Find open-source science resources
A directory of tools, AI models, datasets, and research resources for biotech, bioinformatics, and other scientific fields. Aggregated from curated GitHub awesome-lists, HuggingFace, bio.tools, Bioconductor, and more.
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87 of 5,923 resources
Showing 51–87
Simple RDKit molecule editor GUI using PySide.
Descriptor computation(chemistry) and (optional) storage for machine learning.
Molecular property prediction with unified API for diverse models and respresentations,
A python package for optimizing chemical reactions using machine learning (contains 10 algorithms + several benchmarks).
NIST's open-source platform for data-driven atomistic materials design, integrating DFT datasets (JARVIS-DFT), machine learning property prediction (JARVIS-ML), and a comprehensive leaderboard for benchmarking materials AI methods across the periodic table (384+ stars)
PyTorch toolkit for deep neural networks in atomistic simulations, implementing SchNet, DimeNet++, PaiNN, and GemNet for molecular dynamics and quantum chemistry (900+ stars)
Crystal property prediction
AstraZeneca's industrial-grade retrosynthetic planning tool using MCTS to recursively decompose molecules into purchasable precursors, with multi-step route scoring and support for custom one-step models (v4.0, 2024)
End-to-end molecular dynamics engine built on PyTorch, enabling differentiable simulations with neural network potentials and GPU acceleration for machine learning-accelerated molecular dynamics (MIT License, 707+ stars)
Ensemble of automated QM workflows that can be run through jupyter notebooks, command lines and yaml files.
A Python program to compute quasi-harmonic thermochemical data from Gaussian frequency calculations.
Calculate mass, elemental composition, and mass distribution spectrum of a molecule given by its chemical formula, relative element weights, or sequence.
A toolkit for visualizations in materials informatics.
A library for processing, analyzing and modeling spectroscopic data.
Library of descriptors to aid in the data-mining of materials properties, created by the Lawrence Berkeley National Laboratory.
Aims to provide useful high-level interfaces that make ML for materials science as easy as possible.
Library for fast calculations of **mo**lecula**r** **fe**at**u**re**s** from 3D structures for machine learning with a focus on steric descriptors.
Ensemble of automated machine learning protocols that can be run sequentially through a single command line. The program works for regression and classification problems.
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation.
Library with several compositional and structural material descriptors, along with a few pre-trained neural network models of material properties.
A benchmarking platform for molecular generation models.
Makes alchemical free energy calculations easier by leveraging the full power and flexibility of the PyData stack.
A tool and library for creating quantum chemistry input files.
A package to 'build' collections of materials properties from the output of computational materials calculations.
The "FRamewOrk for Molecular AGgregate Excitations" enables localised QM/QM' excited state calculations in a solid state environment.
High-Throughput Molecular Dynamics: Programming Environment for Molecular Discovery.
Open source PEM (Proton Exchange Membrane) fuel cell simulation tool.
A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.
Python Library for Automating Molecular Simulation: input preparation, job execution, file management, output processing and building data workflows.
Usage-Instructions) - A program to visualize reaction networks.
An open, extensible Python framework for GPU-accelerated alchemical free energy calculations.
Convert AMBER forcefields from ANTECHAMBER to GROMACS format.
A Chemical Knowledge Graph and Toolkit, writting in IUPAC/SMILES/SMARTS, for common small molecules from diverse communities to aid users in selecting compounds for forcefield parametirization.
A benchmark for ML-guided high-throughput materials discovery.
A [Jupyter](https://jupyter.org/) widget to interactively view molecular structures and trajectories.
High-throughput PubChem client for batch queries with caching, validation, rate-limit-aware retries, and a simple CLI.
Scientific Computing for Chemists with Python is a Jupyter book teaching basic python in chemistry skills, including relevant libraries, and applies them to solving chemical problems.