Understanding genetic traits through advanced computational methods
Traits on trees: Population genomics for understanding complex phenotypes
This study is looking at how our genes can affect health traits by using big data from health studies, and it aims to help people understand the genetic factors that might influence their health conditions.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Southern California NIH-funded |
| Lab location | 1 site (Los Angeles, UNITED STATES) |
| Project ID | NIH-10895298 on NIH RePORTER |
What this research studies
This research investigates how genetic variations influence complex traits by utilizing large datasets from biobank studies. It combines advanced computational tools with statistical methods to analyze the genealogical relationships among genomic segments from diverse individuals. By studying the evolution of genetic variants linked to important health traits, the research aims to uncover insights into disease causes and improve genome-wide association studies (GWAS). Patients may benefit from a better understanding of genetic factors that contribute to their health conditions.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals enrolled in biobank studies with available genetic and phenotypic data.
Not a fit: Patients who do not have genetic data or are not part of biobank studies may not receive benefits from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved identification of genetic risk factors for diseases, enhancing personalized medicine approaches.
How similar studies have performed: Other research has successfully utilized large genetic datasets and advanced computational methods to uncover genetic associations with diseases, indicating a promising approach.
Where this research is happening
Los Angeles, UNITED STATES
- University of Southern California — Los Angeles, United States (Active)
Researchers
- Principal investigator: Edge, Michael Donald — University of Southern California
- Study coordinator: Edge, Michael Donald
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 below.