The use of network centralities in the field of network analysis plays an important role when the relative importance of nodes within the network topology should be rated. A single network can easily be represented by the use of standard graph drawing algorithms, but not only the exploration of one centrality might be important: the comparison of two or more of them is often crucial for a better understanding. When visualizing the comparison of several network centralities, we are facing new problems of how to show them in a meaningful way. For instance, we want to be able to track all the changes of centralities in the networks as well as to display the single networks as best as possible. In the life sciences, centrality measures help scientists to understand the underlying biological processes and have been successfully applied to different biological networks. The aim of this paper is to present a novel system for the interactive visualization of biochemical networks and its centralities. Researchers can focus on the exploration of the centrality values including the network structure without dealing with visual clutter or occlusions of nodes. Simultaneously, filtering based on statistical data concerning the network elements and centrality values supports this.
|Title of host publication||Proceedings of the International Conference on Information Visualization Theory and Applications|
|Publication status||Published - 2012|
|Event||IVAPP 12 - Rome, Italy, Austria|
Duration: 24 Feb 2012 → 26 Feb 2012
|Period||24.02.2012 → 26.02.2012|