Exploring Clustering Techniques for Microarray Gene Expression Data

  • Purnendu Mishra, Nilamani Bhoi


Analysis of DNA microarray has become the most commonly used valuable genomics approach in the field of bioinformatics. Clustering of genes information is a standard exploratory procedure used to distinguish firmly related genes. Clustering is fundamental in the process of data mining to uncover regular structures and distinguish intriguing patterns with regards to the basic large number of genes and the complex of biological data. Progressing research in this domain show that microarray managing will be supportive for the characterization disease genes. Various Artificial Intelligent strategies are in like way used to perceive the tumors and malady cells. Here, in this paper, distinctive proficient clustering techniques are discussed and analyzed about for the grouping of genes from the microarray gene expression dataset.