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Table 6 Results for models trained and tested with mouse data

From: A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts

Test data set  
Method GRCm38 (mm10)
Radial using GRCm38 and first ORF
  Sensitivity 9 8 . 7 0 %
  Specificity 96.96%
  Accuracy 9 7 . 8 3 %
CPCa
  Sensitivity 75.46%
  Specificity 9 8 . 3 7 %
  Accuracy 86.91%
CPATa
  Sensitivity 95.34%
  Specificity 88.17%
  Accuracy 91.76%
lncRScan-SVMa
Sensitivity 95.29%
  Specificity 89.14%
  Accuracy 92.21%
iSeeRNAb,c
  Sensitivity 94.20%
  Specificity 92.70%
  Accuracy 93.45%
FEELncd
  Sensitivity 94.10%
  Specificity 93.80%
  Accuracy 93.90%
  1. Results in bold are the best ones for each test data set
  2. aResults obtained in Han et al. [25]
  3. bResults obtained in Sun et al. [27]
  4. cThis method was created to classify only lincRNAs
  5. dResults obtained in Wucher et al. [28]