Gene Selection for Sample Classification in Microarray: Clustering Based Method
Micro array technology is one of the important biotechnological means that allows recording the expression levels of thousands of genes simultaneously within a number of different samples. An important application of micro array gene expression data is to classify samples according to their gene expression profiles. The gene expression dataset can be represented by an expression table, where each row corresponds to one particular gene, each column to a sample. The relevance of each attribute (attribute represents the gene expression conversion into numerical values) with respect to the class label and the redundancy between two attributes in terms of mutual information are calculated using supervised similarity measure.