Training and prediction scripts for Chemprop models trained on ADMET datasets

Repository for storing the source files of the new interface documentation. https://chembl.gitbook.io/chembl-interface-documentation/

Datasets used in the tox21 challenge

Deep Learning package for Python

Summaries of machine learning papers

Large-scale comparison of machine learning methods for drug target prediction on ChEMBL

Comparison of active site and full kinase sequences for drug-target affinity prediction and molecular generation. Full paper: https://pubs.acs.org/doi/10.1021/acs.jcim.1c00889

Refined and extended version of ChemTS

Analysis scripts for the IDG-DREAM Drug Kinase Binding Prediction Challenge

Programmatic interface to Synapse services for Python

DL models to test added value of using generated complex data for affinity prediction

Protein kinase-ligand complex generation using template docking

This is the source code of large-scale bi-directional generative adversarial network (BigBiGAN) for deep learning semantic feature extraction.

MMGX: Multiple Molecular Graph eXplainable Discovery

Graph neural networks for molecular machine learning. Implemented and compatible with TensorFlow and Keras.

Molecular Property Prediction via LSTM and BiLSTM

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.

Graph Neural Network

FraGAT: a fragment-oriented multi-scale graph attention model for molecular property prediction

This repository implements MAGCN

PyTorch implementation of M-GCN: Brain-inspired Memory Graph Convolutional Network for Multi-Label Image Recognition (Neural Computing and Applications 2021.11)

Multi-View Graph Convolutional Network for Multimedia Recommendation

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)