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Table 3 Means and standard derivations of AUC values of prediction of subnetwork genes on simulation data sets with different false positive rate (FPR) for netSVM, other network-based methods and gene-based methods.

From: Identifying cancer biomarkers by network-constrained support vector machines

FPR
(%)
network-based method gene-based method
  netSVM F-norm SVM Larsnet* Chuang's method SVM Lasso* T-test
25 0.95 ± 0.02 0.90 ± 0.03 0.93 ± 0.02 0.92 ± 0.03 0.90 ± 0.03 0.81 ± 0.04 0.91 ± 0.02
27 0.95 ± 0.02 0.90 ± 0.03 0.92 ± 0.02 0.93 ± 0.02 0.88 ± 0.02 0.80 ± 0.03 0.89 ± 0.02
29 0.94 ± 0.02 0.89 ± 0.03 0.91 ± 0.02 0.90 ± 0.02 0.86 ± 0.02 0.80 ± 0.03 0.88 ± 0.03
33 0.91 ± 0.03 0.87 ± 0.02 0.89 ± 0.02 0.90 ± 0.02 0.83 ± 0.03 0.79 ± 0.03 0.86 ± 0.04
39 0.92 ± 0.03 0.85 ± 0.03 0.87 ± 0.03 0.87 ± 0.03 0.80 ± 0.04 0.78 ± 0.03 0.83 ± 0.03
46 0.89 ± 0.01 0.83 ± 0.03 0.82 ± 0.02 0.83 ± 0.02 0.75 ± 0.04 0.76 ± 0.03 0.77 ± 0.03
58 0.86 ± 0.02 0.79 ± 0.03 0.77 ± 0.02 0.80 ± 0.02 0.70 ± 0.03 0.72 ± 0.03 0.73 ± 0.04
68 0.83 ± 0.05 0.76 ± 0.03 0.73 ± 0.02 0.72 ± 0.03 0.64 ± 0.05 0.71 ± 0.02 0.66 ± 0.04
77 0.77 ± 0.04 0.70 ± 0.04 0.69 ± 0.02 0.67 ± 0.04 0.55 ± 0.05 0.67 ± 0.02 0.58 ± 0.03
86 0.74 ± 0.04 0.66 ± 0.04 0.64 ± 0.02 0.66 ± 0.03 0.51 ± 0.06 0.63 ± 0.02 0.52 ± 0.04
98 0.70 ± 0.05 0.62 ± 0.04 0.59 ± 0.00 0.56 ± 0.03 0.49 ± 0.05 0.59 ± 0.01 0.47 ± 0.04
  1. *: noise = 0; others: SNR = 0 db;
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