Artificial Intelligence and Machine Learning Core for Biomedical Genomics
Official title: Artificial Intelligence and Machine Learning Core
Funded at Oklahoma Medical Research Foundation · NIH-11349616 · Data updated 2026-11-12
A dedicated AI and machine learning core will help researchers use advanced AI methods to analyze high-throughput genomic data and imaging, improving their chances to secure larger grants and advance patient-focused science.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Oklahoma Medical Research Foundation NIH-funded |
| Lab location | 1 site (Oklahoma City, United States) |
| Project start | June 10, 2025 |
| Project end | April 30, 2030 |
| Funding year | 2026 |
| Award (this year) | $177,598 |
| NIH project number | 5P20GM156711-02 |
| Project ID | NIH-11349616 on NIH RePORTER |
Who could benefit from this research
✓Could help
Researchers and clinicians in Oklahoma COBRE who generate high-throughput genomic or imaging data and are seeking to leverage AI/ML in their work.
✕Less likely to help
This core support may not directly benefit individual patients unless their data contribute to the broader projects or tools developed.
What this research studies
The AI/ML Core expands a bioscience support center to provide COBRE researchers with expert AI/ML guidance, specialized computing infrastructure, and tools for genomic and image data analysis. It will help researchers apply state-of-the-art AI methods, including transformers and deep learning, to understand genomic regulation and cytology images. The core will also develop new genomic analysis tools and data integration workflows to make sense of complex data from high-throughput experiments, all within Oklahoma’s genomics community. Researchers will receive hands-on support to implement AI-driven analyses that could accelerate discovery and translation.
Why it matters
Potential benefit: If successful, patients could benefit from faster and more accurate genomic analyses that inform diagnosis, prognosis, and personalized treatment strategies.
How similar studies have gone: Similar AI/ML cores have shown that advanced analytics can speed up data interpretation and tool development in biomedical research.
Where this research is happening
-
Oklahoma Medical Research Foundation
Oklahoma City, United States Active
Researchers
- Principal investigator: Wren, Jonathan Daniel — Oklahoma Medical Research Foundation
- Study coordinator: Wren, Jonathan Daniel
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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.