Binding site discovery from nucleic acid sequences by discriminative learning of hidden Markov models

We present a discriminative learning method for pattern discovery of binding sites in nucleic acid sequences based on hidden Markov models. Sets of positive and negative example sequences are mined for sequence motifs whose occurrence frequency varies between the sets.

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