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• W2333987421 endingPage "52" @default.
• W2333987421 startingPage "1" @default.
• W2333987421 abstract "Identification of biological significant subspace clusters (biclusters and triclusters) of genes from microarray experimental data is a very daunting task that emerged, especially with the development of high throughput technologies. Several methods and applications of subspace clustering (biclustering and triclustering) in DNA microarray data analysis have been developed in recent years. Various computational and evaluation methods based on diverse principles were introduced to identify new similarities among genes. This review discusses and compares these methods, highlights their mathematical principles, and provides insight into the applications to solve biological problems." @default.
• W2333987421 created "2016-06-24" @default.
• W2333987421 creator A5014709314 @default.
• W2333987421 creator A5019868633 @default.
• W2333987421 creator A5066354389 @default.
• W2333987421 date "2014-07-01" @default.
• W2333987421 modified "2023-09-27" @default.
• W2333987421 title "Subspace Clustering of DNA Microarray Data" @default.
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