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130626 ||| eng |
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|a 9783642166327
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|a Etheridge, Alison
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|a Some Mathematical Models from Population Genetics
|h Elektronische Ressource
|b École d'Été de Probabilités de Saint-Flour XXXIX-2009
|c by Alison Etheridge
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|a 1st ed. 2011
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2011, 2011
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| 300 |
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|a VIII, 119 p. 15 illus
|b online resource
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|a Mathematical and Computational Biology
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|a Biostatistics
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|a Population genetics
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|a Biomathematics
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|a Population Genetics
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|a Mathematical Modeling and Industrial Mathematics
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|a Differential Equations
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|a Biometry
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|a Differential equations
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|a Mathematical models
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|a eng
|2 ISO 639-2
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|b Springer
|a Springer eBooks 2005-
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|a École d'Été de Probabilités de Saint-Flour
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|a 10.1007/978-3-642-16632-7
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|u https://doi.org/10.1007/978-3-642-16632-7?nosfx=y
|x Verlag
|3 Volltext
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|a 576.58
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|a This work reflects sixteen hours of lectures delivered by the author at the 2009 St Flour summer school in probability. It provides a rapid introduction to a range of mathematical models that have their origins in theoretical population genetics. The models fall into two classes: forwards in time models for the evolution of frequencies of different genetic types in a population; and backwards in time (coalescent) models that trace out the genealogical relationships between individuals in a sample from the population. Some, like the classical Wright-Fisher model, date right back to the origins of the subject. Others, like the multiple merger coalescents or the spatial Lambda-Fleming-Viot process are much more recent. All share a rich mathematical structure. Biological terms are explained, the models are carefully motivated and tools for their study are presented systematically
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