Exploration of Gene Expression Data in a Visually Linked Environment

The development of high throughput genetic analysis techniques, such as microarray DNA chips, opened the gates for the simultaneous analysis of gene expression of thousands of genes. This data can be used for diagnostic and research purposes alike. With ever more data being generated, the problem of deriving knowledge from it increases, not at last due to its multidimensionality. In this thesis the integrated application of two established multidimensional information visualization methods is proposed: parallel coordinates and heat maps. The true value of knowledge about gene expression regulation can only be exploited when information about the biological context is available. That knowledge is modeled in special graphs, called pathways. Previous work in the Caleydo framework established a 2.5D pathway visualization method. The goal of this thesis is to bring the pathways into context with high level gene expression visualization methods, by employing visual links among pathway elements and expression data. The visual links are drawn among up to five independent views, arranged in 3D, simultaneously, thereby showing relations which were previously difficult to identify.

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