Semi-bipartite Graph Visualization for Gene Ontology Networks

  • Kai Xu
  • Rohan Williams
  • Seok-Hee Hong
  • Qing Liu
  • Ji Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5849)


In this paper we propose three layout algorithms for semi-bipartite graphs—bipartite graphs with edges in one partition—that emerge from microarray experiment analysis. We also introduce a method that effectively reduces visual complexity by removing less informative nodes. The drawing quality and running time are evaluated with five real-world datasets, and the results show significant reduction in crossing number and total edge length. All the proposed methods are available in visualization package GEOMI [1], and are well received by domain users.


Gene Ontology Bipartite Graph Directed Acyclic Graph Gene Node Visual Complexity 
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.


  1. 1.
    Ahmed, A., Dwyer, T., Forster, M., Fu, X., Ho, J., Hong, S.H., Koschützki, D., Murray, C., Nikolov, N.S., Taib, R., Tarassov, A., Xu, K.: GEOMI: Geometry for maximum insight. In: Healy, P., Nikolov, N.S. (eds.) GD 2005. LNCS, vol. 3843, pp. 468–479. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  2. 2.
    Schena, M., Shalon, D., Davis, R.W., Brown, P.O.: Quantitative monitoring of gene expression patterns with a complementary dna microarray. Science 270(5235), 467–470 (1995)CrossRefGoogle Scholar
  3. 3.
    Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Dolinski, K., Dwight, S.S., Eppig, J.T., Harris, M.A., Hill, D.P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J.C., Richardson, J.E., Ringwald, M., Rubin, G.M., Sherlock, G.: Gene ontology: tool for the unification of biology. Nature Genetics 25(1), 25–29 (2000)CrossRefGoogle Scholar
  4. 4.
    Khatri, P., Draghici, S.: Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics 21(18), 3587–3595 (2005)CrossRefGoogle Scholar
  5. 5.
    Maere, S., Heymans, K., Kuiper, M.: Bingo: a cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21(16), 3448–3449 (2005)CrossRefGoogle Scholar
  6. 6.
    Baehrecke, E.H., Dang, N., Babaria, K., Shneiderman, B.: Visualization and analysis of microarray and gene ontology data with treemaps. BMC Bioinformatics 5, 84 (2004)CrossRefGoogle Scholar
  7. 7.
    Shneiderman, B.: Tree visualization with treemaps: A 2d space-filling approach. ACM Transactions on Graphics 11(1), 92–99 (1992)zbMATHCrossRefGoogle Scholar
  8. 8.
    Lee, J.S.M., Katari, G., Sachidanandam, R.: GObar: A gene ontology based analysis and visualization tool for gene sets. BMC Bioinformatics 6, 189 (2005)CrossRefGoogle Scholar
  9. 9.
    Gansner, E.R., North, S.C.: An open graph visualization system and its applications to software engineering. Software Practice and Experience 30(11), 1203–1233 (2000)zbMATHCrossRefGoogle Scholar
  10. 10.
    Joslyn, C.A., Mniszewski, S.M., Smith, S.A., Weber, P.M.: Spindleviz: A three dimensional, order theoretical visualization environment for the gene ontology. In: Proceedings of Joint BioLINK and 9th Bio-Ontologies Meeting (2006)Google Scholar
  11. 11.
    Sugiyama, K., Tagawa, S., Toda, M.: Methods for visual understanding of hierarchical system structures. IEEE Transactions on Systems, Man, and Cybernetics 11(2), 109–125 (1981)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Katifori, A., Halatsis, C., Lepouras, G., Vassilakis, C., Giannopoulou, E.: Ontology visualization methods—a survey. ACM Comput. Surv. 39(4), 10 (2007)CrossRefGoogle Scholar
  13. 13.
    Xu, K., Huang, X.X., Cotsapas, C., Hong, S.H., McCaughan, G., Gorrell, M., Little, P., Williams, R.: Combined visualisation and analysis of gene ontology annotations using multivariate representations of annotations and bipartite networks. Technical Report 09/166, CSIRO (2009)Google Scholar
  14. 14.
    Robinson, P.N., Wollstein, A., Bohme, U., Beattie, B.: Ontologizing gene-expression microarray data: characterizing clusters with gene ontology. Bioinformatics 20(6), 979–981 (2004)CrossRefGoogle Scholar
  15. 15.
    Alterovitz, G., Xiang, M., Mohan, M., Ramoni, M.F.: GO PaD: the gene ontology partition database. Nucleic Acids Research 35, D322–D327 (2007)CrossRefGoogle Scholar
  16. 16.
    Shannon, P., Markiel, A., Ozier, O., Baliga, N.S., Wang, J.T., Ramage, D., Amin, N., Schwikowski, B., Ideker, T.: Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research 13, 2498–2504 (2003)CrossRefGoogle Scholar
  17. 17.
    Battista, G.D., Eades, P., Tamassia, R., Tollis, I.G.: Graph Drawing: Algorithms for the Visualization of Graphs. Prentice Hall, Englewood Cliffs (1999)zbMATHGoogle Scholar
  18. 18.
    Kaufmann, M., Wagner, D. (eds.): Drawing Graphs, Methods and Models. LNCS, vol. 2025. Springer, Heidelberg (2001)zbMATHGoogle Scholar
  19. 19.
    Eades, P., Wormald, N.C.: Edge crossings in drawings of bipartite graphs. Algorithmica 11(4), 379–403 (1994)zbMATHCrossRefMathSciNetGoogle Scholar
  20. 20.
    Garey, M.R., Johnson, D.S.: Crossing number is NP-complete. SIAM J. Algebraic and Discrete Methods 4(3), 312–316 (1983)zbMATHCrossRefMathSciNetGoogle Scholar
  21. 21.
    Nagamochi, H.: An improved bound on the one-sided minimum crossing number in two-layered drawings. Discrete & Computational Geometry 33(4), 569–591 (2005)zbMATHCrossRefMathSciNetGoogle Scholar
  22. 22.
    Xu, K., Williams, R., Hong, S.H., Liu, Q., Zhang, J.: Semi-bipartite graph visualization for gene ontology networks. Technical Report EP091883, CSIRO (2009),
  23. 23.
    Gansner, E.R., Koutsofios, E., North, S.C., Vo, K.P.: A technique for drawing directed graphs. IEEE Transactions on Software Engineering 19(3), 214–230 (1993)CrossRefGoogle Scholar
  24. 24.
    Chvatal, V.: Linear Programming. W.H. Freeman, New York (1983)zbMATHGoogle Scholar
  25. 25.
    Purchase, H.C.: Which aesthetic has the greatest effect on human understanding? In: Proceedings of the 5th International Symposium on Graph Drawing, London, UK, pp. 248–261. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  26. 26.
    Cowley, M.J., Cotsapas, C.J., Williams, R.B.H., Chan, E.K.F., Pulvers, J.N., Liu, M.Y., Luo, O.J., Nott, D.J., Little, P.F.R.: Intra- and inter-individual genetic differences in gene expression. Nature Proceedings (2008),

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Kai Xu
    • 1
  • Rohan Williams
    • 2
  • Seok-Hee Hong
    • 3
  • Qing Liu
    • 1
  • Ji Zhang
    • 4
  1. 1.CSIROAustralia
  2. 2.Australian National UniversityAustralia
  3. 3.School of Information TechnologiesUniversity of SydneyAustralia
  4. 4.The University of Southern QueenslandAustralia

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