Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks.
Jack HansonKuldip K. PaliwalThomas LitfinYuedong YangYaoqi ZhouPublished in: Bioinform. (2019)
Keyphrases
- solvent accessibility
- protein secondary structure
- secondary structure
- contact maps
- amino acid sequences
- protein sequences
- amino acids
- tertiary structure
- convolutional neural networks
- protein structure
- contact map
- coarse grained
- molecular biology
- computational methods
- computational biology
- protein secondary structure prediction
- protein function
- protein structure prediction
- training data
- protein folding
- psi blast
- sequence analysis
- training set
- computational approaches
- link prediction
- fine grained