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Probability Models for DNA Sequence Evolution (Probability and Its Applications)

Probability Models for DNA Sequence Evolution (Probability and Its Applications)

Probability Models for DNA Sequence Evolution (Probability and Its Applications)
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Probability Models for DNA Sequence Evolution (Probability and Its Applications) Hardback -

by Richard Durrett Rick Durrett

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Springer , pp. viii + 240 1st Edition . Hardback. New.
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Details

  • Title Probability Models for DNA Sequence Evolution (Probability and Its Applications)
  • Author Richard Durrett Rick Durrett
  • Binding Hardback
  • Edition 1st
  • Condition New
  • Pages 240
  • Volumes 1
  • Language ENG
  • Publisher Springer , New York
  • Publication date pp. viii + 240 1st Edition
  • Illustrated Yes
  • Bookseller's Inventory # 6285647
  • ISBN 9780387954356 / 038795435X
  • Weight 1.06 lbs (0.48 kg)
  • Dimensions 9.14 x 6.82 x 0.64 in (23.22 x 17.32 x 1.63 cm)
  • Category Science
  • Library of Congress subjects Evolutionary genetics - Statistical methods, Nucleotide sequence - Statistical methods
  • Library of Congress Catalogue Number 2002016001
  • Dewey Decimal Code 572.838
  • Quantity available 1

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Reader reviews for Probability Models for DNA Sequence Evolution (Probability and Its Applications)

From the publisher

As a starting point to this volume, the authors address the fundamental question What underlying forces are responsible for the observed patterns of variability, given a collection of DNA sequences? In approaching this question they introduce and analyze a number of probability models: the Wright-Fisher model, the coalescent, the infinite alleles model and the infinite sites model. They then discuss the complications that come from nonconstant population size, recombination, population subdivision and three forms of natural selection: directional selection, balancing selection and background selection. These theoretical results set the stage for the investigation of various statistical tests to detect departures from neutral evolution.

First line

Before we can discuss modeling the evolution of DNA sequences, the reader needs a basic knowledge of the object being modeled.
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