AI that links genetic differences to specific human cell types
Deep Learning for Single-Cell Genetics
This project builds AI tools to connect genetic differences to how individual human cells behave, aiming to help people with complex diseases.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project ID | NIH-11322983 on NIH RePORTER |
What this research studies
Researchers will combine large human genetics datasets (like the UK Biobank) with single-cell maps of human tissues (like the Human Cell Atlas) and train deep learning models to find which genes and variants act in which cell types. The team will develop methods to prioritize genes, interpret variants, and predict disease risk by integrating genetic and single-cell data. The work uses existing human data and computer modeling rather than recruiting people for new clinical procedures. If successful, these tools could point to the specific cells and molecular processes behind many common diseases.
Who could benefit from this research
Good fit: People with complex, genetically influenced conditions (for example cardiovascular, autoimmune, or neurodegenerative diseases) or those who have donated genetic and tissue data to large biobanks are the most likely to benefit from the findings.
Not a fit: People whose illnesses are driven purely by non-genetic causes or who lack relevant genetic/tissue data are less likely to benefit directly from this work.
Why it matters
Potential benefit: If successful, this could help pinpoint disease-causing genes and the exact cell types they affect, guiding more precise treatments and new drug targets.
How similar studies have performed: AI and large-scale genetics studies have already helped discover disease genes, but combining single-cell maps with genetics at this scale is largely new and exploratory.
Where this research is happening
New Haven, United States
- Yale University — New Haven, United States (Active)
Researchers
- Principal investigator: Zhang, Sai — Yale University
- Study coordinator: Zhang, Sai
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 below.