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The ever growing number of completely sequenced prokaryotic genomes facilitates cross-species comparisons by genomic annotation algorithms. This paper introduces a new probabilistic framework for comparative genomic analysis and demonstrates its utility in the context of improving the accuracy of prokaryotic gene start site detection. Our framework employs a product hidden Markov model (PROD-HMM) with state architecture to model the species-speci®c trinucleotide frequency patterns in sequencesdoi:10.1093/nar/gkf423 pmid:12136100 pmcid:PMC135744 fatcat:7acsgn2nkjft7ommwsretzxvre