Abstract #300584

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JSM 2003 Abstract #300584
Activity Number: 250
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300584
Title: Mixture Functional Discriminant Analysis for Gene Functional Classification
Author(s): Jiang Gui*+ and Hongzhe Li
Companies: University of California, Davis and University of California, Davis
Address: 3800 Solano Park Circle, Davis, CA, 95616,
Keywords: B-spline ; Linear Discriminant analysis ; Classification ; Clustering ; EM algorithm
Abstract:

We introduce a technique of functionally classifying genes based on the microarray time course gene expression data. This procedure, which we call mixture functional discriminant analysis (MFDA), is designed to account for time dependency of the measurements and the noisy nature of the micoarray data. MFDA projects the time course data into a low dimension by using B-spline transformations and fits Gaussian mixtures for each class. Simulated data indicate that MFDA can effectively identifying sets functional data with a common function. We demonstrate the MFDA to predict functional classes of uncharacterized yeast ORFs based on their cell-cycle gene expression profiles.

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