Deep learning tools for understanding human genetics from big DNA data
Official title: Deep learning for population genetics
Funded at University of Oregon · NIH-11396326 · Data updated 2026-11-12
A research team is using advanced computer learning to read very large human genome datasets and uncover patterns in population genetics.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Oregon NIH-funded |
| Lab location | 1 site (Eugene, United States) |
| Project start | April 21, 2020 |
| Project end | June 30, 2029 |
| Funding year | 2026 |
| Award (this year) | $703,509 |
| NIH project number | 5R01HG010774-06 |
| Project ID | NIH-11396326 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals whose genetic data are or could be part of biobank-scale studies may benefit from improved methods, tools, and interpretations.
✕Less likely to help
Direct patient benefit may be limited to those whose data contribute to biobank resources and to eventual clinical translation.
What this research studies
This project will develop and apply deep learning methods to whole-genome data from biobanks to reveal how genetic variation shapes populations. By combining modern neural networks with population-genetic theory, the team aims to extract meaningful signals from massive DNA sequences without relying only on traditional statistics. The work builds on prior advances in deep learning and genomic analysis to improve our understanding of human genetic diversity and history. Results could guide future studies and help interpret genetic information related to health and disease.
Why it matters
Potential benefit: If successful, this work could improve how we analyze large genetic datasets, potentially informing personalized medicine and our understanding of disease risk across populations.
How similar studies have gone: Previous work shows deep learning can improve interpretation of genetic data, supporting the potential for meaningful advances in this area.
Where this research is happening
-
University of Oregon
Eugene, United States Active
Researchers
- Principal investigator: Kern, Andrew D — University of Oregon
- Study coordinator: Kern, Andrew D
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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.