Feature based representation and detection of transcription factor binding sites

Abstract

The prediction of transcription factor binding sites is an important problem, since it reveals information about the transcriptional regulation of genes. A commonly used representation of these sites are position specific weight matrices which show weak predictive power. We introduce a feature-based modelling approach, which is able to deal with various kind of biological properties of binding sites and models them via Bayesian belief networks. The presented results imply higher model accuracy in contrast to the PSSM approach.