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  • Modeling HIV adaptation: Insights into HIV virology, immunology and vaccine design from machine learning and computational biology

    Tue, Oct 23, 2012 @ 03:30 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jonathan Carlson, Microsoft Research

    Talk Title: Modeling HIV adaptation: Insights into HIV virology, immunology and vaccine design from machine learning and computational biology

    Series: CS Colloquium

    Abstract: The human immunodeficiency virus (HIV-1) mutates at a startling rate, with millions of viral variants generated in each patient each day. This high rate of mutation, coupled with high mutational tolerance, provides the virus with the ability to rapidly adapt to changing environments and typically proves an insurmountable challenge to the human immune system. Viral mutation is not, however, without constraints: given large enough datasets, patterns begin to emerge. By studying these patterns, we have gained significant new insights into what is attacking the virus (immunology), what is being attacked (virology), how that attack is evaded (evolution), and how adaptation influences disease progression (pathology). In addition, we have begun to identify features of individuals who naturally control the virus, offering tantalizing hints at how an effective vaccine might work. In this talk, I will describe the statistical models we have developed for studying HIV adaptation, the insights these models have provided and the open questions we continue to pursue.

    Biography: Jonathan Carlson, Ph.D., joined the Escience Group at Microsoft Research in 2008, where he studies viral evolution, immunology and vaccine design through statistical modeling. His models of viral escape have achieved broad recognition in the HIV community, where they have led to the discovery of novel viral-host interactions, insights into mechanisms of natural immune control, and the identification of vaccine candidates that are slated for clinical trials. He has authored over 50 papers in the field and has served on advisory panels and committees for the Institutes of Medicine, the Gates Foundation and the Center for HIV/AIDS Vaccine Immunology (CHAVI). In 2009, he received his Ph.D. in computer science and computational molecular biology from the University of Washington, where he studied under David Heckerman (Microsoft Research) and Larry Ruzzo (UW) and was given the university’s Distinguished Dissertation Award. He received his B.A. in Biology and Computer Science from Dartmouth in 2003, where he studied bioinformatics and transcriptional regulation under Bob Gross.

    Host: Ethan Katz-Bassett

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Contact: Assistant to CS chair

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