PSI-AI

Advancing AI-readiness of Public Proteomics Data

Mission

The PSI AI-readiness working group bridges the gap between public proteomics data and the use of artificial intelligence. We focus on making proteomics data AI-ready while standardizing AI workflows that generate new data through community standards and reproducible pipelines.

Key Objectives

📊 Data Accessibility
Enhance metadata annotation for AI discoverability

🔄 Harmonize Raw Data Formats
Convert to open formats (mzML, mzPeak)

⚡ Streamlined Data Reprocessing
Lightweight ML-ready data processing workflows

🎯 Benchmark Resources
Curated datasets and methods for AI development

📋 Best Practices
Ethical and effective reproducibility standards

🤝 Community Standards
AI model frameworks and HUPO-PSI integration


About This Resource

This site serves as the dynamic hub for PSI-AI working group outputs, including:

📚 Living Documentation
Guidelines and standards that evolve with the field

📋 Best Practice Guides
Crowd-sourced recommendations

🔗 Curated Links
Community-curated resources and tools

Everyone can contribute!

Whether through commenting, writing documentation, sharing resources, or joining working groups - this platform thrives on community participation.

Get Involved

🤝 Contribute content

  • Submit documentation
  • Share best practices
  • Review community submissions
  • Provide feedback

💬 Join discussions

  • Comment on proposals
  • Attend community calls
  • Participate in the working group task forces
  • Share project experiences

Ways to Participate

  • Working Group Charter - Learn about our mission and structure
  • Community Surveys - Help shape priorities and direction
  • Collaborative Writing - Co-author documentation and guidelines
  • Resource Sharing - Contribute tools, datasets, and workflows
  • Peer Review - Help validate and improve community contributions
Note

Ready to Start? Join our efforts to make proteomics data more accessible and useful for the AI/ML community. Every contribution, no matter how small, helps advance the field.