Importance of Similarity Measure in Gene Expression Data-A Survey

Abstract

The usage of data mining techniques in research fields of computational biology include gene finding, genome assembly , prediction of gene expression etc, are very promising because the large amount of data is involved in these research fields. These techniques aims that to disclose the unknown knowledge and relationships. Different data sources are available one such as DNA Micro Array is the technology which enables the researchers to investigate and address issues which are non traceable. DNA Micro Array experiments generates thousands of gene expression measurements and provide a simple way for collecting huge amounts of data in short time. Micro array data analysis allows identifying the most relevant genes for a target disease and group of genes with similar patterns under different experimental conditions.Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. The goal of clustering in micro array technology is to group genes or experiments into clusters according to a similarity measure. In this paper we introduce the concept of micro Array technology, clustering on gene expression data and survey on similarity measure. Finally we conclude this paper promising that similarity measure plays an important role on gene expression data while using one of the data mining techniques is clustering.