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Abstract Details
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Activity Number:
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489
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Type:
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Invited
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Date/Time:
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Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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| Abstract - #303655 |
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Title:
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Order Statistics and Gene Regulation
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Author(s):
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Donald Geman*+
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Companies:
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The Johns Hopkins University
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Address:
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Clark Hall, Baltimore, MD, 21218,
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Keywords:
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Computational biology ;
order statistics ;
gene regulation ;
disease prognosis
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Abstract:
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I will present a research program in statistical genomics focused on discovering gene regulatory patterns in health and disease from high-dimensional molecular data. Two barriers to mature applications are the complexity of the descriptions which typically emerge from standard computational learning, impeding biomedical understanding, and mixed performance in cross-study validation, impeding further development and eventual clinical applications. I will argue that low-dimensional order statistics are easy to interpret, relatively invariant to data normalization and resistant to over-fitting, and can account for combinatorial interactions among genes and gene products. These ideas will be illustrated by diagnosing cancers from expression reversals, measuring pathway regulation with rank invariants, and modeling with pairwise comparisons.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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