Cytoscape: Software for Visualization and Analysis of Biological Networks

  • Michael Kohl
  • Sebastian Wiese
  • Bettina Warscheid
Part of the Methods in Molecular Biology book series (MIMB, volume 696)


Substantial progress has been made in the field of “omics” research (e.g., Genomics, Transcriptomics, Proteomics, and Metabolomics), leading to a vast amount of biological data. In order to represent large biological data sets in an easily interpretable manner, this information is frequently visualized as graphs, i.e., a set of nodes and edges. Nodes are representations of biological molecules and edges connect the nodes depicting some kind of relationship.

Obviously, there is a high demand for computer-based assistance for both visualization and analysis of biological data, which are often heterogeneous and retrieved from different sources. This chapter focuses on software tools that assist in visual exploration and analysis of biological networks. Global requirements for such programs are discussed. Utilization of visualization software is exemplified using the widely used Cytoscape tool. Additional information about the use of Cytoscape is provided in the Notes section. Furthermore, special features of alternative software tools are highlighted in order to assist researchers in the choice of an adequate program for their specific requirements.


Biological Network Visualization Tool Visualization Software Molecular Interaction Network Visual Style 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is funded by the Bundesministerium für Bildung und Forschung (BMBF, grant 01 GS 08143) and by the Deutsche Forschungsgemeinschaft within the SFB 642. Thanks are also due to the Agilent Laboratories and Annette Adler for the financial support for the color versions of the figures.


