Awesome Cytodata Overview

A curated list of awesome cytodata resources https://www.cytodata.org/awesome-cytodata/

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🔬 Awesome CytoData

Awesome CytoData is a website that collects research papers, software, and datasets related to image-based profiling in one place.

🌟 Purpose

Image-based profiling (often done using the Cell Painting assay) produces large amounts of complex data from microscopy images. As the field grows, it gets harder to keep track of important papers, tools, and datasets.

This project aims to:

• Centralize Knowledge: Provide a "one-stop shop" for foundational and state-of-the-art research.
• Lower Entry Barriers: Help new researchers navigate "Influential Papers" selected by the community.
• Promote Open Science: Highlight publicly available datasets and open-source pipelines.
• Standardize Discovery: Offer a professional, searchable index for DOIs and software repositories.

🚀 Key Features

📚 The Literature Corpus

• Advanced Search: Real-time fuzzy searching via Fuse.js across titles, authors, journals, and abstracts.
• Author Formatting: Scientific citation style (Lastname, F. et al.) for professional scanning.
• Filtering: Sort by year, category (Methods, Biology, Reviews, etc.), or influential status.
• Direct Access: One-click DOI links to publisher pages.

💾 Dataset Index

• A curated table of massive public releases like the Cell Painting Gallery, JUMP-CP, and RxRx.
• Filterable by description and reference paper.

🛠️ Software Directory

• Catalog of community-standard tools including CellProfiler, DeepProfiler, and PyCytominer.
• Categorized by purpose (Feature Extraction, Data Engineering, etc.).

🛠️ Technical Architecture

This application is built as a serverless, static web app optimized for GitHub Pages:

• Frontend: React 19+ (ESM-based via CDN for zero-install development).
• Styling: Tailwind CSS for a clean, academic aesthetic.
• Search Engine: Fuse.js for client-side fuzzy indexing of JSON data.
• Data Layer: Flat JSON files in /data/ acting as a "Local Database" for easy community contributions.
• Deployment: Automated GitHub Actions workflow for validation and hosting.

🤝 Contributing

We want your input! If you have a new paper, a dataset release, or a software tool:

1. Read the CONTRIBUTING.md guide.
2. Run python3 scripts/add_resource.py paper or python3 scripts/add_resource.py dataset to add your entry (or edit the JSON files in public/data/ by hand).
3. Open a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Maintained by the CytoData Community. Join the conversation at cytodata.org.