Improving methods to analyze genetic data for infectious diseases
Official title: Tree-based population genetics methods for genetic epidemiology
Funded at Cornell University · NIH-11021642 · Data updated 2026-11-12
This study is working on new ways to analyze the genetic information of germs that cause infections, so we can better understand how diseases spread and change, which could help improve how we track and treat these illnesses for patients like you.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cornell University NIH-funded |
| Lab location | 1 site (Ithaca, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $346,582 |
| NIH project number | 1R35GM156957-01 |
| Project ID | NIH-11021642 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research include individuals affected by communicable diseases, particularly those with disseminated tuberculosis.
✕Less likely to help
Patients with non-communicable diseases or those not affected by infectious diseases may not receive any benefit from this research.
What this research studies
This research focuses on enhancing computational methods to better understand the genetic data of pathogens, particularly in the context of infectious diseases. By developing new statistical and computational techniques, the project aims to incorporate complex biological and epidemiological factors that influence disease dynamics. The research will utilize high-throughput sequencing data to create more accurate models that reflect real-world scenarios of infection spread and evolution. Patients may benefit from improved disease surveillance and understanding of how infections behave at a genetic level.
Why it matters
Potential benefit: If successful, this research could lead to more effective strategies for monitoring and controlling infectious diseases.
How similar studies have gone: Other research has shown success in using advanced computational methods for genetic epidemiology, indicating that this approach has potential for significant advancements.
Where this research is happening
-
Cornell University
Ithaca, United States Active
Researchers
- Principal investigator: Kim, Jaehee — Cornell University
- Study coordinator: Kim, Jaehee
Related research
Other NIH-funded projects on the same topics.
-
PORTENT 3.0 Technical Core for global health point-of-care tools
A NIH U54 grant supports Cornell and partners in advancing point-of-care technologies for nutrition, infection, and cancer to real-world use, especially in global health settings.
-
Point-of-care zinc test strips to verify infant zinc medicines in low-resource settings
A fast, low-cost smartphone‑based test strips method checks zinc-containing infant medicines in places with limited lab access.
-
Center for Spillover Prevention and One Health Readiness in Asia
A center in Asia works to prevent pandemics by studying how animal infections jump to humans and by building tools to detect and respond quickly to spillovers.
-
SAGE: A privacy-friendly system to monitor antimicrobial use in animals
A nationwide, privacy-preserving data hub will securely collect and standardize antimicrobial use data across animal species to support smarter stewardship and regulatory science.
-
Rapid, bedside KS diagnosis in Africa with KS-COMPLETE
A fast, point-of-care test using skin biopsies to diagnose Kaposi’s sarcoma in sub-Saharan Africa, helping patients get results in about an hour.
-
Nuclear mechanics in tight cell movement
Scientists are studying how the nucleus changes its shape and function when cells squeeze through very small spaces, which could affect health and disease.
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.