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Quantifying similarity between motifs

Shobhit Gupta1, John A Stamatoyannopoulos1, Timothy L Bailey2 and William Stafford Noble13*

Author Affiliations

1 Department of Genome Sciences, University of Washington, 1705 NE Pacific Street, Box 355065, Seattle, WA 98195, USA

2 Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia

3 Department of Computer Science and Engineering, University of Washington, 185 Stevens Way, Box 352350, Seattle, WA 98105, USA

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Genome Biology 2007, 8:R24  doi:10.1186/gb-2007-8-2-r24

Published: 26 February 2007

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.