Figure 2.

Search method overview. Overview of search method. The input sequences are converted into a suffix tree which is used to efficiently enumerate over-represented words. These words are tested as possible seeds for a HMM. For each seed we consider a number of different placements of the gap character. Highly scoring seeds are used to initialise HMMs which are trained using the Baum-Welch algorithm. Each trained HMM defines a gapped PWM and these are scored and ranked. The best gapped PWMs are reported as the output of the method.