Spatial ML tools for huge maps of tissue biology
Official title: DMS/NIGMS 1: Spatial statistical machine learning models and algorithms for large-scale spatial multiomics data
Funded at Texas A&m University · NIH-11537582 · Data updated 2026-11-12
A high-tech project develops scalable computer methods to analyze very large, spatially-resolved tissue data from patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Texas A&m University NIH-funded |
| Lab location | 1 site (College Station, United States) |
| Project start | September 4, 2026 |
| Project end | June 30, 2029 |
| Funding year | 2026 |
| Award (this year) | $200,000 |
| NIH project number | 1R01GM169403-01 |
| Project ID | NIH-11537582 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include patients whose tissue samples are analyzed with spatial molecular imaging and who could benefit from advanced data interpretation.
✕Less likely to help
Patients whose tissue data is not part of such analyses or whose conditions are not studied by spatial multiomics may see no direct benefit.
What this research studies
This grant aims to create robust, interpretable statistical tools that can handle massive spatial molecular data from tissue samples. By focusing on scalable clustering, local spatial factor analysis, and multi-omics integration, the work seeks to reveal how cells and proteins arrange themselves in healthy and diseased tissues. The methods are designed to work with whole-slide images and complex datasets, making advanced analytics more accessible to researchers and clinicians. If successful, these tools could help translate spatial biology insights into better diagnoses and treatment plans.
Why it matters
Potential benefit: Could enable doctors to better understand tissue architecture and molecular patterns that relate to disease, potentially guiding personalized therapies.
How similar studies have gone: Prior work shows promise in spatial data analysis, but scalable, multi-omics integration at tissue-wide scale is an emerging area.
Where this research is happening
-
Texas A&m University
College Station, United States Active
Researchers
- Principal investigator: Peng, Xiyu — Texas A&m University
- Study coordinator: Peng, Xiyu
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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.