Visualizing Related Metabolic Pathways in Two and a Half Dimensions

  • Ulrik Brandes
  • Tim Dwyer
  • Falk Schreiber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2912)

Abstract

We propose a method for visualizing a set of related metabolic pathways using \(2\frac{1}{2}\)D graph drawing. Interdependent, two-dimensional layouts of each pathway are stacked on top of each other so that biologists get a full picture of subtle and significant differences among the pathways. Layouts are determined by a global layout of the union of all pathway-representing graphs using a variant of the proven Sugiyama approach for layered graph drawing that allows edges to cross if they appear in different graphs.

References

  1. 1.
    Alizadeh, F., Karp, R.M., Weisser, D.K., Zweig, G.: Physical mapping of chromosomes using unique probes. In: Proceedings of the 5th ACM-SIAM Symposium on Discrete Algorithms (SODA 1994), pp. 489–500 (1994)Google Scholar
  2. 2.
    Becker, M.Y., Rojas, I.: A graph layout algorithm for drawing metabolic pathways. Bioinformatics 17(5), 461–467 (2001)CrossRefGoogle Scholar
  3. 3.
    Booth, K.S., Lueker, G.S.: Testing for the consecutive ones property, interval graphs, and graph planarity using PQ-tree algorithms. Journal of Computer and System Sciences 13(3), 335–379 (1976)MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Brandes, U., Corman, S.R.: Visual unrolling of network evolution and the analysis of dynamic discourse. In: Proceedings of the IEEE Symposium on Information Visualization 2002 (InfoVis 2002), pp. 145–151 (2002)Google Scholar
  5. 5.
    Brandes, U., Willhalm, T.: Visualization of bibliographic networks with a reshaped landscape metaphor. In: Proceedings of the 4th Joint Eurographics and IEEE TCVG Symposium on Visualization (VisSym 2002), pp. 159–164. ACM, New York (2002)Google Scholar
  6. 6.
    Dandekar, T., Schuster, S., Snel, B., Huynen, M., Bork, P.: Pathway alignment: application to the comparative analysis of glycolytic enzymes. Biochemical Journal 343, 115–124 (1999)CrossRefGoogle Scholar
  7. 7.
    Dwyer, T., Eades, P.: Visualising a fund manager flow graph with columns and worms. In: Proceedings of the 6th International Conference on Information Visualisation (IV 2002), pp. 147–152. IEEE Computer Society Press, Los Alamitos (2002)Google Scholar
  8. 8.
    Dwyer, T., Eckersley, P.: The WilmaScope 3D graph drawing system. In: Mutzel, P., Jünger, M. (eds.) Graph Drawing Software, Mathematics and Visualization, Springer, Heidelberg (2003)Google Scholar
  9. 9.
    Eades, P., Feng, Q.: Multilevel visualization of clustered graphs. In: North, S.C. (ed.) GD 1996. LNCS, vol. 1190, pp. 113–128. Springer, Heidelberg (1997)Google Scholar
  10. 10.
    Eades, P., Sugiyama, K.: How to draw a directed graph. Journal of Information Processing 13, 424–437 (1990)MATHGoogle Scholar
  11. 11.
    Forst, C.V., Schulten, K.: Phylogenetic analysis of metabolic pathways. Journal Molecular Evolution 52, 471–489 (2001)Google Scholar
  12. 12.
    Forster, M., Pick, A., Raitner, M., Schreiber, F., Brandenburg, F.J.: The system architecture of the BioPath system. Silico Biology 2(3), 415–426 (2002)Google Scholar
  13. 13.
    Gansner, E.R., Koutsofios, E., North, S.C., Vo, K.-P.: A technique for drawing directed graphs. Software Engineering 19(3), 214–230 (1993)CrossRefGoogle Scholar
  14. 14.
    Goldberg, P.W., Golumbic, M.C., Kaplan, H., Shamir, R.: Four strikes against physical mapping of DNA. Journal of Computational Biology 2(1), 139–152 (1995)CrossRefGoogle Scholar
  15. 15.
