Visual Analysis of Bipartite Biological Networks

Abstract : In life sciences, the importance of complex network visualization is ever increasing. Yet, existing approaches for the visualization of networks are general purpose techniques that are often not suited to support the specific needs of researchers in the life sciences, or to handle the large network sizes and specific network characteristics that are prevalent in the field. Examples for such networks are biomedical ontologies and biochemical reaction networks, which are bipartite networks - a particular graph class which is rarely addressed in visualization. Our table-based approach allows to visualize large bipartite networks alongside with a multitude of attributes and hyperlinks to biological databases. To explore complex network motifs and perform intricate selections within the visualized network data, we introduce a new script-based brushing mechanism that integrates naturally with the interlinked, tabular representation. A prototype for exploring bipartite graphs, which uses the proposed visualization and interaction techniques, is also presented and used on real data sets from the application domain.
Type de document :
Communication dans un congrès
Eurographics Workshop on Visual Computing for Biomedicine, Oct 2008, Delft, Netherlands. 2008, 〈10.2312/VCBM/VCBM08/135-142〉
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Soumis le : mardi 3 janvier 2012 - 17:31:33
Dernière modification le : mercredi 11 avril 2018 - 16:16:01
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Hans-Jörg Schulz, Mathias John, Andrea Unger, Heidrun Schumann. Visual Analysis of Bipartite Biological Networks. Eurographics Workshop on Visual Computing for Biomedicine, Oct 2008, Delft, Netherlands. 2008, 〈10.2312/VCBM/VCBM08/135-142〉. 〈hal-00656214〉



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