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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Abstract
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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