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Background: Mitosis is the key step in eukaryotic cell cycle at which the mother cell divided into two daughter cells.Mitotic failure causes chromosome mis-segregation and aneuploidy, thus may lead to apoptosis or tumorigenesis.In recent years, the regulatory mechanism of mitosis is much investigated.Several mitotic kinases, including cyclindependent kinase 1, Aurora kinases, and polo-like kinase 1, have been considered as targets for anti-cancer drug discovery.As these kinases regulates different processes in mitosis, combinations of their inhibitors were considered as more effective treatment of cancer.As the therapeutic window of anti-cancer drugs are often narrow, quantitative study of mitosis is necessary.Methods: The mitosis network was constructed according to published information.The network dynamic was simulated using ordinary differential equations.The reactions were described using sigmoid function.Western-blot and F(o)ster resonance energy transfer data from literature were used for data fitting to determine parameters used in the model.Parameter adjustment and parameter sensitivity analysis were done using an in-house program.Results: The mitotic regulatory network we built contains the main processes of mitosis: mitotic entry, spindle assembly checkpoint, and the effect of anaphase-promoting complex (ubiquitin ligase).Only the major interactions of the key regulators are included in the network.All the regulation of cyclin dependent kinase 1, Aurora kinase A and B, and pololike kinase 1 are preserved.The model contains 13 substances and 24 reactions.Different sets of parameters have been obtained by fitting to experimental data.Further analysis of the distribution of the parameter sets and parameter sensitivity analysis are under investigation.Conclusions: A simplified network model of the mitosis regulation was built and parameters were estimated by fitting to experimental data.The model is being used to study the dynamics property of mitosis process and to search for effective inhibitor combinations of different drug targets .