Abstract
The complexity of biological regulatory networks calls for the development of proper mathematical methods to model their structures and to obtain insight in their dynamical behaviours. One qualitative approach consists in modelling regulatory networks in terms of logical equations (using either Boolean or multi-valued discretisation).
In this paper, we propose a novel implementation of the generalised logical formalism by means of Multi-valued Decision Diagrams. We show that the use of this representation enables the development of efficient algorithms for the analysis of specific dynamical properties of the regulatory graphs. In particular, we address the question of determining conditions insuring the functionality of feedback circuits, as well as the identification of stable states. Finally, we apply these algorithms to logical models of T cell activation and differentiation.
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References
Bryant, R.E.: Graph-based algorithms for boolean function manipulation. IEEE Trans. Comput. 35, 677–691 (1986)
Burch, J.R., Clarke, E.M., Long, D.E., MacMillan, K.L., Dill, D.L.: Symbolic Model Checking for Sequential Circuit Verification. IEEE Trans. Comput.-Aided Design Integrated Circuits 13, 401–424 (1994)
Chaouiya, C., Remy, E., Mossé, B., Thieffry, D.: Qualitative analysis of regulatory graphs: a computational tool based on a discrete formal framework. In: Cori, R., Wirsing, M. (eds.) STACS 88. LNCS, vol. 294, pp. 119–126. Springer, Heidelberg (1988)
Garg, A., Xenarios, I., Mendoza, L., DeMicheli, G.: An Efficient Method for Dynamic Analysis of Gene Regulatory Networks and in-silico Gene Perturbation Experiments. Lect. Notes Comp. Sci. 4453, 62–76 (2007)
González, A., Naldi, A., Sanchez, L., Thieffry, D., Chaouiya, C.: GINsim: A software suite for the qualitative modelling, simulation and analysis of regulatory networks. Biosystems 84, 91–100 (2006)
Kam, T., Villa, T., Brayton, R.K., Sangiovanni-Vincentelli, A.L.: Multi-valued decision diagrams: Theory and applications. Int. J. Multiple-Valued Logic 4, 9–12 (1998)
Klamt, S., Saez-Rodriguez, J., Lindquist, J.A., Simeoni, L., Gilles, E.D.: A methodology for the structural and functional analysis of signaling and regulatory networks. BMC Bioinformatics 7(56) (2006)
Mendoza, L.: A network model for the control of the differentiation process in Th cells. Biosystems 84, 101–114 (2006)
Remy, E., 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., Nielson, H.R. (eds.) Transactions on Computational Systems Biology VII. LNCS (LNBI), vol. 4230, pp. 55–72. Springer, Heidelberg (2006)
Soulé, C.: Graphic requirements for multistationarity. ComPlexUs 1, 123–133 (2003)
Thomas, R.: On the relation between the logical structure of systems and their ability to generate multiple steady states of sustained oscillations. Springer Series Synergetics 9, 180–193 (1988)
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)
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Naldi, A., Thieffry, D., Chaouiya, C. (2007). Decision Diagrams for the Representation and Analysis of Logical Models of Genetic Networks. In: Calder, M., Gilmore, S. (eds) Computational Methods in Systems Biology. CMSB 2007. Lecture Notes in Computer Science(), vol 4695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75140-3_16
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DOI: https://doi.org/10.1007/978-3-540-75140-3_16
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