Find open-source science resources

Open-source image analysis toolkit for high-throughput plant phenotyping, extracting morphological, color, and texture traits from RGB, hyperspectral, and thermal imagery with modular Python workflows for crop improvement, stress detection, and plant biology research (Donald Danforth Plant Science Center, 795+ stars, MPL-2.0)

Standard data-centric AI package for data quality and machine learning, automatically detecting label errors, outliers, and dataset issues to improve scientific dataset reliability and model performance (11K+ stars, MIT License)

First versatile medical reasoning agent for chest X-ray interpretation, dynamically integrating state-of-the-art CXR analysis tools and multimodal LLMs into a unified framework; introduces ChestAgentBench with 2,500 complex medical queries across 7 categories (bowang-lab, 1.1K+ stars)

ekokrati computes habitat connectivity metrics (PC, IIC, EC(PC), dPC and its decomposition into intra-patch, flux and connector components) for habitat patch networks. Users upload polygon data as GeoPackage or shapefile, set species-specific dispersal parameters, and receive patch importance scores and landscape-level indices. Designed for conservation planners, landscape ecologists and environmental consultants. No installation required.

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)

End-to-end composable multi-agent framework for automating OpenFOAM-based CFD simulations from natural language prompts, managing meshing, case setup, execution, error correction, and post-processing; achieves 100% success rate on 110 FoamBench tasks with Claude Opus 4.6 through Architect-Input Writer-Runner-Reviewer agent collaboration with RAG-enhanced generation and MCP tool integration (RPI CSML, 242+ stars, MIT License)

AI scientist framework for autonomous deep research in biological sciences, combining literature analysis agents with data scientist agents to enable iterative scientific discovery through user feedback integration; achieves state-of-the-art performance on BixBench benchmark (48.78% open-answer, 64.39% multiple-choice) outperforming Kepler and GPT-5 (bio-xyz, arXiv 2601.12542, 160+ stars, 2025-2026)

Verbex is a private, on-device Voice-to-ELN iOS app for scientists. It helps researchers capture experiment notes by voice as work happens, organize those notes into scientific sections, and prepare clean, reviewable, ELN-ready scientific records.

Full spaCy pipeline and models for scientific/biomedical documents, enabling named entity recognition, abbreviation resolution, and UMLS linking for scientific literature mining (1.9K+ stars, Apache 2.0)

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)

Universal foundation model for grounded biomedical image interpretation, enabling comprehensive visual understanding, reasoning, and grounding across diverse biomedical imaging modalities with strong zero-shot generalization (55+ stars, Apache 2.0, 2025-2026)

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)

Open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives, enabling quantum algorithm development for quantum chemistry, materials science, and optimization research (IBM, 7.4K+ stars, Apache 2.0)

MITObim - mitochondrial baiting and iterative mapping

First fully autonomous open-ended scientific discovery system with official implementation: hypothesis→experiment→writing→review simulation (13.8K+ stars, 2024)

Decentralized self-organizing teams of AI agents for long-running computational scientific experimentation; agents critique each other's proposals before spending compute and share successes/failures to avoid redundant exploration, achieving +8.33% on BioML-Bench, 1.9× faster nanoGPT optimization, and +12.5% on ProteinGym ACE2-Spike (425+ stars, 2026)

First real quadrotor robot trained end-to-end with differentiable physics for vision-based agile flight, bridging simulation-based learning and real-world deployment with physics-informed neural network controllers (558+ stars)

The MetaProteomeAnalyzer Cloud (MPA Cloud) is an intuitive, open-source tool for metaproteomics data analysis and interpretation, designed to analyse comprehensive metaproteomics data from tandem mass spectrometry experiments through a web interface.

A comprehensive R package for identifying and ranking influential nodes in biological and other complex networks. The package implements the Integrated Value of Influence (IVI), Experimental data-based Integrative Ranking (ExIR), SIRIR, and numerous network centrality measures, enabling network topology analysis, influential node detection, feature prioritization, and candidate biomarker discovery. It also provides functions for network reconstruction, centrality assessment, visualization, and analysis of relationships between centrality measures.