English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Invasion and effective size of graph-structured populations

MPS-Authors
/persons/resource/persons199253

Giaimo,  Stefano
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons191815

Arranz,  Jordi
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons56973

Traulsen,  Arne
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

journal.pcbi.1006559.pdf
(Publisher version), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Giaimo, S., Arranz, J., & Traulsen, A. (2018). Invasion and effective size of graph-structured populations. PLoS Computational Biology, 14(11): e1006559. doi:10.1371/journal.pcbi.1006559.


Cite as: https://hdl.handle.net/21.11116/0000-0002-9870-4
Abstract
Author summary Evolving populations, companies, social circles are networks in which genes, resources and ideas circulate. Imagine a useful novelty is introduced in the network: a favorable mutation, a new product concept or a smart idea. Will this novelty be retained and propagated through the network or rather lost? Using tools originally devised for demographic research, we model the dynamics of the very initial spread of a useful novelty in a network. The network structure has a strong impact on these dynamics by affecting the effective network size through random effects. This effective network size, which correlates with the probability that a novelty spreads and is different from the actual size (i.e. number of nodes), varies with network structure. The effective size can even become independent of the actual network size and thus remain very small even for huge networks.