In this repository, I reproduce AI/machine learing papers for drug discovery.
Currently available reproductions for:
- Neural Message Passing for Quantum Chemistry, ICML 2017 · arXiv
- GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders, 2018 · arXiv · Authors' github
- Junction Tree Variational Autoencoder for Molecular Graph Generation, ICML 2018 · arXiv · Authors' github
- DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks (Bioinformatics, 35(18), 3329–3338) · Paper (PubMed Central) · Paper DOI · Authors' github
- DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations · Paper DOI · Authors' github
- MolGAN: An implicit generative model for small molecular graphs · arXiv · Authors' github
In the folder are three notebooks with relevant theory on Deep Learning, Chemistry and Cheminformatics
These Programms and notebooks are run on a GPU/Cuda cluster. The notebook <Environment_Hardware_Check.ipynb> shows the environment and data of the cluster.