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A biologically motivated individual-based framework for evolution in network-structured populations is developed that can accommodate eco-evolutionary dynamics. This framework is used to construct a network birth and death model. The…

种群与进化 · 定量生物学 2021-03-19 Karan Pattni , Christopher E. Overton , Kieran J. Sharkey

Evolutionary graph theory (EGT) studies the effect of population structure on evolutionary dynamics. The vertices of the graph represent the $N$ individuals. The edges denote interactions for competitive replacement. Two standard update…

种群与进化 · 定量生物学 2026-04-01 David A. Brewster , Yichen Huang , Michael Mitzenmacher , Martin A. Nowak

Natural microbial populations often have complex spatial structures. This can impact their evolution, in particular the ability of mutants to take over. While mutant fixation probabilities are known to be unaffected by sufficiently…

种群与进化 · 定量生物学 2024-12-30 Alia Abbara , Anne-Florence Bitbol

We analyze evolutionary dynamics on graphs, where the nodes represent individuals of a population. The links of a node describe which other individuals can be displaced by the offspring of the individual on that node. Amplifiers of…

种群与进化 · 定量生物学 2016-10-27 Laura Hindersin , Arne Traulsen

In evolutionary processes, population structure has a substantial effect on natural selection. Here, we analyze how motion of individuals affects constant selection in structured populations. Motion is relevant because it leads to changes…

种群与进化 · 定量生物学 2017-10-10 Madison S. Krieger , Alex McAvoy , Martin A. Nowak

The spatial structure of an evolving population affects which mutations become fixed. Some structures amplify selection, increasing the likelihood that beneficial mutations become fixed while deleterious mutations do not. Other structures…

Evolutionary games on graphs describe how strategic interactions and population structure determine evolutionary success, quantified by the probability that a single mutant takes over a population. Graph structures, compared to the…

种群与进化 · 定量生物学 2017-05-08 Philipp M. Altrock , Arne Traulsen , Martin A. Nowak

Hypergraphs have been a useful tool for analyzing population dynamics such as opinion formation and the public goods game occurring in overlapping groups of individuals. In the present study, we propose and analyze evolutionary dynamics on…

物理与社会 · 物理学 2023-10-16 Ruodan Liu , Naoki Masuda

Evolution occurs in populations of reproducing individuals. It is well known that population structure can affect evolutionary dynamics. Traditionally, natural selection is studied between mutants that differ in reproductive rate, but are…

种群与进化 · 定量生物学 2021-11-23 Josef Tkadlec , Kamran Kaveh , Krishnendu Chatterjee , Martin A. Nowak

In nature, most microbial populations have complex spatial structures that can affect their evolution. Evolutionary graph theory predicts that some spatial structures modelled by placing individuals on the nodes of a graph affect the…

种群与进化 · 定量生物学 2024-12-30 Alia Abbara , Lisa Pagani , Celia García-Pareja , Anne-Florence Bitbol

A key question in evolution is how likely a mutant is to take over. This depends on natural selection and on stochastic fluctuations. Population spatial structure can impact mutant fixation probabilities. We introduce a model for structured…

种群与进化 · 定量生物学 2021-11-23 Loïc Marrec , Irene Lamberti , Anne-Florence Bitbol

A central question of evolutionary dynamics on graphs is whether or not a mutation introduced in a population of residents survives and eventually even spreads to the whole population, or gets extinct. The outcome naturally depends on the…

种群与进化 · 定量生物学 2020-08-05 Hendrik Richter

The population structure often impacts evolutionary dynamics. In constant-selection evolutionary dynamics between two types, amplifiers of selection are networks that promote the fitter mutant to take over the entire population, and…

物理与社会 · 物理学 2024-09-04 Jnanajyoti Bhaumik , Naoki Masuda

We consider a generalized version of the birth-death (BD) and death-birth (DB) processes introduced by Kaveh, Komarova, and Kohandel (2015), in which two constant fitnesses, one for birth and the other for death, describe the selection…

概率论 · 数学 2025-12-08 Poly H. da Silva , Max O. Souza

Population structure has been known to substantially affect evolutionary dynamics. Networks that promote the spreading of fitter mutants are called amplifiers of natural selection, and those that suppress the spreading of fitter mutants are…

物理与社会 · 物理学 2023-10-26 Jnanajyoti Bhaumik , Naoki Masuda

Evolutionary graph theory studies the evolutionary dynamics of populations structured on graphs. A central problem is determining the probability that a small number of mutants overtake a population. Currently, Monte Carlo simulations are…

计算机科学与博弈论 · 计算机科学 2013-01-14 Paulo Shakarian , Patrick Roos , Geoffrey Moores

Evolutionary models on graphs, as an extension of the Moran process, have two major implementations: birth-death (BD) models (or the invasion process) and death- birth (DB) models (or voter models). The isothermal theorem states that the…

定量方法 · 定量生物学 2015-05-19 Kamran Kaveh , Natalia Komarova , Mohammad Kohandel

We examine population structures for their ability to maintain diversity in neutral evolution. We use the general framework of evolutionary graph theory and consider birth-death (bd) and death-birth (db) updating. The population is of size…

种群与进化 · 定量生物学 2025-09-18 David A. Brewster , Jakub Svoboda , Dylan Roscow , Krishnendu Chatterjee , Josef Tkadlec , Martin A. Nowak

The paper deals with two interrelated topics, identifying transient amplifiers in an iterative process and analyzing the process by its spectral dynamics, which is the change in the graph spectra by edge manipulations. Transient amplifiers…

种群与进化 · 定量生物学 2022-04-28 Hendrik Richter

Evolution in finite populations is often modelled using the classical Moran process. Over the last ten years this methodology has been extended to structured populations using evolutionary graph theory. An important question in any such…

种群与进化 · 定量生物学 2015-05-25 Karan Pattni , Mark Broom , Jan Rychtar , Lara J. Silvers
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