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A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction
BACKGROUND: Direct prediction of the three-dimensional (3D) structures of proteins from one-dimensional (1D) sequences is a challenging problem. Significant structural characteristics such as solvent accessibility and contact number are essential for deriving restrains in modeling protein folding an...
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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2017
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5751690/ https://ncbi.nlm.nih.gov/pubmed/29297299 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-017-1971-7 |
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