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An empirical analysis of training protocols for probabilistic gene finders

BACKGROUND: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the recent proliferation of GHMM implementations. While prevailing methods for modeling and parsing genes using GHMMs have been...

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Autori principali: Majoros, William H, Salzberg, Steven L
Natura: Artigo
Lingua:Inglês
Pubblicazione: BioMed Central 2004
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC544851/
https://ncbi.nlm.nih.gov/pubmed/15613242
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-5-206
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