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Cagatay Turkay, Julius Parulek, Helwig Hauser (University of Bergen, Bergen, Norway)
Biologists aim to understand the underlying relations in the complex and large datasets that are produced in their daily scientific practices. They generally make use of different computational tools to discover these relations. However, with the increasing complexity and the size of the datasets, these tools usually fail to provide reliable and interpretable results. We develop techniques for the interactive visual analysis (IVA) of biological data. With such techniques, we aim to de-couple the knowledge of the biologists with the computational tools in an iterative analysis loop. Here, we present examples of how IVA can improve the analysis of biological data, namely, molecular dynamics simulations, gene expression datasets and, molecular surfaces and cavities.