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Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
BACKGROUND: The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous) proteins is not available, w...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2006
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC1479840/ https://ncbi.nlm.nih.gov/pubmed/16571137 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-7-178 |
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