New technology for detecting how proteins bind to DNA
Official title: Collaborative Research: DMS/NIGMS 2: Novel machine-learning framework for AFMscanner in DNA-protein interaction detection
Funded at University of Georgia · NIH-10932280 · Data updated 2026-11-12
This study is working on a new way to use special imaging technology to see how proteins called transcription factors attach to DNA, which could help us better understand gene regulation and its role in diseases.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Georgia NIH-funded |
| Lab location | 1 site (Athens, United States) |
| Project start | September 21, 2023 |
| Project end | August 31, 2027 |
| Funding year | 2024 |
| Award (this year) | $304,500 |
| NIH project number | 5R01GM152814-02 |
| Project ID | NIH-10932280 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with genetic disorders or cancers related to gene regulation.
✕Less likely to help
Patients with conditions unrelated to DNA-protein interactions or gene regulation may not benefit from this research.
What this research studies
This research focuses on developing a novel imaging method using atomic force microscopy (AFM) to detect and quantify how transcription factors (TFs) bind to DNA. By integrating advanced mathematical and statistical techniques with bioengineering, the project aims to create a fully automated system for precise imaging of these interactions. This innovative approach seeks to overcome limitations of traditional methods by enhancing image resolution and automating the search for binding sites. The ultimate goal is to improve our understanding of gene regulation and its implications for various diseases.
Why it matters
Potential benefit: If successful, this research could lead to breakthroughs in understanding gene regulation, potentially impacting treatments for genetic disorders and cancers.
How similar studies have gone: While the integration of machine learning with AFM for DNA-protein interaction detection is a novel approach, similar methodologies in other areas of molecular biology have shown promising results.
Where this research is happening
-
University of Georgia
Athens, United States Active
Researchers
- Principal investigator: Zhong, Wenxuan — University of Georgia
- Study coordinator: Zhong, Wenxuan
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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.