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Biomodel Engineering – From Structure to Behavior

  • Rainer Breitling
  • Robin A. Donaldson
  • David R. Gilbert
  • Monika Heiner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5945)

Abstract

Biomodel engineering is the science of designing, constructing and analyzing computational models of biological systems. It forms a systematic and powerful extension of earlier mathematical modeling approaches and has recently gained popularity in systems biology and synthetic biology. In this brief review for systems biologists and computational modelers, we introduce some of the basic concepts of successful biomodel engineering, illustrating them with examples from a variety of application domains, ranging from metabolic networks to cellular signaling cascades. We also present a more detailed outline of one of the major techniques of biomodel engineering – Petri net models – which provides a flexible and powerful tool for building, validating and exploring computational descriptions of biological systems.

Keywords

Systems biology Petri nets computational modeling differential equations 

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References

  1. 1.
    Fisher, J., Henzinger, T.A.: Executable cell biology. Nat. Biotechnol. 25, 1239–1249 (2007)CrossRefGoogle Scholar
  2. 2.
    Gilbert, D., Fuss, H., Gu, X., Orton, R., Robinson, S., Vyshemirsky, V., Kurth, M.J., Downes, C.S., Dubitzky, W.: Computational methodologies for modelling, analysis and simulation of signalling networks. Brief Bioinform. 7, 339–353 (2006)CrossRefGoogle Scholar
  3. 3.
    Gilbert, D., Heiner, M., Lehrack, S.: A Unifying Framework for Modelling and Analysing Biochemical Pathways Using Petri Nets. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 200–216. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  4. 4.
    Nagasaki, M., Doi, A., Matsuno, H., Miyano, S.: Computational modeling of biological processes with Petri Net-based architecture. In: Chen, Y. (ed.) Bioinformatics Technologies, pp. 179–242. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Matsuno, H., Li, C., Miyano, S.: Petri net based descriptions for systematic understanding of biological pathways. IEICE Trans Fundam Electron Commun. Comput Sci. E89-A, 3166–3174 (2006)CrossRefGoogle Scholar
  6. 6.
    Nagasaki, M., Doi, A., Matsuno, H., Miyano, S.: Genomic Object Net: a platform for modeling and simulating biopathways. Applied Bioinformatics 2, 181–184 (2003)Google Scholar
  7. 7.
    Chaouiya, C.: Petri net modelling of biological networks. Brief Bioinform. 8, 210–219 (2007)CrossRefGoogle Scholar
  8. 8.
    Heiner, M., Gilbert, D., Donaldson, R.: Petri nets for Systems and Synthetic Biology. In: Bernardo, M., Degano, P., Zavattaro, G. (eds.) SFM 2008. LNCS, vol. 5016, pp. 215–264. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  9. 9.
    Petri, C.A., Reisig, W.: Petri nets. Scholarpedia 3, 6477 (2008)CrossRefGoogle Scholar
  10. 10.
    Breitling, R., Gilbert, D., Heiner, M., Orton, R.: A structured approach for the engineering of biochemical network models, illustrated for signalling pathways. Brief Bioinform. 9, 404–421 (2008)CrossRefGoogle Scholar
  11. 11.
    Shaw, O., Koelmans, A., Steggles, J., Wipat, A.: Applying Petri Nets to Systems Biology using XML Technologies. Technical Report Series. University of Newcastle upon Tyne (2004); CS-TR-827Google Scholar
  12. 12.
    Nagasaki, M., Saito, A., Li, C., Jeong, E., Miyano, S.: Systematic reconstruction of TRANSPATH data into cell system markup language. BMC Syst. Biol. 2, 53 (2008)CrossRefGoogle Scholar
  13. 13.
    Krull, M., Pistor, S., Voss, N., Kel, A., Reuter, I., Kronenberg, D., Michael, H., Schwarzer, K., Potapov, A., Choi, C., et al.: TRANSPATH: an information resource for storing and visualizing signaling pathways and their pathological aberrations. Nucleic Acids Res. 34, D546–D551 (2006)CrossRefGoogle Scholar
  14. 14.
    Edwards, J.S., Palsson, B.O.: Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions. BMC Bioinformatics 1, 1 (2000)CrossRefGoogle Scholar
  15. 15.
    Reed, J.L., Famili, I., Thiele, I., Palsson, B.O.: Towards multidimensional genome annotation. Nat. Rev. Genet. 7, 130–141 (2006)CrossRefGoogle Scholar
  16. 16.
    Becker, S.A., Feist, A.M., Mo, M.L., Hannum, G., Palsson, B.O., Herrgard, M.J.: Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat. Protoc. 2, 727–738 (2007)CrossRefGoogle Scholar
  17. 17.
    Palsson, B.O.: Systems Biology: Properties of Reconstructed Networks. Cambridge University Press, Cambridge (2006)CrossRefGoogle Scholar
