Feature Selection for Cancer Classification Using Microarray Gene Expression Data

Wenyan Zhong and Jingjing Wu
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Wenyan Zhong: Department of Mathematics and Statistics, University of Calgary, Canada
Jingjing Wu: Department of Mathematics and Statistics, University of Calgary, Canada

Biostatistics and Biometrics Open Access Journal, 2017, vol. 1, issue 2, 33-39

Abstract: The DNA microarray technology enables us to measure the expression levels of thousands of genes simultaneously, providing great chance for cancer diagnosis and prognosis. The number of genes often exceeds tens of thousands, whereas the number of subjects available is often no more than a hundred. Therefore, it is necessary and important to perform gene selection for classification purpose. A good subset of discriminative genes can improve prediction accuracy of classifiers and save computational cost with reduced dimension of data.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:1:y:2017:i:2:p:33-39

DOI: 10.19080/BBOAJ.2017.01.555557

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