Date/Time
Date(s) - 02/20/2017
3:00 pm

Jessilyn Dunn, Ph.D., Postdoctoral Fellow, Snyder Lab, Department of Genetics, Stanford University

Integrative Personalized Omics and Physiological Profiling of Health and Disease

The high prevalence of unhealthy lifestyles is driving rising healthcare costs, which highlights the need to transition from a reactive to a proactive healthcare model. Recent significant improvements in mobile health (mHealth) technologies, biomolecular sensing, and computing capacity provide an unprecedented opportunity to collect vast amounts of health data towards the promise of precision health. The grand challenges facing this vision include the lack of mature data acquisition, transfer, preprocessing, and analytic methods.

To tackle these challenges we are developing cutting-edge biomedical big data pipelines, which have enabled us to design predictive health models and discern actionable insights. In my talk I will present two innovative biomedical data integration projects focused on cardiometabolic health. I will first describe our work disentangling the endothelial cell epigenome and transcriptome to explore the link between fluid mechanics and vascular pathology. Next, I will discuss our findings on the utility of portable biosensors for monitoring physiology and their role in managing health and detecting disease. Finally, I will describe future plans for integrating omics, mHealth, and electronic health records data using machine learning to dramatically improve cardiometabolic care at the population scale.