Graph-tools for uncovering redundant genetic pathways in cancer biology
Official title: DMS/NIGMS 2: Building and Testing a Graph Theory Toolbox for Uncovering Redundant Pathways in Genetic Interaction Networks
Funded at Tufts University Medford · NIH-11406268 · Data updated 2026-11-12
A research team will build new graph-based methods to map how genes work together in cancer-related networks, helping predict what happens when genes are turned off or stressed.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Tufts University Medford NIH-funded |
| Lab location | 1 site (Boston, UNITED STATES) |
| Project start | September 1, 2025 |
| Project end | August 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $310,149 |
| NIH project number | 5R01GM163241-02 |
| Project ID | NIH-11406268 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with cancers whose progression involves complex genetic interactions may eventually benefit from insights derived from this research.
✕Less likely to help
Patients with cancers not driven by the studied genetic interaction networks may see limited direct benefit.
What this research studies
This project develops a formal graph-theory framework to study redundancy and fault tolerance in genetic interaction networks. Using diffusion-based, low-dimensional embeddings, the team will identify compensatory pathways and generate phenotype predictions for unseen gene knockouts or environmental conditions. The work combines computational modeling with biological data from cancer-relevant genes to reveal how cells might adapt to disruptions. The goal is to uncover mechanisms that could inform future cancer therapies by targeting robust gene networks.
Why it matters
Potential benefit: If successful, patients may benefit from better understanding of redundant gene pathways that sustain cancer cell survival, guiding future therapeutic strategies.
How similar studies have gone: Previous work shows that graph-based analyses can reveal meaningful gene modules, but this project aims to extend methods to fine-scale redundancy in genetic interaction networks.
Where this research is happening
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Tufts University Medford
Boston, United States Active
Researchers
- Principal investigator: Cowen, Lenore Jennifer — Tufts University Medford
- Study coordinator: Cowen, Lenore Jennifer
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.