  Microarrays are made it possible to simultaneously monitor the expression
profiles of thousands of genes under various experimental conditions.
Identification of co-expressed genes and coherent patterns is the central goal
in microarray or gene expression data analysis and is an important task in
Bioinformatics research. In this paper, K-Means algorithm hybridised with
Cluster Centre Initialization Algorithm (CCIA) is proposed Gene Expression
Data. The proposed algorithm overcomes the drawbacks of specifying the number
of clusters in the K-Means methods. Experimental analysis shows that the
proposed method performs well on gene Expression Data when compare with the
traditional K- Means clustering and Silhouette Coefficients cluster measure.
