Statistics for topic drug-discovery
RepositoryStats tracks 651,542 Github repositories, of these 133 are tagged with the drug-discovery topic. The most common primary language for repositories using this topic is Python (77). Other languages include: Jupyter Notebook (27)
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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.
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
NequIP is a code for building E(3)-equivariant interatomic potentials
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
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
An interoperable Python framework for biomolecular simulation.
Single-Cell (Perturbation) Model Library
Implementation of DiffDock-Pocket: Diffusion for Pocket-Level Docking with Side Chain Flexibility
An interoperable Python framework for biomolecular simulation.
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
This repo contains the codes for our paper Conditional Antibody Design as 3D Equivariant Graph Translation.
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
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Single-Cell (Perturbation) Model Library
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
Implementation of DiffDock-Pocket: Diffusion for Pocket-Level Docking with Side Chain Flexibility
The official repository for the book "Machine Learning for Drug Discovery" (Manning Publications)
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025 oral]
[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
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
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025 oral]
Implementation for ICML 2024 paper "MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space"
Codebase and CLI for PLAPT: A state-of-the-art protein-ligand binding affinity model for drug discovery
All in one Structure-Based Virtual Screening workflow based on the concept of consensus docking.