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Global Optimization in Systems Biology: Stochastic Methods and Their Applications

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Book cover Advances in Systems Biology

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 736))

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Abstract

Mathematical optimization is at the core of many problems in systems biology: (1) as the underlying hypothesis for model development, (2) in model identification, or (3) in the computation of optimal stimulation procedures to synthetically achieve a desired biological behavior. These problems are usually formulated as nonlinear programing problems (NLPs) with dynamic and algebraic constraints. However the nonlinear and highly constrained nature of systems biology models, together with the usually large number of decision variables, can make their solution a daunting task, therefore calling for efficient and robust optimization techniques. Here, we present novel global optimization methods and software tools such as cooperative enhanced scatter search (eSS), AMIGO, or DOTcvpSB, and illustrate their possibilities in the context of modeling including model identification and stimulation design in systems biology.

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Acknowledgments

This work was supported by the Spanish MICINN project “MultiSysBio” (ref. DPI2008-06880-C03-02), and by CSIC intramural project “BioREDES” (ref. PIE-201170E018).

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Authors and Affiliations

  1. (Bio)Process Engineering Group, IIM-CSIC, C/Eduardo Cabello 6, 36208, Vigo, Spain

    Eva Balsa-Canto, J. R. Banga, A. Fernandez-Villaverde & G. M. de Hijas-Liste

  2. Department of Applied Mathematics and Statistics, Technical University of Cartagena (UPCT), Cartagena, Spain

    J. A. Egea

Authors
  1. Eva Balsa-Canto
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  2. J. R. Banga
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  3. J. A. Egea
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  4. A. Fernandez-Villaverde
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  5. G. M. de Hijas-Liste
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Corresponding author

Correspondence to Eva Balsa-Canto .

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Editors and Affiliations

  1. School of Informatics, University of Edinburgh, Crichton Street 10, Edinburgh, EH89AB, UK

    Igor I. Goryanin

  2. School of Biological Sciences, University of Edinburgh, Mayfield Road, Edinburgh, EH93JR, UK

    Andrew B. Goryachev

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Balsa-Canto, E., Banga, J.R., Egea, J.A., Fernandez-Villaverde, A., de Hijas-Liste, G.M. (2012). Global Optimization in Systems Biology: Stochastic Methods and Their Applications. In: Goryanin, I.I., Goryachev, A.B. (eds) Advances in Systems Biology. Advances in Experimental Medicine and Biology, vol 736. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7210-1_24

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