Speaker: Gary Bader, Department of Computer Science, U of T
Title: Big Data in Medicine and Genomics
Genomics is mapping complex data about human biology and promises major medical advances. In particular, genomics is enabling precision medicine, the use of a patient's genome and physiological state to improve therapeutic efficacy and outcome. However, routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with "Big data". These data are so complex and large that typical researchers are not able to cope with them. Collectively, these data require an understanding of many aspects of experimental biology and medicine to correctly process and interpret. Data size is also an issue, as individual researchers may need to handle tens of terabytes (genomes from a few hundred patients), which is challenging to download and store on typical workstations. To effectively support precision medicine, scientists from a wide range of disciplines, including computer science, must develop algorithms to improve precision medicine (e.g. diagnostics and prognostics), genome interpretation, raw data processing and secure high performance computing.
Gary D. Bader is a computational biology faculty member at the University of Toronto, since 2006. He is in the Department of Molecular Genetics in the Faculty of Medicine and also the Department of Computer Science. Gary runs a research lab of about 20 researchers and primarily works in the area of biological network analysis as applied to the study of a number of diseases, including cancer. Gary studied at Memorial Sloan-Kettering Cancer Center in New York, Mount Sinai Hospital in Toronto
and McGill University and has a background in Biochemistry and Computer Science. Gary has published over 100 peer-reviewed articles which have garnered over 19,000 citations and an h-index of 47.
See baderlab.org and scholar.google.ca/citations
For additional information, contact: Jarek Szlichta