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The state of the art in promoter modeling for higher eukaryotes is predicting not single transcription factor binding sites (TFBSs), but their combinations. The new tool utilizes a previously developed method of distance distributions of TFBS pairs. We model the random distribution of distances and compare it with the distribution observed in the query sequences. Comparison of the profiles allows filtering out the 'noise' and retaining the potentially functional combinations. This approach hasdoi:10.1093/bioinformatics/btq132 pmid:20360058 fatcat:lakwjtxx5jghffchkfbtxqoj7e