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Using pair approximations to predict takeover dynamics in spatially structured populations
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Genetic And Evolutionary Computation Conference archive
Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation table of contents
London, United Kingdom
SESSION: Late-breaking papers table of contents
Pages 2557-2564  
Year of Publication: 2007
ISBN:978-1-59593-698-1
Authors
Joshua L. Payne  University of Vermont, Burlington, VT
Margaret J. Eppstein  University of Vermont, Burlington, VT
Sponsors
ACM: Association for Computing Machinery
SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
Publisher
ACM  New York, NY, USA
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ABSTRACT

The topological properties of a network directly impact the flow of information through a system. For example, in natural populations, the network of inter-individual contacts affects the rate of flow of infectious disease. Similarly, in evolutionary systems, the topological properties of the underlying population structure affect the rate of flow of genetic information, and thus affect selective pressure. One commonly employed method for quantifying the influence of the population structure on selective pressure is through the analysis of takeover time. In this study, we reformulate takeover time analysis in terms of the well-known Susceptible-Infectious-Susceptible (SIS) model of disease spread. We then adapt an analytical technique, called the pair approximation, to provide a general model of takeover dynamics. We compare the results of this model to simulation data on a total of six regular population structures and discuss the strengths and limitations of the approximation.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Joshua L. Payne: colleagues
Margaret J. Eppstein: colleagues