Learning objectives

• How can we use genetic biobanks to discover links between genetics and brain disease?
• What are the strengths and limitations of using gene expression quantitative trait loci to prioritize causal genes from genetic studies?
• How can we use machine learning and network biology to prioritize causal genes from genetic studies?

Speaker bio:

Michael is an Investigator at the Prosserman Centre for Public Health Research, part of the Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital in Toronto. He is an Assistant Professor of Psychiatry and an Associate Member of the Institute of Medical Science at the University of Toronto. He was previously a Banting postdoctoral fellow at the Centre for Addiction and Mental Health’s Krembil Centre for Neuroinformatics in Toronto, and received a PhD in Computer Science from Stanford University and Bachelor’s and Master’s degrees from the University of Toronto. His research focuses on mining genetic, genomic, and biomedical datasets for clinically and therapeutically relevant insights into brain disease etiology, and incorporates aspects of human genetics, functional genomics, systems biology, statistical modeling, machine learning, and epidemiology.