title: Quantifying similarity between motifs.
abstract: A common question within the context of de novo motif discovery is whether a newly discovered, putative motif resembles any previously discovered motif in an existing database. To answer this question, we define a statistical measure of motif-motif similarity, and we describe an algorithm, called Tomtom, for searching a database of motifs with a given query motif. Experimental simulations demonstrate the accuracy of Tomtom's E values and its effectiveness in finding similar motifs.
authors.affiliation: Department of Genome Sciences, University of Washington, 1705 NE Pacific Street, Box 355065, Seattle, WA 98195, USA. shobhitg@u.washington.edu
authors.forename: Shobhit
authors.initials: S
authors.lastname: Gupta
authors.forename: John A
authors.initials: JA
authors.lastname: Stamatoyannopoulos
authors.forename: Timothy L
authors.initials: TL
authors.lastname: Bailey
authors.forename: William Stafford
authors.initials: WS
authors.lastname: Noble
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D017385:Sequence Homology; D012984:Software