Heterogeneous Networks on Multiple Levels

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8380)


Heterogeneous networks and multi-level networks occur in several application fields where their integration, combination, comparison, analysis, and visualization poses major challenges. In this chapter, we analyze the general characteristics of this type of data and identify examples in three application domains: biology, social sciences, and software engineering. Conceptually, we focus on sets of multivariate networks at two or more levels. Each level may describe a specific scale, and within each level several related heterogeneous networks are represented. We allow n:m mappings within the same level, but only 1:n mappings across levels that must be consecutive. This leads to a structured data set that is the basis for further visual analysis. Our chapter ends with ideas to visualize those networks together with the relationships between them and highlights research challenges.


Metabolic Network Gene Regulatory Network Biological Network Multivariate Data Heterogeneous Network 
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.


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  1. 1.
    Abuthawabeh, A., Beck, F., Zeckzer, D., Diehl, S.: Finding Structures in Multi-Type Code Couplings with Node-Link and Matrix Visualizations. In: Proceedings of the First IEEE Working Conference on Software Visualization, VISSOFT 2013 (2013)Google Scholar
  2. 2.
    Abuthawabeh, A., Zeckzer, D.: IMMV: An Interactive Multi-Matrix Visualization for Program Comprehension. In: Proceedings of the First IEEE Working Conference on Software Visualization, VISSOFT 2013 (2013)Google Scholar
  3. 3.
    Albrecht, M., Kerren, A., Klein, K., Kohlbacher, O., Mutzel, P., Paul, W., Schreiber, F., Wybrow, M.: On open problems in biological network visualization. In: Eppstein, D., Gansner, E.R. (eds.) GD 2009. LNCS, vol. 5849, pp. 256–267. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Bader, G.D., Cary, M.P., Sander, C.: Pathguide: a pathway resource list. Nucleic Acids Research 34, D504–D506 (2006)CrossRefGoogle Scholar
  5. 5.
    Balasundaram, B., Butenko, S.: Network clustering. In: Junker, B.H., Schreiber, F. (eds.) Analysis of Biological Networks. Wiley Series on Bioinformatics, Computational Techniques and Engineering, pp. 113–138. Wiley (2008)Google Scholar
  6. 6.
    Bezerianos, A., Chevalier, F., Dragicevic, P., Elmqvist, N., Fekete, J.D.: Graphdice: A system for exploring multivariate social networks. Computer Graphics Forum (Proc. EuroVis 2010) 29(3), 863–872 (2010)CrossRefGoogle Scholar
  7. 7.
    Borisjuk, L., Hajirezaei, M., Klukas, C., Rolletschek, H., Schreiber, F.: Integrating data from biological experiments into metabolic networks with the DBE information system. In Silico Biology 5, e11 (2004)Google Scholar
  8. 8.
    Byelas, H., Bondarev, E., Telea, A.: Visualization of areas of interest in component-based system architectures. In: Proceedings of the 32nd Euromicro Conference on Software Engineering and Advanced Applications, pp. 160–169. IEEE Computer Society Press (2006)Google Scholar
  9. 9.
    Börner, K., Sanyal, S., Vespignani, A.: Network science. In: Cronin, B. (ed.) Annual Review of Information Science and Technology, pp. 537–607. Information Today, Inc./American Society for Information Science and Technology (2007)Google Scholar
  10. 10.
    Christakis, N.A., Fowler, J.H.: The spread of obesity in a large social network over 32 years. New England Journal of Medicine 357, 370–379 (2007)CrossRefGoogle Scholar
  11. 11.
    Cohen-Cole, E., Fletcher, J.M.: Detecting implausible social network effects in acne, height, and headaches: longitudinal analysis. BMJ, 337 (2008)Google Scholar
  12. 12.
    Collins, C., Carpendale, S.: Vislink: Revealing relationships amongst visualizations. IEEE Transactions on Visualization and Computer Graphics 13(6), 1192–1199 (2007)CrossRefGoogle Scholar
  13. 13.
    Czauderna, T., Klukas, C., Schreiber, F.: Editing, validating and translating of SBGN maps. Bioinformatics 26(18), 2340–2341 (2010)CrossRefGoogle Scholar
  14. 14.
