关键字：Bayesian network; gene regulatory network; greedy search algorithm; K2 algorithm

摘要： Gene regulatory network, which focuses on the complex interactions of genes in 1ife, is an important part in the study of the functiona1 genomics and the frontier of bioinformatics and systems biology research. Bayesian network is powerfu1 tools to genetic networks research. As for the empirical analysis, a subset consisting of 15 genes is chosen from yeast gene expressing data as training data, we first use greedy search (GS) algorithm to get the priori information for the K2 algorithm, and then apply the K2 method to the dataset of gene expression profile to get the topological structure of the Bayesian networks, thus inferring the interaction between genes. We verify the effectiveness of our approach by consulting the corresponding experiment articles, and reduce the computational time in learning network, finally get more stable structures.

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