This is an unofficial implementation of Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model, which is a deep learning method for prediction of pretein contact map, with predicted contact map by other software(for example CCMpred, PSICOV, and so on) as input.
- Network structure: 2 networks(residual network and highway network) were implemented;
- Batch normalization and L2 regulation were implemented for optimization.
- Get protein structure 1D features(for example sequence, sse, ACA, and so on), and 2D features(for example predicted CCMpred, PSICOV and other pairwise features)
- Modify
./read_into_tfrecord.py
, and used it to transfer your data to tfrecord - set your own config in
./libs/config/config.py
- run
python train.py