Comparing Metabolic Pathways through Reactions and Potential Fluxes

  • Paolo Baldan
  • Nicoletta Cocco
  • Federica Giummolè
  • Marta Simeoni
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8100)


Comparison of metabolic pathways is useful in phylogenetic analysis and for understanding metabolic functions when studying diseases and in drugs engineering. In the literature many techniques have been proposed to compare metabolic pathways. Most of them focus on structural aspects, while behavioural or functional aspects are generally not considered. In this paper we propose a new method for comparing metabolic pathways of different organisms based on a similarity measure which considers both homology of reactions and functional aspects of the pathways. The latter are captured by relying on a Petri net representation of the pathways and comparing the corresponding T-invariant bases, which represent minimal subsets of reactions that can operate at a steady state. A prototype tool, CoMeta, implements this approach and allows us to test and validate our proposal. Some experiments with CoMeta are presented.


Metabolic Pathway Metabolic Network Glycolysis Pathway Stoichiometric Matrix Full 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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kegg Markup Language manual,
  2. 2.
    KEGG pathway database - Kyoto University Bioinformatics Centre,
  3. 3.
    Petri Net Markup Language,
  4. 4.
  5. 5.
    Taxonomy - site guide - NCBI,
  6. 6.
    4ti2 team. 4ti2—a software package for algebraic, geometric and combinatorial problems on linear spaces,
  7. 7.
    Ay, F., Dang, M., Kahveci, T.: Metabolic network alignment in large scale by network compression. BMC Bioinformatics 13(suppl. 3) (2012)Google Scholar
  8. 8.
    Ay, F., Kahveci, T., de Crecy-Lagard, V.: Consistent alignment of metabolic pathways without abstraction. In: Int. Conf. on Computational Systems Bioinformatics (CSB), pp. 237–248 (2008)Google Scholar
  9. 9.
    Ay, F., Kellis, M., Kahveci, T.: SubMAP: Aligning metabolic pathways with subnetwork mappings. Journal of Computational Biology 18(3), 219–235 (2011)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Baldan, P., Cocco, N., Marin, A.: M Simeoni. Petri nets for modelling metabolic pathways: a survey. Natural Computing 9(4), 955–989 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Baldan, P., Cocco, N., De Nes, F., Llabrés Segura, M., Simeoni, M.: MPath2PN - Translating metabolic pathways into Petri nets. In: Heiner, M., Matsuno, H. (eds.) BioPPN2011 Int. Workshop on Biological Processes and Petri Nets. CEUR Workshop Proceedings, vol. 724, pp. 102–116 (2011),
  12. 12.
    Baldan, P., Cocco, N., Simeoni, M.: Comparison of metabolic pathways by considering potential fluxes. In: Heiner, M., Hofestädt, R. (eds.) BioPPN2012 - 3rd International Workshop on Biological Processes and Petri Nets, Satellite Event of Petri Nets 2012, Hamburg, Germany, June 25. CEUR Workshop Proceedings, vol. 852, pp. 2–17. (2012),
  13. 13.
    Casasnovas, J., Clemente, J.C., Miró-Julià, J., Rosselló, F., Satou, K., Valiente, G.: Fuzzy clustering improves phylogenetic relationships reconstruction from metabolic pathways. In: Proc. of the 11th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems (2006)Google Scholar
  14. 14.
    Chen, M., Hofestadt, R.: Web-based information retrieval system for the prediction of metabolic pathways. IEEE Trans. on NanoBioscience 3(3), 192–199 (2004)CrossRefGoogle Scholar
  15. 15.
    Cheng, Q., Harrison, R., Zelikovsky, A.: MetNetAligner: a web service tool for metabolic network alignments. Bioinformatics 25(15), 1989–1990 (2009)CrossRefGoogle Scholar
  16. 16.
    Clemente, J., Satou, K., Valiente, G.: Reconstruction of phylogenetic relationships from metabolic pathways based on the enzyme hierarchy and the gene ontology. Genome Informatics 16(2), 45–55 (2005)Google Scholar
  17. 17.
    Ebenhöh, O., Handorf, T., Heinrich, R.: A cross species comparison of metabolic network functions. Genome Informatics 16(1), 203–213 (2005)Google Scholar
  18. 18.
    Esparza, J., Nielsen, M.: Decidability issues for Petri Nets - a survey. Journal Inform. Process. Cybernet. EIK 30(3), 143–160 (1994)zbMATHGoogle Scholar
  19. 19.
    Forst, C.V., Flamm, C., Hofacker, I.L., Stadler, P.F.: Algebraic comparison of metabolic networks, phylogenetic inference, and metabolic innovation. BMC Bioinformatics 7(1), 1–11 (2006)CrossRefGoogle Scholar
  20. 20.
    Forst, C.V., Schulten, K.: Evolution of metabolism: a new method for the comparison of metabolic pathways using genomics information. Journal of Computational Biology 6(3/4), 343–360 (1999)CrossRefGoogle Scholar
  21. 21.
