Using AI to decode human genetic variation

Deep learning for population genetics

['FUNDING_R01'] · UNIVERSITY OF OREGON · NIH-11223828

This project uses AI to find patterns in very large human genetic datasets to help researchers and people with inherited conditions better understand how genes vary across populations.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF OREGON (nih funded)
Locations1 site (EUGENE, UNITED STATES)
Trial IDNIH-11223828 on ClinicalTrials.gov

What this research studies

Researchers are training deep neural networks on whole-genome data from large biobanks so the models can learn useful signals directly from DNA alignments instead of relying only on hand-crafted summaries. They will develop, train, and validate these models using a mix of simulated genomes and real human sequencing data to ensure accuracy and scalability. The team aims to scale methods to biobank-sized datasets to reveal population history, selection, and genetic structure that may relate to health. As a data contributor, your de-identified genome could help improve tools that researchers use to study genetic influences on disease.

Who could benefit from this research

Good fit: Ideal candidates are people who have or are willing to share whole-genome sequence data through participating biobanks or research repositories.

Not a fit: People without available genomic data or those seeking immediate clinical treatment are unlikely to receive direct benefit from this computational methods project.

Why it matters

Potential benefit: If successful, this could help researchers discover genetic patterns linked to health and improve genetic risk tools that eventually inform care for people with inherited conditions.

How similar studies have performed: Related AI approaches have shown promise for genomic tasks, but applying deep learning at population-scale whole-genome inference is still relatively new and being actively tested.

Where this research is happening

EUGENE, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.