PAG XXVII has ended.

PAG XXVIII will be January 11-15, 2020  - San Diego, CA, USA 
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john.quackenbush-smProfessor of Biostatistics and Computational Biology, Professor of Cancer Biology, Director, Center for Cancer Computational Biology, Dana-Farber Cancer Institute;  Professor of Computational Biology and Bioinformatics, Harvard TH Chan School of Public Health; Co-Founder and Board Chair, Genospace, LLC, USA
Tues., Jan. 12 - 8:00 AM / Town & Country Ballroom

Talk Title: Using Networks to Discover Biology in Complex Systems

Talk Topic:  I will present a new way of thinking about the genotype-phenotype connection using network models and their structures to discover biology.

Bio:  John Quackenbush received his PhD in theoretical physics from UCLA in 1990. Following a physics postdoc, he received a Special Emphasis Research Career Award from the National Center for Human Genome Research to work on the Human Genome Project. He spent two years at the Salk Institute and then two years at Stanford University working in genomics and computational biology. In 1997 he moved to The Institute for Genomic Research (TIGR), pioneering expression analysis. He joined the Dana-Farber Cancer Institute and the Harvard TH Chan School of Public Health in 2005, and works on the reconstruction of gene networks and analysis of their structural properties to understand factors that drive the development of diseases. He also founded and directs that Center for Cancer Computational Biology at Dana-Farber, which provides analytical support for genomic data analysis.
He currently serves on the boards of five major journals, and is editor-in-chief at Genomics. He has also served on several committees at the US National Academies and the Institute of Medicine, and is a member of scientific advisory boards of a number of biotech start-up companies. With his colleague Mick Correll, he co-founded Genospace, a company that has developed advanced cloud-based software tools to support genomic research and precision medicine. In 2013 he was honored as a White House Open Science Champion of Change for his work in making large-scale data available, usable, and useful.