JSM 2005 - Toronto

Abstract #304784

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 226
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #304784
Title: Eigenanalysis-based Method for Gene Subset Selection and Cancer Classification Using Microarray Data
Author(s): Simin Hu*+ and J. Sunil Rao
Companies: Case Western Reserve University and Case Western Reserve University
Address: Department of Epidemiology and Biostatistics, Cleveland, OH, 44106,
Keywords: eigenanalysis ; eigen-ratio criterion ; cancer classification ; gene subset selection ; microarray data
Abstract:

In this paper, we propose a novel eigenanalysis-based method for gene selection and cancer classification using microarray data. We cluster the genes and carry out linear discriminant analysis in each and all clusters. To select gene subset in each cluster, we define an eigen-ratio criterion to sequentially remove irrelevant and redundant genes. The resultant compact gene subset is then used to build the classification rule in the cluster. Experimental results have demonstrated the effectiveness of our method for identifying biologically important genes and classifying different cancer types.

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