicellular linear segments. To explain the emergence of such structures, we propose a simple model of preferential attraction to stretched cells. Numerical simulations reveal that the model evolves into a quasi-stationary pattern containing linear segments, which interconnect above the critical volume fraction of 0.2. In the quasi-stationary state the generation of new branches offset the coarsening driven by surface tension. In agreement with empirical data, the characteristic size of the resulting polygonal pattern is density-independent within a wide range of volume fractions.
|
2405.11010
|
Diego Bonatto
|
Ana Paula Wives, Isabelli Seiler de Medeiros Mendes, Sofia Turatti dos
Santos, and Diego Bonatto
|
Molecular techniques employed in CTG(Ser1) and CTG(Ala) D-xylose
metabolizing yeast clades for strain design and industrial applications
|
32 pages, 4 tables
| null | null | null |
q-bio.QM
|
http://creativecommons.org/licenses/by/4.0/
|
D-xylose is the second most abundant monosaccharide found in lignocellulose
and is of biotechnological importance for producing second-generation ethanol
and other high-value chemical compounds. D-xylose conversion to ethanol is
promoted by microbial fermentation, mainly by bacteria, yeasts, or filamentous
fungi. Considering yeasts, species belonging to the CTG(Ser1) or CTG(Ala) clade
display a remarkable ability to ferment D-xylose to ethanol and other
compounds; however, these yeasts are not employed on an industrial scale due to
the poor fermentative performance compared to conventional yeasts, like
Saccharomyces cerevisiae, and also due to the lack of a molecular toolbox for
development of new strains tailored to fermentation stress tolerance and
performance. Thus, the purpose of this review is to evaluate the major
molecular tools (e.g., transformation markers and techniques, vectors,
regulatory sequences, and gene editing techniques) available for the most
studied yeasts of CTG(Ser1) clade, like Scheffersomyces, Spathaspora, Candida
and Yamadazyma species, and the CTG(Ala) clade representative Pachysolen
tannophilus. Furthermore, we synthesized the current state-of-the-art molecular
developments and perspectives for D-xylose fermenting yeast strain design.
|
[
{
"created": "Fri, 17 May 2024 15:06:50 GMT",
"version": "v1"
},
{
"created": "Tue, 21 May 2024 16:32:50 GMT",
"version": "v2"
}
] |
2024-05-22
|
[
[
"Wives",
"Ana Paula",
""
],
[
"Mendes",
"Isabelli Seiler de Medeiros",
""
],
[
"Santos",
"Sofia Turatti dos",
""
],
[
"Bonatto",
"Diego",
""
]
] |
D-xylose is the second most abundant monosaccharide found in lignocellulose and is of biotechnological importance for producing second-generation ethanol and other high-value chemical compounds. D-xylose conversion to ethanol is promoted by microbial fermentation, mainly by bacteria, yeasts, or filamentous fungi. Considering yeasts, species belonging to the CTG(Ser1) or CTG(Ala) clade display a remarkable ability to ferment D-xylose to ethanol and other compounds; however, these yeasts are not employed on an industrial scale due to the poor fermentative performance compared to conventional yeasts, like Saccharomyces cerevisiae, and also due to the lack of a molecular toolbox for development of new strains tailored to fermentation stress tolerance and performance. Thus, the purpose of this review is to evaluate the major molecular tools (e.g., transformation markers and techniques, vectors, regulatory sequences, and gene editing techniques) available for the most studied yeasts of CTG(Ser1) clade, like Scheffersomyces, Spathaspora, Candida and Yamadazyma species, and the CTG(Ala) clade representative Pachysolen tannophilus. Furthermore, we synthesized the current state-of-the-art molecular developments and perspectives for D-xylose fermenting yeast strain design.
|
2005.11615
|
Vahe Galstyan Mr.
|
Vahe Galstyan, Kabir Husain, Fangzhou Xiao, Arvind Murugan, Rob
Phillips
|
Proofreading through spatial gradients
| null | null | null | null |
q-bio.MN physics.bio-ph
|
http://creativecommons.org/licenses/by/4.0/
|
Key enzymatic processes in biology use the nonequilibrium error correction
mechanism called kinetic proofreading to enhance their specificity. Kinetic
proofreading typically requires several dedicated structural features in the
enzyme, such as a nucleotide hydrolysis site and multiple enzyme-substrate
conformations that delay product formation. Such requirements limit the
applicability and the adaptability of traditional proofreading schemes. Here,
we explore an alternative conceptual mechanism of error correction that
achieves delays between substrate binding and subsequent product formation by
having these events occur at distinct physical locations. The time taken by the
enzyme-substrate complex to diffuse from one location to another is leveraged
to discard wrong substrates. This mechanism does not require dedicated
structural elements on the enzyme, making it easier to overlook in experiments
but also making proofreading tunable on the fly. We discuss how tuning the
length scales of enzyme or substrate concentration gradients changes the
fidelity, speed and energy dissipation, and quantify the performance
limitations imposed by realistic diffusion and reaction rates in the cell. Our
work broadens the applicability of kinetic proofreading, and sets the stage for
the study of spatial gradients as a possible route to specificity.
