Eisen’s tree view is a useful tool for clustering and displaying of microarray gene expression data. In Eisen’s tree view system, a hierarchical method is used for clustering data. However, some useful information in gene expression data may not be well drawn when a hierarchical clustering is directly used in Eisen’s tree view. In this paper, we embed the similarity-based clustering method (SCM) into the tree view system so that microarray data can be re-organized according to the structure of data. The created SCM-driven tree view can give a better dendrogram display for microarray gene expression data with more useful information.
Relation:
Artificial Intelligence and Soft Computing Lecture Notes in Computer Science, 8648 , 207-215
