Visual Analysis of Microarray Data from Bioinformatics Applications

Abstract

We present a new application designed for the visual exploration of microarray 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, which proved to be particularly successful in this application domain. We will demonstrate the usefulness on several multidimensional gene-expression datasets from different bioinformatics applications.