|
[
{
"created": "Sat, 23 May 2020 22:41:40 GMT",
"version": "v1"
}
] |
2020-05-26
|
[
[
"Galstyan",
"Vahe",
""
],
[
"Husain",
"Kabir",
""
],
[
"Xiao",
"Fangzhou",
""
],
[
"Murugan",
"Arvind",
""
],
[
"Phillips",
"Rob",
""
]
] |
Key enzymatic processes in biology use the nonequilibrium error correction mechanism called kinetic proofreading to enhance their specificity. Kinetic proofreading typically requires several dedicated structural features in the enzyme, such as a nucleotide hydrolysis site and multiple enzyme-substrate conformations that delay product formation. Such requirements limit the applicability and the adaptability of traditional proofreading schemes. Here, we explore an alternative conceptual mechanism of error correction that achieves delays between substrate binding and subsequent product formation by having these events occur at distinct physical locations. The time taken by the enzyme-substrate complex to diffuse from one location to another is leveraged to discard wrong substrates. This mechanism does not require dedicated structural elements on the enzyme, making it easier to overlook in experiments but also making proofreading tunable on the fly. We discuss how tuning the length scales of enzyme or substrate concentration gradients changes the fidelity, speed and energy dissipation, and quantify the performance limitations imposed by realistic diffusion and reaction rates in the cell. Our work broadens the applicability of kinetic proofreading, and sets the stage for the study of spatial gradients as a possible route to specificity.
|
1902.07303
|
Su-Chan Park
|
Alexander Klug, Su-Chan Park, Joachim Krug
|
Recombination and mutational robustness in neutral fitness landscapes
|
15 figures, Supplementary appendix, supplementary figures
|
PLoS Comput Biol 15(8): e1006884 (2019)
|
10.1371/journal.pcbi.1006884
| null |
q-bio.PE cond-mat.stat-mech
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Mutational robustness quantifies the effect of random mutations on fitness.
When mutational robustness is high, most mutations do not change fitness or
have only a minor effect on it. From the point of view of fitness landscapes,
robust genotypes form neutral networks of almost equal fitness. Using
deterministic population models it has been shown that selection favors
genotypes inside such networks, which results in increased mutational
robustness. Here we demonstrate that this effect is massively enhanced by
recombination. Our results are based on a detailed analysis of mesa-shaped
fitness landscapes, where we derive precise expressions for the dependence of
the robustness on the landscape parameters for recombining and non-recombining
populations. In addition, we carry out numerical simulations on different types
of random holey landscapes as well as on an empirical fitness landscape. We
show that the mutational robustness of a genotype generally correlates with its
recombination weight, a new measure that quantifies the likelihood for the
genotype to arise from recombination. We argue that the favorable effect of
recombination on mutational robustness is a highly universal feature that may
have played an important role in the emergence and maintenance of mechanisms of
genetic exchange.
|
[
{
"created": "Tue, 19 Feb 2019 21:57:41 GMT",
"version": "v1"
},
{
"created": "Mon, 21 Oct 2019 00:56:09 GMT",
"version": "v2"
}
] |
2019-10-22
|
[
[
"Klug",
"Alexander",
""
],
[
"Park",
"Su-Chan",
""
],
[
"Krug",
"Joachim",
""
]
] |
Mutational robustness quantifies the effect of random mutations on fitness. When mutational robustness is high, most mutations do not change fitness or have only a minor effect on it. From the point of view of fitness landscapes, robust genotypes form neutral networks of almost equal fitness. Using deterministic population models it has been shown that selection favors genotypes inside such networks, which results in increased mutational robustness. Here we demonstrate that this effect is massively enhanced by recombination. Our results are based on a detailed analysis of mesa-shaped fitness landscapes, where we derive precise expressions for the dependence of the robustness on the landscape parameters for recombining and non-recombining populations. In addition, we carry out numerical simulations on different types of random holey landscapes as well as on an empirical fitness landscape. We show that the mutational robustness of a genotype generally correlates with its recombination weight, a new measure that quantifies the likelihood for the genotype to arise from recombination. We argue that the favorable effect of recombination on mutational robustness is a highly universal feature that may have played an important role in the emergence and maintenance of mechanisms of genetic exchange.
|
1809.00449
|
Peter Gawthrop
|
Peter J. Gawthrop and Edmund J. Crampin
|
Bond Graph Representation of Chemical Reaction Networks
| null |
IEEE Transactions on NanoBioscience ( Volume: 17 , Issue: 4 , Oct.
