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Petri nets for modelling metabolic pathways: a survey

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Abstract

In the last 15 years, several research efforts have been directed towards the representation and the analysis of metabolic pathways by using Petri nets. The goal of this paper is twofold. First, we discuss how the knowledge about metabolic pathways can be represented with Petri nets. We point out the main problems that arise in the construction of a Petri net model of a metabolic pathway and we outline some solutions proposed in the literature. Second, we present a comprehensive review of recent research on this topic, in order to assess the maturity of the field and the availability of a methodology for modelling a metabolic pathway by a corresponding Petri net.

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Notes

  1. By definition, a mole of any substance contains the same number of elementary particles as there are atoms in exactly 12 g of the 12C isotope of carbon.

  2. We denote by \({\mathbb{N}}\) the set of natural numbers, \( {\mathbb{N}} = \{ 0, 1, 2, \ldots\}.\)

  3. Some papers do not mention explicitly the use of any specific tool, even if the complexity of the considered case studies clearly suggests that calculations have not been performed manually. Still, in this case the tool entry will be empty.

References

  • Agerwala T (1974) A complete model for representing the coordination of asynchronous processes. Hopkins computer research report 32. John Hopkins University

  • Ajmone Marsan M, Balbo G, Conte G, Donatelli S, Franceschinis G (1995) Modelling with generalized stochastic Petri nets. Wiley series in parallel computing. Wiley, New York

  • Atkin P, de Paula J (2006) Atkins’ physical chemistry. Oxford University Press, Oxford

    Google Scholar 

  • Balbo G (2007) Introduction to generalized stochastic Petri nets. In: Bernardo M and Hillston J (eds) Formal methods for performance evaluation, vol 4486 of LNCS. Springer, Berlin, pp 83–131

  • Beasley JE, Planes FJ (2007) Recovering metabolic pathways via optimization. Bioinformatics 23(1):92–98

    Article  Google Scholar 

  • BioCarta: charting pathways of life. http://www.biocarta.com

  • BioCyc: database collection. http://www.BioCyc.org

  • Biomodels database. http://www.ebi.ac.uk/biomodels

  • Biomolecular interaction networks database. http://www.bond.unleashedinformatics.com

  • Borger S, Liebermeister W, Klipp E (2006) Prediction of enzyme kinetic parameters based on statistical learning. Genome Inf Ser 1(17):80–87

    Google Scholar 

  • Borger S, Uhlendorf J, Helbig A, Liebermeister W (2007) Integration of enzyme kinetic data from various sources. In Silico Biol 7(S1 09)

  • Breitling R, Gilbert D, Heiner M, Orton R (2008) A structured approach for the engineering of biochemical network models, illustrated for signalling pathways. Brief Bioinform 9(5):404–421

    Article  Google Scholar 

  • BRENDA: the comprehensive enzyme information system. http://www.brenda-enzymes.info

  • Busi N (2002) Analysis issues in Petri nets with inhibitor arcs. Theor Comput Sci 275(1–2):127–177

    Article  MATH  MathSciNet  Google Scholar 

  • Caspi R, Foerster H, Fulcher CA, Kaipa P, Krummenacker M, Latendresse M, Paley S, Rhee SY, Shearer AG, Tissier C, Walk TC, Zhang P, Karp PD (2008) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 36(Database Issue):D623–D631

    Google Scholar 

  • Chang A, Scheer M, Grote A, Schomburg I, Schomburg D (2009) BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Res 37(Database Issue):D588–D592

    Google Scholar 

  • Chaouiya C (2007) Petri net modelling of biological networks. Brief Bioinform 8(4):210–219

    Article  Google Scholar 

  • Chaouiya C, Remy E, Thieffry D (2008) Petri net modelling of biological regulatory networks. J Discrete Algorithms 6(2):165–177

