title: GIMSAN: a Gibbs motif finder with significance analysis.
abstract: We present GIMSAN (GIbbsMarkov with Significance ANalysis): a novel tool for de novo motif finding. GIMSAN combines GibbsMarkov, our variant of the Gibbs Sampler, described here for the first time, with our recently introduced significance analysis.
  
  
  BACKGROUND
  GIMSAN is currently available as a web application and a stand-alone application on Unix and PBS (Portable Batch System) cluster through links from http://www.cs.cornell.edu/~keich.
authors.affiliation: Department of Computer Science, Cornell University, Ithaca, NY 14853, USA.
authors.forename: Patrick
authors.initials: P
authors.lastname: Ng
authors.forename: Uri
authors.initials: U
authors.lastname: Keich
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA; D012984:Software