A Visual Analytics Approach for Gene Expression Data

We present a new application, SpRay, designed for the visual exploration
of gene expression data. It is based on an extension and
adaption of parallel coordinates to support the visual exploration of
large and high-dimensional datasets. In particular, we investigate
the visual analysis of gene expression data as generated by microarray
experiments; We combine refined visual exploration with statistical
methods to a visual analytics approach that proved to be
particularly successful in this application domain. We will demonstrate
the usefulness on several multidimensional gene expression
datasets from different bioinformatics applications.