Discovering disease pathways using advanced molecular network analysis
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-11011412 · Data updated 2026-11-12
This study is looking at how proteins related to certain diseases work together in the body, using smart computer techniques to better understand these connections, which could help create more effective treatments for patients.
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 | 2025 |
| Award (this year) | $378,714 |
| NIH project number | 1R35GM156653-01 |
| Project ID | NIH-11011412 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with specific cancers or cardiovascular diseases who are interested in understanding the molecular basis of their conditions.
✕Less likely to help
Patients with diseases not related to the focus areas of this research, such as rare genetic disorders or non-cancerous conditions, may not receive direct benefits.
What this research studies
This research investigates how different molecular components interact to reveal insights into diseases, particularly focusing on how proteins related to specific diseases form complex networks. By utilizing advanced techniques like graph neural networks, the study aims to identify and connect these molecular pathways that are often fragmented and tissue-specific. The approach combines deep learning with Bayesian analysis to enhance the understanding of disease mechanisms and their connections across various tissues, potentially leading to better-targeted therapies.
Why it matters
Potential benefit: If successful, this research could lead to more effective treatments by uncovering the underlying pathways of diseases, particularly cancers and cardiovascular disorders.
How similar studies have gone: Other research has shown promise in using graph neural networks for molecular pathway discovery, indicating that this approach could yield significant insights.
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.