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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;