Molecular Evolution:
A Statistical Approach

Ziheng Yang, 2014, Oxford University Press

512 pages | 246x189mm

978-0-19-960261-2 | Paperback | 15 May 2014
978-0-19-960260-5 | Hardback | 15 May 2014

The book can be ordered at

Reviews of the book

The book gives a lot of mathematical insight while retaining readability. ... Yang has a talent for making general statistical concepts come to life in a very readable way.
Yang has produced a book that could be read and enjoyed by different audiences for different purposes. I think that the book will be welcomed by biologists who want some mathematical intuition for what's underneath the hood of the methods they rely on. Yang has made a serious effort to keep the book understandable to non-mathematicians, and as a result the book does not feel overly mathematical or dense with notation despite the fact that it covers a lot of mathematical terrain.
I think Molecular Evolution: A Statistical Approach would also work very well as a text for a graduate level course in statistical phylogenetics. It is hard to think of a topic better than phylogenetics to provide a broad tour of mathematics and statistics...

Barbara R. Holland, in Systematic Biology, 64:545-546 (2015)
This book is beautiful in its precision and mathematical clarity. Although the mathematical treatment of statistical approaches to molecular evolution is extensive, most of the equations are described in words that will help readers understand and interpret the math... Although this book would be a difficult starting point to learn about the field of molecular evolution, more experienced users (with a background and understanding of the problems and literature of molecular evolution) will find it extremely useful, detailed, and insightful in its coverage of specific topics.
David Hillis, in The Quarterly Review of Biology, 90:89-90 (2015)

Errata

Please send me errors or typos etc. by email.

This errata applies to the 2014 edition.

Data files and small programs for examples in the book

I have packed the example data files, and C and R programs in this archive (Yang2014.MESA.data.tgz) (59MB). Make sure you save the file with the correct name. After unpacking, the files will be 225MB. There is a large file C2/primate6s.nuc.txt (190MB), which has alignments of protein-coding gene sequences for 6 primates, used for figure 2.1c. Delete it if you want to save the space.

Please read the README files if they exist.

If I can find the time, I will try to develop a web page for the problems and programs in the book.

If you use the book for teaching and want the slides, please write to me. I may have some powerpoint slides based on figures in the book.

Book description and contents

Description from OUP web site

Presents and explains the statistical methods and computational algorithms developed in molecular evolution, phylogenetics and phylogeography for the comparative analysis of genetic sequence data
Clear explanations of complex statistical models and principles, using examples of real data analysis and numerical calculations to illustrate the theory
Web-based support material includes example data sets, C and R programs that implement computational algorithms discussed in the book, and a primer on probability and statistics
Ideal graduate seminar course material with working problems at the end of each chapter

Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation.

Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, statistical phylogeography, and comparative genomics. Written by an expert in the field, the book emphasizes conceptual understanding rather than mathematical proofs. The text is enlivened with numerous examples of real data analysis and numerical calculations to illustrate the theory, in addition to the working problems at the end of each chapter. The coverage of maximum likelihood and Bayesian methods are in particular up-to-date, comprehensive, and authoritative.

This advanced textbook is aimed at graduate level students and professional researchers (both empiricists and theoreticians) in the fields of bioinformatics and computational biology, statistical genomics, evolutionary biology, molecular systematics, and population genetics. It will also be of relevance and use to a wider audience of applied statisticians, mathematicians, and computer scientists working in computational biology.

Readership: Graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, mathematics and statistics.

Table of Contents (Extended Table of Contents).

Foreword
Preface
1: Models of nucleotide substitution
2: Models of amino acid and codon substitution
3: Phylogeny reconstruction: overview
4: Maximum likelihood methods
5: Comparison of phylogenetic methods and tests on trees
6: Bayesian theory
7: Bayesian computation (MCMC)
8: Bayesian phylogenetics
9: Coalescent theory and species trees
10: Molecular clock and estimation of species divergence times
11: Neutral and adaptive protein evolution
12: Simulating molecular evolution
Appendixes
References

Ziheng Yang's research group page

Molecular Evolution: A Statistical Approach