Computational Molecular Evolution.
Title:
Computational Molecular Evolution.
Author:
Yang, Ziheng.
ISBN:
9780191513763
Personal Author:
Physical Description:
1 online resource (374 pages)
Series:
Oxford Series in Ecology and Evolution
Contents:
Contents -- PART I: MODELLING MOLECULAR EVOLUTION -- 1 Models of nucleotide substitution -- 1.1 Introduction -- 1.2 Markov models of nucleotide substitution and distance estimation -- 1.3 Variable substitution rates across sites -- 1.4 Maximum likelihood estimation -- 1.5 Markov chains and distance estimation under general models -- 1.6 Discussions -- 1.7 Exercises -- 2 Models of amino acid and codon substitution -- 2.1 Introduction -- 2.2 Models of amino acid replacement -- 2.3 Estimation of distance between two protein sequences -- 2.4 Models of codon substitution -- 2.5 Estimation of synonymous and nonsynonymous substitution rates -- 2.6 Numerical calculation of the transition-probability matrix -- 2.7 Exercises -- PART II: PHYLOGENY RECONSTRUCTION -- 3 Phylogeny reconstruction: overview -- 3.1 Tree concepts -- 3.2 Exhaustive and heuristic tree search -- 3.3 Distance methods -- 3.4 Maximum parsimony -- 4 Maximum likelihood methods -- 4.1 Introduction -- 4.2 Likelihood calculation on tree -- 4.3 Likelihood calculation under more complex models -- 4.4 Reconstruction of ancestral states -- 4.5 Numerical algorithms for maximum likelihood estimation -- 4.6 Approximations to likelihood -- 4.7 Model selection and robustness -- 4.8 Exercises -- 5 Bayesian methods -- 5.1 The Bayesian paradigm -- 5.2 Prior -- 5.3 Markov chain Monte Carlo -- 5.4 Simple moves and their proposal ratios -- 5.5 Monitoring Markov chains and processing output -- 5.6 Bayesian phylogenetics -- 5.7 MCMC algorithms under the coalescent model -- 5.8 Exercises -- 6 Comparison of methods and tests on trees -- 6.1 Statistical performance of tree-reconstruction methods -- 6.2 Likelihood -- 6.3 Parsimony -- 6.4 Testing hypotheses concerning trees -- 6.5 Appendix: Tuffley and Steel's likelihood analysis of one character -- PART III: ADVANCED TOPICS.
7 Molecular clock and estimation of species divergence times -- 7.1 Overview -- 7.2 Tests of the molecular clock -- 7.3 Likelihood estimation of divergence times -- 7.4 Bayesian estimation of divergence times -- 7.5 Perspectives -- 8 Neutral and adaptive protein evolution -- 8.1 Introduction -- 8.2 The neutral theory and tests of neutrality -- 8.3 Lineages undergoing adaptive evolution -- 8.4 Amino acid sites undergoing adaptive evolution -- 8.5 Adaptive evolution affecting particular sites and lineages -- 8.6 Assumptions, limitations, and comparisons -- 8.7 Adaptively evolving genes -- 9 Simulating molecular evolution -- 9.1 Introduction -- 9.2 Random number generator -- 9.3 Generation of continuous random variables -- 9.4 Generation of discrete random variables -- 9.5 Simulating molecular evolution -- 9.6 Exercises -- 10 Perspectives -- 10.1 Theoretical issues in phylogeny reconstruction -- 10.2 Computational issues in analysis of large and heterogeneous data sets -- 10.3 Genome rearrangement data -- 10.4 Comparative genomics -- Appendices -- A: Functions of random variables -- B: The delta technique -- C: Phylogenetics software -- References -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- W -- Y.
Abstract:
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 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. -.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Genre:
Electronic Access:
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