This paper proposes a method to capture the dynamics of gene expression data using S-system formalism and construct genetic network models. The proposed method exploits the probabilistic heuristic search and divide-and-conquer approach to generate candidate network structures. In evaluating the network structure, we attempt a primitive integration of other knowledge to the statistical criterion. The robustness analysis uses Z-score to identify significant parameters from results of stochastic search. We evaluated the proposed method on artificial generated data and E.coli mRNA expression data.