Trending repositories for topic drug-discovery
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
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
A powerful and flexible machine learning platform for drug discovery
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
A powerful and flexible machine learning platform for drug discovery
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.
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
Mixed continous/categorical flow-matching model for de novo molecule generation.
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
A powerful and flexible machine learning platform for drug discovery
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Mixed continous/categorical flow-matching model for de novo molecule generation.
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
P2Rank: Protein-ligand binding site prediction from protein structure based on machine learning.
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A powerful and flexible machine learning platform for drug discovery
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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.
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
Mixed continous/categorical flow-matching model for de novo molecule generation.
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
NequIP is a code for building E(3)-equivariant interatomic potentials
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
A powerful and flexible machine learning platform for drug discovery
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
[ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
BioNeMo Framework: For building and adapting AI models in drug discovery at scale
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
Mixed continous/categorical flow-matching model for de novo molecule generation.
Single-Cell (Perturbation) Model Library
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
[TMLR 2024] Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
Uncover meaningful structures of latent spaces learned by generative models with flows!
A tool for creating Quantitative Structure Property/Activity Relationship (QSPR/QSAR) models.
Toolkit for open antiviral drug discovery by the ASAP Discovery Consortium
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
An interoperable Python framework for biomolecular simulation.
A powerful cheminformatics and molecule rendering toolbelt for JavaScript, powered by RDKit .
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
Uncover meaningful structures of latent spaces learned by generative models with flows!
All in one Structure-Based Virtual Screening workflow based on the concept of consensus docking.
NVIDIA BioNeMo blueprint for generative AI-based virtual screening
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
Single-Cell (Perturbation) Model Library
[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
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
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
NequIP is a code for building E(3)-equivariant interatomic potentials
Multi-modal Molecule Structure-text Model for Text-based Editing and Retrieval, Nat Mach Intell 2023 (https://www.nature.com/articles/s42256-023-00759-6)
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Therapeutics Commons (TDC-2): Multimodal Foundation for Therapeutic Science
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
A powerful and flexible machine learning platform for drug discovery
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
Python package for graph neural networks in chemistry and biology
Mixed continous/categorical flow-matching model for de novo molecule generation.
Multi-target de novo molecular generator conditioned on AlphaFold's latent protein embeddings.
A tool for creating Quantitative Structure Property/Activity Relationship (QSPR/QSAR) models.
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
This is a curated list of research papers, resources and tools related to using Graph Neural Networks (GNNs) for drug discovery.
TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design
Multi-modal Molecule Structure-text Model for Text-based Editing and Retrieval, Nat Mach Intell 2023 (https://www.nature.com/articles/s42256-023-00759-6)
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Toolkit for open antiviral drug discovery by the ASAP Discovery Consortium
Searching for structural similarities across billions of molecules in milliseconds
rDock is a fast and versatile Open Source docking program that can be used to dock small molecules against proteins and nucleic acids. It is designed for High Throughput Virtual Screening (HTVS) campa...
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
An interoperable Python framework for biomolecular simulation.
DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins
HyperPCM: Robust task-conditioned modeling of drug-target interactions