
This paper proposes a method to select a set of genes from a large number of genes with the ability of classifying types of diseases. The proposed gene selection method is designed according to correlation analysis and the concept of 95% reference range. The method is very simple and uses the information of all genes. We have used the method in leukemia patients and achieved good classification results.
Leukemia, Models, Statistical, Models, Genetic, Biochemistry, molecular biology, Gene Expression Profiling, Computational Biology, Reproducibility of Results, Applications of statistics to biology and medical sciences; meta analysis, Medical applications (general), Reference Values, Neoplasms, Humans, Biomechanics, Algorithms, Software, Research Article, Oligonucleotide Array Sequence Analysis
Leukemia, Models, Statistical, Models, Genetic, Biochemistry, molecular biology, Gene Expression Profiling, Computational Biology, Reproducibility of Results, Applications of statistics to biology and medical sciences; meta analysis, Medical applications (general), Reference Values, Neoplasms, Humans, Biomechanics, Algorithms, Software, Research Article, Oligonucleotide Array Sequence Analysis
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