  1. 1.
    Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504CrossRefPubMedGoogle Scholar
  2. 2.
    Harris MA, Clark J, Ireland A, Lomax J, Ashburner M, Foulger R et al (2004) The gene ontology (GO) database and informatics resource. Nucleic Acids Res 32:D258–D261CrossRefPubMedGoogle Scholar
  3. 3.
    Ashburner M, Ball CA, Blake JA, Butler H, Cherry JM, Corradi J et al (2001) Creating the gene ontology resource: design and implementation. Genome Res 11:1425–1433CrossRefGoogle Scholar
  4. 4.
    Vailaya A, Bluvas P, Kincaid R, Kuchinsky A, Creech M, Adler A (2005) An architecture for biological information extraction and representation. Bioinformatics 21:430–438CrossRefPubMedGoogle Scholar
  5. 5.
    Bader GD, Hogue CW (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform 4:2CrossRefGoogle Scholar
  6. 6.
    Maere S, Heymans K, Kuiper M (2005) BiNGO: a cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21:3448–3449CrossRefPubMedGoogle Scholar
  7. 7.
    Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C et al (2007) Integration of biological networks and gene expression data using cytoscape. Nat Protoc 2:2366–2382CrossRefPubMedGoogle Scholar
  8. 8.
    Rho S, You S, Kim Y, Hwang D (2008) From proteomics toward systems biology: integration of different types of proteomics data into network models. BMB Rep 41:184–193PubMedGoogle Scholar
  9. 9.
    Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M (1999) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 27:29–34CrossRefPubMedGoogle Scholar
  10. 10.
    Kanehisa M, Goto S (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27–30CrossRefPubMedGoogle Scholar
  11. 11.
    von Mering C, Jensen LJ, Snel B, Hooper SD, Krupp M, Foglierini M et al (2005) STRING: known and predicted protein–protein associations, integrated and transferred across organisms. Nucleic Acids Res 33:D433–D437CrossRefGoogle Scholar
  12. 12.
    Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J et al (2009) STRING 8: a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 37:D412–D416CrossRefPubMedGoogle Scholar
  13. 13.
    Krummenacker M, Paley S, Mueller L, Yan T, Karp PD (2005) Querying and computing with BioCyc databases. Bioinformatics 21:3454–3455CrossRefPubMedGoogle Scholar
  14. 14.
    Shannon PT, Reiss DJ, Bonneau R, Baliga NS (2006) The Gaggle: an open-source software system for integrating bioinformatics software and data sources. BMC Bioinform 7:176CrossRefGoogle Scholar
  15. 15.
    Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N et al (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34:374–378PubMedGoogle Scholar
  16. 16.
    Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S et al (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5:R80CrossRefPubMedGoogle Scholar
  17. 17.
    Team RDC (2005) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
  18. 18.
    Bare JC, Shannon PT, Schmid AK, Baliga NS (2007) The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications. BMC Bioinform 8:456CrossRefGoogle Scholar
  19. 19.
    Klukas C, Junker BH, Schreiber F (2006) The VANTED software system for transcriptomics, proteomics and metabolomics analysis. J Pestic Sci 31:289–292CrossRefGoogle Scholar
  20. 20.
    Junker BH, Klukas C, Schreiber F (2006) VANTED: a system for advanced data analysis and visualization in the context of biological networks. BMC Bioinform 7:109CrossRefGoogle Scholar
  21. 21.
    Funahashi A, Matsuoka Y, Jouraku A, Morohashi M, Kikuchi N, Kitano H (2008) Cell Designer 3.5: a versatile modeling tool for biochemical networks. Proc IEEE 96:1254–1265CrossRefGoogle Scholar
  22. 22.
    Funahashi A, Tanimura N, Morohashi M, Kitano H (2003) Cell Designer: a process diagram editor for gene-regulatory and biochemical networks. BioSilico 1:159–162CrossRefGoogle Scholar
  23. 23.
    Kitano H, Funahashi A, Matsuoka Y, Oda K (2005) Using process diagrams for the graphical representation of biological networks. Nat Biotechnol 23:961–966CrossRefPubMedGoogle Scholar
  24. 24.
    Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H et al (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19:524–531CrossRefPubMedGoogle Scholar
  25. 25.
    Hucka M, Finney A, Sauro H, Kovitz B, Keating S, Matthews J et al. (2003) Introduction to the systems biology workbench. []
  26. 26.
    Sauro HM, Hucka M, Finney A, Wellock C, Bolouri H, Doyle J et al (2003) Next generation simulation tools: the systems biology workbench and BioSPICE integration. OMICS 7:355–372CrossRefPubMedGoogle Scholar
  27. 27.
    Ulitsky I, Gat-Viks I, Shamir R (2008) MetaReg: a platform for modeling, analysis and visualization of biological systems using large-scale experimental data. Genome Biol 9:R1CrossRefPubMedGoogle Scholar
  28. 28.
    Iragne F, Nikolski M, Mathieu B, Auber D, Sherman D (2005) ProViz: protein interaction visualization and exploration. Bioinformatics 21:272–274CrossRefPubMedGoogle Scholar
  29. 29.
    Baitaluk M, Sedova M, Ray A, Gupta A (2006) Biological networks: visualization and analysis tool for systems biology. Nucleic Acids Res 34:W466–W471CrossRefPubMedGoogle Scholar
  30. 30.
    Baitaluk M, Qian XF, Godbole S, Raval A, Ray A, Gupta A (2006) PathSys: integrating molecular interaction graphs for systems biology. BMC Bioinform 7:55CrossRefGoogle Scholar
  31. 31.
    Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N et al (2005) Towards a proteome-scale map of the human protein–protein interaction network. Nature 437:1173–1178CrossRefPubMedGoogle Scholar
  32. 32.
    Agne B, Meindl NM, Niederhoff K, Einwachter H, Rehling P, Sickmann A et al (2003) Pex8p: an intraperoxisomal organizer of the peroxisomal import machinery. Mol Cell 11:635–646CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Michael Kohl
    • 1
  • Sebastian Wiese
    • 1
  • Bettina Warscheid
    • 1
    • 2
  1. 1.Medizinisches Proteom-CenterRuhr-Universität BochumBochumGermany
  2. 2.Clinical & Cellular Proteomics, Medical Faculty and Center for Medical BiotechnologyDuisburg-Essen UniversityEssenGermany

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