Improving understanding of Alzheimer's disease using advanced data analysis techniques
Official title: Administrative Supplement: Enhancing cell-type-specific inference with millions of snRNA-seq and deep learning methods
Funded at Univ of North Carolina Chapel Hill · NIH-11200669 · Data updated 2026-11-12
This study is looking at how certain cells in the brain are affected by Alzheimer's disease using advanced technology, which could help researchers find better treatments for patients like you.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project start | May 1, 2023 |
| Project end | January 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $91,474 |
| NIH project number | 3R01AG079291-03S1 |
| Project ID | NIH-11200669 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are older adults diagnosed with Alzheimer's disease or those at risk of developing it.
✕Less likely to help
Patients with other forms of dementia unrelated to Alzheimer's may not receive direct benefits from this research.
What this research studies
This research focuses on enhancing the understanding of Alzheimer's disease by utilizing advanced deep learning models and single-cell RNA sequencing data. By analyzing millions of individual cell data points, the study aims to improve the accuracy of identifying specific cell types involved in Alzheimer's. This approach will help researchers better understand the cellular mechanisms underlying the disease, potentially leading to more targeted therapies. Patients may benefit from insights gained through this innovative analysis of cellular data.
Why it matters
Potential benefit: If successful, this research could lead to improved diagnostic tools and targeted treatments for Alzheimer's disease.
How similar studies have gone: Other research utilizing deep learning and single-cell analysis has shown promising results in understanding complex diseases, indicating a potential for success in this approach.
Where this research is happening
-
Univ of North Carolina Chapel Hill
Chapel Hill, United States Active
Researchers
- Principal investigator: Li, Yun — Univ of North Carolina Chapel Hill
- Study coordinator: Li, Yun
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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.