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Bioinformatics Advance Access originally published online on November 24, 2006
Bioinformatics 2007 23(4):502-503; doi:10.1093/bioinformatics/btl601
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© 2006 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Mclip: motif detection based on cliques of gapped local profile-to-profile alignments

Tancred Frickey and Georg Weiller *

ARC Centre of Excellence for Integrative Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University GPO Box 475, Canberra, ACT 2601, Australia

*To whom correspondence should be addressed.


  Abstract

Summary: A multitude of motif-finding tools have been published, which can generally be assigned to one of three classes: expectation-maximization, Gibbs-sampling or enumeration. Irrespective of this grouping, most motif detection tools only take into account similarities across ungapped sequence regions, possibly causing short motifs located peripherally and in varying distance to a ‘core’ motif to be missed. We present a new method, adding to the set of expectation-maximization approaches, that permits the use of gapped alignments for motif elucidation.

Availability: The program is available for download from: http://bioinfoserver.rsbs.anu.edu.au/downloads/mclip.jar

Contact: Georp.Weiller{at}anu.edu.au

Supplementary information: http://bioinfoserver.rsbs.anu.edu.au/utils/mclip/info.php

Associate Editor: John Quackenbush

Received on September 15, 2006; revised on November 5, 2006; accepted on November 20, 2006

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