Improving methods to understand how genes and gut bacteria affect health and disease
Official title: Advancing Causal Inference in Integrative Omics Analysis
Funded at University of Washington · NIH-10940873 · Data updated 2026-11-12
This study is working on new ways to analyze complex biological data to help doctors and scientists understand how genes, proteins, and gut bacteria affect health and disease, and they’ll create easy-to-use software tools to make this information clearer for everyone.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project start | September 1, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $354,139 |
| NIH project number | 1R35GM155070-01 |
| Project ID | NIH-10940873 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with complex health conditions that may be influenced by genetic and microbiota factors.
✕Less likely to help
Patients with straightforward health issues that do not involve complex biological interactions may not benefit from this research.
What this research studies
This research focuses on developing advanced statistical methods to analyze complex biological data from genes, proteins, and gut microbiota. By integrating large-scale omics data, the project aims to uncover the causal relationships that contribute to health and disease, rather than just identifying associations. The researchers will create user-friendly software tools that can help clinicians and scientists better understand the underlying mechanisms of diseases. This innovative approach combines machine learning techniques with traditional statistical methods to provide deeper insights into biological processes.
Why it matters
Potential benefit: If successful, this research could lead to more effective treatments and personalized healthcare strategies based on a better understanding of disease mechanisms.
How similar studies have gone: Other research has shown promise in using advanced statistical methods and machine learning to analyze omics data, indicating that this approach could yield significant insights.
Where this research is happening
-
University of Washington
Seattle, United States Active
Researchers
- Principal investigator: Ye, Ting — University of Washington
- Study coordinator: Ye, Ting
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.