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We have tailored the Gibbs algorithm (see methods) to this problem by searching for only one site at a time, and then masking only the central 1-2 bases of each sequence motif found before iterating.
Both Ahab and Gibbs, use counts of short strings or single bases, within the window of interest to compute the significance of longer motifs.
Namely, following the hierarchical structure in Figure 1, Argos could be used to predict modules, then the customized Gibbs sampler to predict binding sites (weight matrices) and finally Ahab to predict, genome wide, genes in the same regulatory network.
Hopefully some of the new motifs discovered by Gibbs sampling are real; perhaps they are binding sites for corepressors.
Thus a potentially important aspect of our work is the combination of motif discovery from modules via Gibbs sampling and generalization to the entire genome with Ahab.