    Forst, C.V., Schulten, K.: Phylogenetic analysis of metabolic pathways. Journal of Molecular Evolution 52(16), 471–489 (2001)Google Scholar
  22. 22.
    Grafahrend-Belau, E., Schreiber, F., Heiner, M., Sackmann, A., Junker, B.H., Grunwald, S., Speer, A., Winder, K., Koch, I.: Modularization of biochemical networks based on classification of Petri net t-invariants. BMC Bioinformatics 9(1), 1–17 (2008)CrossRefGoogle Scholar
  23. 23.
    Hardy, S., Robillard, P.N.: Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways. Bioinformatics 24(2), 209–217 (2008)CrossRefGoogle Scholar
  24. 24.
    Heiner, M., Koch, I.: Petri net based model validation in systems biology. In: Cortadella, J., Reisig, W. (eds.) ICATPN 2004. LNCS, vol. 3099, pp. 216–237. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  25. 25.
    Heymans, M., Singh, A.M.: Deriving phylogenetic trees from the similarity analysis of metabolic pathways. Bioinformatics 19(1), i138–i146 (2003)CrossRefGoogle Scholar
  26. 26.
    Hofestädt, R.: A Petri net application of metabolic processes. Journal of System Analysis, Modelling and Simulation 16, 113–122 (1994)zbMATHGoogle Scholar
  27. 27.
    Hong, S.H., Kim, T.Y., Lee, S.Y.: Phylogenetic analysis based on genome-scale metabolic pathway reaction content. Applied Microbiology and Biotechnology 65(2), 203–210 (2004)CrossRefGoogle Scholar
  28. 28.
    Jaccard, P.: Distribution de la flore alpine dans le bassin des Dranses et dans quelques régions voisines. Bulletin del la Société Vaudoise des Sciences Naturelles 37, 241–272 (1901)Google Scholar
  29. 29.
    Kanehisa, M., Araki, M., Goto, S., Hattori, M., Hirakawa, M., Itoh, M., Katayama, T., Kawashima, S., Okuda, S., Tokimatsu, T., Yamanishi, Y.: KEGG for linking genomes to life and the environment. Nucleic Acids Research, 480–484 (2008)Google Scholar
  30. 30.
    Klau, G.W.: A new graph-based method for pairwise global network alignment. BMC Bioinformatics 10(suppl. 1), 1–9 (2009)Google Scholar
  31. 31.
    Koch, I., Heiner, M.: Petri nets. In: Junker, B.H., Schreiber, F. (eds.) Analysis of Biological Networks. Book Series in Bioinformatics, pp. 139–179. Wiley & Sons (2008)Google Scholar
  32. 32.
    Kuchaiev, O., Milenkovic, T., Memisevic, V., Hayes, W., Przulj, N.: Topological network alignment uncovers biological function and phylogeny. Journal of the Royal Society Interface 7(50), 1341–1354 (2010)CrossRefGoogle Scholar
  33. 33.
    Li, Y., de Ridder, D., de Groot, M.J.L., Reinders, M.J.T.: Metabolic pathway alignment between species using a comprehensive and flexible similarity measure. BMC Systems Biology 2(1), 1–15 (2008)CrossRefGoogle Scholar
  34. 34.
    Li, Z., Zhang, S., Wang, Y., Zhang, X.S., Chen, L.: Alignment of molecular networks by integer quadratic programming. Bioinformatics 23(13), 1631–1639 (2007)CrossRefGoogle Scholar
  35. 35.
    Liao, L., Kim, S., Tomb, J.F.: Genome comparisons based on profiles of metabolic pathways. In: Proc. of the 6th Int. Conf. on Knowledge-Based Intelligent Information and Engineering Systems (KES 2002), pp. 469–476 (2002)Google Scholar
  36. 36.
    Lo, E., Yamada, T., Tanaka, M., Hattori, M., Goto, S., Chang, C., Kanehisa, M.: A method for customized cross-species metabolic pathway comparison. In: Proc. of Genome Informatics 2004. GIW 2004 Poster Abstract: P068 (2004)Google Scholar
  37. 37.
    Mithani, A., Preston, G.M., Hein, J.: Rahnuma: Hypergraph based tool for metabolic pathway prediction and network comparison. Bioinformatics 25(14), 1831–1832 (2009)CrossRefGoogle Scholar
  38. 38.
    Murata, T.: Petri Nets: Properties, Analysis, and Applications. Proceedings of IEEE 77(4), 541–580 (1989)CrossRefGoogle Scholar
  39. 39.
    Saitou, N., Nei, M.: The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology and Evolution 4(4), 406–425 (1987)Google Scholar
  40. 40.
    Oehm, S., Gilbert, D., Tauch, A., Stoye, J., Goessmann, A.: Comparative Pathway Analyzer - a web server for comparative analysis, clustering and visualization of metabolic networks in multiple organisms. Nucleic Acids Research 36, 433–437 (2008)CrossRefGoogle Scholar
  41. 41.
    Pedersen, M.: Compositional definitions of minimal flows in petri nets. In: Heiner, M., Uhrmacher, A.M. (eds.) CMSB 2008. LNCS (LNBI), vol. 5307, pp. 288–307. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  42. 42.
