MAY 13, 2015 7:30 AM PDT

Keynote: Big Data in Health Care and Biomedical Research

Speaker
  • Professor of Computational Biology and Bioinformatics, Chair of the Department of Biostatistics, Harvard University, Dana-Farber Cancer Institute
    Biography
      John Quackenbush is Professor of Computational Biology and Bioinformatics and Chair of the Department of Biostatistics at the Harvard TH Chan School of Public Health and Professor of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute. John's PhD was in Theoretical Physics, in 1992 he received a fellowship from the National Institutes of Health to work on the Human Genome Project, which led him from the Salk Institute to Stanford University to The Institute for Genomic Research (TIGR) before moving to Harvard in 2005. He currently directs the Computational Biology and Quantitative Genetics MS program and is PI of the BD2K Training Grant at HSPH. John's research uses massive data from DNA sequencing and other assays to model functional networks in human cells. By comparing networks between groups of individuals, he has found new drug targets, explored chemotherapy resistance, and investigated differences between the sexes. He has received numerous awards for his work, including recognition in 2013 as a White House Open Science Champion of Change. He is also the co-founder of Genospace, a precision medicine software company that was purchased by the Hospital Corporation of America in 2017.

    Abstract

    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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