HCIL-2003-25, CS-TR-4486, UMIACS-TR-2003-55, ISR-TR-2005-68
Motivation: Multidimensional data sets are common in many research areas, including
microarray experiment data sets. Genome researchers are using cluster analysis to find
meaningful groups in microarray data. However, the high dimensionality of the data sets hinders
users from finding interesting patterns, clusters, and outliers. Determining the biological
significance of such features remains problematic due to the difficulties of integrating biological
knowledge. In addition, it is not efficient to perform a cluster analysis over the whole data set in
cases where researchers know the approximate temporal pattern of the gene expression that they
Results: To address these problems, we add three new features to the Hierarchical Clustering
Explorer (HCE): (1) scatterplot ordering methods so that all 2D projections of a high
dimensional data set can be ordered according to relevant criteria, (2) a gene ontology browser,
coupled with clustering results so that known gene functions within a cluster can be easily
studied, (3) a profile search so that genes with a certain temporal pattern can be easily identified.
Availability: HCE 2.0 is a PC application written in Microsoft Visual C++. The full application
and user's manual of HCE 2.0 with three new features is freely available at
http://www.cs.umd.edu/hcil/hce/ for academic or research purposes.