    Article  MATH  MathSciNet  Google Scholar 

  • Chatraryamontri A, Ceol A, Montecchi Palazzi L, Nardelli G, Schneider MV, Castagnoli L, Cesareni G (2007) MINT: the Molecular INTeraction database. Nucleic Acids Res 35(Database Issue):D572–D574

    Google Scholar 

  • Chen M (2002) Modelling and simulation of metabolic networks: Petri nets approach and perspective. In: Proceedings of the European simulation multiconference on modelling and simulation, pp 441–444

  • Chen M, Hofestädt R (2003) Quantitative Petri net model of gene regulated metabolic networks in the cell. In Silico Biol 3(0029):347–365

    Google Scholar 

  • Chen M, Freier A, Koehler J, Ruegg A (2002) The biology Petri net markup language. In: Promise2002. Lecture notes in informatics, pp 150–161

  • Crampin EJ, Schnell S, McSharry PE (2004) Matematical and computational techniques to deduce complex biochemical reaction mechanisms. Prog Biophys Mol Biol 86:77–112

    Article  Google Scholar 

  • Database of Interacting Proteins. http://www.dip.doe-mbi.ucla.edu

  • David R, Alla H (2005) Discrete, continuous, and hybrid Petri nets. Springer, Heidelberg

    MATH  Google Scholar 

  • de Jong H (2002) Modelling and simulation of genetic regulatory systems: a literature review. J Comput Biol 9(1):67–103

    Article  Google Scholar 

  • Desel J, Esparza J (2005) Free choice Petri nets. Cambridge University Press, Cambridge

    Google Scholar 

  • Design/CPN: computer tool for coloured petri nets. http://www.daimi.au.dk/designCPN

  • Deville Y, Gilbert D, van Helden J, Wodak SJ (2003) An overview of data models for the analysis of biochemical pathways. Brief Bioinform 4(3):246–259

    Article  Google Scholar 

  • Doi A, Fujita S, Matsuno H, Nagasaki M, Miyano S (2004) Constructing biological pathway models with hybrid functional Petri net. In Silico Biol 4(0023):271–291

    Google Scholar 

  • Doi A, Nagasaki M, Matsuno H (2006) Simulation-based validation of the p53 transcriptional activity with hybrid functional Petri net. In Silico Biol 6(0001):1–13

    Google Scholar 

  • Edwards JS, Covert M, Palsson BO (2002) Metabolic modelling of microbes: the flux-balance approach. Environ Microbiol 4(3):133–140

    Article  Google Scholar 

  • ENZYME: enzyme nomenclature database. http://www.expasy.ch/enzyme

  • Esparza J, Heljanko K (2008) Unfoldings—a partial order approach to model checking. EACTS monographs in theoretical computer science. Springer, Berlin

  • Esparza J, Nielsen M (1994) Decidability issues for Petri nets—a survey. J Inf Process Cybern EIK 30(3):143–160

    MATH  Google Scholar 

  • Extensible Markup Language. http://www.w3.org/XML

  • Fell DA (1992) Metabolic control analysis: a survey of its theoretical and experimental development. Biochem J 286:313–330

    Google Scholar 

  • Ganty P, Raskin J-F, Van Begin L (2007) From many places to few: automatic abstraction refinement for Petri nets. In: Kleijn J, Yakovlev A (eds) Proceedings of ICATPN’07, vol 4546 of LNCS. Springer, Berlin, pp 124–143

  • Genrich H, Küeffner R, Voss K (2000) Executable Petri net models for the analysis of metabolic pathways. In: Proceedings of the workshop on practical use of high-level Petri nets, pp 1–14

  • Gibson MA, Bruck J (2000) Efficient exact stochastic simulation of chemical systems with many species and many channels. J Phys Chem 25(104):1876–1889

    Google Scholar 

  • Gilbert D, Heiner M (2006) From Petri nets to differential equations—an integrative approach for biochemical networks analysis. In: Petri nets and other models of concurrency—ICATPN 2006, vol 4024 of LNCS. Springer, Berlin, pp 181–200

