  We present a Markov chain Monte Carlo algorithm for local alignments of
nucleotide sequences aiming to infer putative transcription factor binding
sites, referred to as the quadratic programming sampler. The new motif finder
incorporates detailed biophysical modeling of the transcription factor binding
site recognition which arises an intrinsic threshold discriminating putative
binding sites from other/background sequences. We validate the principal
functioning of the algorithm on a sample of four promoter regions from
Escherichia coli. The resulting description of the motif can be readily
evaluated on the whole genome to identify new putative binding sites.
