Motivation: The problem of finding transcription factor binding sites in the upstream regions of given genes is algorithmically an interesting and challenging problem in computational biology. A degenerate pattern over a finite alphabet Sigma is a sequence of subsets of Sigma. A string over IUPAC nucleic acid codes is also a degenerate pattern over Sigma = {A, C, G, T}, and is used as one of the major patterns modeling transcription factor binding sites in the upstream regions of genes. However, it is known that the problem of finding a degenerate pattern consistent with both positive and negative string sets is in general NP-complete. Our aim is to devise a heuristic algorithm to find a degenerate pattern which is optimal for positive and negative string sets w.r.t. a given score function.
Results: We have proposed an enumerative algorithm called SUPERPOSITION for finding optimal degenerate patterns with a pruning technique, which works with most all reasonable score functions. The performance score of the algorithm has been compared with those of other popular motif-finding algorithms YMF, MEME and AlignACE on various sets of co-regulated genes of yeast. In the computational experiment, SUPERPOSITION has outperformed the others on several gene sets.
Availability: The python script SUPERPOSITION is available at http://www.math.kyushu-u.ac.jp/~om/softwares.html