Popular GitHub Repositories for Drug Combination

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database?.

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Message Passing Neural Networks for Molecule Property Prediction

A powerful and flexible machine learning platform for drug discovery

List of Molecular and Material design using Generative AI and Deep Learning

Python package for graph neural networks in chemistry and biology

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

A knowledge graph and a set of tools for drug repurposing

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

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

bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.

A Euclidean diffusion model for structure-based drug design.

Deep Reinforcement Learning for de-novo Drug Design

Original implementation of the paper "SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery" by Shion Honda et al.

Machine learning games. Use combination of genetic algorithms and neural networks to control the behaviour of in-game objects.

[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs