Computational Molecular Evolution [Oxford-Serie in Ökologie und Evolution]-

Ursprünglicher Text
Computational Molecular Evolution [Oxford Series in Ecology and Evolution]
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Artikelzustand
Sehr gut: Buch, das nicht neu aussieht und gelesen wurde, sich aber in einem hervorragenden Zustand ...
ISBN
9780198567028
Kategorie

Über dieses Produkt

Product Identifiers

Publisher
Oxford University Press, Incorporated
ISBN-10
0198567022
ISBN-13
9780198567028
eBay Product ID (ePID)
56982224

Product Key Features

Number of Pages
376 Pages
Publication Name
Computational Molecular Evolution
Language
English
Subject
Life Sciences / Molecular Biology, Life Sciences / General
Publication Year
2006
Type
Textbook
Author
Ziheng Yang
Subject Area
Science
Series
Oxford Series in Ecology and Evolution Ser.
Format
Perfect

Dimensions

Item Height
0.8 in
Item Weight
19.6 Oz
Item Length
9.2 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2007-271492
Dewey Edition
22
Reviews
What sets this books 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 an invaluable resource both for new graduate students and established researchers. It will be a major source for insight and enormously helpful for anyone who wants to understandmolecular phylogenies., "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, "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, "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
Illustrated
Yes
Dewey Decimal
572.838015118
Table Of Content
Preface1. Models of Nucleotide Substitution2. Models of Amino Acid and Codon Substitution3. Phylogeny Reconstruction: Overview4. Maximum Likelihood Methods5. Bayesian Methods6. Comparison of Methods and Tests on Trees7. Molecular Clock and Estimation of Species Divergence Times8. Neutral and Adaptive Protein Evolution9. Simulating Molecular Evolution10. PerspectivesAppendixesReference
Synopsis
This book 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 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., 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 analyse 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.
LC Classification Number
QH371.3.M37

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