You are here

The visual analytics approach

This visual analytics system supports an uncertainty-aware analysis of static and dynamic attributes of biochemical reaction networks (BRNs). These are often described by mathematical models, such as ordinary differential equations (ODEs), which enable the integration of a multitude of different data and data types using parameter estimation. Due to the 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 to 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 identification of uncertainties and the analysis of their mutual dependencies as well as their time dependencies.

See the project page for further details.

Release Date:
June, 2013
Data type:
Java, Java Universal Network/Graph Framework Version 2.0.1, JMathPlot - Java library JMathTools, Systems Biology Markup Language
Windows, Mac, Ubuntu

Project development

Institution: VISUS – Visualization Research Center, University of Stuttgart, Germany, ST – Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany