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. 2015 Oct 5;10(10):e0139654. doi: 10.1371/journal.pone.0139654

Table 3. Method comparison on Testing-A and Testing-B of hg19.

Testing-A Testing-B
SES(%) SPC(%) ACC(%) MCC(%) AUC(%) SES(%) SPC(%) ACC(%) MCC(%) AUC(%)
CPC 97.62 67.23 82.425 68.069 94.55 97.328 69.262 82.831 68.898 94.78
CPAT 85.28 94.60 89.94 80.23 95.17 83.941 95.223 89.768 79.896 95.14
lncRScan-SVM 89.20 93.88 91.54 83.17 96.39 88.215 94.479 91.45 82.985 96.39
iSeeRNA 87.97 92.32 90.13 80.36 95.33 87.04 92.965 90.082 80.238 95.28
iSeeRNA2 90.02 92.409 91.205 82.44 96.23 89.103 92.885 91.045 82.106 96.18
RNAcon 69.11 84.53 76.82 54.29 86.11 68.039 85.454 77.034 54.475 86.1

CPC and CPAT were run by submitting the GTF files of Testing-A and Testing-B through their web interfaces. The lncRScan-SVM predictor was run after feature scaling. Besides, we tested the default iSeeRNA predictor and iSeeRNA2, an iSeeRNA model re-trained on Training-A, as well as RNAcon with a parameter T equals 0. The biggest value in each column is in bold font while the smallest one is underlined.