Public Health and Health Professions
Benos Lab
Led by Takis Benos · Epidemiology
What we study
The lab uses machine learning and data analysis to study aging, diseases, and health. They develop tools to predict risks and improve treatments using biomedical data.
What working here is like
- Computational
- No organisms (data only)
- Coding required
- Projects
- 5
Current projects
Novel biomarkers for kidney disease in Type 1 Diabetes
Finding new ways to detect kidney problems in Type 1 Diabetes patients.
Deep Learning for Single-Cell Genetics
Using deep learning to analyze genetic data from single cells.
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EpiGNOME: Epigenetic Graphical Networks Of Methylation Effectors for COPD Progression
Studying how epigenetic changes affect COPD progression using graphical models.
Integrative Model of Metabolomics, Equol and Atherosclerotic Cardiovascular Disease (IMMEA)
Exploring how metabolomics and equol relate to cardiovascular disease.
COPD SUBTYPES AND EARLY PREDICTION USING INTEGRATIVE PROBABILISTIC GRAPHICAL MODELS R01HL157879
Uses machine learning on patient data to find subtypes of chronic obstructive pulmonary disease (COPD) and predict it earlier.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
How to reach out
Takis Benos hasn't set up this page yet. You can also look them up in the UF directory (search “Takis Benos”).