Abstract: Among the methods for modeling gene regulation networks， Bayesian network model can intuitively express the regulatory relationship between genes. However， due to the high complexity of Bayesian network model in the structure learning， the efficiency of the gene regulation networks modeling is low and the scale of the reconstructed network is limited. Therefore， this paper proposed a method which is called the parent node screening-based Bayesian network(PS-BN). The PS-BN method combines the correlation model with Bayesian network model. Under the premise of making full use of the search strategy of structure learning in Bayesian network model， the parent node screening method is used to remove some redundant nodes， thus reducing the search space. The experimental results show that compared with the Bayesian network model， the PS-BN method greatly improves the efficiency of modeling gene regulatory networks while improving the accuracy.

Key words: gene regulatory networks, parent node screening, Bayesian network model, correlation model, structure learning