title: A taxonomy of visualization tasks for the analysis of biological pathway data.
abstract: BACKGROUND
  Understanding complicated networks of interactions and chemical components is essential to solving contemporary problems in modern biology, especially in domains such as cancer and systems research. In these domains, biological pathway data is used to represent chains of interactions that occur within a given biological process. Visual representations can help researchers understand, interact with, and reason about these complex pathways in a number of ways. At the same time, these datasets offer unique challenges for visualization, due to their complexity and heterogeneity.
  
  
  RESULTS
  Here, we present taxonomy of tasks that are regularly performed by researchers who work with biological pathway data. The generation of these tasks was done in conjunction with interviews with several domain experts in biology. These tasks require further classification than is provided by existing taxonomies. We also examine existing visualization techniques that support each task, and we discuss gaps in the existing visualization space revealed by our taxonomy.
  
  
  CONCLUSIONS
  Our taxonomy is designed to support the development and design of future biological pathway visualization applications. We conclude by suggesting future research directions based on our taxonomy and motivated by the comments received by our domain experts.
authors.affiliation: Electronic Visualization Laboratory, University of Illinois at Chicago, Chicago, IL, USA. pmurra5@uic.edu.
authors.forename: Paul
authors.initials: P
authors.lastname: Murray
authors.affiliation: eScience Group, Environmental Research and Innovation (ERIN) department, Luxembourg Institute of Science and Technology, Esch/Alzette, Luxembourg.
authors.forename: Fintan
authors.initials: F
authors.lastname: McGee
authors.affiliation: Electronic Visualization Laboratory, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Angus G
authors.initials: AG
authors.lastname: Forbes
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D036262:Empirical Research; D006801:Humans; D011506:Proteins / Q000737:chemistry / Q000235:genetics; D012107:Research Design; D012984:Software; D011795:Surveys and Questionnaires
chemical_list: D011506:Proteins
keywords: Biological pathways; Pathway visualization; Task taxonomy