Bioinformatics Advance Access first published online on November 24, 2006
This version published online on December 5, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl601
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1 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.
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. Supplementary_information: http://bioinfoserver.rsbs.anu.edu.au/utils/mclip/info.php. Associate Editor: John Quackenbush The corresponding author's email address has been corrected.
Received September 15, 2006
Revised November 5, 2006
Accepted November 20, 2006
Applications note
Mclip: motif detection based on cliques of gapped local profile-to-profile alignments
Tancred Frickey 1 and Georg Weiller 1 *
Georg Weiller, E-mail: Georg.Weiller{at}anu.edu.au
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