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Contact inhibition refers to a reduction in the rate of cell migration and/or cell proliferation in regions of high cell density. Under normal conditions contact inhibition is associated with the proper functioning tissues, whereas abnormal…

Cell Behavior · Quantitative Biology 2018-03-01 David J. Warne , Ruth E. Baker , Matthew J. Simpson

We discuss a population of sequences subject to mutations and frequency-dependent selection, where the fitness of a sequence depends on the composition of the entire population. This type of dynamics is crucial to understand the evolution…

Disordered Systems and Neural Networks · Physics 2009-11-07 M. Laessig , L. Peliti , F. Tria

We introduce a simple theoretical approach for an equilibrium study of proteins with known native state structures. We test our approach with results on well-studied globular proteins, Chymotrypsin Inhibitor (2ci2), Barnase and the alpha…

Statistical Mechanics · Physics 2009-11-07 Cristian Micheletti , Jayanth Banavar , Amos Maritan

Evolutionary models for populations of constant size are frequently studied using the Moran model, the Wright-Fisher model, or their diffusion limits. When evolution is neutral, a random genealogy given through Kingman's coalescent is used…

Populations and Evolution · Quantitative Biology 2012-07-31 Peter Pfaffelhuber , Benedikt Vogt

The self-alignment concentrations, $c(x)$, as functions of the length, $x$, of the identically matching maximal segments in the genomes of a variety of species, typically present power-law tails extending to the largest scales, i.e., $c(x)…

Populations and Evolution · Quantitative Biology 2014-12-23 Kun Gao , HongGuang Sun , Jian-Zhou Zhu

Epidemic spreading often occurs in spatially heterogeneous environments, yet how quenched heterogeneity reshapes its onset and critical dynamics remains poorly understood. The diffusive epidemic process, a minimal reaction-diffusion model…

Statistical Mechanics · Physics 2026-03-24 Valentin Anfray , Hong-Yan Shih

Solving the recombination equation has been a long-standing challenge of \emph{deterministic} population genetics. We review recent progress obtained by introducing ancestral processes, as traditionally used in the context of…

Probability · Mathematics 2021-06-30 Ellen Baake , Michael Baake

Population genetics struggles to model extinction; standard models track the relative rather than absolute fitness of genotypes, while the exceptions describe only the short-term transition from imminent doom to evolutionary rescue. But…

Populations and Evolution · Quantitative Biology 2017-02-20 Jason Bertram , Kevin Gomez , Joanna Masel

We present a novel mathematical model of heterogeneous cell proliferation where the total population consists of a subpopulation of slow-proliferating cells and a subpopulation of fast-proliferating cells. The model incorporates two…

Cell Behavior · Quantitative Biology 2021-11-04 Sean T. Vittadello , Scott W. McCue , Gency Gunasingh , Nikolas K. Haass , Matthew J. Simpson

We introduce a model of DNA sequence evolution which can account for biases in mutation rates that depend on the identity of the neighboring bases. An analytic solution for this class of non-equilibrium models is developed by adopting…

Biological Physics · Physics 2007-05-23 Peter F. Arndt , Christopher B. Burge , Terence Hwa

Genetic feedback loops in cells break detailed balance and involve bimolecular reactions; hence exact solutions revealing the nature of the stochastic fluctuations in these loops are lacking. We here consider the master equation for a gene…

Subcellular Processes · Quantitative Biology 2015-06-05 R. Grima , D. R. Schmidt , T. J. Newman

To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetic inference is based on frameworks assuming adaptive evolution is rare. But if…

Populations and Evolution · Quantitative Biology 2014-03-25 Richard A. Neher

Many applications of machine learning methods involve an iterative protocol in which data are collected, a model is trained, and then outputs of that model are used to choose what data to consider next. For example, one data-driven approach…

Machine Learning · Computer Science 2025-04-07 Clara Fannjiang , Stephen Bates , Anastasios N. Angelopoulos , Jennifer Listgarten , Michael I. Jordan

We study the role of recombination, as practiced by genetically-competent bacteria, in speeding up Darwinian evolution. This is done by adding a new process to a previously-studied Markov model of evolution on a smooth fitness landscape;…

Populations and Evolution · Quantitative Biology 2009-11-10 Elisheva Cohen , David A. Kessler , Herbert Levine

A popular current research trend deals with expanding the Monte-Carlo tree search sampling methodologies to the environments with uncertainty and incomplete information. Recently a finite population version of Geiringer theorem with…

Artificial Intelligence · Computer Science 2013-05-14 Boris Mitavskiy , Jun He

We study the dynamics of a population subject to selective pressures, evolving either on RNA neutral networks or in toy fitness landscapes. We discuss the spread and the neutrality of the population in the steady state. Different limits…

Populations and Evolution · Quantitative Biology 2009-11-13 Sumedha , Olivier C Martin , Luca Peliti

Recent advances in deep learning optimization showed that, with some a-posteriori information on fully-trained models, it is possible to match the same performance by simply training a subset of their parameters. Such a discovery has a…

Machine Learning · Computer Science 2022-11-15 Andrea Bragagnolo , Enzo Tartaglione , Marco Grangetto

In this work, we discuss a cell-cell repulsion population dynamic model based on a hyperbolic Keller-Segel equation with two populations. This model can well describe the cell growth and dispersion in the cell co-culture experiment in the…

Analysis of PDEs · Mathematics 2019-07-26 Xiaoming Fu , Quentin Griette , Pierre Magal

Sequence-to-Sequence models were introduced to tackle many real-life problems like machine translation, summarization, image captioning, etc. The standard optimization algorithms are mainly based on example-to-example matching like maximum…

Computation and Language · Computer Science 2018-09-05 Wenhu Chen , Guanlin Li , Shujie Liu , Zhirui Zhang , Mu Li , Ming Zhou

We investigate a class of stochastic growth models involving competition between two phases in which one of the phases has a competitive advantage. The equilibrium populations of the competing phases are calculated using a mean field…

Soft Condensed Matter · Physics 2015-06-25 M. T. Batchelor , B. I. Henry , S. D. Watt