Molecular Evolution and Phylogenetics (英語) ペーパーバック – 2000/8/15
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This book presents the statistical methods that are useful in the study of molecular evolution and illustrates how to use them in actual data analysis. Molecular evolution has been developing at a great pace over the past decade or so, driven by the huge increase in genetic sequence data from many organisms, the improvement of high-speed microcomputers, and the development of several new methods for phylogenetic analysis. This book for graduate students and researchers, assuming a basic knowledge of evolution, molecular biology, and elementary statistics, should make it possible for many investigators to incorporate refined statistical analysis of large-scale data in their own work. Nei is one of the leading workers in this area. He and Kumar have developed a computer program called MEGA, which has been sold for about $20 to over 1900 users. For the book, the authors are thoroughly revising MEGA and will make it available via FTP. The book also included analysis using the other most popular programs for phylogenetic studies, including PAUP, PHYLIP, MOLPHY, and PAML.
It is worth its price (Plant Systematics and Evolution)
I would recommend this book to anybody in the life sciences.
The first section gives the clearest and most detailed description of nucleotide sequence comparisons I've seen. I'm no biologist, but it really got me thinking about some new ways to talk about substitution matrices.
The bulk of the book covers what I hoped for originally: phylogenetic trees. The authors choose an unusual approach - it doesn't quite meet the authors' initial promise of math-minimization, but doesn't climb too far up the ivory tower, either. I find it a very practical, usable level of presentation. I'd be nervous about going beyond their formulas, since the math for real understanding isn't all there. Still, the phylogeny discussion covers a lot of material, and covers it well enough for me to write programs about most of it.
The final section addresses population genetics. I have nothing against population genetics, it just never seemed to point where I'm headed. Nei and Kumar corrected my mis-impression. Population gentics is the background model, the null hypothesis, behind the functions that score population differences. It really shows what happens when the tree of life branches out.
The book has some minor weaknesses. It emphasizes nucleotide sequences at the expense of peptides; I can't fault an author for writing what they want as opposed to what I want. On page one, the authors decline an intensely mathematical approach. By page 25, they're up to Poisson and gamma distances. The typography make the section breaks into a "Where's Waldo" experience. Nei's favorite author, based on citations, is Nei. Well, false modesty is no virtue. This book seems authoritative and Nei seems to be an authority, maybe not just in Nei's opinion.
This book really has given me a lot more to work with than most. Education isn't cheap these days, and this book is very educational. I just hope no one asks me to lend it any time soon.
I couldn't even tell it is used. Guess someone just return it after buying.