Rivas Lab aims to uncover the mechanisms of disease and improve health and well-being globally. By combining methods development and
biological and biomedical datasets, we develop statistical models and computational tools for the analysis of population-scale studies.

Scientific Themes

Apr April 14 Sat 2018

Statistical models for prioritizing targets from human genetic data

Oct October 20 Fri 2017

Prioritizing candidate causal genes

Generating effective therapeutic hypotheses

We’re mining large-scale human genetic, clinical outcomes, imaging, wearable sensors, and environmental data to generate effective therapeutic and preventative hypotheses for human diseases. Key disease areas of focus include: Crohn's disease, ulcerative colitis, chronic kidney disease, Alzheimer's disease, type 2 diabetes, coronary heart disease, and exploring additional diseases through electronic health records.