关键词: 基因调控网络； 贝叶斯网络； 边排序贝叶斯网络结构学习算法； 多数据源融合

Abstract:

This paper presents a new Bayesian network structure learning algorithm based on the idea of a fusion of multiple datasets. This algorithm can reconstruct the network with the help of existing Bayesian network structure learning algorithm, which can deal with the problem effectively that different datasets can’t be merged simply. With the microarray datasets of the Cerevisiae yeast cycle under different conditions, the algorithm can increase the correct rate by about 12%. Experimental results show that this algorithm canimprove the accuracy effectively even if there is few microarray data but too many genes.

Key words: gene regulatory network, Bayesian network, line sorting Bayesian structure learning algorithm, multiple data fusion