Operon prediction by Markov clustering
by Wei Du; Zhongbo Cao; Yan Wang; Enrico Blanzieri; Chen Zhang; Yanchun Liang
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 9, No. 4, 2014

Abstract: 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/.

Online publication date: Tue, 21-Oct-2014

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