  • Gilbert D, Heiner M, Lehrack S (2007) A unifying frameworks for modelling and analysing biochemical pathways using Petri nets. In: Proceedings of the workshop on computational methods in systems biology (CMSB), pp 200–216

  • Gillespie DT (1977) Exact stochastic simulation of coupled chemical reactions. J Phys Chem 25(81):2340–2361

    Article  Google Scholar 

  • Goss PJ, Peccoud J (1998) Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets. Proc Natl Acad Sci USA 95(12):6750–6755

    Article  Google Scholar 

  • Grafahrend-Belau E, Schreiber F, Heiner M, Sackmann A, Junker BH, Grunwald S, Speer A, Winder K, Koch I (2008) Modularization of biochemical networks based on classification of Petri net T-invariants. BMC Bioinform 9:90

  • Grunwald S, Speer A, Ackermann J, Koch I (2008) Petri net modelling of gene regulation of the Duchenne muscular dystrophy. BioSystems 92:189–205

    Article  Google Scholar 

  • Hardy S, Robillard PN (2004) Modeling and simulation of molecular biology systems using Petri nets: modeling goals of various approaches. J Bioinform Comput Biol 2(4):619–637

    Article  Google Scholar 

  • Hardy S, Robillard PN (2008) Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways. Bioinformatics 24(2):209–217

    Article  Google Scholar 

  • Heiner M, Koch I (2004) Petri net based model validation in systems biology. In: Petri nets and other models of concurrency—ICATPN 2004, vol 3099 of LNCS. Springer, Berlin, pp 216–237

  • Heiner M, Koch I, Schuster S (2000) Using time-dependent Petri nets for the analysis of metabolic networks. In: Hofestadt R, Lautenbach K, Lange M (eds) Workshop Modellierung und Simulation Metabolischer Netzwerke, preprint no. 10. Otto-von-Guericke University of Magdeburg, pp 15–21

  • Heiner M, Koch I, Voss K (2001) Analysis and simulation of steady states in metabolic pathways with Petri nets. In: Workshop and tutorial on practical use of coloured Petri nets and the CPN tools (CPN’01), pp 15–34

  • Heiner M, Koch I, Will J (2004) Model validation of biological pathways using Petri nets—demostrated for apoptosis. Biosystems 75:15–28

    Article  Google Scholar 

  • Heiner M, Gilbert D, Donaldson R (2008) Petri nets for systems and synthetic biology. In: Proceedings of SFM’08, vol 5016 of LNCS. Springer, Berlin, pp 215–264

  • Heinrich R, Rapoport TA (1974) A linear steady-state treatment of enzymatic chains. Eur J Biochem 42:89–95

    Article  Google Scholar 

  • Hofer T, Heinrich R (1993) A second order approach to metabolic control analysis. J Theor Biol 164:85–102

    Article  Google Scholar 

  • Hofestädt R (1994) A Petri net application of metbolic processes. J Syst Anal Model Simul 16:113–122

    MATH  Google Scholar 

  • Hofestädt R, Thelen S (1998) Quantitative modeling of biochemical networks. In Silico Biol 1(0006)

  • Jensen K (1997) Coloured Petri nets. Basic concepts, analysis methods and practical use. Monographs in Theoretical Computer Science. Springer, Berlin

  • Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y (2008) KEGG for linking genomes to life and the environment. Nucleic Acids Res 34:D480–D484

    Google Scholar 

  • Kant K (1992) Introduction to computer system performance evaluation. McGraw-Hill Inc., New York

    Google Scholar 

  • Kegg Markup Language manual. http://www.genome.ad.jp/kegg/docs/xml

  • KEGG pathway database—Kyoto University Bioinformatics Centre. http://www.genome.jp/kegg/pathway.html

