Qinbin He and Zengrong Liu Pages 13 - 21 ( 9 )
Boolean network is a powerful tool for the study of gene regulatory networks, and dynamics of a Boolean network is mainly determined by its attractors. In this study, a new approach to construct Boolean network is proposed based on biochemical reaction differential equations. We attempt to investigate gene regulatory networks by means of comparing the experimental results from relevant literature with the attractors obtained by the Boolean network. The Boolean regulatory network proposed is simple and robust to alteration of the parameters of the network. The model is applied to investigate p53 gene regulatory network by analyzing the interplay of the key ingredients including p53, Mdm2 (murine double minute 2) and the external signal of DNA damage. The attractors obtained by p53 Boolean network are consistent with the experimental results of relevant literature. Furthermore, we speculate that there is an unknown protein XXXp in the p53 gene regulatory network, where p53p promotes the DNA of XXXp to form the mRNA of mXXXp. mXXXp generates protein XXXp to promote p53 phosphorylation to form p53p, creating a positive feedback loop of XXXp-p53p.
Gene regulatory network, boolean network, attractor.
Department of Mathematics, Taizhou University, Linhai, Zhejiang 317000, China.