    Demir, E., Cary, M.P., Paley, S., Fukuda, K., Lemer, C., Vastrik, I., Wu, G., D’Eustachio, P., Schaefer, C., Luciano, J., Schacherer, F., Martinez-Flores, I., Hu, Z., Jimenez-Jacinto, V., Joshi-Tope, G., Kandasamy, K., Lopez-Fuentes, A.C., Mi, H., Pichler, E., Rodchenkov, I., Splendiani, A., Tkachev, S., Zucker, J., Gopinath, G., Rajasimha, H., Ramakrishnan, R., Shah, I., Syed, M., Anwar, N., Babur, O., Blinov, M., Brauner, E., Corwin, D., Donaldson, S., Gibbons, F., Goldberg, R., Hornbeck, P., Luna, A., Murray-Rust, P., Neumann, E., Ruebenacker, O., Reubenacker, O., Samwald, M., van Iersel, M., Wimalaratne, S., Allen, K., Braun, B., Whirl-Carrillo, M., Cheung, K.H., Dahlquist, K., Finney, A., Gillespie, M., Glass, E., Gong, L., Haw, R., Honig, M., Hubaut, O., Kane, D., Krupa, S., Kutmon, M., Leonard, J., Marks, D., Merberg, D., Petri, V., Pico, A., Ravenscroft, D., Ren, L., Shah, N., Sunshine, M., Tang, R., Whaley, R., Letovksy, S., Buetow, K.H., Rzhetsky, A., Schachter, V., Sobral, B.S., Dogrusoz, U., McWeeney, S., Aladjem, M., Birney, E., Collado-Vides, J., Goto, S., Hucka, M., Novere, N.L., Maltsev, N., Pandey, A., Thomas, P., Wingender, E., Karp, P.D., Sander, C., Bader, G.D.: The BioPAX community standard for pathway data sharing. Nature Biotechnology 28(9), 935–942 (2010)CrossRefGoogle Scholar
  15. 15.
    Dogrusoz, U., Giral, E., Cetintas, A., Civril, A., Demir, E.: A compound graph layout algorithm for biological pathways. In: Pach, J. (ed.) GD 2004. LNCS, vol. 3383, pp. 442–447. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  16. 16.
    Dunne, C., Henry-Riche, N., Lee, B., Metoyer, R., Robertson, G.: Graphtrail: analyzing large multivariate, heterogeneous networks while supporting exploration history. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2012, pp. 1663–1672. ACM, New York (2012), Scholar
  17. 17.
    Dwyer, T., Hong, S.H., Koschützki, D., Schreiber, F., Xu, K.: Visual analysis of network centralities. In: Misue, K., Sugiyama, K., Tanaka, J. (eds.) Proc. Asia-Pacific Symposium on Information Visualization (APVis 2006). CRPIT, vol. 60, pp. 189–198. ACS (2006)Google Scholar
  18. 18.
    Fernández-Suárez, X.M., Galperin, M.Y.: The 2013 Nucleic Acids Research database issue and the online molecular biology database collection. Nucleic Acids Research 41, D1–D7 (2013)Google Scholar
  19. 19.
    Freire, M., Plaisant, C., Shneiderman, B., Golbeck, J.: Manynets: an interface for multiple network analysis and visualization. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2010, pp. 213–222. ACM, New York (2010), Scholar
  20. 20.
    Funahashi, A., Matsuoka, Y., Jouraku, A., Kitano, H., Kikuchi, N.: CellDesigner: a modeling tool for biochemical networks. In: Proceedings of the 38th Conference on Winter Simulation, pp. 1707–1712. Winter Simulation Conference (2006)Google Scholar
  21. 21.
    Fung, D.C.Y., Hong, S.H., Koschützki, D., Schreiber, F., Xu, K.: Visual analysis of overlapping biological networks. In: Proceedings of the 13th International Conference on Information Visualisation, IV 2009, pp. 337–342. IEEE Computer Society Press (2009)Google Scholar
  22. 22.
    Gehlenborg, N., O’Donoghue, S.I., Baliga, N.S., Goesmann, A., Hibbs, M.A., Kitano, H., Kohlbacher, O., Neuweger, H., Schneider, R., Tenenbaum, D., Gavin, A.C.: Visualization of omics data for systems biology. Nature Methods 7, S56–S68 (2010)Google Scholar
  23. 23.
    Heer, J., Shneiderman, B.: Interactive dynamics for visual analysis. Communication of the ACM 55(4), 45–54 (2012), Scholar
  24. 24.
    Herman, I., Melançon, G., Marshall, M.S.: Graph visualization and navigation in information visualization: A survey. IEEE Transactions on Visualization and Computer Graphics 6(1), 24–43 (2000)CrossRefGoogle Scholar
  25. 25.