    Pinter, R.Y., Rokhlenko, O., Yeger-Lotem, E., Ziv-Ukelson, M.: Alignment of metabolic pathways. Bioinformatics 21(16), 3401–3408 (2005)CrossRefGoogle Scholar
  43. 43.
    Reddy, V.N.: Modeling Biological Pathways: A Discrete Event Systems Approach. Master’s thesis, The Universisty of Maryland, M.S. 94-4 (1994)Google Scholar
  44. 44.
    Reddy, V.N., Liebman, M.N., Mavrovouniotis, M.L.: Qualitative Analysis of Biochemical Reaction Systems. Computers in Biology and Medicine 26(1), 9–24 (1996)CrossRefGoogle Scholar
  45. 45.
    Reddy, V.N., Mavrovouniotis, M.L., Liebman, M.N.: Petri net representations in metabolic pathways. In: ISMB93: First Int. Conf. on Intelligent Systems for Molecular Biology, pp. 328–336. AAAI press (1993)Google Scholar
  46. 46.
    Schilling, C.H., Letscherer, D., Palsson, B.O.: Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. Journal of Theoretical Biology 203, 229–248 (2000)CrossRefGoogle Scholar
  47. 47.
    Schilling, C.H., Schuster, S., Palsson, B.O., Heinrich, R.: Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era. Biotechnology Progress 15(3), 296–303 (1999)CrossRefGoogle Scholar
  48. 48.
    Schrijver, A.: Theory of linear and integer programming. Wiley-Interscience series in discrete mathematics and optimization. Wiley (1999)Google Scholar
  49. 49.
    Schuster, S., Dandekar, T., Fell, D.A.: Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnology, 53–60 (March 1999)Google Scholar
  50. 50.
    Schuster, S., Fell, D.A., Dandekar, T.: A general definition of metabolic pathway useful for systematic organization and analysis of complex metabolic networks. Nature Biotechnology 18, 326–332 (2000)CrossRefGoogle Scholar
  51. 51.
    Schuster, S., Hilgetag, C.: On elementary flux modes in biochemical reaction systems at steady state. Journal of Biological Systems 2, 165–182 (1994)CrossRefGoogle Scholar
  52. 52.
    Schuster, S., Pfeiffer, T., Moldenhauer, F., Koch, I., Dandekar, T.: Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae. Bioinformatics 18(2), 351–361 (2002)CrossRefGoogle Scholar
  53. 53.
    Sestoft, P.: Programs for biosequence analysis,
  54. 54.
    Shasha, D., Wang, J.T.L., Zhang, S.: Unordered tree mining with applications to phylogeny. In: 20th Int. Conf. on Data Engineering, pp. 708–719. IEEE Computer Society (2004)Google Scholar
  55. 55.
    Sokal, R., Michener, C.: A statistical method for evaluating systematic relationships. University of Kansas Science Bulletin 38, 1409–1438 (1958)Google Scholar
  56. 56.
    Sørensen, T.: A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on danish commons. Biologiske Skrifter / Kongelige Danske Videnskabernes Selskabg 5(4), 1–34 (1948)Google Scholar
  57. 57.
    Starke, P.H., Roch, S.: The Integrated Net Analyzer. Humbolt University Berlin (1999),
  58. 58.
    Tanimoto, T.T.: Technical report, IBM Internal Report, (November 17, 1957)Google Scholar
  59. 59.
    Tohsato, Y.: A method for species comparison of metabolic networks using reaction profile. IPSJ Digital Courier 2(0), 685–690 (2006)CrossRefGoogle Scholar
  60. 60.
    Tohsato, Y., Matsuda, H., Hashimoto, A.: A multiple alignment algorithm for metabolic pathway analysis using enzyme hierarchy. In: Proc. Int. Conf. Intell. Syst. Mol. Biol., pp. 376–383 (2000)Google Scholar
  61. 61.
    Tohsato, Y., Nishimura, Y.: Metabolic pathway alignment based on similarity between chemical structures. IPSJ Digital Courier 3, 736–745 (2007)CrossRefGoogle Scholar
  62. 62.
    Webb, E.C.: Enzyme nomenclature 1992: recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of enzymes. Published for the International Union of Biochemistry and Molecular Biology by Academic Press, San Diego (1992)Google Scholar
  63. 63.
    Wernicke, S., Rasche, F.: Simple and fast alignment of metabolic pathways by exploiting local diversity. Bioinformatics 23(15), 1978–1985 (2007)CrossRefGoogle Scholar
  64. 64.
    Zhang, K., Wang, J.T.L., Shasha, D.: On the editing distance between undirected acyclic graphs. International Journal of Foundations of Computer Science 3(1), 43–57 (1996)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Paolo Baldan
    • 1
  • Nicoletta Cocco
    • 2
  • Federica Giummolè
    • 2
  • Marta Simeoni
    • 2
  1. 1.Dipartimento di MatematicaUniversità di PadovaItaly
  2. 2.DAISUniversità Ca’ Foscari VeneziaItaly

Personalised recommendations