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dc.contributor.authorDick, Granten_NZ
dc.contributor.authorWhigham, Peter Aen_NZ
dc.date.available2011-04-07T03:01:55Z
dc.date.copyright2005-11en_NZ
dc.identifier.citationDick, G., & Whigham, P. A. (2005). Discovering population structures with extreme fixation rates via evolutionary search (pp. 175–179). Presented at the 17th Annual Colloquium of the Spatial Information Research Centre (SIRC 2005: A Spatio-temporal Workshop).en
dc.identifier.urihttp://hdl.handle.net/10523/702
dc.description.abstractGenetic drift is a well known and important force in directing the evolution of a population. The nature of genetic drift in panmictic populations is well understood, and new research is shedding light on the behaviour of genetic drift. This paper explores the concept of using evolutionary algorithms to search for population structures that exhibit the minimum and maximum conditions for loss of variation via genetic drift. Two spatial structures repeatedly emerge as candidates: a star topology that reduces fixation time to a logarithm of population size, and a “line with islands” topology that can delay fixation via genetic drift to a greater extent than any previously known population structure.en_NZ
dc.format.mimetypeapplication/pdf
dc.relation.urihttp://www.business.otago.ac.nz/SIRC05/conferences/2005/25_dick.pdfen_NZ
dc.subjectgenetic driften_NZ
dc.subjectspatially-structured populationsen_NZ
dc.subjecthyperfixationen_NZ
dc.subjectevolutionary algorithms, multimodal optimisationen_NZ
dc.subjectniching methodsen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleDiscovering population structures with extreme fixation rates via evolutionary searchen_NZ
dc.typeConference or Workshop Item (Paper)en_NZ
dc.description.versionPublisheden_NZ
otago.date.accession2006-08-21en_NZ
otago.relation.pages175-179en_NZ
otago.openaccessOpen
dc.identifier.eprints363en_NZ
dc.description.refereedNon Peer Revieweden_NZ
otago.school.eprintsSpatial Information Research Centreen_NZ
otago.school.eprintsInformation Scienceen_NZ
dc.description.referencesCrow, J. F. & Kimura, M. (1970). Introduction to Population Genetics Theory. Harper and Row. New York, Evanston and London. Darwin, C. (1859). On The Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. John Murray. London. DeJong, K. A. (1975). An Analysis of the Behavior of a Class of Genetic Adaptive Systems. PhD thesis University of Michigan Ann Arbor, MI. Dissertation Abstracts International 36(10), 5140B, University Microfilms Number 76-9381. Dick, G. & Whigham, P. (2005). “The Behaviour of Genetic Drift in a Spatially-Structured Evolutionary Algorithm” 2005 IEEE Congress on Evolutionary Computation. IEEE Press. pp. 1855–1860. Goldberg, D. E. (1989). Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley. Holland, J. H. (1992). Adaptation in Natural and Artifical Systems. MIT Press. Cambridge, MA. Kimura, M. (1983). The Neutral Theory of Molecular Evolution. Cambridge University Press. Mahfoud, S. W. (1992). “Crowding and preselection revisited” In R. M¨anner & B. Manderick (eds), Parallel problem solving from nature 2. North-Holland Amsterdam pp. 27–36. Whigham, P. A. & Dick, G. (2005). “Fixation of neutral alleles in spatially-structured populations via genetic drift: Describing the spatial structure of faster-than-panmictic configurations” The 17th Annual Colloquium of the Spatial Information Research Centre. Dunedin, New Zealand pp. 81–90.en_NZ
otago.event.dates24-25 November 2005en_NZ
otago.event.placeDunedin, New Zealanden_NZ
otago.event.typeconferenceen_NZ
otago.event.title17th Annual Colloquium of the Spatial Information Research Centre (SIRC 2005: A Spatio-temporal Workshop)en_NZ
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