Figure 7 .

Performance of network inference methods with different levels of sparsity using 25 simulated datasets (5 datasets per sparsity level). The horizontal axis shows the methods while the vertical axis shows the AUROC values that represent the quality of the constructed networks. At each level of sparsity, we show the mean AUROC of five datasets for each method. SCOUP is the most stable method. It produces AUROC values that are consistently above 0.5 with very low variability across five sparsity levels.