Summary. In this paper we critically analyze the use of multiagent systems for performing simulations of biological processes. From the one hand, the possibility of associating different elements of a biological process to independent computing entities, called agents, makes multiagent systems a powerful and flexible tool for simulation. From the other hand, the weak validation of the results obtained makes multiagent-based simulations hard to trust. We discuss these issues by referring to a specific example, the simulation of a signal transduction pathway.
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References
Regev, A., Shapiro, E.: Cells as computation. Nature 419 (2002) 343
Wooldridge, M.: An Introduction to Multiagent Systems. John Wiley and Sons, Chichester, UK (2002)
Humphreys, P.: Computer simulations. In Fine, A., Forbes, M., Wessels, L., eds.: Proceedings of the 1990 Biennal Meeting of the Philosophy of Science Asso-ciation, East Lansing, MI, USA (1991) 497-506
Andy, D., Brent, R.: Modelling cellular behaviour. Nature 409 (2001) 391-395
Hughes, R.I.G.: The Ising model, computer simulation, and universal physics. In Morgan, M., Morrison, M., eds.: Models as Mediators. Cambridge University Press, Cambridge, UK (1999) 97-145
Bedau, M.: Can unrealistic computer models illuminate theoretical biology? In: Proceedings of the Genetic and Evolutionary Computation Conference Work-shop Program. (1999) 20-23
Jennings, N.: An agent-based approach for building complex software systems. Communications of the ACM 44 (2001) 35-41
Luck, M., Ashri, R., D’Inverno, M.: Agent-Based Software Development. Artech House, Boston MA, USA (2004)
Karasavvas, K.A., Baldock, R., Burger, A.: Bioinformatics integration and agent technology. Journal of Biomedical Informatics 37 (2004) 205-219
Bazzan, A.L.C., Duarte, R., Pitinga, A.N., Schroeder, L.F., Souto, F.D.A.: ATUCG - An agent-based environment for automatic annotation of genomes. International Journal of Cooperative Information Systems 12 (2003) 241-273
Decker, K., Khan, S., Schmidt, C., Situ, G., Makkena, R., Michaud, D.: Bio-mas: A multi-agent system for genomic annotation. International Journal of Cooperative Information Systems 11 (2002) 265-292
Cannata, N., Corradini, F., Merelli, E., Omicini, A., Ricci, A.: An agent-oriented conceptual framework for systems biology. In Merelli, E., González Perez, P.P., Omicini, A., eds.: Transactions on Computational Systems Biology. Volume III of LNBI. Springer (2005) 105-122
Jonker, C.M., Snoep, J.L., Treur, J., Westerhoff, H.V., Wijngaards, E.C.A.: BDI-modelling of intracellular dynamics. In: Proceedings of the First Interna-tional Workshop on Bioinformatics and Multi-Agent Systems. (2002) 15-23
Ballet, P., Pers, J.O., Rodin, V., Tisseau, J.: A multiagent system to simulate an apoptosis model of B-CD5 cells. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics. (1998) 3799-3803
Bortolussi, L., Dovier, A., Fogolari, F.: Multi-agent simulation of protein folding. In: Proceedings of the First International Workshop on Multi-Agent Systems for Medicine, Computational Biology, and Bioinformatics. (2005)
Lodish, H., Berk, A., Zipursky, L., Matsudaira, P., Baltimore, D., Darnell, J.: Molecular Cell Biology. W.H. Freeman and Company, New York, NY, USA (2000)
Kolch, W., Calderc, M., Gilbert, D.: When kinases meet mathematics: The systems biology of MAPK signalling. FEBS Letters 579 (2005) 1891-1895
Orton, R.J., Sturm, O.E., Vyshermirsky, V., Calder, M., Gilbert, D.R., Kolch, W.: Computational modelling of the receptor-tyrosine-kinase-activated MAPK pathway. Biochemical Journal 392 (2005) 249-261
Querrec, G., Rodin, V., Abgrall, J.F., Kerdelo, S., Tisseau, J.: Uses of multi-agents systems for simulation of mapk pathway. In: Proceedings of the Third IEEE Symposium on Bioinformatics and Bioengineering (BIBE03). (2003) 421-425
Gonzáles, P.P., Cárdenas, M., Camacho, D., Franyuti, A., Rosas, O., Lagúnez-Otero, J.: Cellulat: An agent-based intracellular signalling model. BioSystems 68 (2003) 171-185
Khan, S., Makkena, R., McGeary, F., Decker, K., Gillis, W., Schmidt, C.: A multiagent system for the quantitative simulation of biological networks. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS2003). (2003) 385-392
Naylor, T.H.: Computer Simulation Techniques. John Wiley, New York, NY, USA (1966)
Hartmann, S.: The world as a process: Simulations in the natural and social sciences. In Hegselmann, R., Mueller, U., Troitzsch, K.G., eds.: Simulation and Modeling in the Social Sciences from the Philosophy of Science Point of View. Theory and Decision Library. Kluwer, Dordrecht, The Netherlands (1996) 77-100
Rohrlich, F.: Computer simulation in the physical sciences. In Fine, A., Forbes, M., Wessels, L., eds.: Proceedings of the 1990 Biennal Meeting of the Philosophy of Science Association, East Lansing, MI, USA (1991) 145-163
Zhao, J., Stevens, R.D., Wroe, C.J., Greenwood, M., Goble, C.A.: The origin and history of in silico experiments. In: Proceedings of the UK e-Science All Hands Meeting. (2006)
Desmeulles, G., Querrec, J., Redou, P., Kerdlo, S., Misery, L., Rodin, V., Tisseau, J.: The virtual reality applied to biology understanding: The in virtuo experimentation. Expert Systems with Applications 30 (2006) 82-92
Tisseau, J.: Virtual reality, in virtuo autonomy. Accreditation to Direct Research, University of Rennes 1 (2001)
Winsberg, E.: Models of success vs. success of models: Reliability without truth. Synthese 152 (2006) 1-19
Hacking, I.: Representing and Intervening. Cambridge University Press, Cambridge, MA, USA (1983)
Smallwood, R.H., Holcombe, W.M.L., Wlaker, D.: Development and validation of computational models of cellular interaction. Journal of Molecular Histology 35 (2004) 659-665
Amigoni, F., Schiaffonati, V.: A multiagent approach to modelling complex phenomena. Foundations of Science (forthcoming)
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Amigoni, F., Schiaffonati, V. (2007). Multiagent-Based Simulation in Biology. In: Magnani, L., Li, P. (eds) Model-Based Reasoning in Science, Technology, and Medicine. Studies in Computational Intelligence, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71986-1_10
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