• [Photo] Shaina Andelman September 28, 2010
    DATES: November 15-16, 2010
    LOCALE: Joseph B. Martin Conference Center at Harvard Medical School, Boston, MA
    HOST: The Program in Quantitative Genomics at the Harvard School of Public Health
    URL: http://www.hsph.harvard.edu/research/pqg-conference-2010/

    Many different data sources that can be utilized to shed more light into the mechanics of complex diseases and phenotypes are now more and more commonly available to the scientific community. While the technology development is rapid, the analysis strategies for their integration lag behind. This is particularly true for integrative approaches that are aimed at assessing the different influences of the epigenome, DNA, RNA, and protein on the disease phenotype simultaneously. This meeting aims to bring experts for the different technologies and their analysis strategies together to foster the development of integrative approaches to analysis. The topics for this year’s conference are:
    • Epigenetics
    • Rare Variants
    • Data Integration and Network Analysis
    The conference schedule includes time for scientific presentations, as well as time for more informal panel and round-table discussions. A poster session will also be held to display selected abstracts relating to this year's theme. Top abstracts will also either be selected for short talks to be presented at the conference, or for the Stellar Abstract Awards, which provide up to $500 in travel assistance. We hope the conference will spur discussions and future developments in the field and generate a white-paper report.

    Speakers: Rafael Irizarry, Suzanne Leal, John Quackenbush, Brad Bernstein, Martha Bulyk, Aravinda Chakravarti, Margaret Daniele Fallin, Peter Laird, Douglas Lauffenburger, Shamil Sunyaev, Bruce Weir

    Sponsors: PQG, NIH/NCI, DFCI, DF/HCC, Illumina

    Contact Person: Shaina Andelman (617-432-7449); sandelma[at]hsph.harvard.edu

Discussion forums: Events: 2010 PQG Conference: Putting It All Together: Integrating Genetic, Epi-genetic, Genomic, and Complex Phenotypic Data

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