Literature DB >> 10368429

A probabilistic treatment of phylogeny and sequence alignment.

G J Mitchison1.   

Abstract

Carrying out simultaneous tree-building and alignment of sequence data is a difficult computational task, and the methods currently available are either limited to a few sequences or restricted to highly simplified models of alignment and phylogeny. A method is given here for overcoming these limitations by Bayesian sampling of trees and alignments simultaneously. The method uses a standard substitution matrix model for residues together with a hidden Markov model structure that allows affine gap penalties. It escapes the heavy computational burdens of other models by using an approximation called the "*" rule, which replaces missing data by a sum over all possible values of variables. The behavior of the model is demonstrated on test sets of globins.

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Year:  1999        PMID: 10368429     DOI: 10.1007/pl00006524

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  6 in total

1.  Kernel-based logistic regression model for protein sequence without vectorialization.

Authors:  Youyi Fong; Saheli Datta; Ivelin S Georgiev; Peter D Kwong; Georgia D Tomaras
Journal:  Biostatistics       Date:  2014-12-22       Impact factor: 5.279

2.  Standard maximum likelihood analyses of alignments with gaps can be statistically inconsistent.

Authors:  Tandy Warnow
Journal:  PLoS Curr       Date:  2012-03-09

3.  Long-term trends in evolution of indels in protein sequences.

Authors:  Yuri Wolf; Thomas Madej; Vladimir Babenko; Benjamin Shoemaker; Anna R Panchenko
Journal:  BMC Evol Biol       Date:  2007-02-13       Impact factor: 3.260

4.  Evolutionary models for insertions and deletions in a probabilistic modeling framework.

Authors:  Elena Rivas
Journal:  BMC Bioinformatics       Date:  2005-03-21       Impact factor: 3.169

5.  Parameterizing sequence alignment with an explicit evolutionary model.

Authors:  Elena Rivas; Sean R Eddy
Journal:  BMC Bioinformatics       Date:  2015-12-10       Impact factor: 3.169

6.  Probabilistic phylogenetic inference with insertions and deletions.

Authors:  Elena Rivas; Sean R Eddy
Journal:  PLoS Comput Biol       Date:  2008-09-19       Impact factor: 4.475

  6 in total

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