Deep learning framework for data mining protein-protein interactions using CNN
- Predefined atom-level and residue-level PPI feature types, e.g. atomic density, vdw energy, residue contacts, PSSM, etc. - Predefined target types, e.g. binary class, CAPRI categories, DockQ, RMSD, FNAT, etc. - Flexible definition of both new features and targets - 3D grid feature mapping - Efficient data storage in HDF5 format - Support both classification and regression (based on PyTorch) DeepRank is a general, configurable deep learning framework for data mining protein-protein interactions (PPIs) using 3D convolutional neural networks (CNNs). DeepRank contains useful APIs for pre-processing PPIs data, computing features and targets, as well as training and testing CNN models. #### Features: - Predefined atom-level and residue-level PPI feature types, e.g. atomic density, vdw energy, residue contacts, PSSM, etc. - Predefined target types, e.g. binary class, CAPRI categories, DockQ, RMSD, FNAT, etc. - Flexible definition of both new features and targets - 3D grid feature mapping - Efficient data storage in HDF5 format - Support both classification and regression (based on PyTorch)
DeepRank: a deep learning framework for data mining 3D protein-protein interfaces