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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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... in genomic sequences, following a computational approach inspired by a generalized hidden Markov model (GHMM). References: 1. M. Rho et al., "De novo identification of LTR retrotransposons in eukaryotic genomes", BMC Genomics (2007) 8:90. 2. M. Rho and H. Tang, "MGEScan-non-LTR: computational identification and classification of autonomous non-LTR retrotransposons in eukaryotic genomes", Nucleic Acids Research (2009) 37:21.
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