Find open-source science resources

Machine learning interatomic potentials

A collection of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and transport processes.

Local-first, open-source AI workbench for scientists — an open alternative to Claude Science (by ai4s-research, maintainers of this list; TypeScript, MIT, 2026)

Toolkit for large-scale whole-slide image processing supporting 22+ patch encoders (UNI, CONCH, Virchow, H-Optimus-0, etc.), slide encoders (TITAN, GigaPath, PRISM, CHIEF, Madeleine, Feather), tissue segmentation, and multi-GPU inference with end-to-end pipeline and smart resume for standardized deployment of computational pathology foundation models (Mahmood Lab, Harvard Medical School, 553+ stars)

98B-parameter frontier generative model jointly reasoning over protein sequence, structure, and function, trained on 2.78 billion proteins; generated a novel fluorescent protein (esmGFP) with only 58% sequence identity to known GFPs (EvolutionaryScale, 2024)

Directed message passing neural networks for property prediction of molecules and reactions with uncertainty and interpretation.

Machine learning model predicting cellular perturbation response across diverse contexts with State Transition (ST) and State Embedding (SE) variants, featuring CLI tooling, PyPI distribution, and Virtual Cell Challenge integration (575+ stars)

High-Throughput Molecular Dynamics: Programming Environment for Molecular Discovery.

Probabilistic programming

Julia differential equations suite

Curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines, enabling reproducible social science research with AI agents (Stanford REAP & CoPaper.AI, 1.1K+ stars, 2026)

Python Library for Automating Molecular Simulation: input preparation, job execution, file management, output processing and building data workflows.

First open-source agentic AI physicist turning research questions into structured workflows with rigorous verification and multi-step analytical work for long-horizon physics projects; integrates with Claude Code, Codex, Gemini CLI, and OpenCode (804+ stars, Apache 2.0, 2026)

Turn any AI agent into a life science expert with NVIDIA BioNeMo skills, enabling agentic workflows for drug discovery, protein engineering, and biomolecular design (329+ stars, Apache 2.0 / CC-BY-4.0, 2026)

Foundation model for tabular data that predicts on unseen real-world tables in a single forward pass, achieving accurate small-data classification and regression without task-specific training; widely applicable to scientific datasets with limited samples (7.4K+ stars, 2022-2026)

Machine learning in Julia

Molecular dynamics analysis

A Python package for protein dynamics analysis

AI-powered note linking and research graph navigation

Official MathWorks toolkit connecting AI agents to MATLAB via the MATLAB MCP Server and curated skills, enabling trusted engineering and scientific computing workflows with idiomatic code generation, testing, and error diagnosis in Claude Code, GitHub Copilot, OpenAI Codex, and Gemini CLI (686+ stars, BSD-3-Clause, 2026)

Meta's comprehensive ML ecosystem for materials/chemistry with 118M+ DFT calculations, EquiformerV2 models achieving top Matbench Discovery performance

A library for processing, analyzing and modeling spectroscopic data.

Acausal modeling framework for automatically parallelized scientific machine learning (1.5k+ stars)

SPAdes (St. Petersburg genome assembler) is an assembly toolkit containing various assembly pipelines and the de-facto standard for prokaryotic genome assemblies.

A package to 'build' collections of materials properties from the output of computational materials calculations.

Library of descriptors to aid in the data-mining of materials properties, created by the Lawrence Berkeley National Laboratory.

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.

Python Materials Genomics: robust materials analysis library defining classes for structures and molecules with support for many electronic structure codes; foundational toolkit powering the Materials Project (Berkeley Lab, 1.8K+ stars)

Microsoft's foundation model for the Earth system supporting weather, air pollution, and ocean wave forecasting at multiple resolutions, trained on 1M+ hours of diverse atmospheric data (Nature 2025)

Meta FAIR's foundation model of vision, audition, and language for in-silico neuroscience, predicting fMRI brain responses to naturalistic multimodal stimuli (video, audio, text) through unified Transformer architecture mapped to the cortical surface (2026)

Sparse identification of nonlinear dynamics

Chemical reaction network and systems biology interface for scientific machine learning (SciML), enabling high-performance, GPU-parallelized simulation and analysis of complex biochemical systems with O(1) solvers (SciML, 518+ stars, Julia)

Differentiable tokamak core transport simulator for fusion energy research, coupling PDE solvers with JAX auto-differentiation and neural-network surrogates for fast forward modelling, pulse-design, and trajectory optimization (Google DeepMind, Apache 2.0)

A swiss army knife for manipulating and editing PDB files.

PyTorch toolkit for deep neural networks in atomistic simulations, implementing SchNet, DimeNet++, PaiNN, and GemNet for molecular dynamics and quantum chemistry (900+ stars)

Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the [Open Bioinformatics Foundation](http://open-bio.org/). Contains the very useful [Entrez](https://biopython.org/DIST/docs/api/Bio.Entrez-module.html) package for API access to the NCBI databases.

This package provides a periodic table of the elements with support for mass, density and xray/neutron scattering information.

Diffusion MR imaging.

Latent-space probabilistic denoising diffusion model for predicting coarse-grained conformational ensembles of intrinsically disordered proteins and regions from sequence, with GPU/CPU inference, trajectory export, and FAISS-based similarity search (67+ stars, LGPL-3.0)

A molecule manipulation library.

A compressor of common genomic file formats (BAM, CRAM, FASTQ, VCF etc).

Physics-informed neural networks in Julia

samtools/bcftools are a suite of tools for manipulating NGS data and can be used to call variants.

Neuro-imaging file formats.

dadi is a bioinformatics tool for inferring demographic history and selection from genetic data using diffusion approximations, offering speed and flexibility in modeling population dynamics. It supports up to three populations with customizable parameters and provides efficient computational performance.

atomate2 is a library of computational materials science workflows.

The package provides `rlang` data masks for the SummarizedExperiment class. The enables the evaluation of unquoted expression in different contexts of the SummarizedExperiment object with optional access to other contexts. The goal for `plyxp` is for evaluation to feel like a data.frame object without ever needing to unwind to a rectangular data.frame.

Simulations of spiking neural networks.

SOTA multimodal document parsing with 1.2B parameters outperforming GPT-4o, converts PDFs to LLM-ready Markdown/JSON

Learnable latent embeddings for joint behavioral and neural analysis, enabling consistent and interpretable mapping of neural activity to behavior across modalities, species, and experiments (EPFL & Harvard, 1K+ stars)