LEADER 03043nam 2200601Ia 450 001 9910824017603321 005 20200520144314.0 010 $a1-280-84627-5 010 $a0-19-151376-8 010 $a1-4294-5951-4 035 $a(CKB)1000000000471472 035 $a(EBL)431402 035 $a(OCoLC)609832571 035 $a(SSID)ssj0000127699 035 $a(PQKBManifestationID)11141126 035 $a(PQKBTitleCode)TC0000127699 035 $a(PQKBWorkID)10062559 035 $a(PQKB)11176511 035 $a(MiAaPQ)EBC431402 035 $a(OCoLC)72868007 035 $a(FINmELB)ELB161913 035 $a(EXLCZ)991000000000471472 100 $a20070302d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aComputational molecular evolution /$fZiheng Yang 205 $a1st ed. 210 $aOxford $cOxford University Press$d2006 215 $a1 online resource (374 p.) 225 1 $aOxford series in ecology and evolution 300 $aDescription based upon print version of record. 311 $a0-19-856699-9 320 $aIncludes bibliographical references (p. [319]-352) and index. 327 $aContents; PART I: MODELLING MOLECULAR EVOLUTION; 1 Models of nucleotide substitution; 2 Models of amino acid and codon substitution; PART II: PHYLOGENY RECONSTRUCTION; 3 Phylogeny reconstruction: overview; 4 Maximum likelihood methods; 5 Bayesian methods; 6 Comparison of methods and tests on trees; PART III: ADVANCED TOPICS; 7 Molecular clock and estimation of species divergence times; 8 Neutral and adaptive protein evolution; 9 Simulating molecular evolution; 10 Perspectives; Appendices; A: Functions of random variables; B: The delta technique; C: Phylogenetics software; References; Index; A 327 $aBC; D; E; F; G; H; I; J; K; L; M; N; O; P; Q; R; S; T; U; W; Y 330 $aThis book describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. - ;The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyse and interpr 410 0$aOxford series in ecology and evolution. 606 $aMolecular evolution$xMathematical models 606 $aMolecular evolution$xData processing 615 0$aMolecular evolution$xMathematical models. 615 0$aMolecular evolution$xData processing. 676 $a572.838015118 700 $aYang$b Ziheng$01633983 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910824017603321 996 $aComputational Molecular Evolution$93974008 997 $aUNINA