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Mutant fate in spatially structured populations on graphs: Connecting models to experiments.

PLoS computational biology - 1 Sept 2024

Abbara Alia, Pagani Lisa, García-Pareja Celia, Bitbol Anne-Florence

Abstract excerpt

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 probability that a mutant will fix. Evolution experiments are beginning to explicitly address the impact of graph structures on mutant fixation. However, the assumptions of...

Topics

Mutation
Computational Biology
Biological Evolution
Models, Genetic
Selection, Genetic
Computer Simulation
Genetics, Population

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Identifiers

PMID: 39241045
DOI: 10.1371/journal.pcbi.1012424
PMCID: PMC11410244

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

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