Understanding the 3D structure of chromatin and its role in gene regulation
Official title: Deep integrative analysis of Hi-C data
Funded at University of Washington · NIH-10979053 · Data updated 2026-11-12
This study is looking at the 3D shape of chromatin, which helps us understand how genes work, and it aims to use smart computer tools to combine different types of genetic information, so we can learn more about how changes in chromatin might affect diseases and lead to new treatments for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project start | September 17, 2024 |
| Project end | June 30, 2029 |
| Funding year | 2024 |
| Award (this year) | $504,949 |
| NIH project number | 1R01HG013321-01A1 |
| Project ID | NIH-10979053 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with genetic conditions or diseases that may be influenced by chromatin structure and gene regulation.
✕Less likely to help
Patients with conditions unrelated to chromatin structure or gene regulation may not receive any benefit from this research.
What this research studies
This research focuses on analyzing the 3D structure of chromatin, which is crucial for understanding how genes are regulated within the genome. By developing advanced machine learning models, the project aims to integrate various types of genomic data, including Hi-C, RNA-seq, and ATAC-seq, to provide a comprehensive view of chromatin architecture and its dynamics. Patients may benefit from insights gained about how chromatin structure influences cell differentiation and disease progression, potentially leading to new therapeutic strategies. The research will utilize innovative computational approaches to tackle the complexities of large-scale genomic data.
Why it matters
Potential benefit: If successful, this research could lead to breakthroughs in understanding gene regulation and the development of targeted therapies for diseases linked to chromatin structure.
How similar studies have gone: Other research has shown success in using machine learning to analyze genomic data, indicating that this approach has the potential for significant advancements in the field.
Where this research is happening
-
University of Washington
Seattle, United States Active
Researchers
- Principal investigator: Wang, Sheng — University of Washington
- Study coordinator: Wang, Sheng
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.