Explicitly considering all variables and chemical reactions in a cell is unrealistic for a gene regulatory network from modeling, analyzing and computing viewpoint. However, in a cell, many different time scales characterize the gene regulatory processes, which can be exploited to reduce the complexity of the mathematical models. For instance, the transcription and translation processes generally evolve on a time scale that is much slower than that of phosphorylation, dimerization or binding reactions. Moreover, in biological systems, there are many subsystems, such as gene regulatory network, protein network or metabolic network, which dynamically interact with each other but also are relatively independent. In this work, we exploit such properties to simplify the gene-protein network, which can be applied to the quantitative simulation of a large cellular system.