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Efficient decoding algorithms for generalized hidden Markov model gene finders
BACKGROUND: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility and probabilistic underpinnings. As the focus of the gene finding community shifts toward the use of homology information t...
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| Опубликовано в: : | BMC Bioinformatics |
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| Главные авторы: | , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
BMC
2005
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.govhttps://pmc.ncbi.nlm.nih.gov/articles/PMC552317/ https://ncbi.nlm.nih.govhttps://pubmed.ncbi.nlm.nih.gov/15667658/ https://ncbi.nlm.nih.govhttps://doi.org/10.1186/1471-2105-6-16 |
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