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Advances of high-throughput experimental techniques have generated large amounts of gene expression data. Biologically meaningful dynamic structures are expected to be hidden in these data, which are important for understanding the mechanism of cellular activities and identifying the function of genes. In this paper, a novel scheme is presented to reveal the dynamics of gene expression. state-space model (SSM) is developed based on the modern control theory. Based on the decomposition of functional modules, an effective strategy is designed to determine the SSMpsilas parameters. Via SSM, gene expression dynamics can be well revealed. To validate our approach and demonstrate its application, numerical experiments are designed by using cell cycle-regulated gene data sets of Yeast Saccharomyces cerevisiae.