A Survey on Similarity Measures for Microarray Gene Expression Data Analysis

Microarray technology is a present advancement used to concurrently monitor the expression profiles of thousands of genes under different experimental conditions. This paper first momentarily introduce the concepts of microarray technology, survey on similarity measure and discuss the basic elements of clustering on gene expression data. Finding groups of gens with similar expression is usually achieved by exploratory techniques such as cluster analysis. From the detailed survey it mainly concentrates on similarity measure. Similarity measure is important task in gene expression data for clustering technique. In gene expression data two similarity measures are used. Mutual Information similarity measure will be used first and then redundancy can be removed, after that Intuitionistic Fuzzy Sets are used to get more accuracy and it can be applicable for multiple data sets.