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Search results for deep learning drug discovery
deep-learning
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drug-discovery
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55 search results found
Deeplearningexamples
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12,073
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Deepchem
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4,876
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Torchdrug
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1,297
A powerful and flexible machine learning platform for drug discovery
Graphein
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932
Protein Graph Library
Tdc
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889
Therapeutics Data Commons: Artificial Intelligence Foundation for Therapeutic Science
Deeppurpose
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826
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
Chemicalx
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657
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
Dgl Lifesci
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558
Python package for graph neural networks in chemistry and biology
Nequip
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478
NequIP is a code for building E(3)-equivariant interatomic potentials
Openchem
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450
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Release
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232
Deep Reinforcement Learning for de-novo Drug Design
Ligan
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206
Deep generative models of 3D grids for structure-based drug discovery
Allegro
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169
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
Reinvent4
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150
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Chemml
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142
ChemML is a machine learning and informatics program suite for the chemical and materials sciences.
Bidd Molmap
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125
MolMapNet: An Efficient ConvNet with Knowledge-based Molecular Represenations for Molecular Deep Learning
Deeplytough
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115
DeeplyTough: Learning Structural Comparison of Protein Binding Sites
Chemgan Challenge
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113
Code for the paper: ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.
Awesome Molecular Docking
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85
We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.
Deepscreen
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85
DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images
Equidock_public
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81
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
Drugex
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74
De Novo Drug Design with RNNs and Transformers
Transformercpi
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71
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
Dd_protocol
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67
Official repository for the Deep Docking protocol
Mxmnet
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66
Source code for "Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures"
Awesome Deep Learning 4 Life Sciences
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65
A collection of resources for Deep Learning in Python for Life Sciences (with focus on biotech and pharma).
Litmatter
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55
Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.
Selformer
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55
SELFormer: Molecular Representation Learning via SELFIES Language Models
Awesome Denovo Papers
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53
Awesome De novo drugs design papers
Py4chemoinformatics
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53
Python for chemoinformatics
Moldqn Pytorch
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40
A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
Gnina Torch
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33
🔥 PyTorch implementation of GNINA scoring function for molecular docking
Druggen
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31
Official implementation of DrugGEN
Drug Drug Interaction Prediction
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30
Drug-Drug Interaction Prediction Based on Knowledge Graph Embeddings and Convolutional-LSTM Network
Hyper Dti
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29
HyperPCM: a HyperNetwork approach to drug-target interaction (DTI) prediction.
Ai Bind
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27
Interpretable AI pipeline improving binding predictions for novel protein targets and ligands
Paccmann_rl
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20
Code pipeline for the PaccMann^RL in iScience: https://www.cell.com/iscience/fulltext/S2589-0042(
Molecular Vae
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19
Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"
Ai Bind
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18
Interpretable AI pipeline improving binding predictions for novel protein targets and ligands
Pharmaconet
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14
Official Github for "PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling" (NeurIPS 2023 Workshop)
Paccmann_chemistry
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11
Generative models of chemical data for PaccMann^RL
2021 Icyp Mfe
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10
Source code and data of the paper entitled "iCYP-MFE: Identifying Human Cytochrome P450 Inhibitors using Multi-task Learning and Molecular Fingerprint-embedded Encoding"
Paccmann_sarscov2
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9
Code for paper on automation of discovery and synthesis of targeted molecules: https://iopscience.iop.org/article/10.1088/2632-21
Diffusion Hopping
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9
DiffHopp: A Graph Diffusion Model for Novel Drug Design via Scaffold Hopping
Deep Purpose Tutorial
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9
Repository for the HackBio'2021 Internship for Team Drug-Development-A
Pocket2drug
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9
Pytorch implementation of Pocket2Drug: a generative deep learning model to predict binding drugs for ligand-binding sites.
Toxinpred2
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8
An improved method for predicting toxicity of proteins
Awesome Drug Discovery
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8
A collection of drug discovery, classification and representation learning papers with deep learning.
Awesome Ml For Biochemistry
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8
Community-curated resources for research at the intersection of AI and molecular sciences
Awesome Gnn Based Drug Discovery
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8
This is a curated list of resources and tools related to using Graph Neural Networks (GNNs) for drug discovery.
Bifusion
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7
Prtm
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7
Deep learning for protein science
Mldd23
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7
The repository for the course "Machine Learning in Drug Design" taught at the Jagiellonian University in 2023. The page is hosted by the machine learning research group GMUM.
Molkgnn
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6
MolKGNN is a deep learning model for predicting biological activity or molecular properties. It features in 1. SE(3)-invariance 2. conformation-invariance 3. interpretability. MolKGNN uses a novel molecular convolution to leverage the similarity of molecular neighborhood and kernels. It shows superior results in realistic drug discovery datasets.
Pocket Cfdm
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6
Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets
2020 Dili Cnn Mfe
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5
Source code and data of the paper entitled "Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features"
Aimlinker
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5
Fragment Linker Prediction Using Deep Encoder-Decoder Network for PROTAC Drug Design
Aidd Codebase
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5
Public version of the AIDD consortium code base
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