Subspace clustering for microarray data analysis:multiple criteria and significance assessment

As one of the latest breakthroughs in experimental molecular biology, microarray technology provides a powerful tool for monitoring the expression patterns of thousands of genes simultaneously, producing huge amounts of valuable gene expression data. Gene expression data are organized as matrices --- tables where rows represent genes, columns represent various samples such as tissues or experimental conditions, and a cell number indicates the expression level of a particular gene in a particular sample.