Find open-source science resources

METPO (Microbial Ecophysiological Trait and Phenotype Ontology) provides standardized terms for describing microbial phenotypes, growth characteristics, and culture conditions. It includes classes for growth media, temperature tolerances, pH tolerances, and relationships like "grows in" and "does not grow in".

First fully customizable open-source multiagent framework automating complete research lifecycle from idea conception to LaTeX papers with dynamic workflows

An ontology that permits the number of in-text citations of a cited source to be recorded, together with their textual citation contexts, along with the number of citations a cited entity has received globally on a particular date.

An ontology meant to define bibliographic records, bibliographic references, and their compilation into bibliographic collections and bibliographic lists, respectively.

An ontology that provides a structured vocabulary written of document components, both structural (e.g., block, inline, paragraph, section, chapter) and rhetorical (e.g., introduction, discussion, acknowledgements, reference list, figure, appendix).

An ontology that enables characterization of the nature or type of citations, both factually and rhetorically.

Pythonic access to FASTA files.

JCVI is a versatile toolkit for comparative genomics analysis. It is a collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

Official Jupyter extension with `%%ai` magic commands and sidebar chat assistant, connecting multiple model providers and local inference

First large vision-language assistant for gigapixel whole-slide pathology image understanding, released with the SlideInstruction dataset and SlideBench benchmark (uni-medical, Apache 2.0, 2025)

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.

Comprehensive collection of 125+ ready-to-use scientific skill modules for Claude AI across bioinformatics, cheminformatics, clinical research, ML, and materials science

Converts Protein Data Bank structures into 3D-printable models. Each polymer chain is meshed separately and written as a named object in a single 3MF file, so a multi-material printer can assign one filament per chain. Protein chains can be rendered as a solvent-excluded surface, a cartoon, or a backbone tube; nucleic acids as a tube-and-rung form with the strands of a duplex welded at every base pair. Press-fit magnet pockets are optionally placed at chain interfaces, so a complex comes apart where its subunits actually meet. All meshes are checked for watertightness before export.

Open-source hybrid scientific research agent and workbench replicating Claude Science, combining JSON tool orchestration with persistent Python/R Code-as-Action kernels, 604 bundled science skills, MCP connectors, sandboxed local execution, and multi-provider LLM support for end-to-end scientific workflows (PKU–YuanKong Intelligence, 377+ stars, MIT License, 2026)

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

Comprehensive Claude Code skill suite covering the full academic pipeline from deep research and paper writing to multi-perspective peer review, revision, and finalization; features multi-agent teams, PRISMA systematic review, style calibration, claim-level citation audits, integrity gates, and human-in-the-loop safeguards (38K+ stars, CC BY-NC 4.0, 2026)

Python library from KIT for training deep learning models on large-sample hydrology, introducing LSTM-based rainfall-runoff modeling that learns universal, regional, and local hydrological behaviors from hundreds of catchments; widely used for streamflow forecasting, flood prediction, and drought research, supporting the CAMELS and Caravan benchmark datasets (581+ stars, BSD-3-Clause, actively maintained)

A molecule manipulation library.

Noodle is a public, read-only web application for semantic discovery and exploration of biomedical literature sourced from PubMed, Europe PMC, and OpenAlex. It accepts natural-language research questions and presents ranked publications together with gene, genetic variant, and phenotype views. Publication pages provide provenance, identifiers, source links, indexed concepts, and navigable semantic-neighbourhood graphs. The companion Noodle Biomedical Literature Discovery MCP exposes the same public discovery domain through a read-only, source-linked Model Context Protocol interface with bounded citation and semantic graph traversal. Semantic proximity, citation distance, co-mention, and search rank are discovery signals and do not establish scientific evidence, causality, diagnosis, or treatment.

SSSOM is a Simple Standard for Sharing Ontological Mappings, providing - a TSV-based representation for ontology term mappings - a comprehensive set of standard metadata elements to describe mappings and - a standard translation between the TSV and the Web Ontology Language (OWL). Most metadata elements, such as "sssom:mapping_justification" are defined in the sssom namespace.

Deep learning software to decode EEG, ECG or MEG signals, providing standardized neural network models, preprocessing pipelines, and evaluation workflows for brain-computer interfaces and cognitive neuroscience research (1.2K+ stars, BSD 3-Clause, actively maintained)

Free-text promptable universal 3D medical image segmentation foundation model enabling zero-shot segmentation of diverse anatomical structures and pathologies via natural language prompts across CT, MRI, and other volumetric imaging modalities (DKFZ, 195+ stars, Apache 2.0)

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)

atomate2 is a library of computational materials science workflows.

RAiSD-AI is a tool for training, testing, and deploying Convolutional Neural Networks to detect selective sweeps in genomic data, extending the functionality of the original RAiSD software with machine learning capabilities. It supports SNP data processing, CNN model training with TensorFlow or PyTorch, and genome-wide selective sweep detection.

