Abstract
This paper presents an evolutionary-based parameter estimation procedure able to deal with the particularities of the constraints arising in mathematical models of biological systems. A measure of the constraint satisfaction degree and several feasibility-based ranking rules are proposed and comparatively analyzed for the problem of estimating the parameters involved in a model describing the dynamics of thymocytes. The numerical results illustrate the effectiveness of the procedure in inferring models which fit well the experimental data and also satisfy the biological constraints.
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References
Deb, K.: An efficient constraint handling method for genetic algorithms. Comput. Methods Appl. Mech. Eng. 186, 311–338 (2000)
Mehr, R., Globerson, A., Perelson, A.S.: Modeling positive and negative selection and differentiation processes in the thymus. J. Theor. Biol. 175, 103–126 (1995)
Mezura-Montes, E., Coello Coello, C.A.: Constraint-handling in nature-inspired numerical optimization: past, present and future. Swarm Evol. Comput. 1, 173–194 (2011)
Mezura-Montes, E., Miranda-Varela, M.E., Gomez-Ramon, R.C.: Differential evolution in constrained numerical optimization: an empirical study. Inf. Sci. 180, 4223–4262 (2010)
Runarsson, T.P., Yao, X.: Stochastic ranking for constrained evolutionary optimization. IEEE Trans. Evol. Comput. 4, 284–294 (2000)
Takahama, T., Sakai, S.: Constrained optimization by \(\epsilon \)-constrained particle swarm optimizer with \(\epsilon \)-level control. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds.) WSTST 2005. Advances in Soft Computing, vol. 29, pp. 1019–1029. Springer, Heidelberg (2005)
Tashkova, K., Korošek, P., Šilc, J., Todorovski, L., Džeroski, S.: Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis. BMC Syst. Biol. 5, 159 (2011). doi:10.1186/1752-0509-5-159
Zhang, J., Sanderson, A.C.: JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13(5), 945–958 (2009)
Acknowledgments
This work was supported by grant no. PN-II-ID-PCE-2011-3-0571 and by the strategic grant POSDRU/CPP107/DMI1.5/S/78421, Project ID 78421 (2010), co-financed by the European Social Fund Investing in People, within the Sectoral Operational Programme Human Resources Development 2007–2013. The authors thank Dr. Felix Mic (University of Medicine and Pharmacy, Timisoara) for providing the experimental data.
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Moatar-Moleriu, L., Negru, V., Zaharie, D. (2014). Evolutionary Estimation of Parameters in Computational Models of Thymocyte Dynamics. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2013. Lecture Notes in Computer Science(), vol 8353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43880-0_30
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DOI: https://doi.org/10.1007/978-3-662-43880-0_30
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