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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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    TransGeneScan

    TransGeneScan is a gene finding tool for metatranscriptomic sequences

    ...TransGeneScan is no longer maintained in SourceForge. Please find the latest version in Github. TransGeneScan is a gene finding tool for Metatranscriptomic sequences. TransGeneScan incorporates strand-speci c hidden states, representing coding sequences in sense and anti-sense strands on transcripts in a Hidden Markov Model similar to the one used in FragGeneScan (http://fraggenescan.sourceforge.net/), and can predict a sense transcript containing one or multiple genes (in an operon) or an antisense transcript.
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    ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.
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