  • Kielbassa J, Bortfeldt R, Schuster S, Koch I (2008) Modeling of the U1 snRNP assembly pathway in alternative splicing in human cell using Petri nets. Comput Biol Chem 33:46–61

    Google Scholar 

  • Kitano H (2002a) Computational systems biology. Nature 420:206–210

    Article  Google Scholar 

  • Kitano H (2002b) Systems biology: a brief overview. Science 295:1662–1664

    Article  Google Scholar 

  • Koch I, Heiner M (2008) Petri nets. In: Junker BH, Schreiber F (eds) Analysis of biological networks, book series in bioinformatics. Wiley, New York, pp 139–179

  • Koch I, Junker BH, Heiner M (2005) Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber. Syst Biol 21(7):1219–1226

    Google Scholar 

  • Koza JR (2003) Handbook of metaheuristics—chap 7: automatic synthesis of topologies and numerical parameters, vol 57 of International Series in Operations Research and Management Science. Springer, New York

  • Liebermeister W, Uhlendorf J, Borger S, Klipp E (2007) Automatic integration of kinetic data for metabolic network modelling. In: ICSB 2007, ACM, pp 80–87

  • Lipton RJ (1976) The reachability problem requires exponential space, research report 62. Yale University, New Haven

  • Mandel J, Palfreyman NM, Lopez JA, Dubitzky W (2004) Representing bioinformatics causality. Brief Bioinform 5(3):270–283

    Article  Google Scholar 

  • Marwan W, Sujatha A, Starostzik C (2005) Reconstructing the regulatory network controlling commitment and sporulation in Physarum polycephalum based on hierarchical Petri net modelling and simulation. J Theor Biol 236:349–365

    Article  Google Scholar 

  • Matsuno H, Fujita S, Doi A, Nagasaki M, Miyano S (2003a) Towards biopathway modeling and simulation. In: ICATPN 2003, vol 2679 of LNCS. Springer, Berlin, pp 3–22

  • Matsuno H, Tanaka Y, Aoshima H, Doi A, Matsui M, Miyano S (2003b) Biopathway representation and simulation on hybrid functional Petri net. In Silico Biol 3(0032):389–404

  • Matsuno H, Li C, Miyano S (2006) Petri net based descriptions for systematic understanding of biological pathways. EICE Trans Fundam Electron Commun Comput Sci E89-A(11):3166–3174

    Article  Google Scholar 

  • Mayr EW (1981) Persistence of vector replacement systems is decidable. Acta Inform 15:309–318

    Article  MATH  MathSciNet  Google Scholar 

  • Merlin PM, Farber DJ (1976) Recoverability of communication protocols—implications of a theoretical study. IEEE Trans Commun 24(9):1036–1043

    Article  MATH  MathSciNet  Google Scholar 

  • MetaCyc encyclopedia of metabolic pathways. http://www.metacyc.org

  • MINT: the Molecular INTeraction database. http://www.mint.bio.uniroma2.it

  • Miyano S, Matsuno H (2004) How to model and simulate biological pathways with Petri Nets—a new challenge for system biology. In: International conference on applications and theory of Petri nets, Bologna, Italy

  • Moles CG, Mendes P, Banga R (2003) Parameter estimation in biochemical pathways: a comparison of global optimization methods. Genome Res 13:2467–2474

    Article  Google Scholar 

  • Molloy MK (1981) On the integration of delay and throughput measures in distributed processing models. PhD thesis, UCLA, Los Angeles

  • Murata T (1989) Petri nets: properties, analysis, and applications. Proc IEEE 77(4):541–580

    Article  Google Scholar 

  • Nagasaki M, Doi A, Matsuno H, Miyano S (2005) Petri net based description and modeling of biological pathways. In: Proceedings of the algebraic biology 2005. Universal Academy Press, pp 19–31

  • Oliveira JS, Bailey CG, Jones-Oliveira JB, Dixon DA, Gull DW, Chandler ML (2003) A computational model for the identification of biochemical pathways in the Krebs cycle. J Comput Biol 10(1):57–82

