title: MotifSuite: workflow for probabilistic motif detection and assessment.
abstract: BACKGROUND
  Probabilistic motif detection requires a multi-step approach going from the actual de novo regulatory motif finding up to a tedious assessment of the predicted motifs. MotifSuite, a user-friendly web interface streamlines this analysis flow. Its core consists of two post-processing procedures that allow prioritizing the motif detection output. The tools offered by MotifSuite are built around the well-established motif detection tool MotifSampler and can also be used in combination with any other probabilistic motif detection tool. Elaborate guidelines on each of its applications have been provided.
  
  
  BACKGROUND
  http://homes.esat.kuleuven.be/bioi_marchal/MotifSuite/Index.htm
authors.affiliation: Department of Microbial and Molecular Systems, Katholieke Universiteit Leuven, Kasteelpark Arenberg 20, Heverlee, Belgium.
authors.forename: Marleen
authors.initials: M
authors.lastname: Claeys
authors.forename: Valerie
authors.initials: V
authors.lastname: Storms
authors.forename: Hong
authors.initials: H
authors.lastname: Sun
authors.forename: Tom
authors.initials: T
authors.lastname: Michoel
authors.forename: Kathleen
authors.initials: K
authors.lastname: Marchal
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D020407:Internet; D017434:Protein Structure, Tertiary; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software