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Abstract:
In recent years Systems Biology has become a massive information science, driven by data produced by the omics evolution. In order to interpret and discuss the data in interdisciplinary teams, visual representations are essential.
However, due to the tremendous amount and complexity of data, novel visualization techniques and navigation pattern are required which must be designed towards a specific task (e. g. looking for certain protein interactions) and should support modeling and exploratory analysis.
For this purpose we have developed a new GUI component using two complementary approaches - Zoomable User Interfaces (ZUI) and Visual Scenarios, both implemented in our modeling tool ProMoT. The ZUI approach improves navigation and interaction and enhances the analysis by adaptive visualizations of large-scale, highly complex and structured (modular, hierarchical) networks. Adaptive visualization methods are able to graphically abstract and modify the representation of the network.
The level of alteration is influenced by three criteria: (1) model structue (e. g. module-based features), (2) model semantics (e. g. type of protein) and (3) user task. Based on these criteria, entities in the network are emphasized and de-emphasized or hidden. This technique can be used to show the detail of biological information embedded in its context appropriate for the required task. Thus, a better differentiation between important and non-relevant information can be achieved.
A visual scenario is a set of visual mapping functions for changing visual properties of the network and a definition of adequate user interactions. Therewith, convenient and fast switching between different visual settings is feasible. Visualization techniques and the concept of visual scenarios are illustrated by both dynamic and logical models.