title: iVUN: interactive Visualization of Uncertain biochemical reaction Networks.
abstract: BACKGROUND
  Mathematical models are nowadays widely used to describe biochemical reaction networks. One of the main reasons for this is that models facilitate the integration of a multitude of different data and data types using parameter estimation. Thereby, models allow for a holistic understanding of biological processes. However, due to measurement noise and the limited amount of data, uncertainties in the model parameters should be considered when conclusions are drawn from estimated model attributes, such as reaction fluxes or transient dynamics of biological species.
  
  
  RESULTS
  We developed the visual analytics system iVUN that supports uncertainty-aware analysis of static and dynamic attributes of biochemical reaction networks modeled by ordinary differential equations. The multivariate graph of the network is visualized as a node-link diagram, and statistics of the attributes are mapped to the color of nodes and links of the graph. In addition, the graph view is linked with several views, such as line plots, scatter plots, and correlation matrices, to support locating uncertainties and the analysis of their time dependencies. As demonstration, we use iVUN to quantitatively analyze the dynamics of a model for Epo-induced JAK2/STAT5 signaling.
  
  
  CONCLUSIONS
  Our case study showed that iVUN can be used to perform an in-depth study of biochemical reaction networks, including attribute uncertainties, correlations between these attributes and their uncertainties as well as the attribute dynamics. In particular, the linking of different visualization options turned out to be highly beneficial for the complex analysis tasks that come with the biological systems as presented here.
authors.forename: Corinna
authors.initials: C
authors.lastname: Vehlow
authors.forename: Jan
authors.initials: J
authors.lastname: Hasenauer
authors.forename: Andrei
authors.initials: A
authors.lastname: Kramer
authors.forename: Andreas
authors.initials: A
authors.lastname: Raue
authors.forename: Sabine
authors.initials: S
authors.lastname: Hug
authors.forename: Jens
authors.initials: J
authors.lastname: Timmer
authors.forename: Nicole
authors.initials: N
authors.lastname: Radde
authors.forename: Fabian J
authors.initials: FJ
authors.lastname: Theis
authors.forename: Daniel
authors.initials: D
authors.lastname: Weiskopf
mesh_terms: D019295:Computational Biology / Q000379:methods; D003196:Computer Graphics; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D008956:Models, Chemical; D015398:Signal Transduction; D035501:Uncertainty