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Search results for python drug discovery

drug-discovery x

96 search results found

Deepchem ⭐ 4,876

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Chemprop ⭐ 1,405

Message Passing Neural Networks for Molecule Property Prediction

Torchdrug ⭐ 1,297

A powerful and flexible machine learning platform for drug discovery

Graphein ⭐ 932

Protein Graph Library

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

Chemicalx ⭐ 657

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

Dgl Lifesci ⭐ 558

Python package for graph neural networks in chemistry and biology

NequIP is a code for building E(3)-equivariant interatomic potentials

Openchem ⭐ 450

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research

Datamol ⭐ 423

Molecular Processing Made Easy.

Equibind ⭐ 321

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Moleculekit ⭐ 183

MoleculeKit: Your favorite molecule manipulation kit

Allegro ⭐ 169

Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials

Ersilia ⭐ 161

The Ersilia Model Hub, a repository of AI/ML models for infectious and neglected disease research.

An open, extensible Python framework for GPU-accelerated alchemical free energy calculations.

Reinvent4 ⭐ 150

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

ChemML is a machine learning and informatics program suite for the chemical and materials sciences.

Fragmenstein ⭐ 139

Merging, linking and placing compounds by stitching bound compounds together like a reanimated corpse

Drug Computing ⭐ 131

Educational materials for, and related to, UC Irvine's Drug Discovery Computing Techniques course (PharmSci 175/275), currently taught by David Mobley.

Deeplytough ⭐ 115

DeeplyTough: Learning Structural Comparison of Protein Binding Sites

Chatdrug ⭐ 96

LLM for Drug Editing, ICLR 2024

Moleculestm ⭐ 81

Multi-modal Molecule Structure-text Model for Text-based Editing and Retrieval, Nat Mach Intell 2023 (https://www.nature.com/articles/s42256-023-00759-

Deepaffinity ⭐ 80

Protein-compound affinity prediction through unified RNN-CNN

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

Deep Drug Coder ⭐ 75

A tensorflow.keras generative neural network for de novo drug design, published in Nature Machine Intelligence while working at AstraZeneca.

Transformercpi ⭐ 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

Code for the paper Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language

Dd_protocol ⭐ 67

Official repository for the Deep Docking protocol

Typedb Bio ⭐ 67

TypeDB Bio: Biomedical Knowledge Graph

Source code for "Molecular Mechanics-Driven Graph Neural Network with Multiplex Graph for Molecular Structures"

Awesome Deep Learning 4 Life Sciences ⭐ 65

A collection of resources for Deep Learning in Python for Life Sciences (with focus on biotech and pharma).

DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins

PyTrial: A Comprehensive Platform for Artificial Intelligence for Drug Development

Py4chemoinformatics ⭐ 53

Python for chemoinformatics

Biosimspace ⭐ 48

An interoperable Python framework for biomolecular simulation.

Reinforced Genetic Algorithm ⭐ 46

Structure-based Drug Design; Reinforcement Learning and Genetic Algorithm

Quantum Computing Exploration For Drug Discovery On Aws ⭐ 45

Deploy a solution to research on drug discovery problems using quantum computing and classical computing resources.

Matcher is a tool for understanding how chemical structure optimization problems have been solved. Matcher enables deep control over searching structure/activity relationships (SAR) derived from large datasets, and takes the form of an accessible web application with simple deployment. Matcher is built around the mmpdb platform.

RxDock is a fork of rDock. Note: the latest code is under development. Please do git checkout patched-rdock after clone if you want patched rDock. [IMPORTANT NOTE: pull requests should be posted on GitLab, this is a read-only source code mirror]

Moldqn Pytorch ⭐ 40

A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".

Geometric Latent Diffusion Models for 3D Molecule Generation

Ligdream ⭐ 34

Novel molecules from a reference shape!

Gnina Torch ⭐ 33

🔥 PyTorch implementation of GNINA scoring function for molecular docking

An integrated negative design python library for desirable HTS/VS database design

This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)

Official implementation of DrugGEN

Protwis is the backbone of the GPCRdb. The GPCRdb contains reference data, interactive visualisation and experiment design tools for G protein-coupled receptors (GPCRs).

Computational Analysis of Novel Drug Opportunities

Hyper Dti ⭐ 29

HyperPCM: a HyperNetwork approach to drug-target interaction (DTI) prediction.

Kgem In Drug Discovery ⭐ 26

Code to accompany the "Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery" manuscript (Artificial Intelligence in the Life Sciences, 2022)

Gflownet ⭐ 25

A PyTorch implementation of a Generative Flow Network (GFlowNet) proposed by Bengio et al. (2021)

Synthetic lethality (SL) is a promising gold mine for the discovery of anti-cancer drug targets. KG4SL is the first graph neural network (GNN)-based model that uses knowledge graph for SL prediction.

TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design

Pyplif Hippos ⭐ 22

HIPPOS Is PyPLIF On Steroids. A Molecular Interaction Fingerprinting Tool for Docking Results of Autodock Vina and PLANTS

(differentiable) gradient-based optimization on a chemical graph for de novo molecule design/optimization (ICLR 2022)

Reinvent Randomized ⭐ 20

Recurrent Neural Network using randomized SMILES strings to generate molecules

Calibrated Boosting Forest ⭐ 19

Original implementation of Calibrated Boosting-Forest

Extracting Patients' information from clinical notes and export them to an OMOP CDM database.

Molecular Vae ⭐ 19

Pytorch implementation of the paper "Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules"

Drug2ways ⭐ 18

A Python package for drug discovery by analyzing causal paths on multiscale networks

Screenlamp ⭐ 18

screenlamp is a Python toolkit for hypothesis-driven virtual screening

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization (AAAI 21')

Chemprop ⭐ 16

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Enrich_omics ⭐ 15

A python package to explore pathways, diseases and drugs associated to a list of targets (genes, proteins, etc)

CORE: Automatic Molecule Optimization using Copy & Refine Strategy (AAAI 2020)

Pharmaconet ⭐ 14

Official Github for "PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling" (NeurIPS 2023 Workshop)

Drug-Drug Interaction Predicting by Neural Network Using Integrated Similarity

Assaytools ⭐ 14

Modeling and Bayesian analysis of fluorescence and absorbance assays.

Gentropy ⭐ 13

Open Targets python framework for post-GWAS analysis

Cbh21 Protein Solubility Challenge ⭐ 13

Template with code & dataset for the "Structural basis for solubility in protein expression systems" challenge at the Copenhagen Bioinformatics Hackathon 2021.

A simplified drug discovery pipeline -- generating SMILE molecular with AlphaSMILES, predicting protein structure with AlphaFold, and checking the druggability with fpocket/Amber.

Probabilistic Inference for NOvel Therapeutics

Egfr Att ⭐ 12

Drug effect prediction using neural network

Drug_named_entity_recognition ⭐ 11

Paccmann_chemistry ⭐ 11

Generative models of chemical data for PaccMann^RL

Canceromicsnet ⭐ 10

A Graph Neural Network Model for prediction of the effectiveness of a drug on a given cancer cell lines

2021 Icyp Mfe ⭐ 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"

Diffusion Hopping ⭐ 9

DiffHopp: A Graph Diffusion Model for Novel Drug Design via Scaffold Hopping

Source code and data files for "PEMT: A patent enrichment tool with applicability in drug discovery"

Dose response curves and DIP rates for cell proliferation data in Python

Pocket2drug ⭐ 9

Pytorch implementation of Pocket2Drug: a generative deep learning model to predict binding drugs for ligand-binding sites.

Deepdrugdomain ⭐ 8

DeepDrugDomain: A versatile Python toolkit for streamlined preprocessing and accurate prediction of drug-target interactions and binding affinities, leveraging deep learning for advancing computational drug discovery.

Pele_platform ⭐ 8

Wrap up Platform to launch all PELE features. [AdaptivePELE, MSM, LigandGrowing, Glide Rescoring]

Registry Factory ⭐ 8

An abstract implementation of the registry design pattern proposed in (Hartog et. al., 2023). Provides a factory for registries that dynamically organize modular functionalities.

Deep learning for protein science

Thunor Web ⭐ 7

Web app for high throughput cell proliferation data

Paccmann_generator ⭐ 6

Generative models for transcriptomic-driven or protein-driven molecular design (PaccMann^RL).

Uqbio2023 ⭐ 6

3rd Annual Undergraduate Quantitative Biology (UQ-bio) Summer School

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.

PiLSL is a pairwise interaction learning-based graph neural network (GNN) model for prediction of synthetic lethality (SL) as anti-cancer drug targets. It learns the representation of pairwise interaction between two genes from a knowledge graph (KG).

Pocket Cfdm ⭐ 6

Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets

2020 Dili Cnn Mfe ⭐ 5

Source code and data of the paper entitled "Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features"

Insilicoq ⭐ 5

Quantum Computing and Machine Learning for Drug Design and Proteins Engineering

Este repositorio debe ser el punto de partida y encuentro para cualquier investigador o estudiante que quiera comenzar a trabajar con/en la UIBCDF. Si has caído aquí por otro motivo y este material te es útil, eres más que bienvenido a usarlo e interaccionar con nosotros.

Aidd Codebase ⭐ 5

Public version of the AIDD consortium code base

Aimlinker ⭐ 5

Fragment Linker Prediction Using Deep Encoder-Decoder Network for PROTAC Drug Design

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