Graph Drawing: Algorithms for the Visualization of Graphs
Graph Drawing: Algorithms for the Visualization of Graphs
Planar Polyline Drawings with Good Angular Resolution
GD '98 Proceedings of the 6th International Symposium on Graph Drawing
GRIP: Graph dRawing with Intelligent Placement
GD '00 Proceedings of the 8th International Symposium on Graph Drawing
Comparison of metabolic pathways using constraint graph drawing
APBC '03 Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003 - Volume 19
Querying and computing with BioCyc databases
Bioinformatics
Visualizing biological pathways: requirements analysis, systems evaluation and research agenda
Information Visualization - Special issue: Bioinformatics visualization
Motif Search in Graphs: Application to Metabolic Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
GD'05 Proceedings of the 13th international conference on Graph Drawing
An efficient implementation of sugiyama's algorithm for layered graph drawing
GD'04 Proceedings of the 12th international conference on Graph Drawing
A compound graph layout algorithm for biological pathways
GD'04 Proceedings of the 12th international conference on Graph Drawing
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Metabolic networks have been drawn manually for many years, and over time have developed representational conventions that make them familiar to biologists. With increasing current biological discoveries, these networks need to be frequently updated and modified, and automatic visualization algorithms are thus becoming a necessity. Many existing automatic graph layout algorithms exist, and it is not known whether such generic algorithms are sufficiently useful for biologists, or whether algorithms that specifically consider the existing representational conventions are necessary. No prior task efficiency evaluation studies have been performed on biological network visualizations. This paper reports on an experiment comparing the task efficiency of biologically relevant motif-search tasks using three layouts, two of which were produced using existing generic graph layout algorithms (Force Directed, Hierarchical), and one which was specifically designed to take existing metabolic representation conventions into account (MetaViz). Despite the search task favouring the easy identification of node connectivity in the Force Directed layout, the results showed no efficiency difference between Force Directed and MetaViz. We conclude that embodying the representational conventions in an automatic algorithm is not an impediment to task efficiency, and that some minor improvements to MetaViz would enhance its usefulness for biologists even further.