QPS -- quadratic programming sampler, a motif finder using biophysical modeling

TL;DR

This paper introduces QPS, a novel motif finder using biophysical modeling and Markov chain Monte Carlo to identify transcription factor binding sites with high accuracy.

Contribution

The paper presents the quadratic programming sampler, a new motif finding algorithm that integrates detailed biophysical modeling for improved detection of binding sites.

Findings

Validated on E. coli promoter regions

Effective discrimination of binding sites from background sequences

Potential for genome-wide application

Abstract

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.