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Table 2 Means and standard derivations of AUC values of prediction of subnetwork genes on simulation data sets with different signal-to-noise levels for netSVM, other network-based methods and gene-based methods.

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

SNR

(db)

network-based method

gene-based method

 

netSVM

F∞-norm SVM

Larsnet

Chuang's method

SVM

Lasso

T-test

10

0.89 ± 0.00

0.80 ± 0.03

0.64 ± 0.02

0.85 ± 0.03

0.79 ± 0.00

0.62 ± 0.02

0.78 ± 0.03

8

0.90 ± 0.02

0.81 ± 0.03

0.64 ± 0.02

0.81 ± 0.03

0.79 ± 0.02

0.62 ± 0.01

0.78 ± 0.04

6

0.90 ± 0.02

0.81 ± 0.03

0.63 ± 0.02

0.84 ± 0.03

0.79 ± 0.03

0.62 ± 0.02

0.77 ± 0.04

4

0.90 ± 0.02

0.81 ± 0.04

0.63 ± 0.01

0.82 ± 0.02

0.80 ± 0.02

0.61 ± 0.01

0.78 ± 0.04

2

0.90 ± 0.02

0.80 ± 0.03

0.63 ± 0.01

0.83 ± 0.02

0.79 ± 0.02

0.62 ± 0.02

0.77 ± 0.04

0

0.90 ± 0.03

0.81 ± 0.03

0.63 ± 0.02

0.83 ± 0.04

0.79 ± 0.03

0.61 ± 0.02

0.78 ± 0.04

-2

0.91 ± 0.02

0.80 ± 0.03

0.63 ± 0.02

0.82 ± 0.03

0.80 ± 0.02

0.61 ± 0.02

0.79 ± 0.03

-4

0.89 ± 0.02

0.79 ± 0.03

0.63 ± 0.01

0.83 ± 0.02

0.78 ± 0.02

0.61 ± 0.02

0.78 ± 0.03

-6

0.88 ± 0.02

0.79 ± 0.03

0.63 ± 0.02

0.83 ± 0.04

0.75 ± 0.02

0.61 ± 0.01

0.76 ± 0.05

-8

0.89 ± 0.02

0.77 ± 0.03

0.63 ± 0.01

0.83 ± 0.03

0.75 ± 0.04

0.61 ± 0.01

0.77 ± 0.04

-10

0.87 ± 0.03

0.75 ± 0.03

0.63 ± 0.02

0.80 ± 0.04

0.74 ± 0.03

0.61 ± 0.01

0.76 ± 0.04