Applying Information Visualization Principles to Biological Network Displays

Tamara Munzner
Proc. SPIE-IS&T Human Vision and Electronic Imaging 2011, SPIE Vol 7865, 78650D1-13.
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We use the principles of information visualization to guide the design of systems to best meet the needs of specific targets group of users, namely biologists who have different tasks involving the visual exploration of biological networks. For many biologists who explore networks of interacting proteins and genes, the topological structure of these node-link graphs is only one part of the story. The Cerebral system supports graph layout in a style inspired by hand-drawn pathway diagrams, where location of the proteins within the cell constrains the location within the drawing, and functional groups of proteins are visually apparent as clusters. It also supports exploration of expression data using linked views, to show these multiple attributes at each node in the graph. The Pathline system attacks the problem of visually encoding the biologically interesting relationships between multiple pathways, multiple genes, and multiple species. We propose new methods based on the principle that perception of spatial position is the most accurate visual channel for all data types. The curvemap view is an alternative to heatmaps, and linearized pathways support the comparison of quantitative display as a primary task while showing topological information at a secondary level.



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