Algorithms with Ubiquitous Genetic Information
In the last decade, the human population has produced zettabytes (1021) of digital data. Growing numbers of individuals are obtaining genetic information for medical and recreational purposes and sharing this data via Web 2.0 resources. The first part of my talk will describe the implications of these resources for genetic privacy. I will present an algorithm to recover surnames of anonymous male DNA samples, which can lead to a complete breach of anonymity. In the second part, I will present the dissection of the genetic architecture of complex traits by mining millions of records from a genealogy-driven social network and the construction of a single family tree with 13 million individuals. I will show how by analyzing the covariance structure of phenotypes in this massive family tree, we can infer robust genetic models that can guide risk predictions for personalized medicine.
About Yaniv Erlich
Dr. Yaniv Erlich is an Andria and Paul Heafy Family Fellow and Principal Investigator at the Whitehead Institute for Biomedical Research (MIT), where he leads his own group at the interface of genetics and internet data mining. Dr. Erlich received a bachelor’s degree from Tel-Aviv University, Israel (2006) and a PhD from the Watson School of Biological Sciences at Cold Spring Harbor Laboratory (2010), where he worked on compressed sensing applications for DNA sequencing. Dr. Erlich is the recipient of the Burroughs Wellcome Career Award (2013), Harold M. Weintraub Award (2010), the IEEE/ACM-CS High Performance Computing PhD Award (2008), and was selected as one of 2010 Tomorrow’s PIs team of Genome Technology.
For more information, visit the Erlich Lab website.