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Myra Samuels Memorial Lecture

Modeling Strategies for Bioinformatic Data

Marty Wells
Cornell University

Start Date and Time: Thu, 28 Apr 2011, 4:30 PM

End Date and Time: Thu, 28 Apr 2011, 5:30 PM

Venue: MATH 175

Abstract:

Modern bioinformatic data sets often consist of large numbers of predictors and small samples sizes. This fact has generated a vast literature on statistical methods for the so-called large p small n problem. Examples in biology include gene expression data from micro-arrays and association studies involving a large number of genetic markers with a given phenotype. In this talk I will discuss the use of some modeling and computational strategies for such problems: random effects to induce shrinkage and for model parsimony; mixtures for empirical Bayes prediction and classification; computation via the EM algorithm; and regularization with non-convex penalty functions.

Reception will follow at the home of Professors Dabao and Min Zhang.

Purdue Department of Statistics, 150 N. University St, West Lafayette, IN 47907

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