EquiBind
DiffSBDD
EquiBind | DiffSBDD | |
---|---|---|
2 | 1 | |
452 | 290 | |
- | - | |
0.0 | 4.9 | |
about 1 year ago | 8 months ago | |
Python | Python | |
MIT License | MIT License |
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EquiBind
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[R] EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
Github: https://github.com/HannesStark/EquiBind
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MIT Researchers Develop EquiBind: A Geometric Deep Learning Model That Becomes The Fastest Computational Molecular Docking Models
Continue reading | Checkout the paper, github link
DiffSBDD
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Learn diffusion models with Hugging Face course 🧨
I'm referring to recent works like DiffLinker (https://github.com/igashov/DiffLinker) and DiffSBDD (https://github.com/arneschneuing/diffsbdd) which use diffusion to generate new ligands or fragments of molecules. If there's enough interest, we could find space to include these exciting topics in the course :)
What are some alternatives?
DiffLinker - DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
OpenChem - OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
pypdb - A Python API for the RCSB Protein Data Bank (PDB)
minimal-text-diffusion - A minimal implementation of diffusion models for text generation
DeepInteract - A geometric deep learning pipeline for predicting protein interface contacts. (ICLR 2022)
equidock_public - EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
DDPM_inversion - Official pytorch implementation of the paper: "An Edit Friendly DDPM Noise Space: Inversion and Manipulations". CVPR 2024.
DenoisingDiffusionProbabilityModel-ddpm- - This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.
anomaly-detection-resources - Anomaly detection related books, papers, videos, and toolboxes