In recent years,  relating gene expression to cancer development and
treatment has received a lot of attention. Unfortunately, the
availability of effective analysis tools lacks far behind the
availability of data. In this paper, we present the Gene Expression
Analyzer (GEA) for performing cluster analysis on gene expression data.
In particular, the GEA is developed to support the reality that cluster
analysis is typically a multi-step process. The underlying model of the
GEA provides a set of algebraic operators for manipulating the data, as
well as the intermediate results.  Moreover, the GEA provides
facilities to help the user to identify candidate genes for further
clinical analysis.  Last but not least, the GEA is optimized to
handle the high dimensionality of gene expression data.