Literature DB >> 26356945

Multivariate Network Exploration and Presentation: From Detail to Overview via Selections and Aggregations.

Stef van den Elzen, Jarke J van Wijk.   

Abstract

Network data is ubiquitous; e-mail traffic between persons, telecommunication, transport and financial networks are some examples. Often these networks are large and multivariate, besides the topological structure of the network, multivariate data on the nodes and links is available. Currently, exploration and analysis methods are focused on a single aspect; the network topology or the multivariate data. In addition, tools and techniques are highly domain specific and require expert knowledge. We focus on the non-expert user and propose a novel solution for multivariate network exploration and analysis that tightly couples structural and multivariate analysis. In short, we go from Detail to Overview via Selections and Aggregations (DOSA): users are enabled to gain insights through the creation of selections of interest (manually or automatically), and producing high-level, infographic-style overviews simultaneously. Finally, we present example explorations on real-world datasets that demonstrate the effectiveness of our method for the exploration and understanding of multivariate networks where presentation of findings comes for free.

Entities:  

Year:  2014        PMID: 26356945     DOI: 10.1109/TVCG.2014.2346441

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  9 in total

1.  Lineage: Visualizing Multivariate Clinical Data in Genealogy Graphs.

Authors:  Carolina Nobre; Nils Gehlenborg; Hilary Coon; Alexander Lex
Journal:  IEEE Trans Vis Comput Graph       Date:  2018-03-06       Impact factor: 4.579

2.  Pattern-Driven Navigation in 2D Multiscale Visualizations with Scalable Insets.

Authors:  Fritz Lekschas; Michael Behrisch; Benjamin Bach; Peter Kerpedjiev; Nils Gehlenborg; Hanspeter Pfister
Journal:  IEEE Trans Vis Comput Graph       Date:  2019-08-22       Impact factor: 4.579

Review 3.  Molecular networks in Network Medicine: Development and applications.

Authors:  Edwin K Silverman; Harald H H W Schmidt; Eleni Anastasiadou; Lucia Altucci; Marco Angelini; Lina Badimon; Jean-Luc Balligand; Giuditta Benincasa; Giovambattista Capasso; Federica Conte; Antonella Di Costanzo; Lorenzo Farina; Giulia Fiscon; Laurent Gatto; Michele Gentili; Joseph Loscalzo; Cinzia Marchese; Claudio Napoli; Paola Paci; Manuela Petti; John Quackenbush; Paolo Tieri; Davide Viggiano; Gemma Vilahur; Kimberly Glass; Jan Baumbach
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2020-04-19

4.  TS-Extractor: large graph exploration via subgraph extraction based on topological and semantic information.

Authors:  Kun Fu; Tingyun Mao; Yang Wang; Daoyu Lin; Yuanben Zhang; Junjian Zhan; Xian Sun; Feng Li
Journal:  J Vis (Tokyo)       Date:  2020-09-22       Impact factor: 1.331

5.  GRAPHIE: graph based histology image explorer.

Authors:  Hao Ding; Chao Wang; Kun Huang; Raghu Machiraju
Journal:  BMC Bioinformatics       Date:  2015-08-13       Impact factor: 3.169

6.  Juniper: A Tree+ Table Approach to Multivariate Graph Visualization.

Authors:  Carolina Nobre; Marc Streit; Alexander Lex
Journal:  IEEE Trans Vis Comput Graph       Date:  2018-09-03       Impact factor: 4.579

7.  A taxonomy of visualization tasks for the analysis of biological pathway data.

Authors:  Paul Murray; Fintan McGee; Angus G Forbes
Journal:  BMC Bioinformatics       Date:  2017-02-15       Impact factor: 3.169

8.  Graffinity: Visualizing Connectivity in Large Graphs.

Authors:  E Kerzner; A Lex; C L Sigulinsky; T Umess; B W Jones; R E Marc; M Meyer
Journal:  Comput Graph Forum       Date:  2017-07-04       Impact factor: 2.078

9.  Deep Graph Mapper: Seeing Graphs Through the Neural Lens.

Authors:  Cristian Bodnar; Cătălina Cangea; Pietro Liò
Journal:  Front Big Data       Date:  2021-06-16
  9 in total

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