Literature DB >> 12200481

Codon and rate variation models in molecular phylogeny.

Eric Schadt1, Kenneth Lange.   

Abstract

This article generalizes previous models for codon substitution and rate variation in molecular phylogeny. Particular attention is paid to (1) reversibility, (2) acceptance and rejection of proposed codon changes, (3) varying rates of evolution among codon sites, and (4) the interaction of these sites in determining evolutionary rates. To accommodate spatial variation in rates, Markov random fields rather than Markov chains are introduced. Because these innovations complicate maximum likelihood estimation in phylogeny reconstruction, it is necessary to formulate new algorithms for the evaluation of the likelihood and its derivatives with respect to the underlying kinetic, acceptance, and spatial parameters. To derive the most from maximum likelihood analysis of sequence data, it is useful to compute posterior probabilities assigning residues to internal nodes and evolutionary rate classes to codon sites. It is also helpful to search through tree space in a way that respects accepted phylogenetic relationships. Our phylogeny program LINNAEUS implements algorithms realizing these goals. Readers may consult our companion article in this issue for several examples.

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Year:  2002        PMID: 12200481     DOI: 10.1093/oxfordjournals.molbev.a004216

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  8 in total

1.  Counting labeled transitions in continuous-time Markov models of evolution.

Authors:  Vladimir N Minin; Marc A Suchard
Journal:  J Math Biol       Date:  2007-09-14       Impact factor: 2.259

2.  Complexity reduction in context-dependent DNA substitution models.

Authors:  William H Majoros; Uwe Ohler
Journal:  Bioinformatics       Date:  2008-11-18       Impact factor: 6.937

3.  Bayesian comparisons of codon substitution models.

Authors:  Nicolas Rodrigue; Nicolas Lartillot; Hervé Philippe
Journal:  Genetics       Date:  2008-09-14       Impact factor: 4.562

4.  Detecting site-specific physicochemical selective pressures: applications to the Class I HLA of the human major histocompatibility complex and the SRK of the plant sporophytic self-incompatibility system.

Authors:  Raazesh Sainudiin; Wendy Shuk Wan Wong; Krithika Yogeeswaran; June B Nasrallah; Ziheng Yang; Rasmus Nielsen
Journal:  J Mol Evol       Date:  2005-03       Impact factor: 2.395

5.  Estimating selection pressures on HIV-1 using phylogenetic likelihood models.

Authors:  S L Kosakovsky Pond; A F Y Poon; S Zárate; D M Smith; S J Little; S K Pillai; R J Ellis; J K Wong; A J Leigh Brown; D D Richman; S D W Frost
Journal:  Stat Med       Date:  2008-10-15       Impact factor: 2.373

6.  Pathological rate matrices: from primates to pathogens.

Authors:  Harold W Schranz; Von Bing Yap; Simon Easteal; Rob Knight; Gavin A Huttley
Journal:  BMC Bioinformatics       Date:  2008-12-19       Impact factor: 3.169

7.  Evolution and selection in yeast promoters: analyzing the combined effect of diverse transcription factor binding sites.

Authors:  Daniela Raijman; Ron Shamir; Amos Tanay
Journal:  PLoS Comput Biol       Date:  2008-01       Impact factor: 4.475

8.  Statistical power of phylo-HMM for evolutionarily conserved element detection.

Authors:  Xiaodan Fan; Jun Zhu; Eric E Schadt; Jun S Liu
Journal:  BMC Bioinformatics       Date:  2007-10-05       Impact factor: 3.169

  8 in total

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