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- W2362280329 abstract "Objective To study the differentially expressed gene extraction method for diagnosis and treatment genes associated with tumor.Methods The gene expression spectrum data were preprocessed,and the differentially expressed genes feature subset was screened by relative risk method.The distances in classification and classification of each other were calculated,and the feature genes were weighed and ranked.Finally redundant genes were filtered in terms of its redundant coefficient between genes,the effectiveness of ovarian cancer gene data were analyzed and tested with classifier.Results Dimensions of 20 feature genes were selected to compare and analyze,the rate of accuracy reached at 100 % for false positive rate reached at 0 when feature genes of 3-5,7 and 12-20 dimensions,which was showed good reliability,and selected 2 types of feature genes effectively.Conclusion It is demonstrated that the classification accuracy is improved in comparing with conventional classification methods of differential expressed genes." @default.
- W2362280329 created "2016-06-24" @default.
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- W2362280329 date "2013-01-01" @default.
- W2362280329 modified "2023-09-23" @default.
- W2362280329 title "Gene differential expression analysis for tumor based on relative risk" @default.
- W2362280329 hasPublicationYear "2013" @default.
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