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  Most undirected random graphs are amplifiers of selection for birth-death dynamics, but suppressors of selection for death-birth dynamics

Hindersin, L., & Traulsen, A. (2015). Most undirected random graphs are amplifiers of selection for birth-death dynamics, but suppressors of selection for death-birth dynamics. PLoS Computational Biology, 11(11): e1004437. doi:10.1371/journal.pcbi.1004437.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0026-D121-F Version Permalink: http://hdl.handle.net/21.11116/0000-0004-CC4A-4
Genre: Journal Article

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Hindersin, Laura1, Author              
Traulsen, Arne1, Author              
Affiliations:
1Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445641              

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 Abstract: 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 off- spring of the individual on that node. Amplifiers of selection are graphs for which the fixation probability is increased for advantageous mutants and decreased for disadvantageous mutants. A few examples of such amplifiers have been developed, but so far it is unclear how many such structures exist and how to construct them. Here, we show that almost any undirected random graph is an amplifier of selection for Birth-death updating, where an indi- vidual is selected to reproduce with probability proportional to its fitness and one of its neigh- bors is replaced by that offspring at random. If we instead focus on death-Birth updating, in which a random individual is removed and its neighbors compete for the empty spot, then the same ensemble of graphs consists of almost only suppressors of selection for which the fixation probability is decreased for advantageous mutants and increased for disadvanta- geous mutants. Thus, the impact of population structure on evolutionary dynamics is a sub- tle issue that will depend on seemingly minor details of the underlying evolutionary process.

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Language(s): eng - English
 Dates: 2015-04-142015-06-292015-11-06
 Publication Status: Published online
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 Identifiers: DOI: 10.1371/journal.pcbi.1004437
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 11 (11) Sequence Number: e1004437 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: /journals/resource/1000000000017180_1