Computational modeling of how external signals shape cell states using spatial and single-cell data
Official title: Computational Modeling of the Interplay between External Signaling and Transcription Rewiring using Spatial Transcriptomics and Single Cell Multiome Data
Funded at University of Virginia · NIH-11474018 · Data updated 2026-11-12
A patient-relevant look at how signals from one cell influence another, using advanced tissue-wide and single-cell data to map how cells change their behavior.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Virginia NIH-funded |
| Lab location | 1 site (Charlottesville, United States) |
| Project start | May 11, 2026 |
| Project end | February 28, 2029 |
| Funding year | 2026 |
| Award (this year) | $248,999 |
| NIH project number | 4R00HG013429-03 |
| Project ID | NIH-11474018 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with autoimmune diseases, inflammatory conditions, or cancers where cell signaling and transcriptional changes drive disease progression.
✕Less likely to help
Healthy individuals without immune or inflammatory conditions may not directly benefit, though findings could inform broader biology.
What this research studies
This project will build user-friendly computational tools to understand how external signals affect a patient’s cells, using crowded data from spatial maps and single-cell multiomics. The goal is to make it possible for researchers to see how signals shape transcription factors and downstream gene activity in tissues relevant to health and disease. By improving data deconvolution and creating interpretable models of cell-to-cell communication, the work aims to reveal how inflammation, cancer, and repair processes unfold at the cellular level. The new methods will integrate existing data types to provide clearer insights into how cells respond to their environment in human tissues.
Why it matters
Potential benefit: If successful, these tools could help researchers identify new targets and biomarkers for autoimmune diseases and cancer by revealing how external signals drive harmful cell programs.
How similar studies have gone: Previous methods exist but often rely on limited data; this project adds integrated multiomics and spatial context, representing a newer, potentially more powerful approach.
Where this research is happening
-
University of Virginia
Charlottesville, United States Active
Researchers
- Principal investigator: Chu, Tin Yi — University of Virginia
- Study coordinator: Chu, Tin Yi
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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.