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An adaptive genetic algorithm for parameter estimation of biological oscillator models to achieve target quantitative system response

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Abstract

Mathematical modeling has become an integral part of synthesizing gene regulatory networks. One of the common problems is the determination of parameters, which are a part of the model description. In the present work, we propose a customized genetic algorithm as a method to determine the parameters such that the underlying oscillatory system exhibits the target behavior. We propose a problem specific, adaptive fitness function evaluation and a method to quantify the effect of a single parameter on the system response. The properties of the algorithm are highlighted and confirmed on two test cases of synthetic biological oscillators.

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Acknowledgements

The research was supported by the scientific research programme Pervasive Computing (P2-0359) financed by Slovenian Research Agency in years from 2009 to 2012. Results presented here are in scope of Ph.D. thesis that is being prepared by Martin Stražar.

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Authors and Affiliations

  1. Faculty of Computer and Information Science, University of Ljubljana, Tržaska cesta 25, Ljubljana, Slovenia

    Martin Stražar, Miha Mraz, Nikolaj Zimic & Miha Moškon

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  1. Martin Stražar
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  2. Miha Mraz
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  3. Nikolaj Zimic
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  4. Miha Moškon
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Correspondence to Martin Stražar.

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Stražar, M., Mraz, M., Zimic, N. et al. An adaptive genetic algorithm for parameter estimation of biological oscillator models to achieve target quantitative system response. Nat Comput 13, 119–127 (2014). https://doi.org/10.1007/s11047-013-9383-8

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