2018 )
|
10.1109/TNB.2018.2876391
| null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The Bond Graph approach and the Chemical Reaction Network approach to
modelling biomolecular systems developed independently. This paper brings
together the two approaches by providing a bond graph interpretation of the
chemical reaction network concept of complexes. Both closed and open systems
are discussed.
The method is illustrated using a simple enzyme-catalysed reaction and a
trans-membrane transporter.
|
[
{
"created": "Mon, 3 Sep 2018 04:21:43 GMT",
"version": "v1"
},
{
"created": "Sun, 14 Oct 2018 00:28:29 GMT",
"version": "v2"
}
] |
2019-07-04
|
[
[
"Gawthrop",
"Peter J.",
""
],
[
"Crampin",
"Edmund J.",
""
]
] |
The Bond Graph approach and the Chemical Reaction Network approach to modelling biomolecular systems developed independently. This paper brings together the two approaches by providing a bond graph interpretation of the chemical reaction network concept of complexes. Both closed and open systems are discussed. The method is illustrated using a simple enzyme-catalysed reaction and a trans-membrane transporter.
|
1709.01072
|
Daniel Ruiz-Reyn\'es
|
Daniel Ruiz-Reyn\'es, Dami\`a Gomila, Tom\`as Sintes, Emilio
Hern\'andez-Garc\'ia, N\'uria Marb\`a, Carlos M. Duarte
|
Fairy circle landscapes under the sea
| null |
Science Advances, 2017, vol. 3, no 8, p. e1603262
|
10.1126/sciadv.1603262
| null |
q-bio.PE
|
http://creativecommons.org/licenses/by-nc-sa/4.0/
|
Short-scale interactions yield large-scale vegetation patterns that, in turn,
shape ecosystem function across landscapes. Fairy circles, which are circular
patches bare of vegetation within otherwise continuous landscapes, are
characteristic features of semiarid grasslands. We report the occurrence of
submarine fairy circle seascapes in seagrass meadows and propose a simple model
that reproduces the diversity of seascapes observed in these ecosystems as
emerging from plant interactions within the meadow. These seascapes include two
extreme cases, a continuous meadow and a bare landscape, along with
intermediate states that range from the occurrence of persistent but isolated
fairy circles, or solitons, to seascapes with multiple fairy circles, banded
vegetation, and "leopard skin" patterns consisting of bare seascapes patterns
consisting of bare seascapes dotted with plant patches. The model predicts that
these intermediate seascapes extending across kilometers emerge as a
consequence of local demographic imbalances along with facilitative and
competitive interactions among the plants with a characteristic spatial scale
of 20 to 30 m, consistent with known drivers of seagrass performance. The
model, which can be extended to clonal growth plants in other landscapes
showing fairy rings, reveals that the different seascapes observed hold
diagnostic power as to the proximity of seagrass meadows to extinction points
that can be used to identify ecosystems at risks.
|
[
{
"created": "Mon, 4 Sep 2017 11:55:36 GMT",
"version": "v1"
}
] |
2017-09-06
|
[
[
"Ruiz-Reynés",
"Daniel",
""
],
[
"Gomila",
"Damià",
""
],
[
"Sintes",
"Tomàs",
""
],
[
"Hernández-García",
"Emilio",
""
],
[
"Marbà",
"Núria",
""
],
[
"Duarte",
"Carlos M.",
""
]
] |
Short-scale interactions yield large-scale vegetation patterns that, in turn, shape ecosystem function across landscapes. Fairy circles, which are circular patches bare of vegetation within otherwise continuous landscapes, are characteristic features of semiarid grasslands. We report the occurrence of submarine fairy circle seascapes in seagrass meadows and propose a simple model that reproduces the diversity of seascapes observed in these ecosystems as emerging from plant interactions within the meadow. These seascapes include two extreme cases, a continuous meadow and a bare landscape, along with intermediate states that range from the occurrence of persistent but isolated fairy circles, or solitons, to seascapes with multiple fairy circles, banded vegetation, and "leopard skin" patterns consisting of bare seascapes patterns consisting of bare seascapes dotted with plant patches. The model predicts that these intermediate seascapes extending across kilometers emerge as a consequence of local demographic imbalances along with facilitative and competitive interactions among the plants with a characteristic spatial scale of 20 to 30 m, consistent with known drivers of seagrass performance. The model, which can be extended to clonal growth plants in other landscapes showing fairy rings, reveals that the different seascapes observed hold diagnostic power as to the proximity of seagrass meadows to extinction points that can be used to identify ecosystems at risks.
