Evolutionary HMMs: a Bayesian approach to multiple alignment
Author(s) -
Ian Holmes,
William Bruno
Publication year - 2001
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/17.9.803
Subject(s) - multiple sequence alignment , computer science , alignment free sequence analysis , phylogenetic tree , sequence alignment , pairwise comparison , bayesian probability , inference , source code , probabilistic logic , structural alignment , data mining , algorithm , theoretical computer science , computational biology , artificial intelligence , biology , genetics , peptide sequence , gene , operating system
We review proposed syntheses of probabilistic sequence alignment, profiling and phylogeny. We develop a multiple alignment algorithm for Bayesian inference in the links model proposed by Thorne et al. (1991, J. Mol. Evol., 33, 114-124). The algorithm, described in detail in Section 3, samples from and/or maximizes the posterior distribution over multiple alignments for any number of DNA or protein sequences, conditioned on a phylogenetic tree. The individual sampling and maximization steps of the algorithm require no more computational resources than pairwise alignment.
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