pHMM-tree: phylogeny of profile hidden Markov models
Author(s) -
Luyang Huo,
Han Zhang,
Xueting Huo,
Yasong Yang,
Xueqiong Li,
Yanbin Yin
Publication year - 2016
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/btw779
Subject(s) - hidden markov model , phylogenetic tree , phylogenetics , tree (set theory) , computer science , sequence alignment , artificial intelligence , pattern recognition (psychology) , biology , computational biology , genetics , mathematics , peptide sequence , combinatorics , gene
Protein families are often represented by profile hidden Markov models (pHMMs). Homology between two distant protein families can be determined by comparing the pHMMs. Here we explored the idea of building a phylogeny of protein families using the distance matrix of their pHMMs. We developed a new software and web server (pHMM-tree) to allow four major types of inputs: (i) multiple pHMM files, (ii) multiple aligned protein sequence files, (iii) mixture of pHMM and aligned sequence files and (iv) unaligned protein sequences in a single file. The output will be a pHMM phylogeny of different protein families delineating their relationships. We have applied pHMM-tree to build phylogenies for CAZyme (carbohydrate active enzyme) classes and Pfam clans, which attested its usefulness in the phylogenetic representation of the evolutionary relationship among distant protein families.
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