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One of the most successful methods to date for recognizing protein sequences that are evolutionarily related, has been profile hidden Markov models. However, these models do not capture pairwise statistical preferences of residues that are hydrogen bonded in beta-sheets. We thus explore methods for incorporating pairwise dependencies into these models.

Recognition of beta-structural motifs using hidden Markov models trained with simulated evolution