Analysis of an optimal hidden Markov model for secondary structure prediction

BACKGROUND: Secondary structure prediction is a useful first step toward 3D structure prediction. A number of successful secondary structure prediction methods use neural networks, but unfortunately, neural networks are not intuitively interpretable. On the contrary, hidden Markov models are graphic...

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Detalles Bibliográficos
Autores principales: Martin, Juliette, Gibrat, Jean-François, Rodolphe, François
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1769381/
https://www.ncbi.nlm.nih.gov/pubmed/17166267
http://dx.doi.org/10.1186/1472-6807-6-25

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1769381/
https://www.ncbi.nlm.nih.gov/pubmed/17166267
http://dx.doi.org/10.1186/1472-6807-6-25

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