GeneVis: simulation and visualization of genetic networks

Charles Baker1
Sheelagh Carpendale2
Przemyslaw Prusinkiewicz2
Michael Surette3
1Southern Alberta Mass Spectrometry Centre, Health Sciences Centre, University of Calgary, Calgary, Alberta, Canada
2Department of Computer Science, University of Calgary, Calgary, Alberta, Canada
3Department of Microbiology and Infectious Disease, University of Calgary, Calgary, Alberta, Canada

Abstract

GeneVis simulates genetic networks and visualizes the process of this simulation interactively, providing a visual environment for exploring the dynamics of genetic regulatory networks. The visualization environment supports several representational modes, which include: an individual protein representation, a protein concentration representation, and a network structure representation. The individual protein representation shows the activities of the individual proteins. The protein concentration representation illustrates the relative spread and concentrations of the different proteins in the simulation. The network structure representation depicts the genetic network dependencies that are present in the simulation. GeneVis includes several interactive viewing tools. These include animated transitions from the individual protein representation to the protein concentration representation and from the individual protein representation to the network structure representation. Three types of lenses are used to provide different views within a representation: fuzzy lenses, base pair lenses, and the network structure ring lens. With a fuzzy lens an alternate representation can be viewed in a selected region. The base pair lenses allow users to reposition genes for better viewing or to minimize interference during the simulation. The ring lens provides detail-incontext viewing of individual levels in the genetic network structure representation.

Reference

C. Baker, S., Carpendale, P. Prusinkiewicz, M. Surette: GeneVis: simulation and visualization of genetic networks. Journal of Information Visualization 2 (4), pp. 201-217.

Download from the publisher's site, or download from here (PDF,650kb).

Back to Publications