title: Mclip: motif detection based on cliques of gapped local profile-to-profile alignments.
abstract: 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.
  
  
  BACKGROUND
  The program is available for download from: http://bioinfoserver.rsbs.anu.edu.au/downloads/mclip.jar.
  
  
  BACKGROUND
  http://bioinfoserver.rsbs.anu.edu.au/utils/mclip/info.php.
authors.affiliation: 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.
authors.forename: Tancred
authors.initials: T
authors.lastname: Frickey
authors.forename: Georg
authors.initials: G
authors.lastname: Weiller
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software