BEAM: a beam search algorithm for the identification of cis-regulatory elements in groups of genes

Abstract

The identification of potential protein binding sites (cis-regulatory elements) in the upstream regions of genes is key to understanding the mechanisms that regulate gene expression. To this end, we present a simple, efficient algorithm, BEAM (beam-search enumerative algorithm for motif finding), aimed at the discovery of cis-regulatory elements in the DNA sequences upstream of a related group of genes. This algorithm dramatically limits the search space of expanded sequences, converting the problem from one that is exponential in the length of motifs sought to one that is linear. Unlike sampling algorithms, our algorithm converges and is capable of finding statistically overrepresented motifs with a low failure rate. Further, our algorithm is not dependent on the objective function or the organism used. Limiting the space of candidate motifs enables the algorithm to focus only on those motifs that are most likely to be biologically relevant and enables the algorithm to use direct evaluations of background frequencies instead of resorting to probabilistic estimates. In addition, limiting the space of candidate motifs makes it possible to use computationally expensive objective functions that are able to correctly identify biologically relevant motifs.