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Visualizing Multivariate Hierarchic Data Using Enhanced Radial Space-Filling Layout

  • Ming Jia
  • Ling Li
  • Erin Boggess
  • Eve Syrkin Wurtele
  • Julie A. Dickerson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6453)

Abstract

Currently, visualization tools for large ontologies (e.g., pathway and gene ontologies) result in a very flat wide tree that is difficult to fit on a single display. This paper develops the concept of using an enhanced radial space-filling (ERSF) layout to show biological ontologies efficiently. The ERSF technique represents ontology terms as circular regions in 3D. Orbital connections in a third dimension correspond to non-tree edges in the ontology that exist when an ontology term belongs to multiple categories. Biologists can use the ERSF layout to identify highly activated pathway or gene ontology categories by mapping experimental statistics such as coefficient of variation and overrepresentation values onto the visualization. This paper illustrates the use of the ERSF layout to explore pathway and gene ontologies using a gene expression dataset from E. coli.

Keywords

Gene Ontology Span Tree Information Visualization Minor Parent Gene Ontology Category 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ming Jia
    • 1
  • Ling Li
    • 2
  • Erin Boggess
    • 1
  • Eve Syrkin Wurtele
    • 2
  • Julie A. Dickerson
    • 1
  1. 1.Dept. of Electrical and Computer EngineeringIowa State UniversityAmesUSA
  2. 2.Dept. of Genetics, Development and Cell BiologyIowa State UniversityAmesUSA

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