DeepRank
DE
Deep learning framework for data mining protein-protein interactions using CNN
Updated 8 months ago
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deeprank-core
deeprank-core is the refactorized version of DeepRank GNN, the graph neural network of our DeepRank package. It allows to train graph neural networks to classify protein-protein interface with a greater flexibility for the user.
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contributors
What deeprank-core can do for you
- Creates graphs on protein-protein interface
- Train graph neural network on protein-protein interface
- Provide great flexibility to the user for implementing new classes and functions relevant for specific applications
In recent years, for the purpose of drug design or protein engineering it has become increasingly of interest to predict or classify information based on the 3D protein-protein interactome.
We have previously developed DeepRank and DeepRank-GNN, deep-learning frameworks to facilitate pattern learning from protein-protein interfaces using Convolutional Neural Network (CNN) and Graph Neural Network (GNN) approaches. deeprank-core has been redesigned to be more modular and customizable, and is wrapped into a user-friendly python3 package.
Participating organisations
Contributors
GC
Giulia Crocioni
Netherlands eScience Center
Sven van der Burg
Netherlands eScience Center
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Related tools
DeepRank GNN
DE
DeepRank-GNN is the graph neural network of our DeepRank package. DeepRank GNN allows to train graph neural networks to classify protein-protein interface
Updated 8 months ago
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