DeepRank2 |version| documentation
DeepRank2 is an open-source deep learning (DL) framework for data mining of protein-protein interfaces (PPIs) or single-residue variants (SRVs). This package is an improved and unified version of three previously developed packages: DeepRank, DeepRank-GNN, and DeepRank-Mut.
DeepRank2 allows for transformation of (pdb formatted) molecular data into 3D representations (either grids or graphs) containing structural and physico-chemical information, which can be used for training neural networks. DeepRank2 also offers a pre-implemented training pipeline, using either convolutional neural networks (for grids) or graph neural networks (for graphs), as well as output exporters for evaluating performances.
Main features:
- Predefined atom-level and residue-level feature types (e.g. atom/residue type, charge, size, potential energy, all features' documentation is available under Features notes)
- Predefined target types (binary class, CAPRI categories, DockQ, RMSD, and FNAT, detailed docking scores documentation is available under Docking scores notes)
- Flexible definition of both new features and targets
- Features generation for both graphs and grids
- Efficient data storage in HDF5 format
- Support both classification and regression (based on PyTorch and PyTorch Geometric)
.. toctree:: :maxdepth: 2 :caption: Getting started :hidden: installation getstarted
- :doc:`installation`
- Get DeepRank2 installed on your computer.
- :doc:`getstarted`
- Understand how to use DeepRank2 and how it can help you.
.. toctree:: :caption: Notes :hidden: features docking
- :doc:`features`
- Get a detailed overview about nodes' and edges' features implemented in the package.
- :doc:`docking`
- Get a detailed overview about PPIs' docking metrics implemented in the package.
.. toctree:: :caption: API :hidden: reference/deeprank2
- :doc:`reference/deeprank2`
- This section documents the DeepRank2 API.