Understanding how proteins affect insulin production using advanced computer techniques
Official title: Unmasking conditional dependencies of proteins influencing islet biology using machine learning
Funded at University of Wisconsin-Madison · NIH-11031114 · Data updated 2026-11-12
This study is looking at how certain proteins in the pancreas affect insulin release, which is important for managing diabetes, and it uses advanced computer techniques to find out how these proteins work together, hoping to discover new ways to help people with diabetes.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Wisconsin-Madison NIH-funded |
| Lab location | 1 site (Madison, United States) |
| Project start | December 5, 2024 |
| Project end | November 30, 2028 |
| Funding year | 2025 |
| Award (this year) | $160,584 |
| NIH project number | 1K01DK141909-01 |
| Project ID | NIH-11031114 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with diabetes or those at high risk for developing diabetes.
✕Less likely to help
Patients who do not have diabetes or are not at risk for diabetes may not receive direct benefits from this research.
What this research studies
This research investigates the complex relationships between proteins that influence insulin secretion in the pancreas, particularly focusing on islet cells. By utilizing machine learning methods, the study aims to uncover hidden dependencies among these proteins that could affect their function. The research will analyze data from both mouse models and human samples to develop predictive models that can identify how specific proteins, like transketolase, impact insulin secretion. Patients may benefit from insights gained about these proteins, potentially leading to new therapeutic targets for diabetes management.
Why it matters
Potential benefit: If successful, this research could lead to new strategies for improving insulin secretion in diabetes patients.
How similar studies have gone: Previous research using machine learning to analyze protein interactions has shown promise in identifying new therapeutic targets, suggesting this approach could be effective.
Where this research is happening
-
University of Wisconsin-Madison
Madison, United States Active
Researchers
- Principal investigator: Emfinger, Christopher — University of Wisconsin-Madison
- Study coordinator: Emfinger, Christopher
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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.