    Hu, Z., Hung, J.H., Wang, Y., Chang, Y.C., Huang, C.L., Huyck, M., DeLisi, C.: VisANT 3.5: Multi-scale network visualization, analysis and inference based on the gene ontology. Nucleic Acids Research 37(Web Server issue), W115–W121 (2009)Google Scholar
  26. 26.
    Hucka, M., Finney, A., Sauro, H.M., Bolouri, H., Doyle, J.C., Kitano, H., Arkin, A.P., Bornstein, B.J., Bray, D., Cornish-Bowden, A., Cuellar, A.A., Dronov, S., Gilles, E.D., Ginkel, M., Gor, V., Goryanin, I., Hedley, W.J., Hodgman, T.C., Hofmeyr, J.H., Hunter, P.J., Juty, N.S., Kasberger, J.L., Kremling, A., Kummer, U., Novere, N.L., Loew, L.M., Lucio, D., Mendes, P., Minch, E., Mjolsness, E.D., Nakayama, Y., Nelson, M.R., Nielsen, P.F., Sakurada, T., Schaff, J.C., Shapiro, B.E., Shimizu, T.S., Spence, H.D., Stelling, J., Takahashi, K., Tomita, M., Wagner, J., Wang, J.: The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19, 524–531 (2003)CrossRefGoogle Scholar
  27. 27.
    van Iersel, M.P., Kelder, T., Pico, A.R., Hanspers, K., Coort, S., Conklin, B.R., Evelo, C.: Presenting and exploring biological pathways with PathVisio. BMC Bioinformatics 9, 399.1–399.9 (2008)Google Scholar
  28. 28.
    Johnson, B., Shneiderman, B.: Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: Proceedings of the 2nd Conference on Visualization (Vis 1991), pp. 284–291. IEEE Computer Society Press, Los Alamitos (1991), Scholar
  29. 29.
    Junker, A., Rohn, H., Schreiber, F.: Visual analysis of transcriptome data in the context of anatomical structures and biological networks. Frontiers in Plant Science 3, 252 (2012)CrossRefGoogle Scholar
  30. 30.
    Junker, B.H., Klukas, C., Schreiber, F.: VANTED: A system for advanced data analysis and visualization in the context of biological networks. BMC Bioinformatics 7, 109 (2006)CrossRefGoogle Scholar
  31. 31.
    Jusufi, I.: Multivariate Networks: Visualization and Interaction Techniques. Ph.D. Thesis, Linnaeus University, Växjö, Sweden (2013)Google Scholar
  32. 32.
    Jusufi, I., Kerren, A., Zimmer, B.: Multivariate network exploration with JauntyNets. In: Proceedings of the 17th International Conference on Information Visualisation (IV 2013), pp. 19–27. IEEE Computer Society Press (2013)Google Scholar
  33. 33.
    Juty, N., Le Novère, N., Laibe, C.: and MIRIAM registry: community resources to provide persistent identification. Nucleic Acids Research 40(1), D580–D5869 (2012)Google Scholar
  34. 34.
    Kanehisa, M., Goto, S.: KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research 28(1), 27–30 (2000)CrossRefGoogle Scholar
  35. 35.
    Kerren, A., Köstinger, H., Zimmer, B.: Vincent – visualisation of network centralities. In: Proceedings of the International Conference on Information Visualization Theory and Applications (IVAPP 2012), pp. 703–712. INSTICC (2012)Google Scholar
  36. 36.
    Kerren, A., Purchase, H., Ward, M.O.: Information Visualization – Towards Multivariate Network Visualization (Dagstuhl Seminar 13201). Dagstuhl Reports 3(5), 19–42 (2013), Scholar
  37. 37.
    Kerren, A., Schreiber, F.: Toward the role of interaction in visual analytics. In: Proceedings of the Winter Simulation Conference, WSC 2012, pp. 420:1–420:13. Winter Simulation Conference (2012),
  38. 38.
    Kerren, A., Stasko, J.T., Fekete, J.-D., North, C. (eds.): Information Visualization. LNCS, vol. 4950, pp. 65–91. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  39. 39.
    Klukas, C., Schreiber, F.: Integration of -omics data and networks for biomedical research with Vanted. Journal of Integrative Bioinformatics 7(2), 112 (2010)Google Scholar
  40. 40.
    Knodel, J., Muthig, D., Naab, M.: Understanding software architectures by visualization–an experiment with graphical elements. In: Working Conference on Reverse Engineering, pp. 39–50 (2006)Google Scholar
  41. 41.
    Köhler, J., Baumbach, J., Taubert, J., Specht, M., Skusa, A., Rüegg, A., Rawlings, C., Verrier, P., Philippi, S.: Graph-based analysis and visualization of experimental results with ONDEX. Bioinformatics 22(11), 1383–1390 (2006)CrossRefGoogle Scholar
  42. 42.