    Article  Google Scholar 

  • Pastor E, Cortadella J, Peña M (1999) Structural methods to improve the symbolic analysis of Petri nets. In: Donatelli S, Kleijn HCM (eds) Proceedings of ICATPN’99, vol 1639 of LNCS. Springer, Berlin, pp 26–45

  • PED—a hierarchical Petri net editor. http://www.dssz.informatik.tu-cottbus.de/index.html?/software/ped.htmll

  • Peleg M, Yeh I, Altman RB (2002) Modelling biological processes using workflow and Petri net models. Bioinformatics 18(6):825–837

    Article  Google Scholar 

  • Peleg M, Rabin D, Altman RB (2005) Using Petri net tools to study properties and dynamics of biological systems. J Am Med Inform Assoc 12:181–199

    Article  Google Scholar 

  • Peterson JL (1981) Petri net theory and the modelling of systems. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  • Petri Net Markup Language. http://www.pnml.org

  • Petri net tools. http://www.informatik.uni-hamburg.de/TGI/PetriNets/tools

  • Popova-Zeugmann L, Heiner M and Koch I (2005) Timed Petri nets for modelling and analysis of biochemical networks. Fundam Inform 67:149–162

    MATH  MathSciNet  Google Scholar 

  • REACTOME a curated knowledgebase of biological pathways. http://www.reactome.org

  • Reddy VN (1994) Modeling biological pathways: a discrete event systems approach. Master’s thesis, The Universisty of Maryland, M.S. 94-4

  • Reddy VN, Mavrovouniotis ML, Liebman MN (1993) Petri net representations in metabolic pathways. In: ISMB93: first international conference on intelligent systems for molecular biology. AAAI Press, pp 328–336

  • Reddy VN, Liebman MN, Mavrovouniotis ML (1996) Qualitative analysis of biochemical reaction systems. Comput Biol Med 26(1):9–24

    Article  Google Scholar 

  • Reisig W (1985) Petri nets: an introduction. EACTS monographs on theoretical computer science. Springer-Verlag, Berlin

  • Sackmann A, Heiner M, Koch I (2006) Application of Petri net based analysis techniques to signal transduction pathways. BMC Bioinform 7:482

    Google Scholar 

  • Sackmann A, Formanowicz D, Formanowicz P, Koch I, Blazewicz J (2007) An analysis of the Petri net based model of the human body iron homeostasis process. Comput Biol Chem 31:1–10

    Article  MATH  Google Scholar 

  • Salwinski L, Miller CS, Smith AJ, Pettit FK, Bowie JU, Eisenberg D (2004) The database of interacting proteins: 2004 update. Nucleic Acids Res 32(Database Issue):D449–D451

    Google Scholar 

  • SBML: Systems Biology Markup Language. http://www.sbml.org

  • Schilling CH, Schuster S, Palsson BO, Heinrich R (1999) Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era. Biotechnol Prog 15:296–303

    Article  Google Scholar 

  • Schilling CH, Letscherer D, Palsson BO (2000) Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective. J Theor Biol 203:229–248

    Article  Google Scholar 

  • Schroter C, Schwoon S, Esparza J (2003) The model checking kit. In: Proceedings of the 24th international conference on application and theory of Petri nets (ICATPN 03), vol 2697 of LNCS. Springer, Berlin, pp 463–472

  • Schuster S, Hilgetag C (1994) On elementary flux modes in biochemical reaction systems at steady state. J Biol Syst 2:165–182

    Article  Google Scholar 

  • Schuster S, Dandekar T, Fell DA (1999) Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol 17:53–60

    Article  Google Scholar 

  • Schuster S, Fell DA, Dandekar T (2000) A general definition of metabolic pathway useful for systematic organization and analysis of complex metabolic networks. Nat Biotechnol 18:326–332

