Modeling how mammalian cells change over time and space using advanced genomics techniques
Official title: Predictive modeling of mammalian cell fate transitions over time and space with single-cell genomics
Funded at Stanford University · NIH-11045756 · Data updated 2026-11-12
This study is exploring how different types of cells in our bodies change over time and in different situations, using advanced technology to understand how blood cells and other important cells develop, so we can better predict how they behave.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | March 1, 2024 |
| Project end | December 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $249,000 |
| NIH project number | 5R00HG012887-03 |
| Project ID | NIH-11045756 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with conditions affecting blood cell formation or those interested in the underlying mechanisms of cell development.
✕Less likely to help
Patients with stable blood cell conditions or those not affected by hematopoietic or related disorders may not benefit from this research.
What this research studies
This research investigates how mammalian cells transition between different states over time and in various environments by utilizing single-cell genomics. It combines experimental technology development with mathematical modeling and machine learning to create predictive models of cell fate transitions. The approach aims to identify key regulatory networks that maintain stem cells and progenitors, particularly focusing on blood cell formation and other biological systems. By integrating advanced sequencing techniques, the research seeks to validate predictions about cell behavior and development.
Why it matters
Potential benefit: If successful, this research could lead to improved understanding and treatment of diseases related to blood cell formation and other cellular processes.
How similar studies have gone: Other research has shown success in using predictive modeling and machine learning in biological systems, indicating a promising approach in this area.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Qiu, Xiaojie — Stanford University
- Study coordinator: Qiu, Xiaojie
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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.