A system to recommend features for discovering disease mechanisms efficiently
Official title: DMS/NIGMS 2: A Stability Driven Recommendation System for Efficient Disease Mechanistic Discovery
Funded at University of California Berkeley · NIH-10933563 · Data updated 2026-11-12
This study is working on a smarter way to find genes that might cause heart diseases, using a two-step method to suggest and then test these genes, so doctors can better understand and treat these conditions without wasting time or money.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Berkeley NIH-funded |
| Lab location | 1 site (Berkeley, United States) |
| Project start | September 25, 2023 |
| Project end | June 30, 2027 |
| Funding year | 2024 |
| Award (this year) | $271,288 |
| NIH project number | 5R01GM152718-02 |
| Project ID | NIH-10933563 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with genetic predispositions to cardiac diseases or disorders.
✕Less likely to help
Patients with non-genetic cardiac issues or those not affected by cardiac diseases may not benefit from this research.
What this research studies
This research focuses on improving the process of identifying biological features that contribute to diseases, particularly cardiac disorders. It employs a two-step approach where statistical analyses first recommend candidate genes for further investigation, followed by experiments to validate these findings. The goal is to create a recommendation system that minimizes costs and maximizes the efficiency of experiments by using advanced decision tree methodologies. By addressing challenges such as heritability gaps and the need for more informative features, this research aims to enhance the applicability of genetic associations in clinical settings.
Why it matters
Potential benefit: If successful, this research could lead to more effective treatments for cardiac diseases by uncovering critical biological mechanisms.
How similar studies have gone: Other research has shown promise in using decision tree methodologies for genetic studies, indicating potential success for this novel approach.
Where this research is happening
-
University of California Berkeley
Berkeley, United States Active
Researchers
- Principal investigator: Yu, Bin — University of California Berkeley
- Study coordinator: Yu, Bin
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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.