| Literature DB >> 17921492 |
Emmanuelle Becker1, Aurélie Cotillard, Vincent Meyer, Hocine Madaoui, Raphaël Guérois.
Abstract
Recent development of strategies using multiple sequence alignments (MSA) or profiles to detect remote homologies between proteins has led to a significant increase in the number of proteins whose structures can be generated by comparative modeling methods. However, prediction of the optimal alignment between these highly divergent homologous proteins remains a difficult issue. We present a tool based on a generalized Viterbi algorithm that generates optimal and sub-optimal alignments between a sequence and a Hidden Markov Model. The tool is implemented as a new function within the HMMER package called hmmkalign.Mesh:
Substances:
Year: 2007 PMID: 17921492 DOI: 10.1093/bioinformatics/btm492
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937