    Article  Google Scholar 

  • Schuster S, Pfeiffer T, Moldenhauer F, Koch I, Dandekar T (2002) Exploring the pathway structure of metabolism: decomposition into subnetworks and application to Mycoplasma pneumoniae. Bioinformatics 18(2):351–361

    Article  Google Scholar 

  • Shaw O, Koelmans A, Steggles J, Wipat A (2004) Applying Petri nets to systems biology using XML technologies. In: Kindler E (ed) Proceedings of the workshop on the definition, implementation and application of a standard interchange format for Petri nets. Satellite event of ATPN, pp 11–25

  • Shaw O, Steggles J, Wipat A (2006) Automatic parameterisation of stochastic Petri net models of biological networks. Electron Notes Theor Comput Sci 151(3):111–129. Proceedings of the second international workshop on the practical application of stochastic modeling (PASM 2005).

    Google Scholar 

  • Simão E, Remy E, Thieffry D, Chaouiya C (2005) Qualitative modelling of regulated metabolic pathways: application to the tryptophan biosynthesis in E. coli. Syst Biol 21(2):ii190–ii196

    Google Scholar 

  • SNOOPY: a software tool to design and animate hierarchical graphs. http://www.dssz.informatik.tu-cottbus.de/index.html?/software/snoopy.html

  • Starke PH, Roch S (1999) The integrated net analyzer. Humbolt University, Berlin. http://www.informatik.hu-berlin.de/starke/ina.html

  • Tovchigrechko A (2006) Model checking using interval decision diagrams. PhD thesis, Department of Computer Science, BTU Cottbus

  • TRANSPATH: the pathway database. http://www.biobase-international.com

  • Valk R (1978) Self-modifying nets, a natural extension of Petri nets. In: Ausiello G, Böhm C (eds) Proceedings of ICALP’78, vol 62 of LNCS. Springer, Berlin, pp 464–476

  • Valk R, Vidal-Naquet G (1981) Petri nets and regular languages. J Comput Syst Sci 23(3):299–325

    Article  MATH  MathSciNet  Google Scholar 

  • Varma A, Palsson BO (1994) Metabolic flux balancing: basic concepts, scientific and practical use. Bio/Technology 12:994–998

    Article  Google Scholar 

  • Voet DJ, Voet JG (2004) Biochemistry. Wiley, New York

    Google Scholar 

  • Voss K, Heiner M, Koch I (2003) Steady state analysis of metabolic pathways using Petri nets. In Silico Biol 3(0031):367–387

  • Wiekert W (2002) Modelling and simulation: tools for metabolic engineering. J Biotechnol 94(1):37–63

    Article  Google Scholar 

  • Wilkinson DJ (2006) Stochastic modelling for systems biology. Chapman and Hall/CRC, Boca Raton

    MATH  Google Scholar 

  • Zevedei-Oancea I, Schuster S (2003) Topological analysis of metabolic networks based on Petri net theory. In Silico Biol 3(0029):323–345

    Google Scholar 

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Acknowledgements

The authors are grateful to Marcantonio Bragadin of the Dipartimento di Scienze Ambientali—Università Ca’ Foscari di Venezia, for enlightening discussions on metabolic pathways and biochemical issues. They are also greatly indebted to the anonymous referees for their extensive and valuable comments and suggestions on preliminary versions of the paper.

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  1. Dipartimento di Matematica Pura e Applicata, Università di Padova, via Trieste 63, 35121, Padova, Italy

    Paolo Baldan

  2. Dipartimento di Informatica, Università Ca’ Foscari di Venezia, via Torino 155, 30172, Venezia Mestre, Italy

    Nicoletta Cocco, Andrea Marin & Marta Simeoni

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  1. Paolo Baldan
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Baldan, P., Cocco, N., Marin, A. et al. Petri nets for modelling metabolic pathways: a survey. Nat Comput 9, 955–989 (2010). https://doi.org/10.1007/s11047-010-9180-6

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