Description

The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyze and interpret them, generating both computational and conceptual challenges for the field.

Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. The book emphasizes essential concepts rather than mathematical proofs. It includes detailed derivations and implementation details, as well as numerous illustrations, worked examples, and exercises. It will be of relevance and use to students and professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, population genetics, mathematics, statistics and computer science. Biologists who have used phylogenetic software programs to analyze their own data will find the book particularly rewarding, although it should appeal to anyone seeking an authoritative overview of this exciting area of computational biology.

Features

• Authored by a world-renowned specialist in the field
• Adopts a statistical approach to phylogenetics
• Web-based example data sets used to clarify the theory
• Emphasises the models and methods designed for understanding the evolutionary process of genes and genomes
• Ideal graduate seminar course material

Reviews

"What sets this book apart is the authority and thoughtfulness with which it is written, the thorough coverage of the relevant literature, and the great care that has been taken in the computational examples to compare different methods on the same set of data, and to present the results clearly. It will be a major source for insight and enormously helpful for anyone who wants to understand molecular phylogenies." -- The Quarterly Review of Biology, Vol. 83

Product Details

376 pages; 96 illus.; ISBN13: 978-0-19-856702-8ISBN10: 0-19-856702-2

About the Author(s)