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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...
Autores principales: | Martin, Juliette, Gibrat, Jean-François, Rodolphe, François |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2006
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Materias: | |
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 |
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