Inference of genetic networks using S-system: information criteria for model selection

Authors:
Nasimul Noman;Hitoshi Iba
Affiliations:
The University of Tokyo, Chiba, Japan;The University of Tokyo, Chiba, Japan
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

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Abstract

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.