Finding New Ways to Fight Antibiotic-Resistant Infections
Leveraging evolutionary analyses and machine learning to discover multiscale molecular features associated with antibiotic resistance
This project uses advanced computer methods to understand how bacteria become resistant to antibiotics, helping us find new ways to fight serious infections.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Colorado Denver NIH-funded |
| Lab location | 1 site (Aurora, UNITED STATES) |
| Project ID | NIH-11171497 on NIH RePORTER |
What this research studies
Antibiotic resistance is a major health concern, making common infections harder to treat. This project uses powerful computer tools, like machine learning, to look at how bacteria change and develop resistance at a very detailed level. By combining information from many different sources, researchers hope to better understand how resistance starts and spreads. The goal is to predict which bacteria might become resistant and discover new ways to overcome these tough infections.
Who could benefit from this research
Good fit: This foundational computational work does not directly involve patient participation at this stage.
Not a fit: Patients not currently affected by antibiotic-resistant infections would not directly benefit from this specific computational research.
Why it matters
Potential benefit: If successful, this work could lead to new strategies for developing effective antibiotics and better ways to predict and combat antibiotic-resistant infections.
How similar studies have performed: While genetic and drug screens have identified some resistance mechanisms, this project introduces a novel computational framework to integrate diverse data for a more holistic understanding of antibiotic resistance evolution.
Where this research is happening
Aurora, UNITED STATES
- University of Colorado Denver — Aurora, United States (Active)
Researchers
- Principal investigator: Ravi, Janani — University of Colorado Denver
- Study coordinator: Ravi, Janani
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.