|
1602.08568
|
Pavol Bokes
|
Pavol Bokes and Abhyudai Singh
|
Gene expression noise is affected differentially by feedback in burst
frequency and burst size
|
27 pages, 11 figures
| null | null | null |
q-bio.MN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Inside individual cells, expression of genes is stochastic across organisms
ranging from bacterial to human cells. A ubiquitous feature of stochastic
expression is burst-like synthesis of gene products, which drives considerable
intercellular variability in protein levels across an isogenic cell population.
One common mechanism by which cells control such stochasticity is negative
feedback regulation, where a protein inhibits its own synthesis. For a single
gene that is expressed in bursts, negative feedback can affect the burst
frequency or the burst size. In order to compare these feedback types, we study
a piecewise deterministic model for gene expression of a self-regulating gene.
Mathematically tractable steady-state protein distributions are derived and
used to compare the noise suppression abilities of the two feedbacks. Results
show that in the low noise regime, both feedbacks are similar in term of their
noise buffering abilities. Intriguingly, feedback in burst size outperforms the
feedback in burst frequency in the high noise regime. Finally, we discuss
various regulatory strategies by which cells implement feedback to control
burst sizes of expressed proteins at the level of single cells.
|
[
{
"created": "Sat, 27 Feb 2016 08:16:11 GMT",
"version": "v1"
},
{
"created": "Sun, 11 Sep 2016 14:35:39 GMT",
"version": "v2"
}
] |
2016-09-13
|
[
[
"Bokes",
"Pavol",
""
],
[
"Singh",
"Abhyudai",
""
]
] |
Inside individual cells, expression of genes is stochastic across organisms ranging from bacterial to human cells. A ubiquitous feature of stochastic expression is burst-like synthesis of gene products, which drives considerable intercellular variability in protein levels across an isogenic cell population. One common mechanism by which cells control such stochasticity is negative feedback regulation, where a protein inhibits its own synthesis. For a single gene that is expressed in bursts, negative feedback can affect the burst frequency or the burst size. In order to compare these feedback types, we study a piecewise deterministic model for gene expression of a self-regulating gene. Mathematically tractable steady-state protein distributions are derived and used to compare the noise suppression abilities of the two feedbacks. Results show that in the low noise regime, both feedbacks are similar in term of their noise buffering abilities. Intriguingly, feedback in burst size outperforms the feedback in burst frequency in the high noise regime. Finally, we discuss various regulatory strategies by which cells implement feedback to control burst sizes of expressed proteins at the level of single cells.
|
1401.1798
|
Juli\'an Candia
|
Juli\'an Candia, Srujana Cherukuri, Yin Guo, Kshama A. Doshi, Jayanth
R. Banavar, Curt I. Civin, Wolfgang Losert
|
Uncovering low-dimensional, miR-based signatures of acute myeloid and
lymphoblastic leukemias with a machine-learning-driven network approach
|
34 pages, 12 figures (contains Supporting Information). To appear in
Convergent Science Physical Oncology
|
Converg. Sci. Phys. Oncol. 1 (2015) 025002
|
10.1088/2057-1739/1/2/025002
| null |
q-bio.QM
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
Complex phenotypic differences among different acute leukemias cannot be
fully captured by analyzing the expression levels of one single molecule, such
as a miR, at a time, but requires systematic analysis of large sets of miRs.
