Abstract
Biologists use diagrams to represent interactions between molecular species, and on the computer, diagrammatic notations are also employed in interactive maps. These diagrams are fundamentally of two types: reaction graphs and activation/inhibition graphs. In this tutorial, we study these graphs with formal methods originating from programming theory. We consider systems of biochemical reactions with kinetic expressions, as written in the Systems Biology Markup Language (SBML), and interpreted in the Biochemical Abstract Machine (Biocham) at different levels of abstraction, by either an asynchronous boolean transition system, a continuous time Markov chain, or a system of Ordinary Differential Equations over molecular concentrations. We show that under general conditions satisfied in practice, the activation/inhibition graph is independent of the precise kinetic expressions, and is computable in linear time in the number of reactions. Then we consider the formalization of the biological properties of systems, as observed in experiments, in temporal logics. We show that these logics are expressive enough to capture semi-qualitative semi-quantitative properties of the boolean and differential semantics of reaction models, and that model-checking techniques can be used to validate a model w.r.t. its temporal specification, complete it, and search for kinetic parameter values. We illustrate this modelling method with examples on the MAPK signalling cascade, and on Kohn’s map of the mammalian cell cycle.
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Kohn, K.W.: Molecular interaction map of the mammalian cell cycle control and DNA repair systems. Molecular Biology of the Cell 10, 2703–2734 (1999)
Hucka, M., et al.: The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics 19, 524–531 (2003)
Thomas, R., Gathoye, A.M., Lambert, L.: A complex control circuit: regulation of immunity in temperate bacteriophages. European Journal of Biochemistry 71, 211–227 (1976)
Kaufman, M., Soulé, C., Thomas, R.: A new necessary condition on interaction graphs for multistationarity. Journal of Theoretical Biology 248, 675–685 (2007)
Soulé, C.: Mathematical approaches to differentiation and gene regulation. C.R. Biologies 329, 13–20 (2006)
Soulé, C.: Graphic requirements for multistationarity. ComplexUs 1, 123–133 (2003)
Snoussi, E.: Necessary conditions for multistationarity and stable periodicity. J. Biol. Syst. 6, 3–9 (1998)
Gouzé, J.L.: Positive and negative circuits in dynamical systems. J. Biol. Syst. 6, 11–15 (1998)
Calzone, L., Fages, F., Soliman, S.: BIOCHAM: An environment for modeling biological systems and formalizing experimental knowledge. BioInformatics 22, 1805–1807 (2006)
Fages, F., Soliman, S., Chabrier-Rivier, N.: Modelling and querying interaction networks in the biochemical abstract machine BIOCHAM. Journal of Biological Physics and Chemistry 4, 64–73 (2004)
Hlavacek, W.S., Faeder, J.R., Blinov, M.L., Posner, R.G., Hucka, M., Fontana, W.: Rules for modeling signal-transduction systems. Science STKE 344, 6 (2006)
Soliman, S., Fages, F.: CMBSlib: a library for comparing formalisms and models of biological systems. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 231–235. Springer, Heidelberg (2005)
Fages, F., Soliman, S.: Abstract interpretation and types for systems biology. In: Theoretical Computer Science (to appear, 2008)
Calzone, L., Chabrier-Rivier, N., Fages, F., Soliman, S.: Machine learning biochemical networks from temporal logic properties. In: Priami, C., Plotkin, G. (eds.) Transactions on Computational Systems Biology VI. LNCS (LNBI), vol. 4220, pp. 68–94. Springer, Heidelberg (2006)
Fages, F.: From syntax to semantics in systems biology - towards automated reasoning tools. Transactions on Computational Systems Biology IV 3939, 68–70 (2006)
Chabrier-Rivier, N., Chiaverini, M., Danos, V., Fages, F., Schächter, V.: Modeling and querying biochemical interaction networks. Theoretical Computer Science 325, 25–44 (2004)
