A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction
Abstract 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 fo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2017-12-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1971-7 |