Email updates

Keep up to date with the latest news and content from Genome Biology and BioMed Central.

Open Access Highly Accessed Method

Detecting DNA regulatory motifs by incorporating positional trends in information content

Katherina J Kechris14*, Erik van Zwet15, Peter J Bickel1 and Michael B Eisen23

Author Affiliations

1 Department of Statistics, University of California, Berkeley, CA 94720, USA

2 Department of Genome Sciences, Life Sciences Division, Ernest Orlando Lawrence Berkeley National Lab, Cyclotron Road, Berkeley, CA 94720, USA

3 Center for Integrative Genomics, Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA

4 Current address: Department of Biochemistry and Biophysics, 600 16th Street 2240, University of California, San Francisco, CA 94143, USA

5 Current address: Mathematical Institute, University Leiden, 2300 RA Leiden, The Netherlands

For all author emails, please log on.

Genome Biology 2004, 5:R50  doi:10.1186/gb-2004-5-7-r50

Published: 24 June 2004

Abstract

On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods. We assign position-specific prior distributions to the frequency parameters of the model, penalizing deviations from a specified conservation profile. Examples with both simulated and real data show that this extension helps discover motifs as the data become noisier or when there is a competing false motif.