Probability models for DNA sequence evolution / Rick Durrett

Auteur principal : Durrett, Rick, 1951-, AuteurType de document : MonographieCollection : Probability and its applicationsLangue : anglais.Pays: Etats Unis.Éditeur : New York : Springer, 2002Description : 1 vol. (VIII-240 p.) : ill. ; 24 cmISBN: 9780387954356.ISSN: 1431-7028.Bibliographie : Bibliogr. p. [223]-237. Index.Sujet MSC : 92-02, Research exposition (monographs, survey articles) pertaining to biology
92D15, Biology and other natural sciences, Genetics and population dynamics, Problems related to evolution
62P10, Applications of statistics to biology and medical sciences; meta analysis
92D10, Biology and other natural sciences, Genetics and population dynamics, Genetics and epigenetics
60G35, Probability theory and stochastic processes, Signal detection and filtering (aspects of stochastic processes)
En-ligne : Springerlink : ed. 2008 Item type: Monographie
Tags from this library: No tags from this library for this title. Log in to add tags.
Holdings
Current library Call number Status Date due Barcode
CMI
Salle R
92 DUR (Browse shelf(Opens below)) Available 01476-01

The author introduces and analyzes a number of probability models: the Wright-Fisher model, the coalescent, the infinite alleles model, and the infinite sites model. He studies the complications coming from nonconstant population size, recombination, population subdivision, and three forms of natural selection: directional selection, balancing selection, and background selection. Various statistical tests are used to detect departures from `neutral evolution'. The final chapter is devoted to the study of the evolution of whole genomes by chromosomal inversions, reciprocal translocations, and genome duplication. The theory is developed in close connection with experimental data from biology literature that illustrate the use of the results. This book is intended for mathematicians and for biologists alike. No previous knowledge of biological concepts is required but some familiarity with Markov chains and Poisson processes will be very useful. (Zentralblatt)

Bibliogr. p. [223]-237. Index

There are no comments on this title.

to post a comment.