Gene selection guided by feature interdependence

Lai, Hung-Ming, Albrecht, Andreas A. and Steinhofel, Kathleen (2013) Gene selection guided by feature interdependence. World Academy of Science, Engineering and Technology (WASET) (79) . pp. 1432-1438. ISSN 2070-3724 [Article]

Abstract

Cancers could normally be marked by a number of differentially expressed genes which show enormous potential as biomarkers for a certain disease. Recent years, cancer classification based on the investigation of gene expression profiles derived by high-throughput microarrays has widely been used. The selection of discriminative genes is, therefore, an essential preprocess step in carcinogenesis studies. In this paper, we have proposed a novel gene selector using information-theoretic measures for biological discovery. This multivariate filter is a four-stage framework through the analyses of feature relevance, feature interdependence, feature redundancy-dependence and subset rankings, and having been examined on the colon cancer data set. Our experimental result show that the proposed method outperformed other information theorem based filters in all aspect of classification errors and classification performance.

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