Find open-source science resources

DeepMind's graph neural network for materials exploration, discovering 2.2M new crystal structures (380K most stable) equivalent to 800 years of traditional research, with 520K+ materials dataset open-sourced (Nature 2023)

Cross-domain foundation model for continuum dynamics trained on 19 physical scenarios spanning 63 variables, featuring adaptive compute via stride modulation and patch jittering for long-run stability (Polymathic AI, 293+ stars, MIT License)

Bring the power and flexibility of AnnData to the R ecosystem, allowing you to effortlessly manipulate and analyse your single-cell data. This package lets you work with backed h5ad and zarr files, directly access various slots (e.g. X, obs, var), or convert the data into SingleCellExperiment and Seurat objects.

Molecular dynamics analysis

Cheminformatics toolkit

Benchmark evaluating AI agents for end-to-end automated research from re-discovery to new-discovery, with 40 real-science tasks across 10 disciplines, curated datasets from published papers, and expert-curated multimodal rubrics (170+ stars, MIT License)

MCP server, CLI, and agent skills for searching and downloading academic papers from multiple open sources (arXiv, PubMed, bioRxiv, Semantic Scholar, OpenAlex, CORE, Europe PMC, etc.) with unified, deduplicated, LLM-friendly retrieval and an OA-first download fallback chain (OpenAGS, 1.9K+ stars, MIT License, 2025)

Create MSP files containing the isotopic patterns for given molecules with given adducts. The tool is based on enviPat and the RforMassSpectrometry toolbox.

Community-driven model zoo and deployment infrastructure for AI-powered bioimage analysis, enabling standardized sharing, validation, and cross-platform execution of deep learning models across Fiji, Ilastik, napari, and other scientific imaging tools (EPFL, EMBL, and global collaborators, actively maintained)

Curated library of 550+ medical research agent skills spanning evidence insights, protocol design, omics/clinical data analysis, and academic writing; each skill is reviewed through MedSkillAudit and compatible with Claude Code, Codex, Open Code, OpenClaw, and SKILL.md-compatible agents (AIPOCH, 1.2K+ stars, MIT License, 2026)

Unified interface for local, global, gradient-based and derivative-free optimization (800+ stars)

High-accuracy PDF→Markdown/JSON/HTML conversion, specialized for tables/formulas/code blocks with benchmark scripts

STADyUM is a package with functionality for analyzing nascent RNA read counts to infer transcription rates. This includes utilities for processing experimental nascent RNA read counts as well as for simulating PRO-seq data. Rates such as initiation, pause release and landing pad occupancy are estimated from either synthetic or experimental data. There are also options for varying pause sites and including steric hindrance of initiation in the model.

Analysis of molecular dynamics trajectories.

OEO is a domain reference ontology for energy system modeling.

Deep learning library for Chemistry based on Tensorflow

Bioschemas aims to improve the Findability on the Web of life sciences resources such as datasets, software, and training materials. It does this by encouraging people in the life sciences to use Schema.org markup in their websites so that they are indexable by search engines and other services. Bioschemas encourages the consistent use of markup to ease the consumption of the contained markup across many sites. This structured information then makes it easier to discover, collate, and analyse distributed resources. [from BioSchemas.org]

Scalable toolkit for analyzing single-cell gene expression data, including preprocessing, visualization, clustering, and trajectory inference.

Research coding benchmark curated by scientists with 338 subproblems across 16 subdomains (physics, math, materials, biology, chemistry), evaluating LLMs on realistic scientific programming tasks with gold-standard solutions (NeurIPS 2024)

Unified Python framework for extracellular electrophysiology, standardizing interfaces to 10+ ML-based spike sorting algorithms including Kilosort for reproducible neural spike sorting workflows (792+ stars, actively maintained)

A Python package for protein dynamics analysis

An Apache-based persistent URL (PURL) service

Py-HLA-Match is a Python library for standardised, rule-based HLA (Human Leukocyte Antigen) matching in retrospective analyses, method development, benchmarking, and in-silico studies in immunogenetics and related fields.

The information resource registry is a listing of data sources present in the NCATS Data Translator system. Each information resource has an identifier, a short description, and a URL to more information about that resource.

A quality control tool for high throughput sequence data.

