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. 2010 Dec 30;27(3):391–398. doi: 10.1093/bioinformatics/btq670

Fig. 2.

Fig. 2.

A PNA application to the synthetic data. Six differential expression patterns were assigned to the nodes in the synthetic network (A). ONMF correctly captured the six differential expression patterns (B). The resulting PSs successfully represented the activation patterns in the synthetic data (C). We also obtained the active subnetworks using jActiveModules (D) and the edge-based method (E) and then compared the performance of PNA with those of the other two methods using FP, FN and accuracy (Acc) (F). See the text for details.