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An algorithm for finding novel gapped motifs in DNA sequences

We propose a novel algorithm that, given a long DNA sequence, finds approximate repeats, allowing general insertions and deletions. The idea is based on the Gibbs sampling approach of Lawrence et al. The novelty of our algorithm stems largely from our handling of gaps in the motif occurrences. Another contribution is the use of relative entropy as a natural scoring function for alignment of the motif occurrences. We describe the results of experiments with this algorithm on the full H. influenzae genome.