A comparison of benchmark task and insight evaluation methods for information visualization
Information Visualization - Special issue on Evaluation for Information Visualization
Visual comparison for information visualization
Information Visualization - Special issue on State of the Field and New Research Directions
A novel 3D interactive visualization for medical data analysis
Proceedings of the 24th Australian Computer-Human Interaction Conference
Pathline: a tool for comparative functional genomics
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
The "Map" in the mental map: Experimental results in dynamic graph drawing
International Journal of Human-Computer Studies
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Systems biologists use interaction graphs to model the behavior of biological systems at the molecular level. In an iterative process, such biologists obser ve the reactions of living cells under various experimental conditions, view the results in the context of the interaction graph, and then propose changes to the graph model. These graphs ser ve as a form of dynamic knowledge representation of the biological system being studied and evolve as new insight is gained from the experimental data. While numerous graph layout and drawing packages are available, these tools did not fully meet the needs of our immunologist collaborators. In this paper, we describe the data information display needs of these immunologists and translate them into design decisions. These decisions led us to create Cerebral, a system that uses a biologically guided graph layout and incor porates experimental data directly into the graph display. Small multiple views of different experimental conditions and a data-driven parallel coordinates view enable correlations between experimental conditions to be analyzed at the same time that the data is viewed in the graph context. This combination of coordinated views allows the biologist to view the data from many different perspectives simultaneously. To illustrate the typical analysis tasks performed, we analyze two datasets using Cerebral. Based on feedback from our collaboratorsweconcludethat Cerebral is a valuable tool for analyzing experimental data in the context of an interaction graph model.