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Corinna Vehlow, Jan Hasenauer, Andrei Kramer, Julian Heinrich, Nicole Radde, Frank Allgöwer and Daniel Weiskopf (Visualisierungsinstitut, Allmandring 19, 70569 Stuttgart)We present a visual analytics system that supports an uncertainty-aware analysis of static and dynamic attributes of biochemical reaction networks. These networks are often described by mathematical models, such as ODEs, which enable the integration of a multitude of different data and data types using parameter estimation. Due to the nevertheless limited amount of data, parameter estimation does not necessarily yield a single point in parameter space and many attributes of the model remain uncertain. Our system visualizes the model as a graph, where the statistics of the attributes are mapped onto the color of edges and vertices. The graph view is combined with several linked views such as lineplots, scatterplots, and correlation matrices, to support the analysis and location of uncertainties and their time dependencies.