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- W137522587 abstract "DNA microarrays are a technology that is used for monitoring the expression of thousands of genes simultaneously. Microarray data create new opportunities for biomedical sciences but also pose serious challenges for statistical analysis, due to their complexity. Inference of biological meaning from gene expression profiling involves the classification of genes whose expression is correlated to a given functional condition. To test the value of Correspondence Analysis for microarray data classification, we compared gene expression profiles of cells in the presence or absence of a dominant negative Myc mutant. As compared to other microarray analysis methods, this procedures allows the projection of a complex data set into an easily visualized, low dimensional space, in which association between variables (genes) and observations (experiments) can be more easily evaluated. Correspondence Analysisis is a powerful technique for gene-expression data analysis, particularly when combined with other classification techniques.KeywordsCorrespondence AnalysisProbe PairProbe CellCompare Gene Expression ProfileOriginal Data MatrixThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W137522587 date "2003-01-01" @default.
- W137522587 modified "2023-09-27" @default.
- W137522587 title "A Method to Classify Microarray Data" @default.
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- W137522587 doi "https://doi.org/10.1007/978-3-642-18991-3_77" @default.
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