Levchenko, A., Bruck, J., Sternberg, P.W.: Scaffold proteins biphasically affect the levels of mitogen-activated protein kinase signaling and reduce its threshold properties. PNAS 97, 5818–5823 (2000)
Ventura, A.C., Sepulchre, J.A., Merajver, S.D.: A hidden feedback in signaling cascades is revealed. In: PLoS Computational Biology (to appear, 2008)
Markevich, N.I., Hoek, J.B., Kholodenko, B.N.: Signaling switches and bistability arising from multisite phosphorylation in protein kinase cascades. Journal of Cell Biology 164, 353–359 (2005)
Kolch, W., Kotwaliwale, A., Vass, K., Janosch, P.: The role of raf kinases in malignant transformation. In: Expert Reviews in Molecular Medicine, vol. 25, Cambridge University Press, Cambridge (2002)
Shapiro, B.E., Levchenko, A., Meyerowitz, E.M., Wold, B.J., Mjolsness, E.D.: Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations. Bioinformatics 19, 677–678 (2003)
Regev, A., Silverman, W., Shapiro, E.Y.: Representation and simulation of biochemical processes using the pi-calculus process algebra. In: Proceedings of the sixth Pacific Symposium of Biocomputing, pp. 459–470 (2001)
Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry 81, 2340–2361 (1977)
Gillespie, D.T.: General method for numerically simulating stochastic time evolution of coupled chemical-reactions. Journal of Computational Physics 22, 403–434 (1976)
Gibson, M.A., Bruck, J.: A probabilistic model of a prokaryotic gene and its regulation. In: Bolouri, H., Bower, J. (eds.) Computational Methods in Molecular Biology: From Genotype to Phenotype, MIT press, Cambridge (2000)
Reddy, V.N., Mavrovouniotis, M.L., Liebman, M.N.: Petri net representations in metabolic pathways. In: Hunter, L., Searls, D.B., Shavlik, J.W. (eds.) Proceedings of the 1st International Conference on Intelligent Systems for Molecular Biology (ISMB, pp. 328–336. AAAI Press, Menlo Park (1993)
Sackmann, A., Heiner, M., Koch, I.: Application of petri net based analysis techniques to signal transduction pathways. BMC Bioinformatics 7 (2006)
Chaouiya, C.: Petri net modelling of biological networks. Briefings in Bioinformatics (2007)
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, Springer, Heidelberg (2007)
Schuster, S., Pfeiffer, T., Moldenhauer, F., et al.: Exploring the pathway structure of metabolism: decomposition into subnetworks and application to mycoplasma pneumoniae. Bioinformatics 18, 51–61 (2002)
Zevedei-Oancea, I., Schuster, S.: Topological analysis of metabolic networks based on petri net theory. Silico Biology 3 (2003)
Chabrier, N., Fages, F.: Symbolic model cheking of biochemical networks. In: Priami, C. (ed.) CMSB 2003. LNCS, vol. 2602, pp. 149–162. Springer, Heidelberg (2003)
Eker, S., Knapp, M., Laderoute, K., Lincoln, P., Meseguer, J., Sönmez, M.K.: Pathway logic: Symbolic analysis of biological signaling. In: Proceedings of the seventh Pacific Symposium on Biocomputing, pp. 400–412 (2002)
Cousot, P., Cousot, R.: Abstract interpretation: A unified lattice model for static analysis of programs by construction or approximation of fixpoints. In: POPL 1977: Proceedings of the 6th ACM Symposium on Principles of Programming Languages, Los Angeles, pp. 238–252. ACM Press, New York (1977)
Cousot, P.: Constructive design of a hierarchy of semantics of a transition system by abstract interpretation. Theoretical Computer Science 277, 47–103 (2002)
Cousot, P.: Types as abstract interpretation. In: POP 1997: Proceedings of the 24th ACM Symposium on Principles of Programming Languages, pp. 316–331. ACM Press, New York (1997)
Qiao, L., Nachbar, R.B., Kevrekidis, I.G., Shvartsman, S.Y.: Bistability and oscillations in the huang-ferrell model of mapk signaling. PLoS Computational Biology 3, 1819–1826 (2007)
Clarke, E.M., Grumberg, O., Peled, D.A.: Model Checking. MIT Press, Cambridge (1999)
