Software

Measuring similarities between transcription factor binding sites

Szymon M Kielbasa^1*, Didier Gonze^1,2 and Hanspeter Herzel¹

• * Corresponding author: Szymon M Kielbasa s.kielbasa@biologie.hu-berlin.de

Author Affiliations

¹ Institute for Theoretical Biology, Humboldt University, Invalidenstraße 43, D-10115 Berlin, Germany

² Unité de Chronobiologie Théorique, Université Libre de Bruxelles, CP 231, Campus Plaine, Bvd du Triomphe, B-1050 Bruxelles, Belgium

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BMC Bioinformatics 2005, 6:237 doi:10.1186/1471-2105-6-237

Published: 28 September 2005

Abstract

Background

Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites.

Results

We propose to identify and group similar profiles using two independent similarity measures: χ² distances between position frequency matrices (PFMs) and correlation coefficients between position weight matrices (PWMs) scores.

Conclusion

We show that these measures complement each other and allow to associate Jaspar and Transfac matrices. Clusters of highly similar matrices are identified and can be used to optimise the search for regulatory elements. Moreover, the application of the measures is illustrated by assigning E-box matrices of a SELEX experiment and of experimentally characterised binding sites of circadian clock genes to the Myc-Max cluster.