Literature DB >> 17921492

HMM-Kalign: a tool for generating sub-optimal HMM alignments.

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.

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Year:  2007        PMID: 17921492     DOI: 10.1093/bioinformatics/btm492

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

Review 1.  From local structure to a global framework: recognition of protein folds.

Authors:  Agnel Praveen Joseph; Alexandre G de Brevern
Journal:  J R Soc Interface       Date:  2014-04-16       Impact factor: 4.118

Review 2.  Template-based protein modeling: recent methodological advances.

Authors:  Pankaj R Daga; Ronak Y Patel; Robert J Doerksen
Journal:  Curr Top Med Chem       Date:  2010       Impact factor: 3.295

3.  RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences.

Authors:  Francesco Rubino; Marcella Attimonelli
Journal:  BMC Bioinformatics       Date:  2009-06-16       Impact factor: 3.169

  3 in total

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