A STUDY ON MICROARRAY GENE EXPRESSION DATA AND CLUSTERING ANALYSIS

After genome sequencing, DNA microarray analysis has become the most widely used functional genomics approach in the bioinformatics field. Biologists are hugely weighed down by the massive amount of unparalleled qualities of genome-wide data produced by the DNA Microarray experiment.Clustering is the process of grouping data objects into set of disjoint classes called clusters so that objects within a class are highly similar with one another and dissimilar with the objects in other classes.Clustering is one of most useful tools for the microarray gene expression data analysis. The remote method provides a divide-and?conquer strategy to extract information from expression shape. In this paper, the highlighted procedures followed by different categories provide a structure for further development with better understanding.