Find open-source science resources
Cross-domain directory aggregating tools, AI models, datasets, and research resources from bio.tools, Bioconductor, HuggingFace, curated GitHub awesome-lists, and more.
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45 of 5,674 resources
Deep learning library for Chemistry based on Tensorflow
A Python package for protein dynamics analysis
OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend.
The eiR package provides utilities for accelerated structure similarity searching of very large small molecule data sets using an embedding and indexing approach.
A curated list of molecular docking software, datasets, and other closely related resources.
A list of papers, data sets, and other resources for machine learning for small-molecule drug discovery.
Another list focuses on Python stuff related to Chemistry.
Chemoinformatics and drug discovery section in deeplearning-biology repo.
A teaching platform for computer-aided drug design (CADD) using open source packages and data.
an automated workflow for the generation and storage of DFT calculations for organic molecules.
Python-centric Cookiecutter for Molecular Computational Chemistry Packages by [MolSSL](https://molssi.org/)
Parsers and algorithms for computational chemistry logfiles.
Analysis of molecular dynamics trajectories.
Automates and standardizes ligand preparation for AutoDock Vina.
Open source web framework for small molecule analysis based on Django.
[RDKit](http://www.rdkit.org/) and [OSRA](https://cactus.nci.nih.gov/osra/) in the [Bottle](http://bottlepy.org/docs/dev/) on [Tornado](http://www.tornadoweb.org/en/stable/).
A python package for optimizing chemical reactions using machine learning (contains 10 algorithms + several benchmarks).
A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models in R.
A Library for Deep Learning in Biology and Chemistry.
DGL-LifeSci is a [DGL](https://www.dgl.ai/)-based package for various applications in life science with graph neural network.
Molecular property prediction with unified API for diverse models and respresentations,
ChemML is a machine learning and informatics program suite for the analysis, mining, and modeling of chemical and materials data. (based on Tensorflow)
Directed message passing neural networks for property prediction of molecules and reactions with uncertainty and interpretation.
Vector representations of molecular substructures.
Descriptor computation(chemistry) and (optional) storage for machine learning.
Molecular descriptor calculator based on [RDKit](http://www.rdkit.org/).
Simple RDKit molecule editor GUI using PySide.
Chemical 2D structure editor application/applet based on the [Chemistry Development Kit](https://sourceforge.net/projects/cdk/).
An object-oriented, webGL based JavaScript library for online molecular visualization.
A swiss army knife for manipulating and editing PDB files.
A script to run structural alerts using the RDKit and ChEMBL
Molecule validation and standardization based on [RDKit](http://www.rdkit.org/).
Tool designed to provide a simple way of standardising molecules as a prelude to e.g. molecular modelling exercises.
Toolkit for processing molecules, reactions and condensed graphs of reactions. Can be used for chemical standardization, MCS search, tautomers generation with backward compatibility to RDKit and NetworkX.
- Molecular Manipulation Made Easy. A light wrapper build on top of RDKit.
A graph-based molecule modeling and chemoinformatics analysis toolkit fully implemented in Julia
A Python package useful for chemistry (mainly physical/inorganic/analytical chemistry)
Universal molecular toolkit that can be used for molecular fingerprinting, substructure search, and molecular visualization written in C++ package, with Java, C#, and Python wrappers.
Virtual machine with all software and sample data to run 3D-e-Chem Knime workflows