The Community for Technology Leaders
Green Image
Issue No. 06 - November/December (2008 vol. 14)
ISSN: 1077-2626
pp: 1253-1260
Aaron Barsky , University of British Columbia
Tamara Munzner , University of British Columbia
Jennifer Gardy , University of British Columbia
Robert Kincaid , Agilent Labs, Agilent Technologies
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. 
Index Terms—Graph layout, systems biology visualization, small multiples, design study

J. Gardy, A. Barsky, T. Munzner and R. Kincaid, "Cerebral: Visualizing Multiple Experimental Conditions on a Graph with Biological Context," in IEEE Transactions on Visualization & Computer Graphics, vol. 14, no. , pp. 1253-1260, 2008.
1610 ms
(Ver 3.3 (11022016))