Bernot, G., Comet, J.P., Richard, A., Guespin, J.: A fruitful application of formal methods to biological regulatory networks: Extending thomas’ asynchronous logical approach with temporal logic. Journal of Theoretical Biology 229, 339–347 (2004)
Batt, G., Bergamini, D., de Jong, H., Garavel, H., Mateescu, R.: Model checking genetic regulatory networks using gna and cadp. In: Graf, S., Mounier, L. (eds.) SPIN 2004. LNCS, vol. 2989, Springer, Heidelberg (2004)
Calder, M., Vyshemirsky, V., Gilbert, D., Orton, R.: Analysis of signalling pathways using the continuous time markow chains. In: Priami, C., Plotkin, G. (eds.) Transactions on Computational Systems Biology VI. LNCS (LNBI), vol. 4220, pp. 44–67. Springer, Heidelberg (2006)
Heath, J., Kwiatkowska, M., Norman, G., Parker, D., Tymchyshyn, O.: Probabilistic model checking of complex biological pathways. In: Priami, C. (ed.) CMSB 2006. LNCS (LNBI), vol. 4210, pp. 32–47. Springer, Heidelberg (2006)
Antoniotti, M., Policriti, A., Ugel, N., Mishra, B.: Model building and model checking for biochemical processes. Cell Biochemistry and Biophysics 38, 271–286 (2003)
Fages, F.: Temporal logic constraints in the biochemical abstract machine biocham (invited talk). In: Hill, P.M. (ed.) LOPSTR 2005. LNCS, vol. 3901, Springer, Heidelberg (2006)
Cardelli, L.: Brane calculi - interactions of biological membranes. In: Danos, V., Schachter, V. (eds.) CMSB 2004. LNCS (LNBI), vol. 3082, pp. 257–280. Springer, Heidelberg (2005)
Regev, A., Panina, E.M., Silverman, W., Cardelli, L., Shapiro, E.: Bioambients: An abstraction for biological compartments. Theoretical Computer Science 325, 141–167 (2004)
Danos, V., Laneve, C.: Formal molecular biology. Theoretical Computer Science 325, 69–110 (2004)
Phillips, A., Cardelli, L.: A correct abstract machine for the stochastic pi-calculus. Transactions on Computational Systems Biology Special issue of BioConcur (to appear, 2004)
Fages, F., Soliman, S.: Type inference in systems biology. In: Priami, C. (ed.) CMSB 2006. LNCS (LNBI), vol. 4210, Springer, Heidelberg (2006)
Cimatti, A., Clarke, E., Enrico Giunchiglia, F.G., Pistore, M., Roveri, M., Sebastiani, R., Tacchella, A.: Nusmv 2: An opensource tool for symbolic model checking. In: Brinksma, E., Larsen, K.G. (eds.) CAV 2002. LNCS, vol. 2404, Springer, Heidelberg (2002)
Fages, F., Rizk, A.: On the analysis of numerical data time series in temporal logic. In: Calder, M., Gilmore, S. (eds.) CMSB 2007. LNCS (LNBI), vol. 4695, pp. 48–63. Springer, Heidelberg (2007)
Fages, F., Soliman, S.: Model revision from temporal logic properties in systems biology. In: Probabilistic Inductive Logic Programming. LNCS, vol. 4911, pp. 287–304. Springer, Heidelberg (2008)
Hansson, H., Jonsson, B.: A logic for reasoning about time and reliability. Formal Aspects of Computing 6, 512–535 (1994)
Kwiatkowska, M.Z., Norman, G., Parker, D.: Prism 2.0: A tool for probabilistic model checking. In: st International Conference on Quantitative Evaluation of Systems (QEST 2004), pp. 322–323. IEEE Computer Society, Los Alamitos (2004)
Hérault, T., Lassaigne, R., Magniette, F., Peyronnet, S.: Approximate probabilistic model checking. In: Steffen, B., Levi, G. (eds.) VMCAI 2004. LNCS, vol. 2937, pp. 73–84. Springer, Heidelberg (2004)
Gibson, M.A., Bruck, J.: Efficient exact stochastic simulation of chemical systems with many species and many channels. Journal of Physical Chemistry 104, 1876–1889 (2000)
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Fages, F., Soliman, S. (2008). Formal Cell Biology in Biocham. In: Bernardo, M., Degano, P., Zavattaro, G. (eds) Formal Methods for Computational Systems Biology. SFM 2008. Lecture Notes in Computer Science, vol 5016. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68894-5_3
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DOI: https://doi.org/10.1007/978-3-540-68894-5_3
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