State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
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Updated
Aug 12, 2024 - Jupyter Notebook
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
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
Protein Graph Library
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Python package for graph neural networks in chemistry and biology
Working with molecular structures in pandas DataFrames
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
NequIP is a code for building E(3)-equivariant interatomic potentials
A deep learning framework for molecular docking
[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
Molecular Processing Made Easy.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Interaction Fingerprints for protein-ligand complexes and more
Deep Reinforcement Learning for de-novo Drug Design
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