Gene Expression Analysis Using Fuzzy K-Means Clustering

The recent advances of array technologies have made it possible to monitor huge amount of genes expression data. Clustering, for example, hierarchical clustering, self-organizing maps (SOM), kmeans clustering, has become important analysis for such gene expression data. We have applied the Fuzzy adaptive resonance theory (Fuzzy ART) [5] to the gene clustering of DNA microarray data and the clustering result using this method was more suitable for biological knowledge than those of the ordinary method including hierarchical clustering, SOM, and k-means clustering. In this study, therefore, Fuzzy k-means [2, 3] clustering method was applied to this data, since this method also have fuzziness as Fuzzy ART. We verified the clustering results using Fuzzy k-means clustering by comparing with those of hierarchical clustering, k-mean clustering, Fuzzy ART and SOM.