Abstract
The complexity of biological regulatory networks calls for the development of proper mathematical methods to model their structures and to give insight in their dynamical behaviours. One qualitative approach consists in modelling regulatory networks in terms of logical equations (using either Boolean or multi-level discretisation). Petri Nets (PNs) offer a complementary framework to analyse large systems.
In this paper, we propose to articulate the logical approach with PNs. We first revisit the definition of a rigourous and systematic mapping of multi-level logical regulatory models into specific standard PNs, called Multi-level Regulatory Petri Nets (MRPNs). In particular, we consider the case of multiple arcs representing different regulatory effects from the same source. We further propose a mapping of multi-level logical regulatory models into Coloured PNs, called Coloured Regulatory Petri Nets (CRPNs). These CRPNs provide an intuitive graphical representation of regulatory networks, relatively easy to grasp.
Finally, we present the PN translation and the analysis of a multi-level logical model of the core regulatory network controlling the differentiation of T-helper lymphocytes into Th1 and Th2 types.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bryant, R.: Graph-Based Algorithms for Boolean Function Manipulation. IEEE Transactions on Computers C-35, 677–691 (1986)
Chaouiya, C., Remy, E., Mossé, B., Thieffry, D.: Qualitative analysis of regulatory graphs: A computational tool based on a discrete formal framework. LNCIS, vol. 294, pp. 119–126 (2003)
Chaouiya, C., Remy, É., Ruet, P., Thieffry, D.: Qualitative Modelling of Genetic Networks: From Logical Regulatory Graphs to Standard Petri Nets. In: Cortadella, J., Reisig, W. (eds.) ICATPN 2004. LNCS, vol. 3099, pp. 137–156. Springer, Heidelberg (2004)
Chaouiya, C., Remy, E., Thieffry, D.: Petri Net Modelling of Biological Regulatory Networks. In: Proc. of CompBioNets 2004. KCL publications, London (2004)
Comet, J.-P., Klaudel, H., Liauzu, S.: Modeling Multi-valued Genetic Regulatory Networks Using High-Level Petri Nets. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 208–227. Springer, Heidelberg (2005)
de Jong, H.: Modeling and Simulation of Genetic Regulatory Systems: A Literature Review. J. Comput. Biol. 9, 67–103 (2002)
Devloo, V., Hansen, P., Labbe, M.: Identification of all steady states in large networks by logical analysis. Bull. Math. Biol. 65, 1025–1051 (2003)
Glass, L., Kauffman, S.A.: The logical analysis of continuous, non-linear biochemical control networks. J. theor. Biol. 39, 103–129 (1973)
Gonzalez, A.G., Naldi, A., Sánchez, L., Thieffry, D., Chaouiya, C.: GINsim: a software suite for the qualitative modelling, simulation and analysis of regulatory networks. Biosystems 84(2), 91–100 (2006)
Goss, P.J.E., Peccoud, J.: Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets. Proc. Nat. Acad. Sci. USA. 95, 6750–6755 (1998)
Hardy, S., Robillard, P.N.: Modeling and simulation of molecular biology systems using petri nets: modeling goals of various approaches. J. Bioinform. Comput. Biol. 2, 595–613 (2004)
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)
Hofestädt, R., Thelen, S.: Quantitative Modeling of Biochemical Networks. Silico Biol. 1, 39–53 (1998)
Jensen, K.: An introduction to the theoretical aspects of coloured Petri nets. In: de Bakker, J.W., de Roever, W.-P., Rozenberg, G. (eds.) REX 1993. LNCS, vol. 803, pp. 230–272. Springer, Heidelberg (1994)
Matsuno, H., Doi, A., Nagasaki, M., Miyano, S.: Hybrid Petri net representation of gene regulatory networks. In: Proc. Pac. Symp. Biocomput., pp. 341–352 (2000)
Mendoza, L.: A network model for the control of the differentiation process in Th cells. Biosystems 84(2), 101–114 (2006)
Murata, T.: Petri Nets: Properties, Analysis and Applications. Proc. IEEE 77, 541–580 (1989)
Reddy, V.N., Liebman, M.N., Mavrovouniotis, M.L.: Qualitative analysis of biochemical reaction systems. Comput. Biol. Med. 26, 9–24 (1996)
Remy, É., Ruet, P., Mendoza, L., Thieffry, D., Chaouiya, C.: From logical regulatory graphs to standard petri nets: Dynamical roles and functionality of feedback circuits. In: Priami, C., Ingólfsdóttir, A., Mishra, B., Riis Nielson, H. (eds.) Transactions on Computational Systems Biology VII. LNCS (LNBI), vol. 4230, pp. 56–72. Springer, Heidelberg (2006)
Simao, E., Remy, E., Thieffry, D., Chaouiya, C.: Qualitative Modelling of Regulated Metabolic Pathways: Application to the Tryptophan Biosynthesis in E. Coli. Bioinformatics 21, 190–196 (2005)
Thomas, R.: Regulatory networks seen as asynchronous automata: a logical description. J. theor. Biol. 153, 1–23 (1991)
Thomas, R., Thieffry, D., Kaufman, M.: Dynamical behaviour of biological regulatory networks–I. Biological role of feedback loops and practical use of the concept of the loop-characteristic state. Bull. Math. Biol. 57, 247–276 (1995)
Zevedei-Oancea, I., Schuster, S.: Topological analysis of metabolic networks based on Petri net theory. Silico Biol. 3, 0029 (2003)
INA: Integrated Net Analyzer URL: http://www.informatik.hu-berlin.de/lehrstuehle/automaten/ina/
GINsim (Gene Interaction Network simulation), URL http://gin.univ-mrs.fr/GINsim
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chaouiya, C., Remy, E., Thieffry, D. (2006). Qualitative Petri Net Modelling of Genetic Networks. In: Priami, C., Plotkin, G. (eds) Transactions on Computational Systems Biology VI. Lecture Notes in Computer Science(), vol 4220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880646_5
Download citation
DOI: https://doi.org/10.1007/11880646_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45779-4
Online ISBN: 978-3-540-46236-1
eBook Packages: Computer ScienceComputer Science (R0)