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

Authors:
Martin Stražar;Miha Mraz;Nikolaj Zimic;Miha Moškon
Affiliations:
Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia;Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
Venue:
Natural Computing: an international journal
Year:
2014

Citing 4
Cited 0

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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.