Project Themes:
- Virtual AI Co-scientist
Team Lead(s):
- Name: Arvind Ramanathan
- Affiliation: Argonne National Laboratory
- Email: [To be added]
Suggested Team Members and Roles [4-6 members]
| Name | Affiliation | Role / Expertise |
|---|---|---|
| Arvind Ramanathan | Argonne National Laboratory | Principal Investigator, AI Systems Architect |
| Ozan | Argonne National Laboratory | RAG and Data Integration Specialist |
| BV-BRC Developers | - | Model integration and deployment |
| CEPI Scientists | - | Use-case definition and validation |
Project Summary
This project extends the open-source Co-Scientist framework (https://github.com/acadev/Jnana) to build reasoning agents for protein function prediction, using CEPI and BV-BRC datasets as testbeds. The goal is to enable hypothesis-driven dialogue and AI-assisted exploration of uncharacterized genes and proteins relevant to priority pathogens.
Goals and Objectives
- Goal 1: Deploy Co-Scientist framework in the BV-BRC environment
- Goal 2: Implement a reasoning module for protein function prediction using multi-modal evidence (sequence, structure, literature)
- Goal 3: Demonstrate AI-guided hypothesis generation for uncharacterized genes in one pathogen model
Approach
The Co-Scientist framework will use an agentic reasoning loop combining retrieval (via HiPerRAG), synthesis (via Rhea), and hypothesis refinement through dialogue. The system will be trained on BV-BRC pathogen data and evaluated for its interpretability and accuracy in protein function annotation.
Data and Resources Required
| Resource Type | Source / Link | Description / Purpose |
|---|---|---|
| Data | BV-BRC genomes, CEPI curated datasets | Training and evaluation data |
| Tools / Services | Jnana (Co-Scientist GitHub repo) | Agentic reasoning system |
| LLMs / AI Models | GPT-4, Claude 3 | Reasoning and synthesis agents |
| Compute / Storage | Argonne HPC | Experimentation environment |
Expected Outcomes / Deliverables
Prototype AI Co-Scientist agent capable of hypothesis-driven protein function prediction and reasoning trace visualization.
Potential Impact and Next Steps
This project showcases autonomous scientific reasoning and interactive discovery for infectious disease research. It will help CEPI and BV-BRC develop transparent, AI-assisted research workflows and foster a foundation for broader agentic science platforms.
Technical Support Needed
- GPU / LLM access
- Mentor support
- API keys
Additional Comments