NFDI-MatWerk aims to establish a digital infrastructure for Materials Science and Engineering (MSE), fostering improved data sharing and collaboration. This repository provides comprehensive documentation for NFDI MatWerk Ontology (MWO) v3.0.0, a foundational framework designed to structure research data and enhance interoperability within the MSE community. To ensure compliance with top-level ontology standards, MWO v3.0.0 is aligned with the Basic Formal Ontology (BFO) and incorporates the modular approach of the NFDIcore mid-level ontology, enriching metadata through standardized classes and properties. The mwo addresses key aspects of MSE research data, including the NFDI-MatWerk community structure, covering task areas, infrastructure use cases, projects, researchers, and organizations. It also describes essential NFDI resources, such as software, workflows, ontologies, publications, datasets, metadata schemas, instruments, facilities, and educational materials. Additionally, mwo represents NFDI-MatWerk services, academic events, courses, and international collaborations. As the foundation for the MSE Knowledge Graph, mwo facilitates efficient data integration and retrieval, promoting collaboration and knowledge representation across MSE domains. This digital transformation enhances data discoverability, reusability, and accelerates scientific exchange, innovation, and discoveries by optimizing research data management and accessibility. (from repository)

This is the Provenance Information for Materials Science (PRIMA) Ontology, version 3.0, aligned with PMDco v3 and based on BFO (Basic Formal Ontology). This complete module imports all PRIMA modules (core, data-analysis-lifecycle, dataset, experiment, and computational) in their v3.0 versions. [from https://purls.helmholtz-metadaten.de/prima/complete]

Open source PEM (Proton Exchange Membrane) fuel cell simulation tool.

103B-parameter open-source medical language model with 1/32 Mixture-of-Experts architecture, achieving HealthBench-leading performance among open-source models with only 6.1B active parameters; jointly developed by Ant Group and Zhejiang Province Health Information Center (MIT License)

Rust implementations of algorithms and data structures useful for bioinformatics.

A Molecular Interaction-Guided Graph Learning Framework for Multi-Omics Cancer Classification

A package for working with nuclear magnetic resonance (NMR) data including functions for reading common binary file formats and processing NMR data.

Python package for segmenting geospatial data with the Segment Anything Model (SAM), enabling zero-shot object segmentation in satellite and aerial imagery for remote sensing and Earth observation (MIT, 4k+ stars)

AlphaFold/ESMFold accessible implementation with AF3 JSON export, database updates

This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports.

Co-create PowerPoint presentations with Generative AI from documents or topics

PyTorch domain library for geospatial deep learning providing standardized datasets, samplers, transforms, and pre-trained models for remote sensing, land cover mapping, and environmental monitoring (Microsoft, 4K+ stars)

Aggregate results from bioinformatics analyses across many samples into a single report.

A vocabulary used in tandem with SHACL for representing node shapes

The DCAT-AP conversion to a LinkML Schema is the intended point of truth for the DCAT-AP+ schema, but could be used alternatively as a LinkML representation of DCAT-AP for other Projects. It is a port of DCAT-AP to the LinkML world that is as faithful to the original as possible. This Persistent Identifier does not only provide the SHACL Shape, but could also be used as described [here](https://github.com/perma-id/w3id.org/tree/cecbc2e5f40d928f05ed5306d24fc60db0e7bb21/nfdi-de/dcat-ap-plus). DCAT-AP+ is a [LinkML](https://linkml.io/)-based extension of the [DCAT Application Profile 3.0](https://semiceu.github.io/DCAT-AP/releases/3.0.0/) that adds a provenance layer for describing how a dataset was generated and what it is about, using the [Starting Point Terms of PROV-O](https://www.w3.org/TR/prov-o/#description-starting-point-terms), the [QUDT ontology](https://www.qudt.org/), and [Dublin Core Terms](http://purl.org/dc/terms/).

Package to analyze transcription factor enrichment in a gene set using data from ChIP-Seq experiments.

AI-powered note linking and research graph navigation

Parallel computing with task scheduling.

Scalable genomic analysis.

DenoIST identifies and removes contamination in Image-based Spatial Transcriptomics data, using a transposed poisson mixture model with local neighbourhood offsets to infer genes that are likely to be due to neighbourhood contamination rather than endogenous expression.

bambu is a R package for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis such as differential gene expression or transcript usage.

Arc Institute's 40B-parameter genome foundation model trained on 9 trillion nucleotides from all domains of life, supporting 1M base pair context for generalist DNA/RNA/protein prediction and design (Nature 2026)

Graph neural network library for PyTorch enabling molecular modeling, materials discovery, protein interaction networks, and scientific knowledge graph learning (23.7k+ stars)

Low- and high-level wrappers for Gemma's RESTful API. They enable access to curated expression and differential expression data from over 10,000 published studies. Gemma is a web site, database and a set of tools for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles.