In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory interactions in a genetic network the decoupled S-system formalism has been used. We proposed an Information Criteria based fitness evaluation for model selection instead of the traditional Mean Squared Error (MSE) based fitness evaluation. A hill climbing local search method has been incorporated in our evolutionary algorithm for attaining the skeletal architecture which is most frequently observed in biological networks. Using small and medium-scale artificial networks we verified the implementation. The reconstruction method identified the correct network topology and predicted the kinetic parameters with high accuracy.
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