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Phylogenies (evolutionary trees) are basic to thinking about and analyzing differences between species. Statistical, computational, and algorithmic work on them has been ongoing for four decades, with great advances in understanding. Yet no book has summarized this work until now. Inferring Phylogenies explains clearly the assumptions and logic of making inferences about phylogenies, and using them to make inferences about evolutionary processes. It is an essential text and reference for anyone who wants to understand how phylogenies are reconstructed and how they are used.As phylogenies are inferred with various kinds of data, this book concentrates on some of the central ones: discretely coded characters, molecular sequences, gene frequencies, and quantitative traits. Also covered are restriction sites, RAPDs, and microsatellites.Inferring Phylogenies is intended for graduate-level courses, assuming some knowledge of statistics, mathematics (calculus and fundamental matrix algebra), molecular sequences, and quantitative genetics.
Author Biography
Joe Felsenstein is Professor in the Department of Genome Sciences at the University of Washington, Seattle, where he has taught for more than thirty years. He earned a B.S. (Honors) in Zoology from the University of Wisconsin, Madison, and a Ph.D. in Zoology from the University of Chicago. Dr. Felsenstein is the author of the widely used PHYLIP package of programs for inferring phylogenies. He served as President of the Society for the Study of Evolution in 1993 and has received numerous awards, including: election to membership in the American Academy of Arts and Sciences (1992); the Sewall Wright Award, American Society of Naturalists (1993; election to membership in the National Academy of Sciences (1999); and the Weldon Memorial Prize, Oxford University (2000). His work has ranged from theoretical evolutionary genetics to statistical methods for inferring phylogenies. His current research interests include the development of coalescent-based Markov Chain Monte Carlo methods of computing likelihoods for models of evolution within species, and development of statistical methods for inferences about quantitative characters within and between species.
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