Figure 8

ROC and PR curves of different biclustering networks that have learned using linear regression method [41]. A performance comparison of networks generated from learning corresponding biclustering algorithms using linear regression via the gold network retrieved by BioNetBuilder [33]. Comparing Figure 8 with the Bayesian results in Figure 5, we find that the performance of the CMSBE [27] network does not change significantly; the performances of the ALL (this network is produced by integrating edges from all biclustering networks), OPSM [23] and Bivisu [32] networks are greater using the LASSO method than the Bayesian networks method; and the performances of the ISA [31], SAMBA [43] and K-means, networks are lower using the LASSO method than with the Bayesian networks method. We may conclude from Figures 5 and 8 that while different network reconstruction algorithms will lead to differences in the absolute performance, different biclustering schemes consistently have similar relative performances, irrespective of the network reconstruction algorithm used.