    Kolpakov, F.A.: BioUML – framework for visual modeling and simulation of biological systems. In: Proceedings of the International Conference on Bioinformatics of Genome Regulation and Structure, pp. 130–133. Springer (2002)Google Scholar
  43. 43.
    Kono, N., Arakawa, K., Ogawa, R., Kido, N., Oshita, K., Ikegami, K., Tamaki, S., Tomit, M.: Pathway Projector: Web-based zoomable pathway browser using KEGG atlas and Google maps API. PLoS ONE 4(11), e7710 (2009)CrossRefGoogle Scholar
  44. 44.
    Koschützki, D.: Network centralities. In: Junker, B.H., Schreiber, F. (eds.) Analysis of Biological Networks. Wiley Series on Bioinformatics, Computational Techniques and Engineering, pp. 65–84. Wiley (2008)Google Scholar
  45. 45.
    Küntzer, J., Backes, C., Blum, T., Gerasch, A., Kaufmann, M., Kohlbacher, O., Lenhof, H.P.: Bndb - the biochemical network database. BMC Bioinformatics 8, 367 (2007)CrossRefGoogle Scholar
  46. 46.
    von Landesberger, T., Kuijper, A., Schreck, T., Kohlhammer, J., van Wijk, J., Fekete, J.D., Fellner, D.: Visual analysis of large graphs: State-of-the-art and future research challenges. Computer Graphics Forum 30(6), 1719–1749 (2011), Scholar
  47. 47.
    Le Novère, N., Finney, A., Hucka, M., Bhalla, U.S., Campagne, F., Collado-Vides, J., Crampin, E.J., Halstead, M., Klipp, E., Mendes, P., Nielsen, P., Sauro, H., Shapiro, B., Snoep, J.L., Spence, H.D., Wanner, B.L.: Minimum information requested in the annotation of biochemical models (MIRIAM). Nature Biotechnology 23(12), 1509–1515 (2005)CrossRefGoogle Scholar
  48. 48.
    Le Novère, N., Hucka, M., Mi, H., Moodie, S., Schreiber, F., Sorokin, A., Demir, E., Wegner, K., Aladjem, M.I., Wimalaratne, S.M., Bergman, F.T., Gauges, R., Ghazal, P., Kawaji, H., Li, L., Matsuoka, Y., Villéger, A., Boyd, S.E., Calzone, L., Courtot, M., Dogrusoz, U., Freeman, T.C., Funahashi, A., Ghosh, S., Jouraku, A., Kim, S., Kolpakov, F., Luna, A., Sahle, S., Schmidt, E., Watterson, S., Wu, G., Goryanin, I., Kell, D.B., Sander, C., Sauro, H., Snoep, J.L., Kohn, K., Kitano, H.: The Systems Biology Graphical Notation. Nature Biotechnology 27(8), 735–741 (2009)CrossRefGoogle Scholar
  49. 49.
    Lex, A., Partl, C., Kalkofen, D., Streit, M., Wasserman, A.M., Gratzl, S., Schmalstieg, D., Pfister, H.: Entourage: Visualizing relationships between biological pathways using contextual subsets. IEEE Transactions on Visualization and Computer Graphics (InfoVis 2013) 19(12), 2536–2545 (2013)CrossRefGoogle Scholar
  50. 50.
    Mehlhorn, H., Schreiber, F.: TransID – the flexible identifier mapping service. In: Proc. International Symposium on Integrative Bioinformatics, pp. 112–121 (2012)Google Scholar
  51. 51.
    Mi, H., Schreiber, F., Novère, N.L., Moodie, S., Sorokin, A.: Systems biology graphical notation: Activity flow language level1. In: Nature Precedings (2009)Google Scholar
  52. 52.
    Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., Alon, U.: Network motifs: Simple building blocks of complex networks. Science 298(5594), 824–827 (2002)CrossRefGoogle Scholar
  53. 53.
    Moodie, S., Novère, N.L., Sorokin, A., Mi, H., Schreiber, F.: Systems biology graphical notation: Process description language level 1. In: Nature Precedings (2009)Google Scholar
  54. 54.
    Mueller, L.A., Zhang, P., Rhee, S.Y.: AraCyc: a biochemical pathway database for Arabidopsis. Plant Physiology 132(2), 453–460 (2003)CrossRefGoogle Scholar
  55. 55.
    Novère, N.L., Moodie, S., Sorokin, A., Schreiber, F., Mi, H.: Systems biology graphical notation: Entity relationship language level 1. In: Nature Precedings (2009)Google Scholar
  56. 56.