While a popular approach for analysis of such datasets is principal component
analysis (PCA), this method is not designed to optimally discriminate different
phenotypes. Moreover, PCA and other low-dimensional representation methods
yield linear or non-linear combinations of all measured miRs. Global human miR
expression was measured in AML, B-ALL, and T-ALL cell lines and patient RNA
samples. By systematically applying support vector machines to all measured
miRs taken in dyad and triad groups, we built miR networks using cell line data
and validated our findings with primary patient samples. All the coordinately
transcribed members of the miR-23a cluster (which includes also miR-24 and
miR-27a), known to function as tumor suppressors of acute leukemias, appeared
in the AML, B-ALL and T-ALL centric networks. Subsequent qRT-PCR analysis
showed that the most connected miR in the B-ALL-centric network, miR-708, is
highly and specifically expressed in B-ALLs, suggesting that miR-708 might
serve as a biomarker for B-ALL. This approach is systematic, quantitative,
scalable, and unbiased. Rather than a single signature, our approach yields a
network of signatures reflecting the redundant nature of biological signaling
pathways. The network representation allows for visual analysis of all
signatures by an expert and for future integration of additional information.
Furthermore, each signature involves only small sets of miRs, such as dyads and
triads, which are well suited for in depth validation through laboratory
experiments such as loss- and gain-of-function assays designed to drive changes
in leukemia cell survival, proliferation and differentiation.
|
[
{
"created": "Wed, 8 Jan 2014 20:07:43 GMT",
"version": "v1"
},
{
"created": "Fri, 22 Aug 2014 03:44:35 GMT",
"version": "v2"
},
{
"created": "Sat, 21 Nov 2015 00:21:27 GMT",
"version": "v3"
}
] |
2015-12-23
|
[
[
"Candia",
"Julián",
""
],
[
"Cherukuri",
"Srujana",
""
],
[
"Guo",
"Yin",
""
],
[
"Doshi",
"Kshama A.",
""
],
[
"Banavar",
"Jayanth R.",
""
],
[
"Civin",
"Curt I.",
""
],
[
"Losert",
"Wolfgang",
""
]
] |
Complex phenotypic differences among different acute leukemias cannot be fully captured by analyzing the expression levels of one single molecule, such as a miR, at a time, but requires systematic analysis of large sets of miRs. While a popular approach for analysis of such datasets is principal component analysis (PCA), this method is not designed to optimally discriminate different phenotypes. Moreover, PCA and other low-dimensional representation methods yield linear or non-linear combinations of all measured miRs. Global human miR expression was measured in AML, B-ALL, and T-ALL cell lines and patient RNA samples. By systematically applying support vector machines to all measured miRs taken in dyad and triad groups, we built miR networks using cell line data and validated our findings with primary patient samples. All the coordinately transcribed members of the miR-23a cluster (which includes also miR-24 and miR-27a), known to function as tumor suppressors of acute leukemias, appeared in the AML, B-ALL and T-ALL centric networks. Subsequent qRT-PCR analysis showed that the most connected miR in the B-ALL-centric network, miR-708, is highly and specifically expressed in B-ALLs, suggesting that miR-708 might serve as a biomarker for B-ALL. This approach is systematic, quantitative, scalable, and unbiased. Rather than a single signature, our approach yields a network of signatures reflecting the redundant nature of biological signaling pathways. The network representation allows for visual analysis of all signatures by an expert and for future integration of additional information. Furthermore, each signature involves only small sets of miRs, such as dyads and triads, which are well suited for in depth validation through laboratory experiments such as loss- and gain-of-function assays designed to drive changes in leukemia cell survival, proliferation and differentiation.
|
2005.07706
|
Carla Goldman
|
Alexandre Y. C. Cho, Victor R. C. M. Roque, Carla Goldman
|
The fast and the slow axonal transport: a unified approach based on
cargo and molecular motors coupled dynamics
| null |
Phys. Rev. E 102, 032410 (2020)
|
10.1103/PhysRevE.102.032410
| null |
q-bio.SC
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
The origins of the large differences observed to the rates with which the
diverse particles are conveyed along axonal microtubules are still a matter of
debate in the literature. There is evidence that certain neurodegenerative
diseases may be triggered by disturbances to the related transport processes.
Motivated by this, we employ a model to investigate the mobility properties of
certain cargoes which dynamics are coupled with that of molecular motors on
crowded microtubules. For certain initial and boundary conditions, we use the
method of characteristics to resolve perturbatively the pair of equations of
the Burgers type resulting from a mean-field approach to the original
microscopic stochastic model. Extensions to the non-perturbative limits are
explored numerically. In this context, we were able to figure out conditions
under which cargos average velocities may differ up to orders of magnitude just
by changing the number of motors on the considered track. We then discuss
possibilities to connect these theoretical predictions with available
experimental data about axon transport.
