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This book provides a comprehensive review of the many interesting statistical problems arising in molecular evolution provided by the leading researchers in the field. It is intended for researchers and students from the statistical and biological science alike. For the statistician the book provides an introduction to an exciting area of application that often has been overlooked by statisticians. For the biologists the book provides an introduction to the theory underlying many of the methods they use in their daily research. Several of the chapters, including the four introductory chapters, are also highly suitable as texts for advanced undergraduate or graduate level courses in molecular evolution.
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Inside This Book
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First Sentence:
Markov chains (or Markov processes) are memoryless stochastic processes. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
least favorable model, substitution model parameters, posterior mapping, optimize the likelihood function, reversible rate matrix, indel model, codeml program, base composition variation, detecting adaptive evolution, molecular clock property, instantaneous rate matrix, codon model, adaptive molecular evolution, overdispersed molecular clock, chronological rate, divergence time estimation, base composition bias, probability that the tree, simplified working model, noncoding sites, nucleotide models, covarion model, statistical alignment, breakpoint graph, detecting positive selection Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, New York, Mol Biol Evol, Journal of Molecular Evolution, Mol Evol, Systematic Biology, Academic Press, Oxford University Press, Proc Natl Acad Sci, Genome Res, Cambridge University Press, Nucleic Acids Res, Protein Eng, University of California, Theor Popul Biol, World Scientific, John Wiley, Mammalian Protein Metabolism, Sinauer Associates, Biological Sciences, Cornell University, Site Prob, Trends Genet, Annals of Statistics, Appl Probab New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Markov chains (or Markov processes) are memoryless stochastic processes. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
least favorable model, substitution model parameters, posterior mapping, optimize the likelihood function, reversible rate matrix, indel model, codeml program, base composition variation, detecting adaptive evolution, molecular clock property, instantaneous rate matrix, codon model, adaptive molecular evolution, overdispersed molecular clock, chronological rate, divergence time estimation, base composition bias, probability that the tree, simplified working model, noncoding sites, nucleotide models, covarion model, statistical alignment, breakpoint graph, detecting positive selection Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, New York, Mol Biol Evol, Journal of Molecular Evolution, Mol Evol, Systematic Biology, Academic Press, Oxford University Press, Proc Natl Acad Sci, Genome Res, Cambridge University Press, Nucleic Acids Res, Protein Eng, University of California, Theor Popul Biol, World Scientific, John Wiley, Mammalian Protein Metabolism, Sinauer Associates, Biological Sciences, Cornell University, Site Prob, Trends Genet, Annals of Statistics, Appl Probab New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 68
books:
See all 68 books this book cites
5
books
cite this book:
- Atlas of Protein Sequence and Structure (Vol 5, Supplement 3) by Margaret O. Dayhoff on 4 pages
- The Causes of Molecular Evolution (Oxford Series in Ecology and Evolution) by John H. Gillespie on 4 pages
- Mammalian Protein Metabolism (v. 1) by H.N. Munro on page 43, page 223, and page 254
- Inferring Phylogenies by Joseph Felsenstein on page 61, page 253, and page 436
- Molecular Systematics, Second Edition by David M. Hillis on page 255, page 462, and Back Matter
See all 68 books this book cites
- Research in Computational Molecular Biology: 10th Annual International Conference, RECOMB 2006, Venice, Italy, April 2-5, 2006, Proceedings (Lecture Notes ... Science / Lecture Notes in Bioinformatics) by Alberto Apostolico on page 204
- The Statistical Analysis of Interval-censored Failure Time Data (Statistics for Biology and Health) by Jianguo Sun in Front Matter
- Computational Molecular Evolution (Oxford Series in Ecology and Evolution) by Ziheng Yang in Back Matter
- Dose Finding in Drug Development (Statistics for Biology and Health) by Naitee Ting in Front Matter
- Survival Analysis: A Self-Learning Text (Statistics for Biology and Health) by David G. Kleinbaum in Front Matter
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