Dominant Sets in Microarray Data

Clustering allows us to extract groups of genes that are tightly coexpressed from Microarray data. In this paper, a new method DSF_Clust is developed to find dominant sets (clusters). We have preformed DSF_Clust on several gene expression datasets and given the evaluation with some criteria. The results showed that this approach could cluster dominant sets of good quality compared to kmeans method. DSF_Clust deals with three issues that have bedeviled clustering, some dominant sets being statistically determined in a significance level, predefining cluster structure being not required, and the quality of a dominant set being ensured. We have also applied this approach to analyze published data of yeast cell cycle gene expression and found some biologically meaningful gene groups to be dug out. Furthermore, DSF_Clust is a potentially good tool to search for putative regulatory signals. 2. INTRODUCTION