drug-discovery
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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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Aug 12, 2024 - Jupyter Notebook
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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Mar 19, 2025 - Python
Message Passing Neural Networks for Molecule Property Prediction
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Mar 13, 2025 - Python
A powerful and flexible machine learning platform for drug discovery
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Aug 12, 2024 - Python
Protein Graph Library
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Mar 3, 2025 - Jupyter Notebook
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
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Feb 17, 2025 - Jupyter Notebook
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
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Jun 10, 2024 - Jupyter Notebook
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
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Jul 8, 2024 - Python
Python package for graph neural networks in chemistry and biology
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Nov 1, 2023 - Python
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
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Sep 11, 2023 - Python
Working with molecular structures in pandas DataFrames
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Aug 1, 2024 - Python
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
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Nov 26, 2023 - Python
NequIP is a code for building E(3)-equivariant interatomic potentials
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Feb 20, 2025 - Python
A deep learning framework for molecular docking
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Mar 4, 2025 - C++
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
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Jun 17, 2023
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
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Feb 19, 2025 - Python
Molecular Processing Made Easy.
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Jun 10, 2024 - Python
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
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Mar 20, 2025
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
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Mar 11, 2025 - Python
Interaction Fingerprints for protein-ligand complexes and more
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Mar 14, 2025 - Python
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