Using advanced computer models to understand genes and personalize medicine
Advanced machine learning models to integrate multi-modal biomedical datasets for gene regulation and precision medicine
This work creates new computer tools to combine different types of health information, like genetic data and medical records, to better understand diseases and find new treatments for patients.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of North Texas NIH-funded |
| Lab location | 1 site (Denton, United States) |
| Project ID | NIH-11090901 on NIH RePORTER |
What this research studies
Our team is building advanced computer programs that can bring together many different kinds of health data, such as information about your genes, how your body's cells work, and your electronic health records. These programs are designed to handle large amounts of complex information, even when some data is missing or noisy. By developing these smart computer models, we aim to uncover new insights into how diseases develop and how they might be treated. This approach helps us predict health outcomes and discover existing medicines that could be used for new purposes.
Who could benefit from this research
Good fit: This foundational work does not directly involve patient participation, but its future applications could benefit patients with various diseases by improving diagnosis and treatment strategies.
Not a fit: Patients seeking immediate direct clinical intervention or participation in a treatment trial would not find direct benefit from this computational tool development.
Why it matters
Potential benefit: If successful, this work could lead to more personalized treatment plans for patients and help identify new uses for existing medications, potentially improving health outcomes.
How similar studies have performed: While the integration of multi-modal biomedical datasets is an active area of research, this grant focuses on developing novel, generalizable, and interpretable machine learning solutions to address specific challenges in this field.
Where this research is happening
Denton, United States
- University of North Texas — Denton, United States (Active)
Researchers
- Principal investigator: Bozdag, Serdar — University of North Texas
- Study coordinator: Bozdag, Serdar
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.