How can technology help you track real time data about your health and wellbeing? And why should you track anyway? In this episode, Michael Snyder talks about how tracking can help you gain deeper understanding of what is going on in your body at a physiological level. Often, illnesses begin developing in our bodies quietly, before any symptoms begin to show up. Snyder’s research shows that by tracking on a regular basis, we can pre-empt diseases. Health data collection using wearable tech can help us take a proactive approach toward prevention of disease. And like they say, prevention is better than cure.
About Michael Snyder:
Michael Snyder is a pioneer in the field of functional genomics and proteomics, and one of the major participants of the ENCODE project. Snyder Lab was the first to perform a large-scale functional genomics project in any organism and has developed many technologies in genomics and proteomics. These include the development of proteome chips, high resolution tiling arrays for the entire human genome, paired end sequencing for mapping of structural variation in eukaryotes, de novo genome sequencing of genomes using high throughput technologies and RNA-Seq. He has combined different "omics" technologies to perform the first longitudinal detailed integrative personal omics profile (iPOP) of a person and used this to assess disease risk and monitor disease states for personalized medicine. He is also the author of the book: 'Genomics and Personalized Medicine: What Everyone Needs to Know' and the cofounder of Personalis, SensOmics, Qbio, January AI, Filtricine, Mirvie, Protos, Protometrix and Affomix. Michael Snyder, PhD, of Stanford University is the recipient of the 2019 Genetics Society of America (GSA) George W. Beadle Award for developing and disseminating widely-used technology for the simultaneous analysis of thousands of genes, RNA molecules, and proteins. Currently he is a Professor in the Department of Genetics, Stanford University School of Medicine and Director at Stanford Center for Genomics and Personalized Medicine.