    Partl, C., Kalkofen, D., Lex, A., Kashofer, K., Streit, M., Schmalstieg, D.: enroute: Dynamic path extraction from biological pathway maps for in-depth experimental data analysis. In: Proceedings of the 2012 IEEE Symposium on Biological Data Visualization (BioVis) BIOVIS 2012, pp. 107–114. IEEE Computer Society, Washington, DC (2012), Scholar
  57. 57.
    Purchase, H.: Experimental Human-Computer Interaction: A Practical Guide With Visual Examples. Cambridge University Press, New York (2012), Scholar
  58. 58.
    Rao, R., Card, S.K.: The table lens: merging graphical and symbolic representations in an interactive focus+context visualization for tabular information. In: CHI 1994: Conference Companion on Human Factors in Computing Systems, p. 222. ACM (1994)Google Scholar
  59. 59.
    Roberts, J.C.: Exploratory visualization with multiple linked views. In: MacEachren, A., Kraak, M.J., Dykes, J. (eds.) Exploring Geovisualization. Elseviers (2004),
  60. 60.
    Rohn, H., Junker, A., Hartmann, A., Grafahrend-Belau, E., Treutler, H., Klapperstück, M., Czauderna, T., Klukas, C., Schreiber, F.: VANTED v2: a framework for systems biology applications. BMC Systems Biology 6(139) (2012)Google Scholar
  61. 61.
    Schreiber, F., Colmsee, C., Czauderna, T., Grafahrend-Belau, E., Hartmann, A., Junker, A., Junker, B.H., Klapperstück, M., Scholz, U., Weise, S.: MetaCrop 2.0: managing and exploring information about crop plant metabolism. Nucleic Acids Research 40(1), D1173–D1177 (2012)Google Scholar
  62. 62.
    Shen, Z., Ma, K.L.: Mobivis: A visualization system for exploring mobile data. In: Proceedings of IEEE Pacific Visualization Symposium, pp. 175–182. IEEE VGTC (2008)Google Scholar
  63. 63.
    Shen, Z., Ma, K.L., Eliassi-Rad, T.: Visual analysis of large heterogeneous social networks by semantic and structural abstraction. IEEE Transactions on Visualization and Computer Graphics 12(6), 1427–1439 (2006), Scholar
  64. 64.
    Shneiderman, B., Aris, A.: Network visualization by semantic substrates. IEEE Transaction on Visualization and Computer Graphics 12(5) (2006)Google Scholar
  65. 65.
    Smoot, M.E., Ono, K., Ruscheinski, J., Wang, P.L., Ideker, T.: Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3), 431–432 (2011)CrossRefGoogle Scholar
  66. 66.
    Sommer, B., Künsemöller, J., Sand, N., Husemann, A., Rumming, M., Kormeier, B.: Cellmicrocosmos 4.1 - an interactive approach to integrating spatially localized metabolic networks into a virtual 3d cell environment. In: Fred, A.L.N., Filipe, J., Gamboa, H. (eds.) Proc. International Conference on Bioinformatics, pp. 90–95 (2010)Google Scholar
  67. 67.
    Stasko, J., Görg, C., Liu, Z.: Jigsaw: supporting investigative analysis through interactive visualization. Information Visualization 7(2), 118–132 (2008), Scholar
  68. 68.
    Steinberger, M., Waldner, M., Streit, M., Lex, A., Schmalstieg, D.: Context-preserving visual links. IEEE Transactions on Visualization and Computer Graphics (InfoVis 2011) 17(12), 2249–2258 (2011)CrossRefGoogle Scholar
  69. 69.
    Ward, M., Grinstein, G., Keim, D.A.: Interactive Data Visualization: Foundations, Techniques, and Application. A.K. Peters, Ltd. (2010)Google Scholar
  70. 70.
    Ware, C.: Information Visualization: Perception for Design, 2nd edn. Morgan Kaufmann (2004)Google Scholar
  71. 71.
    Wattenberg, M.: Visual exploration of multivariate graphs. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2006), pp. 811–819. ACM, New York (2006)CrossRefGoogle Scholar
  72. 72.
    Zimmer, B., Jusufi, I., Kerren, A.: Analyzing multiple network centralities with ViNCent. In: Proceedings of SIGRAD 2012: Interactive Visual Analysis of Data, Växjö, Sweden, November 29-30. Linköping Electronic Conference Proceedings, vol. 81, pp. 87–90. Linköping University Electronic Press (2012)Google Scholar

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