    Inselberg, A., Dimsdale, B.: Parallel coordinates: A tool for visualizing multidimensional geometry. In: Proceedings of the 1st IEEE Conference on Visualization (Vis 1990), pp. 361–378 (1990)Google Scholar
  16. 16.
    Jünger, M., Lee, E.K., Mutzel, P., Odenthal, T.: A polyhedral approach to the multi-layer crossing minimization problem. In: DiBattista, G. (ed.) GD 1997. LNCS, vol. 1353, pp. 13–24. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  17. 17.
    Kanehisa, M., Goto, S.: KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acid Research 28(1), 27–30 (2000)CrossRefGoogle Scholar
  18. 18.
    Keim, D.A.: Designing pixel-oriented visualization techniques: Theory and applications. IEEE Transactions on Visualization and Computer Graphics 6(1), 59–78 (2000)CrossRefGoogle Scholar
  19. 19.
    Koike, H.: The role of another spatial dimension in software visualization. ACM Transactions on Information Systems 11(3), 266–286 (1993)CrossRefGoogle Scholar
  20. 20.
    Liao, L., Kim, S., Tomb, J.-F.: Genome comparisons based on profiles of metabolic pathways. In: Proceedings of the 6th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2002), pp. 469–476 (2002)Google Scholar
  21. 21.
    Michal, G.: Biochemical Pathways (Poster). Boehringer Mannheim, Penzberg (1993)Google Scholar
  22. 22.
    Murgai, R., Fujita, M., Krishnan, S.C.: Data sequencing for minimum-transition transmission. In: Proceedings of the 9th IFIP International Conference on Very Large Scale Integration, VLSI 1997 (1997)Google Scholar
  23. 23.
    Reddy, V.N., Mavrovouniotis, M.L., Liebman, M.N.: Petri net representations of metabolic pathways. In: Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology (ISMB 1993), pp. 328–336 (1993)Google Scholar
  24. 24.
    Schreiber, F.: High quality visualization of biochemical pathways in BioPath. Silico Biology 2(2), 59–73 (2002)MATHGoogle Scholar
  25. 25.
    Schreiber, F.: Visual Comparison of Metabolic Pathways. Journal of Visual Languages and Computing 14(4), 327–340 (2003)CrossRefMathSciNetGoogle Scholar
  26. 26.
    Shiozawa, H., Okada, K., Matsushita, Y.: 3D interactive visualization for intercell dependencies of spreadsheets. In: Proceedings of the IEEE Symposium on Information Visualization (InfoVis 1999), pp. 79–83 (1999)Google Scholar
  27. 27.
    Sirava, M., Schäfer, T., Eiglsperger, M., Kaufmann, M., Kohlbacher, O., Bornberg-Bauer, E., Lenhof, H.-P.: BioMiner – modeling, analyzing, and visualizing biochemical pathways and networks. Bioinformatics 18(Suppl. 2), 219–230 (2002)Google Scholar
  28. 28.
    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
  29. 29.
    Tohsato, Y., Matsuda, H., Hashimoto, A.: A multiple alignment algorithm for metabolic pathway analysis using enzyme hierarchy. In: Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology (ISMB 2000), pp. 376–383 (2000)Google Scholar
  30. 30.
    Wen, J.: Exploiting orthogonality in three dimensional graphics for visualizing abstract data. Technical Report CS-95-20, Department of Computer Science, Brown University (1995), http://www.cs.brown.edu/publications/techreports/reports/CS-95-20.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ulrik Brandes
    • 1
  • Tim Dwyer
    • 2
  • Falk Schreiber
    • 3
  1. 1.Department of Mathematics & Computer ScienceUniversity of PassauGermany
  2. 2.School of Information TechnologiesUniversity of SydneyAustralia
  3. 3.Bioinformatics Center (BIC-GH)Institute of Plant Genetics and Crop Plant Research GaterslebenGermany

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