|
[
{
"created": "Fri, 15 May 2020 17:10:42 GMT",
"version": "v1"
}
] |
2020-09-30
|
[
[
"Cho",
"Alexandre Y. C.",
""
],
[
"Roque",
"Victor R. C. M.",
""
],
[
"Goldman",
"Carla",
""
]
] |
The origins of the large differences observed to the rates with which the diverse particles are conveyed along axonal microtubules are still a matter of debate in the literature. There is evidence that certain neurodegenerative diseases may be triggered by disturbances to the related transport processes. Motivated by this, we employ a model to investigate the mobility properties of certain cargoes which dynamics are coupled with that of molecular motors on crowded microtubules. For certain initial and boundary conditions, we use the method of characteristics to resolve perturbatively the pair of equations of the Burgers type resulting from a mean-field approach to the original microscopic stochastic model. Extensions to the non-perturbative limits are explored numerically. In this context, we were able to figure out conditions under which cargos average velocities may differ up to orders of magnitude just by changing the number of motors on the considered track. We then discuss possibilities to connect these theoretical predictions with available experimental data about axon transport.
|
1210.4938
|
Thierry Rabilloud
|
C\'ecile Lelong (LCBM), Mireille Chevallet (LCBM), H\'el\`ene Diemer
(IPHC-DSA), Sylvie Luche (LCBM), Alain Van Dorsselaer (IPHC-DSA), Thierry
Rabilloud (LCBM)
|
Improved proteomic analysis of nuclear proteins, as exemplified by the
comparison of two myelo\"id cell lines nuclear proteomes
| null |
Journal of Proteomics (2012) epub ahead of print
|
10.1016/j.jprot.2012.09.034
| null |
q-bio.GN
|
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
|
One of the challenges of the proteomic analysis by 2D-gel is to visualize the
low abundance proteins, particularly those localized in organelles. An
additional problem with nuclear proteins lies in their strong interaction with
nuclear acids. Several experimental procedures have been tested to increase, in
the nuclear extract, the ratio of nuclear proteins compared to contaminant
proteins, and also to obtain reproducible conditions compatible with 2D-gel
electrophoresis. The NaCl procedure has been chosen. To test the interest of
this procedure, the nuclear protein expression profiles of macrophages and
dendritic cells have been compared with a proteomic approach by 2D-gel
electrophoresis. Delta 2D software and mass spectrometry analyses have allowed
pointing out some proteins of interest. We have chosen some of them, involved
in transcriptional regulation and/or chromatin structure for further
validations. The immunoblotting experiments have shown that most of observed
changes are due to post-translational modifications, thereby a exemplifying the
interest of the 2D gel approach. Finally, this approach allowed us to reach not
only high abundance nuclear proteins but also lower abundance proteins, such as
the HP1 proteins and reinforces the interest of using 2DE-gel in proteomics
because of its ability to visualize intact proteins with their modifications.
|
[
{
"created": "Wed, 17 Oct 2012 20:02:51 GMT",
"version": "v1"
}
] |
2012-10-19
|
[
[
"Lelong",
"Cécile",
"",
"LCBM"
],
[
"Chevallet",
"Mireille",
"",
"LCBM"
],
[
"Diemer",
"Hélène",
"",
"IPHC-DSA"
],
[
"Luche",
"Sylvie",
"",
"LCBM"
],
[
"Van Dorsselaer",
"Alain",
"",
"IPHC-DSA"
],
[
"Rabilloud",
"Thierry",
"",
"LCBM"
]
] |
One of the challenges of the proteomic analysis by 2D-gel is to visualize the low abundance proteins, particularly those localized in organelles. An additional problem with nuclear proteins lies in their strong interaction with nuclear acids. Several experimental procedures have been tested to increase, in the nuclear extract, the ratio of nuclear proteins compared to contaminant proteins, and also to obtain reproducible conditions compatible with 2D-gel electrophoresis. The NaCl procedure has been chosen. To test the interest of this procedure, the nuclear protein expression profiles of macrophages and dendritic cells have been compared with a proteomic approach by 2D-gel electrophoresis. Delta 2D software and mass spectrometry analyses have allowed pointing out some proteins of interest. We have chosen some of them, involved in transcriptional regulation and/or chromatin structure for further validations. The immunoblotting experiments have shown that most of observed changes are due to post-translational modifications, thereby a exemplifying the interest of the 2D gel approach. Finally, this approach allowed us to reach not only high abundance nuclear proteins but also lower abundance proteins, such as the HP1 proteins and reinforces the interest of using 2DE-gel in proteomics because of its ability to visualize intact proteins with their modifications.
|
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