Repository Index

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

• machine-learning
• generative-models
• drug-discovery
• benchmark

A knowledge graph and a set of tools for drug repurposing

• drug-repurposing
• knowledge-graph
• graph-neural-networks
• knowledge-graph-embeddings

A Euclidean diffusion model for structure-based drug design.

• ddpm
• drug-design
• equivariance
• generative-model

Deep Reinforcement Learning for de-novo Drug Design

• deeplearning
• reinforcement-learning
• cheminformatics
• molecular-modeling

The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)

• ai-for-science
• diffusion-models
• drug-design
• equivariant-networks

Source code for "DeepDTA: deep drug-target binding affinity prediction"

• protein-ligand-interactions
• convolutional-neural-networks

MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)

A Network Integration Approach for Drug-Target Interaction Prediction

LLM for Drug Editing, ICLR 2024

• chatgpt
• conversation
• drug
• drug-discovery

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

• disentanglement
• drug-discovery
• genomics
• perturbation

TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524

• self-attention
• compound-protein-interaction
• transformercpi
• structure-free-virtual-sreening

Interpretable bilinear attention network with domain adaptation improves drug-target prediction.

NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions

• computational-biology
• bioinformatics
• graph-convolution
• deep-learning

Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.

• alphafold3
• docking
• drug-design
• drug-discovery

Exploring the space of drug combinations to discover synergistic drugs using Active Learning

PyTorch implementation of "TGSA: Protein-Protein Association-Based Twin Graph Neural Networks for Drug Response Prediction with Similarity Augmentation"

Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).

• deep-reinforcement-learning
• generative-model
• vae
• molecule-generation

Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.

GNN-based gene-selection deep learning model for drug response prediction