Detection of cis-element clusters in higher eukaryotic DNA

Motivation: Computational prediction and analysis of transcription. regulat ory regions in DNA sequences has the potential to accelerate greatly our un derstanding of how cellular processes are controlled. We present a hidden M arkov model 'based method for detecting regulatory regions in DNA sequences , by searching for clusters of cis-elements. Results: When applied to regulatory targets of the transcription factor LSF , this method achieves a sensitivity of 67%, while making one prediction pe r 33 kb of nonrepetitive human genomic sequence. When applied to muscle spe cific regulatory regions, we obtain a sensitivity and prediction rate that compare favorably with one of the best alternative approaches. Our method, which we call Cister, can be used! to predict different varieties of regula tory region by searching for clusters of cis-elements of any type chosen by the user. Cister is simple to use and is available on the web.