Graph query algebra and visual proximity rules for biological pathway exploration. (July 2017)

• Record Type: Journal Article
• Authors: Wu, Keqin; Sun, Liang; Schmidt, Carl; Chen, Jian
• Is Part Of: Information visualization. Volume 16:Number 3(2017)
• Page Start: 217
• Page End: 231
• Publication Date: 2017-07
• Subjects: Biological pathway -- relational query -- interactive metaphor -- visual analytics -- graph visualization; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/1473871616666394
• Languages: English
• ISSNs: 1473-8716

Abstract

We present the design and validation of an example-based pathway graph query algebra and visual proximity rules to address challenging large biological pathway exploration tasks. Our pathway graph query algebra interprets relationship queries given by selected examples to find a match for, extract identical parts between, or trace a path from any pathway components. To support the relationship query, users can composite pathway visualizations through visual proximity rules that use proximity to infer users' intentions in the exploration process. By allowing selection of one or more objects from multiple on-screen grouped graphs as query inputs and using the query outputs as next-query inputs, pathway graph query algebra and visual proximity rules achieve intuitiveness, concurrence, and dynamics for pathway exploration.