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acgcn

ACGCN: Graph Convolutional Networks for Activity Cliff Prediction Between Matched Molecular Pairs (Park et al., 2022)

actriplet

automd

Fast to molecular dynamics simulation.

bidd-clsar

Contrastive learning of structure-activity relationship

contrastive-learning-with-hard-negative-samples

ICLR 2021, Contrastive Learning with Hard Negative Samples

contrastive-ring-public

PyTorch implementation for " Conditional Negative Sampling for Contrastive Learning of Visual Representations" (https://arxiv.org/abs/2010.02037).

deepcoy

drug-target-prediction

equibind

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

gclmf

GCLmf: A novel molecular graph contrastive learning framework based on hard negatives and application in toxicity prediction

gem

gpd

Graphormer Based Protein Sequence Design

graph-contrastive-learning

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

graphsol

Code of our JC paper: "Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map"

hgdrug

instructbio

Tsinghua University

large-scale_acprediction

This repository stores data and scripts used in Large-Scale Prediction of Activity Cliffs Using Machine and Deep Learning Methods of Increasing Complexity.

minn-dti

Effective drug-target interaction prediction with mutual interaction neural network

mixcse_aaai2022

Code for AAAI 2022 paper Unsupervised Sentence Representation via Contrastive Learning with Mixing Negatives

molclr_graph-contrastive-learning

Implementation of "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyTorch Geometric

multiobj-rationale

Multi-Objective Molecule Generation using Interpretable Substructures (ICML 2020)

neuralplexer

NeuralPLexer: State-specific protein-ligand complex structure prediction with a multi-scale deep generative model

polypharmacy-side-effect-prediction

Polypharmacy Side effect Prediction with Enhanced Interpretability Based on Graph Feature Attention Net-work

pygcl

PyGCL: A PyTorch Library for Graph Contrastive Learning

qsar-activity-cliff-experiments

rdkit_summary

rdkit总结与实践

reinvent

reinventcommunity

sa-ddi

scaffoldgvae

ScaffoldGVAE: A Variational Autoencoder Based on Multi-View Graph Neural Networks for Scaffold Generation and Scaffold Hopping of Drug Molecules