Abstract: In order to solve the problems of low network construction accuracy and long network construction time in the current methods used to construct gene regulatory networks， so as to reduce the complexity of network construction and improve the efficiency of network construction， a method called high-order dynamic Bayesian network modelling method based on potential regulatory factors screening (PRS-HO-DBN) was proposed. The method combines the correlation model with the high-order dynamic Bayesian network model. Firstly， the potential regulatory factor screening method is used to delete the genes with low association with the target gene under different time delays， and retain the genes with high association with the target gene as the potential regulatory factor set of the target gene to reduce the search space. Then the high-order dynamic Bayesian model is used for structure learning to improve the accuracy of network construction. Compared with other methods， the method can greatly reduce network construction time and improve efficiency and accuracy.

Key words: gene regulatory networks; potential regulatory factors; high-order dynamic Bayesian network; correlation model; structure learning