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A gene selection method based on approximate reduction

Qi Yunsong1,2,Sun Huaijiang1,Song Yuqing1,Xie Jun1(1.School of Computer Science and Technology,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China)(2.School of Computer Science and Engineering,Jiangsu University of Science and Technology,Zhenjiang Jiangsu 212003,China)  
To identify disease related genes from gene expression profiles(DNA microarray) has a very important practical significance for disease,such as cancer,subtype discovery,diagnosis and pathology study.Gene selection is a critical preprocessing technique for the DNA microarray data analysis.Gene sets of interest typically selected by usual ranking methods from DNA microarray data will contain many highly correlated genes and remain high dimension.Thinking of that DNA microarray data sets are typical inconsistent decision system,with introduction of the concept of that a inconsistent decision system is consistent according to its approximate distribution,a set of notions of approximate distribution reduct are proposed.After discussed the relations between the lower and upper approximation reducts of a inconsistent decision system,a gene selection method based on approximate distribute reduct is obtained.The experimental results on two publicly available DNA microarray datasets,lung cancer and NCI60(9-tumors),show that the proposed method got an equivalent classification effect with significantly reduced number of selected gene.
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