CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Selection: 524,288 ways to say "this is interesting"
INFOVIS '96 Proceedings of the 1996 IEEE Symposium on Information Visualization (INFOVIS '96)
Navigating Hierarchies with Structure-Based Brushes
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs
Computational & Mathematical Organization Theory
Implicit brushing and target snapping: data exploration and sense-making on large displays
Proceedings of the working conference on Advanced visual interfaces
Drawing bipartite graphs as anchored maps
APVis '06 Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60
Fisheye Tree Views and Lenses for Graph Visualization
IV '06 Proceedings of the conference on Information Visualization
Dynamic exploration and editing of KEGG pathway diagrams
Bioinformatics
Jigsaw: supporting investigative analysis through interactive visualization
Information Visualization
EdgeLens: an interactive method for managing edge congestion in graphs
INFOVIS'03 Proceedings of the Ninth annual IEEE conference on Information visualization
Visual inspection of multivariate graphs
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
Visual analytics for stochastic simulation in cell biology
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
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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.