DeepRank

• 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)