MAY 13, 2015 07:30 AM PDT
Keynote: Big Data in Health Care and Biomedical Research
Presented at the Genetics and Genomics Virtual Event
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  • Professor of Computational Biology and Bioinformatics, Department of Biostatistics, Harvard University, Dana-Farber Cancer Institute
      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, spending two years at the Salk Institute and 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 School of Public Health in 2005, and works reconstruction of gene networks that drive the development of diseases. In 2012 he and Mick Correll co-Founded GenoSpace, a company that develops software tools to enable precision medicine applications.
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    Every major scientific and technological revolution in history has been driven by one thing: access to data. Today, the availability of Big Data from a wide variety of sources is transforming health and biomedical research into an information science, where discovery is fueled by our ability to effectively collect, manage, analyze, and interpret data, and where Improving outcomes and controlling cost require effective use of available information. Realizing Big Data’s full potential will require that we develop new analytical methods to address a number of fundamental issues and that we develop new ways of integrating, comparing, and synthesizing information, and that we develop approaches that allow us to communicate want we learn in an intuitive and useful fashion to a variety of “consumers” each of whom has unique needs for data access. If we are successful, we have the opportunity to both dramatically improve our understanding of human disease and to implement protocols that will ultimately help to contain costs. Using concrete examples from our work, I will present some vignettes that highlight the challenges and opportunities that present themselves in today’s data rich environment in health care and biomedical research. Learning Objectives: 1. Understand the key opportunities 2. Identify some of the challenges inherent in the use of Big Data in health and biomedical research.

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