Understanding how DNA signals and proteins control gene access in human cells
Official title: Learning cis- and trans-regulatory drivers of chromatin accessibility at single-cell resolution.
Funded at Univ of Massachusetts Med Sch Worcester · NIH-11428118 · Data updated 2026-11-12
Aims to map how regions of the genome and the proteins that bind them control which genes are turned on or off in human cells, using advanced computer methods and single-cell data.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of Massachusetts Med Sch Worcester NIH-funded |
| Lab location | 1 site (Worcester, United States) |
| Project start | September 1, 2026 |
| Project end | May 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $460,625 |
| NIH project number | 1R35GM165622-01 |
| Project ID | NIH-11428118 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not a patient-facing trial; findings may ultimately inform studies on human diseases and personalized medicine.
✕Less likely to help
No direct patient participation in this grant.
What this research studies
This project studies how transcription factors bind to DNA and how that binding shapes chromatin accessibility and other gene-regulation marks at the single-cell level. Researchers will build machine learning models that integrate cis-regulatory features with the cellular environment to predict regulatory outcomes across different cell types. The work combines public data with innovative computational approaches to link nucleotide-level information to how genes are controlled in human biology. Results could help interpret how genetic variants impact regulation and contribute to disease. The five-year plan includes developing methods that account for both local DNA features and the broader regulatory state of cells, including TF sequences.
Why it matters
Potential benefit: If successful, the work could improve our understanding of how genetic differences influence gene regulation and disease risk, potentially guiding precision medicine strategies.
How similar studies have gone: Prior research shows that ML approaches can illuminate regulatory grammar, with growing success in predicting regulatory effects from DNA and TF data.
Where this research is happening
-
Univ of Massachusetts Med Sch Worcester
Worcester, United States Active
Researchers
- Principal investigator: Schreiber, Jacob — Univ of Massachusetts Med Sch Worcester
- Study coordinator: Schreiber, Jacob
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.