gms | German Medical Science

63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

02. - 06.09.2018, Osnabrück

NDExR and Cytoscape: interactive and automated visualization of biological networks using R

Meeting Abstract

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  • Florian Auer - Universitätsmedizin Göttingen, Göttingen, Deutschland
  • Frank Kramer - Universitätsmedizin Göttingen, Göttingen, Deutschland
  • Tim Beißbarth - Universitätsmedizin Göttingen, Göttingen, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Osnabrück, 02.-06.09.2018. Düsseldorf: German Medical Science GMS Publishing House; 2018. DocAbstr. 218

doi: 10.3205/18gmds087, urn:nbn:de:0183-18gmds0877

Veröffentlicht: 27. August 2018

© 2018 Auer et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



Network models form a simple and flexible way of representing diverse associations within complex systems, and its applications are well-established in a wide range of fields in biology [1], [2], [3]. Within a common bioinformatics workflow data integration, network analysis and visualization accompany each other [4], [5], and comprise fundamental challenges of combining various tools. Implementation of fully automated pipelines enhances the intricacy of such tasks furthermore [6].

Using standard technologies, we demonstrate a course from data acquisition to the finished visualization, and options to achieve the individual sub tasks. Thereby the network data exchange (NDEx) platform [7], [8] and the Cytoscape project [9], and appendant R [10], form the core components.

We use our R package ndexr [11] to retrieve networks from the public NDEx platform, and also to store the results for later collaboration and publication. Cytoscape is one of the most popular open-source software tools for the visual exploration of biomedical networks. Beside the graphical interface, the latest release offers a RESTful interface [12], [13] and R packages [14], [15] providing access to it.

Along an exemplary bioinformatics workflow, we demonstrate how the single steps can be performed not only interactively, but also in a fully automated manner. Each step can be done using Cytoscape or R, or a combination of both: Controlling Cytoscape remotely from within R. Starting at an interactive analysis we move towards automation, illustrating the interchangeability and flexibility of the different approaches.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.

This contribution has already been published [16].


Califano A, Butte AJ, Friend S, Ideker T, Schadt E. Leveraging models of cell regulation and GWAS data in integrative network-based association studies. Nat Genet. 2012;44:841–847. DOI: 10.1038/ng.2355 Externer Link
Chung SS, Pandini A, Annibale A, Coolen ACC, Thomas NSB, Fraternali F. Bridging topological and functional information in protein interaction networks by short loops profiling. Sci Rep. 2015;5:8540. DOI: 10.1038/srep08540 Externer Link
Oulas A, Minadakis G, Zachariou M, Sokratous K, Bourdakou MM, Spyrou GM. Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches. Brief Bioinform. 2017. DOI: 10.1093/bib/bbx151 Externer Link
Gligorijević V, Pržulj N. Methods for biological data integration: perspectives and challenges. J R Soc Interface. 2015;12:20150571. DOI: 10.1098/rsif.2015.0571 Externer Link
Pavlopoulos GA, Malliarakis D, Papanikolaou N, Theodosiou T, Enright AJ, Iliopoulos I. Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future. GigaScience. 2015;4:1–27. DOI: 10.1186/s13742-015-0077-2 Externer Link
Leipzig J. A review of bioinformatic pipeline frameworks. Brief Bioinform. 2017;18:530–536. DOI: 10.1093/bib/bbw020 Externer Link
Pillich RT, Chen J, Rynkov V, Welker D, Pratt D. NDEx: A Community Resource for Sharing and Publishing of Biological Networks. Methods Mol Biol. 2017;1558:271–301. DOI: 10.1007/978-1-4939-6783-4_13 Externer Link
Pratt D, Chen J, Welker D, Rivas R, Pillich R, Rynkov V, et al. NDEx, the Network Data Exchange. Cell Syst. 2015;1:302–305. DOI: 10.1016/j.cels.2015.10.001 Externer Link
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–2504. DOI: 10.1101/gr.1239303 Externer Link
R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2008.
Auer F, Hammoud Z, Ishkin A, Pratt D, Ideker T, Kramer F, Kelso J. ndexr - an R package to interface with the network data exchange. Bioinformatics. 2018;34(4):716–717. DOI: 10.1093/bioinformatics/btx683 Externer Link
Fielding RT, Taylor RN. Principled design of the modern Web architecture. ACM Trans Internet Technol TOIT. 2002;2(2):115–150.
Ono K, Muetze T, Kolishovski G, Shannon P, Demchak B. CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API. F1000Research. 2015;4:478. DOI: 10.12688/f1000research.6767.1 Externer Link
Csardi G, Nepusz T. The igraph software package for complex network research. InterJournal Complex Systems. 2006:1695.
Shannon PT, Grimes M, Kutlu B, Bot JJ, Galas DJ. RCytoscape: tools for exploratory network analysis. BMC Bioinformatics. 2013;14:217. DOI: 10.1186/1471-2105-14-217 Externer Link
Auer F, Kramer F, Beißbarth T. NDExR and Cytoscape: Interactive and automated visualization of biological networks using R. In: Workshop on Computational Models in Biology and Medicine 2018, Joint workshop of the GMDS/IBS-DR working groups "Statistical Methods in Bioinformatics" and "Mathematical Models in Medicine and Biology. 2018. Available from: Externer Link