Some Mathematical Models from Population Genetics

École d'Été de Probabilités de Saint-Flour XXXIX-2009

  • Alison Etheridge

Part of the Lecture Notes in Mathematics book series (LNM, volume 2012)

Also part of the Ecole d'Eté Probabilit.Saint-Flour book sub series (LNMECOLE, volume 2012)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Alison Etheridge
    Pages 1-3
  3. Alison Etheridge
    Pages 5-32
  4. Alison Etheridge
    Pages 33-51
  5. Alison Etheridge
    Pages 53-64
  6. Alison Etheridge
    Pages 65-87
  7. Alison Etheridge
    Pages 89-107
  8. Back Matter
    Pages 109-119

About this book


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.


60-02;92D10;92D15;60J70;60J75 Coalescent models Population genetics stochastic models

Authors and affiliations

  • Alison Etheridge
    • 1
  1. 1., Department of StatisticsUniversity of OxfordOxfordUnited Kingdom

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-642-16631-0
  • Online ISBN 978-3-642-16632-7
  • Series Print ISSN 0075-8434
  • Series Online ISSN 1617-9692
  • Buy this book on publisher's site