BioLinker: Bottom-up exploration of protein interaction networks

Tommy Dang, Paul Murray, Angus Forbes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Systems biologists and cancer researchers require interactive visualization tools that enable them to more easily navigate and discover patterns at different levels of the biological hierarchy of signaling pathways. Furthermore, biologists are often interested in understanding and exploring the causal biochemical links between processes. When exploring the literature of particular biological pathways or specific proteins within those pathways, biologists find it useful to know the contexts in which biochemical links are active and, importantly, to be aware of potential conflicts when different experiments introduce alternative interpretations of the function of a pathway or biochemical reaction. We introduce BioLinker, a interactive visualization system that helps users to perform bottom-up exploration of complex protein interaction networks. Five interconnected views provide the user with a range of ways to explore pathway data, including views that show potential conflicts within pathway databases and publications and that highlight contextual information about individual proteins. Additionally, we discuss system details to show how our system manages the large amount of protein interactions extracted from the literature of biological pathways.

Original languageEnglish
Title of host publication2017 IEEE Pacific Visualization Symposium, PacificVis 2017 - Proceedings
EditorsYingcai Wu, Daniel Weiskopf, Tim Dwyer
PublisherIEEE Computer Society
Pages265-269
Number of pages5
ISBN (Electronic)9781509057382
DOIs
StatePublished - Sep 11 2017
Event10th IEEE Pacific Visualization Symposium, PacificVis 2017 - Seoul, Korea, Republic of
Duration: Apr 18 2017Apr 21 2017

Publication series

NameIEEE Pacific Visualization Symposium
ISSN (Print)2165-8765
ISSN (Electronic)2165-8773

Conference

Conference10th IEEE Pacific Visualization Symposium, PacificVis 2017
Country/TerritoryKorea, Republic of
CitySeoul
Period04/18/1704/21/17

Keywords

  • Dynamic network visualization
  • Potential conflict matrix
  • Protein interaction network

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