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Table 4 Support scientists would have liked for explanatory analysis

From: Supporting cognition in systems biology analysis: findings on users' processes and design implications

Content Edges in networks weighted by biological traits
  Overlays of protein-protein interactions and disease associations
  Overlays of protein-protein interactions and relevant pathways
  Distinctions between proteins and other molecules that might serve as mediators of interactions, e.g. enzymes
  Test statistics and counts (e.g. # of interactions, # of articles, overrepresentation of a functional term) and perceptually encoding nodes or links by them
Interactivity Updating of interactions (e.g. selection, color coding) across views – e.g. across overlaid networks
  Facile filtering (users had to use mini-scripting to filter)
  Facile color-coding (at the time it took 15+ steps to color code)
  Integrating one's own data into the displayed dataset
  Simplifying networks through zooming, filtering, color-coding, expanding some nodes but not others, mapping only select neighbors to pathways
  Conducting computations on networks to find e.g. shared paths to identify indirect interactions or recurrent or aberrant patterns that might signal a biologically significant set of relationships
Workspaces Spaces for comparing different networks side-by-side with dynamically linked interactions
  Spaces for aggregating entities on the fly into manipulable qualitative attributes based on emerging knowledge (e.g. normal vs disease conditions)