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Liis Kolberg, Hedi Peterson (University of Tartu, Tartu, Estonia)Clustering followed by functional enrichment analysis is widely applied to extract knowledge from large volumes of high-throughput genomic data. Though useful, this pipeline can be very time and resource demanding. Transforming the results into an informative visualization can be challenging for a researcher. funcExplorer is a web tool that automatically combines hierarchical clustering and enrichment analysis. The tool takes advantage of modern visualization toolkits to present the results in a visually compact and interactive manner, enabling to explore the biological essence of the data and gain better understanding. The underlying idea was first introduced in 2009 with a tool VisHiC. The present method and tool is a complete rewrite of its predecessor. Here we outline the evolution of such redevelopment process and the train of thought while implementing funcExplorer. Furthermore, we discuss the challenges faced while visualizing high-dimensional data, highlighting relevant information and including interactive components. We want to illustrate the learning and decision process of a developer without any previous development experience, as in science this is often the case.