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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176 of 6,590 resources
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Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling.
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)
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)
Machine learning interatomic potentials
Directed message passing neural networks for property prediction of molecules and reactions with uncertainty and interpretation.
Local-first, open-source AI workbench for scientists — an open alternative to Claude Science (by ai4s-research, maintainers of this list; TypeScript, MIT, 2026)
Julia differential equations suite
An object-oriented, webGL based JavaScript library for online molecular visualization.
A small language for defining pipeline stages and linking them together to make pipelines.
OpenTFRaw is a standalone, cross-platform reader for Thermo Fisher Scientific .raw mass-spectrometry files, implemented in pure Rust with no dependency on vendor DLLs or .NET. Python bindings built on PyO3 return NumPy arrays for spectral data, straightforward to load into Pandas or Polars. Covers format versions 8 through 66 (LCQ Classic through Orbitrap Astral and modern TSQ instruments), supporting both centroid and profile spectra.
OpenWRaw is a standalone, cross-platform reader for Waters MassLynx .raw acquisition directories, implemented in pure Rust with no dependency on vendor DLLs. Python bindings built on PyO3 expose functions, scans, and ion-mobility data as native Python objects from Waters QTof and SYNAPT instrument families, ready to be assembled into a Pandas or Polars DataFrame.
OpenTimsTDF is a standalone, cross-platform reader for Bruker timsTOF .tdf and .tdf_bin acquisition files, implemented in pure Rust with no dependency on vendor SDKs. Python bindings built on PyO3 expose frame, scan, and peak data as native Python objects, providing ion-mobility-aware access that can be assembled into a Pandas or Polars DataFrame.
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)
High-Throughput Molecular Dynamics: Programming Environment for Molecular Discovery.
First bioinformatics-native AI agent skill library enabling local-first, reproducible genomic and population-genetics research workflows built on OpenClaw (871+ stars, MIT License, 2026)
A Python package for protein dynamics analysis
A collection of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and transport processes.
Machine learning in Julia
Molecular dynamics analysis
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)
Human-centered research OS with terminal-first harness and local browser Studio, turning research work into reproducible artifact-backed runs through a 9-stage workflow with human approval gates, resume/rollback controls, and venue-aware manuscript packaging (1K+ stars, 2026)
Python Library for Automating Molecular Simulation: input preparation, job execution, file management, output processing and building data workflows.
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)
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)
PyTorch-based differentiable programming framework for physics-informed system identification, parametric constrained optimization, and model predictive control, integrating neural operators, neural ODEs, KANs, SINDy, and differentiable predictive control with 30+ tutorials (1.3k+ stars, BSD License)
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.
Agent skill for AI-assisted scientific manuscript writing review distilled from Stanford's *Writing in the Sciences* course, performing five sequential editorial audit passes on clarity, voice, structure, consistency, and integrity (2026)
AI-powered note linking and research graph navigation
PyTorch toolkit for deep neural networks in atomistic simulations, implementing SchNet, DimeNet++, PaiNN, and GemNet for molecular dynamics and quantum chemistry (900+ stars)
A vocabulary used in tandem with SHACL for representing node shapes
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'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)
A Python script that converts positional information from a SAM dataset into interval format with 0-based start and 1-based end. CIGAR string of SAM format is used to compute the end coordinate.
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.
Non-invasive decoding of typed sentences from MEG and EEG brain recordings using a convolutional encoder, transformer, and character-level language model; official code for the Nature Neuroscience paper and Meta blog post on brain-AI communication (Meta FAIR, 894+ stars, CC BY-NC 4.0, 2026)
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)
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.
Biological vision foundation model trained on TreeOfLife-200M, yielding extraordinary accuracy on diverse biological visual tasks including habitat classification and trait prediction despite a narrow training objective (Ohio State University Imageomics Institute)
197 bioinformatics and life science skills for Claude Code and AI agents, achieving 92.0% accuracy on BixBench. Covers RNA-seq, single-cell analysis, drug discovery, proteomics, and more. Powers OmicsHorizon (195+ stars, 2026)
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)
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)
Use this database to browse the CMECS classification and to get definitions for individual CMECS Units. This database contains the units that were published in the Coastal and Marine Ecological Classification Standard.