New methods to analyze microbiome data for health conditions
Novel Computational Methods for Microbiome Data Analysis in Longitudinal Study
This study is working on new ways to look at the tiny organisms in our bodies over time to better understand health issues like obesity, diabetes, and cancer, so we can help people feel better by connecting changes in these organisms to their health.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York University School of Medicine NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-11019830 on NIH RePORTER |
What this research studies
This research focuses on developing innovative computational methods to analyze microbiome data collected over time, which can help in understanding various health conditions such as obesity, diabetes, inflammatory bowel disease, and cancer. The project aims to create tools that can accurately identify and differentiate microbial strains and their genetic variants from raw sequencing data. By examining how these microbial strains evolve, the research seeks to link changes in the microbiome with specific health traits in individuals. This approach could enhance the clinical utility of microbiome studies and improve patient outcomes.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals suffering from obesity, diabetes, inflammatory bowel disease, or cancer who are interested in understanding the role of their microbiome in their health.
Not a fit: Patients without any of the targeted conditions or those not interested in microbiome analysis may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more precise diagnostics and personalized treatment strategies based on an individual's microbiome.
How similar studies have performed: Other research has shown promising results using similar computational approaches in microbiome studies, indicating potential for success in this novel methodology.
Where this research is happening
New York, United States
- New York University School of Medicine — New York, United States (Active)
Researchers
- Principal investigator: Li, Huilin — New York University School of Medicine
- Study coordinator: Li, Huilin
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.