Large-scale Disease Pathway Discovery with Tissue-Specific Networks
Official title: Large-scale Disease Pathway Discovery by Integrating Tissue-specific Molecular Networks via Hierarchical Bayesian Inference on Graph Neural Networks
Funded at Rochester Institute of Technology · NIH-11336338 · Data updated 2026-11-12
A big research project will use advanced computer methods to map how disease-related proteins connect in tissue-specific networks to better understand disease mechanisms.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rochester Institute of Technology NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project start | June 1, 2025 |
| Project end | May 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $353,810 |
| NIH project number | 5R35GM156653-02 |
| Project ID | NIH-11336338 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not applicable to patients directly; the study informs understanding of human disease mechanisms that could later impact patient care.
✕Less likely to help
Direct benefits to patients may not be immediate; it's a foundational computational study.
What this research studies
This project uses graph neural networks and Bayesian methods to integrate tissue-specific molecular networks and uncover pathways linked to diseases. It focuses on how proteins assemble into disconnected or tissue-specific modules and how to connect these modules to explain genotype-phenotype relationships. The approach aims to reveal topological patterns in disease networks that standard methods may miss, providing a more nuanced view of disease biology. The work blends deep learning with probabilistic reasoning to improve the discovery of disease pathways across tissues.
Why it matters
Potential benefit: If successful, this research could lead to clearer maps of disease pathways, guiding future diagnostics and targeted treatments.
How similar studies have gone: Previous similarly framed network-based approaches have shown promise in identifying disease-related modules, though tissue-specific integration remains challenging.
Where this research is happening
-
Rochester Institute of Technology
Rochester, United States Active
Researchers
- Principal investigator: Li, Rui — Rochester Institute of Technology
- Study coordinator: Li, Rui
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.