Hodges Andrew P, Woolf Peter, He Yongqun
Center for Computational Medicine and Bioinformatics; University of Michigan Medical School; University of Michigan; Michigan USA.
Commun Integr Biol. 2010 Nov;3(6):549-54. doi: 10.4161/cib.3.6.12845. Epub 2010 Nov 1.
A Bayesian network expansion algorithm called BN+1 was developed to identify undocumented gene interactions in a known pathway using microarray gene expression data. In our recent paper, the BN+1 algorithm has been successfully used to identify key regulators including uspE in the E. coli ROS pathway and biofilm formation.18 In this report, a synthetic network was designed to further evaluate this algorithm. The BN+1 method was found to identify both linear and nonlinear relationships and correctly identify variables near the starting network. Using experimentally derived data, the BN+1 method identifies the gene fdhE as a potentially new ROS regulator. Finally, a range of possible score cutoff methods are explored to identify a set of criteria for selecting BN+1 calls.
一种名为BN+1的贝叶斯网络扩展算法被开发出来,用于利用微阵列基因表达数据识别已知通路中未记录的基因相互作用。在我们最近的论文中,BN+1算法已成功用于识别关键调节因子,包括大肠杆菌ROS通路中的uspE和生物膜形成。在本报告中,设计了一个合成网络以进一步评估该算法。发现BN+1方法能够识别线性和非线性关系,并正确识别起始网络附近的变量。利用实验得出的数据,BN+1方法将fdhE基因识别为一种潜在的新型ROS调节因子。最后,探索了一系列可能的评分截断方法,以确定选择BN+1调用的一组标准。