  18. 18.
    Papin, J.A., Stelling, J., Price, N.D., Klamt, S., Schuster, S., Palsson, B.O.: Comparison of network-based pathway analysis methods. Trends Biotechnol. 22, 400–405 (2004)CrossRefGoogle Scholar
  19. 19.
    Famili, I., Palsson, B.O.: The convex basis of the left null space of the stoichiometric matrix leads to the definition of metabolically meaningful pools. Biophys. J. 85, 16–26 (2003)CrossRefGoogle Scholar
  20. 20.
    Heiner, M., Koch, I., Will, J.: Model validation of biological pathways using Petri nets–demonstrated for apoptosis. Biosystems 75, 15–28 (2004)CrossRefzbMATHGoogle Scholar
  21. 21.
    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
  22. 22.
    Duarte, N.C., Becker, S.A., Jamshidi, N., Thiele, I., Mo, M.L., Vo, T.D., Srivas, R., Palsson, B.O.: Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl. Acad. Sci. U S A 104, 1777–1782 (2007)CrossRefGoogle Scholar
  23. 23.
    Herrgard, M.J., Lee, B.S., Portnoy, V., Palsson, B.O.: Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Res. 16, 627–635 (2006)CrossRefGoogle Scholar
  24. 24.
    Heath, J., Kwiatkowska, M., Norman, G., Parker, D., Tymchyshyn, O.: Probabilistic model checking of complex biological pathways. Theoretical Computer Science 391, 239–257 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  25. 25.
    Kwiatkowska, M., Norman, G., Parker, D.: Using probabilistic model checking in systems biology. ACM SIGMETRICS Performance Evaluation Review 35, 14–21 (2008)CrossRefGoogle Scholar
  26. 26.
    Calder, M., Vyshemirsky, V., Gilbert, D., Orton, R.: Analysis of Signalling Pathways using Continuous Time Markov Chains. In: Priami, C., Plotkin, G. (eds.) Transactions on Computational Systems Biology VI. LNCS (LNBI), vol. 4220, pp. 44–67. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  27. 27.
    Chabrier, N., Fages, F.: Symbolic model checking of biochemical networks. In: Priami, C. (ed.) CMSB 2003. LNCS, vol. 2602, pp. 149–162. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  28. 28.
    Clarke, E.M., Grumberg, O., Peled, D.A.: Model checking. MIT Press, Cambridge (1999)Google Scholar
  29. 29.
    Losick, R., Desplan, C.: Stochasticity and cell fate. Science 320, 65–68 (2008)CrossRefGoogle Scholar
  30. 30.
    Gillespie, D.T.: Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem. 58, 35–55 (2007)CrossRefGoogle Scholar
  31. 31.
    Kaern, M., Elston, T.C., Blake, W.J., Collins, J.J.: Stochasticity in gene expression: from theories to phenotypes. Nat. Rev. Genet. 6, 451–464 (2005)CrossRefGoogle Scholar
  32. 32.
    Shetty, R.P., Endy, D., Knight Jr., T.F.: Engineering BioBrick vectors from BioBrick parts. J. Biol. Eng. 2, 5 (2008)CrossRefGoogle Scholar
  33. 33.
    Koch, I., Junker, B.H., Heiner, M.: Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber. Bioinformatics 21, 1219–1226 (2005)CrossRefGoogle Scholar
  34. 34.
    Li, F., Long, T., Lu, Y., Quyang, Q., Tang, C.: The yeast cell-cycle network is robustly designed. Proc. Natl. Acad. Sci. U S A 101, 4781–4786 (2004)CrossRefGoogle Scholar
  35. 35.
    Fisher, J., Piterman, N., Hubbard, E.J., Stern, M.J., Harel, D.: Computational insights into Caenorhabditis elegans vulval development. Proc. Natl. Acad. Sci. U S A 102, 1951–1956 (2005)CrossRefGoogle Scholar
  36. 36.
    Hofestädt, R.: A Petri Net Application of Metabolic Processes. Journal of System Analysis, Modelling and Simulation 16, 113–122 (1994)zbMATHGoogle Scholar
  37. 37.
    Reddy, V.N., Mavrovouniotis, M.L., Liebman, M.N.: Petri Net Representation in Metabolic Pathways. In: First International Conference on Intelligent Systems for Molecular Biology 1993, pp. 328–336. AAAI Press, Menlo Park (1993)Google Scholar
  38. 38.
    Ruths, D., Muller, M., Tseng, J.T., Nakhleh, L., Ram, P.T.: The signaling Petri net-based simulator: a non-parametric strategy for characterizing the dynamics of cell-specific signaling networks. PLoS Comput. Biol. 4, e1000005 (2008)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rainer Breitling
    • 1
  • Robin A. Donaldson
    • 2
  • David R. Gilbert
    • 2
    • 3
  • Monika Heiner
    • 4
  1. 1.Groningen Bioinformatics CentreUniversity of GroningenNN HarenThe Netherlands
  2. 2.Bioinformatics Research CentreUniversity of GlasgowGlasgowUK
  3. 3.School of Information Systems, Computing and MathematicsBrunel UniversityUxbridgeUK
  4. 4.Dept. of Computer ScienceBrandenburg University of Technology at CottbusCottbusGermany

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