Data visualisation can be an extremely efficient way of analyzing and discovering new knowledge from data. More often than not, we have background knowledge about the data, which we can then use to find meaningful and useful visualizations. This thesis examines the influence of gene sets gained from MSigDB upon the quality of visualizations of DNA microarrays. We hypothesize, that we can use gene sets to gain better and clearer visualizations. In the first chapter we explain what data visualization is, and introduce our working methods. At the end of the first chapter we present a method called VizRank, which allows us to automatically find and rate quality visualizations. This is followed by the second chapter, in which we describe the DNA microarray data and the data of gene sets. In the last part we present our experiential work, which is split into three sections. In each individual section we present the idea, procedure, solution and analysis of the results of experimentation.