GlimmerHMM is a new gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM’s GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single). A basic user manual can be consulted here.

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  1. Gupal, A. M.; Ostrovsky, A. V.: Using compositions of Markov models to determine functional gene fragments (2013)
  2. Yau, Christopher; Holmes, Christopher C.: A decision-theoretic approach for segmental classification (2013)
  3. Yok, Non G.; Rosen, Gail L.: Combining gene prediction methods to improve metagenomic gene annotation (2011) ioport
  4. Zeng, Jia; Alhajj, Reda; Demetrick, Douglas J.: Representative transcript sets for evaluating a translational initiation sites predictor (2009) ioport
  5. Shmilovici, Armin; Ben-Gal, Irad: Using a VOM model for reconstructing potential coding regions in EST sequences (2007)