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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...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2004
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC544851/ https://www.ncbi.nlm.nih.gov/pubmed/15613242 http://dx.doi.org/10.1186/1471-2105-5-206 |