AI co-author covering the entire research lifecycle — from an under-specified research direction to a published paper; includes ResearchStudio-Idea for evidence-grounded research ideation and ResearchStudio-Reel for turning finished papers into posters, narrated videos, blogs, and interactive reels; runs as skills on Claude Code and Codex (1.2K+ stars, MIT License, 2026)

RejuvenationKit is an open-source Python toolkit for reproducible auditing and analysis of longitudinal preclinical rejuvenation studies. It provides protocol-aware missingness checks, experimental-confounding diagnostics, attrition and analysis-readiness profiling, covariance-aware multichannel change detection, sequential response monitoring, randomized longitudinal inference, visualization, and integrity-tracked report bundles.

Deep learning with spiking neural networks in Python, providing gradient-based training of SNNs via PyTorch autodifferentiation for brain-inspired computing and neuromorphic research, with online learning capabilities and extensive tutorials (1.9K+ stars, actively maintained)

GAIn is a platform for annotating genetic variants, genomic positions, and regions with reproducible, declarative pipelines using curated Genomic Resource Repositories.

Self-evolving AI scientist with 6 specialized sub-agents (plan/research/code/debug/analyze/write) and persistent memory, #1 on DeepResearch Bench II and AstaBench, supporting multi-provider LLMs and multi-channel deployment (Apache 2.0, 2026)

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)

Markerless pose estimation of user-defined features with deep learning for all animals including humans, enabling quantitative behavioral analysis in neuroscience and ethology (Nature Neuroscience 2018, 5.6K+ stars)

FAIR EVA: Evaluator, Validator & Advisor has been developed to check the FAIRness level of digital objects from different repositories or data portals. It requires the object identifier (preferably persistent and unique identifier) and the repository to check. It also provides a generic and agnostic way to check digital objects. This software started to be developed within IFCA-Advanced-Computing receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 857647.

Accessible protein design platform via Google Colab integrating AlphaFold2, RoseTTAFold, and ProteinMPNN for de novo hallucination, fixed backbone design, and binder design (Sergey Ovchinnikov, 2022+)

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

Diffusion-based generative model for inorganic materials design, steering generation by chemistry, symmetry, bulk modulus, band gap, or magnetic properties, 2× more likely to produce stable novel structures than prior methods, experimentally validated with synthesized TaCr₂O₆ (Microsoft, Nature 2025)

From https://anndata.readthedocs.io/en/latest/ "Python package for handling annotated data matrices in memory and on disk, positioned between pandas and xarray."

Biological simulation tools

Python wrapper for [bedtools](https://github.com/arq5x/bedtools).

High-accuracy RAG for scientific PDFs with citation support, agentic RAG, and contradiction detection

World's first fully open, accelerated weather AI software stack with Medium Range forecasting and Nowcasting models using generative AI (January 2026)

BOLD-Local-DB converts the public TSV/tar.gz data package downloaded from BOLD Systems into a local, indexed SQLite database that can be searched entirely offline. It has two components: a Creator (desktop GUI) that filters, imports, indexes, and optionally adds full-text search to the downloaded data; and a local web viewer for advanced field search, full-text search, batch search by term list, and CSV/FASTA export. Intended for researchers who need to query large BOLD exports (DNA barcode records, taxonomy, collection metadata) repeatedly without depending on an internet connection or BOLD's rate limits.

blue-crab is a tool to convert from ONT POD5 format to the community maintained SLOW5/BLOW5 format. Lossless nanopore pod5 s/blow5 file conversion.

A library containing basis sets for use in quantum chemistry calculations. In addition, this library has functionality for manipulation of basis set data.

Deep learning-based bioacoustic monitoring framework for automated bird species identification from audio recordings, supporting 6,000+ species globally with real-time analysis, batch processing, and API deployment; foundational tool in biodiversity research, conservation biology, and ecological acoustic monitoring (Cornell Lab of Ornithology, 1.5K+ stars, MIT License)

Fast, interactive, multi-dimensional image viewer for Python, foundational platform for scientific imaging AI with a rich plugin ecosystem integrating deep learning segmentation, object tracking, and microscopy analysis workflows (2.6K+ stars)

Apache 2.0 single-cell foundation model family scaling to 3B parameters, pretrained on 266M cell profiles including perturbation data and released with training, embedding, and downstream benchmarking workflows for disease-relevant single-cell tasks (2025)

End-to-end autonomous AI research engine that turns an idea into a complete LaTeX paper by dispatching real computational experiments to local GPUs or SLURM clusters, collecting actual results, generating figures/tables, and writing a data-grounded manuscript rather than LLM hallucinations (OpenRaiser, 1.5K+ stars, MIT License, 2026)

Autonomous ML experimentation for biomedical data.