Directionality of contact networks suppresses selection pressure in evolutionary dynamics

DOI10.1016/j.jtbi.2009.01.025zbMath1402.92317arXiv0812.1076OpenAlexW2079681761WikidataQ51659380 ScholiaQ51659380MaRDI QIDQ1620826

Naoki Masuda

Publication date: 14 November 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0812.1076

zbMATH Keywords

population dynamicsfixation probabilitydirected networks

Mathematics Subject Classification ID

Problems related to evolution (92D15) Applications of graph theory (05C90) Population dynamics (general) (92D25)

Related Items (15)

Modelling evolution in structured populations involving multiplayer interactions ⋮ Two-strategy games with time constraints on regular graphs ⋮ Evolving multiplayer networks: modelling the evolution of cooperation in a mobile population ⋮ Quasi-neutral evolution in populations under small demographic fluctuations ⋮ Fixation probability in evolutionary dynamics on switching temporal networks ⋮ A study of the dynamics of multi-player games on small networks using territorial interactions ⋮ Evolutionary dynamics and the evolution of multiplayer cooperation in a subdivided population ⋮ Methods for approximating stochastic evolutionary dynamics on graphs ⋮ The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population ⋮ Evolutionary games on star graphs under various updating rules ⋮ Evolutionary bet-hedging in structured populations ⋮ Moran process and Wright-Fisher process favor low variability ⋮ Cooperative success in epithelial public goods games ⋮ Fixation probabilities for simple digraphs ⋮ The evolution of cooperation in two-dimensional mobile populations with random and strategic dispersal

Cites Work

• Mathematical population genetics. I: Theoretical introduction.
• Inclusive fitness arguments in genetic models of behaviour
• The replicator equation on graphs
• Statistical mechanics of complex networks
• Finite particle systems and infection models
• The Structure and Function of Complex Networks
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