Visualizing biological pathways: requirements analysis, systems evaluation and research agenda

  • Authors:

  • Purvi Saraiya;Chris North;Karen Duca

  • Affiliations:

  • Center for Human-Computer Interaction, Virginia Polytechnic Institute and State University, Blacksburg, VA and Department of Computer Science, Virginia Polytechnic Institute and State University, ...;Center for Human-Computer Interaction, Virginia Polytechnic Institute and State University, Blacksburg, VA and Department of Computer Science, Virginia Polytechnic Institute and State University, ...;Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University

  • Venue:
  • Information Visualization - Special issue: Bioinformatics visualization
  • Year:
  • 2005

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Abstract

Pathway diagrams are used by life scientists to represent complex interactions at the molecular level in living cells. The recent shift towards data-intensive bioinformatics and systems-level science has created a strong need for advanced pathway visualizations that support exploratory analysis. This paper presents a comprehensive list of requirements for pathway visualization systems, based on interviews conducted to understand life scientists' needs for pathway analysis. A variety of existing pathway visualization systems are examined, to analyze common approaches by which the contemporary systems address these requirements. A heuristic evaluation, by biology domain experts, of five popular pathway visualization systems is conducted to analyze the end-user perception of these systems. Based on these studies, a research agenda is presented concerning five critical requirements for pathway visualization systems. If addressed effectively, these requirements can prove to be most helpful in supporting exploratory pathway analysis. These include: (1) automated construction and updating of pathways by searching literature databases, (2) overlaying information on pathways in a biologically relevant format, (3) linking pathways to multi-dimensional data from high-throughput experiments such as microarrays, (4) overviewing multiple pathways simultaneously with interconnections between them, (5) scaling pathways to higher levels of abstraction to analyze effects of complex molecular interactions at higher levels of biological organization.