Du Wei, Cao Zhongbo, Wang Yan, Blanzieri Enrico, Zhang Chen, Liang Yanchun
Int J Data Min Bioinform. 2014;9(4):424-43. doi: 10.1504/ijdmb.2014.062149.
The prediction of operons is a critical step for the reconstruction of biochemical and regulatory networks at the whole genome level. In this paper, a novel operon prediction model is proposed based on Markov Clustering (MCL). The model employs a graph-clustering method by MCL for prediction and does not need a classifier. In the cross-species validation, the accuracies of E. coli K12, Bacillus subtilis and P. furiosus are 92.1, 86.9 and 87.3%, respectively. Experimental results show that the proposed method has a powerful capability of operon prediction. The compiled program and test data sets are publicly available at http://ccst.jlu.edu.cn/JCSB/OPMC/.
操纵子预测是全基因组水平生化和调控网络重建的关键步骤。本文提出了一种基于马尔可夫聚类（MCL）的新型操纵子预测模型。该模型采用MCL的图聚类方法进行预测，无需分类器。在跨物种验证中，大肠杆菌K12、枯草芽孢杆菌和激烈火球菌的预测准确率分别为92.1%、86.9%和87.3%。实验结果表明，该方法具有强大的操纵子预测能力。编译后的程序和测试数据集可在http://ccst.jlu.edu.cn/JCSB/OPMC/上公开获取。
