Developing advanced statistical models to analyze genomic and biomedical data
Official title: Expressive and scalable statistical models for genomic and biomedical data
Funded at University of California Los Angeles · NIH-11078750 · Data updated 2026-11-12
This study is looking at how our genes can affect health and disease by using advanced computer techniques to analyze large amounts of genetic information from different people, with the hope of finding new ways to understand and improve health for everyone.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | May 1, 2024 |
| Project end | February 28, 2029 |
| Funding year | 2025 |
| Award (this year) | $301,623 |
| NIH project number | 5R35GM153406-02 |
| Project ID | NIH-11078750 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals from diverse genetic backgrounds who are interested in understanding their genetic predispositions to various diseases.
✕Less likely to help
Patients with no interest in genetic research or those who do not have access to genomic testing may not benefit from this research.
What this research studies
This research focuses on creating and applying sophisticated statistical models to interpret large genomic and biomedical datasets. By leveraging the recent advancements in DNA sequencing technology, the project aims to uncover the biological underpinnings of diseases and enhance human health. The researchers will analyze genetic variation across diverse populations, utilizing deep phenotypic and disease information to address complex questions in biology and medicine. The goal is to develop scalable computational methods that can handle the vast amounts of data generated, ultimately leading to better understanding of disease risk and genetic diversity.
Why it matters
Potential benefit: If successful, this research could lead to improved understanding of genetic factors influencing diseases, potentially guiding personalized medicine approaches.
How similar studies have gone: Previous research utilizing advanced statistical models in genomics has shown promise in uncovering significant insights into genetic variation and disease risk.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Sankararaman, Sriram — University of California Los Angeles
- Study coordinator: Sankararaman, Sriram
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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.