Detecting DNA regulatory motifs by incorporating positional trends in information content.

Department of Statistics, University of California, Berkeley, CA 94720, USA. kechris@genome.ucsf.edu

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.

PMID: 15239835 [PubMed - indexed for MEDLINE]

PMCID: PMC463320