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Table 5 Summary of the performance of other state-of-the-art classifiers of mutations, either general or kinase-specific

From: Prioritization of pathogenic mutations in the protein kinase superfamily

Method Scope Accuracy (%) Precision (%) Recall (%) MCC
KinMut Kinase† 83.3 60.0 75.2 0.6
SNPs&GO [18] Kinase† 82.3 62.8 77.5 0.6
Torkamani [19] Kinase 77.0 - - 0.5
MutationAssessor [9] Kinase† 53.8 41.6 95.6 0.5
SNAP [16] Kinase† 49.4 34.0 93.1 0.4
SIFT [7] Kinase† 77.6 37.8 27.9 0.2
SNPs&GO [18] Genome-wide 82.0 83.0 78.0 0.6
MutationAssessor [9] Genome-wide 79.0 - - -
SNAP [16] Genome-wide 78.2 76.7 80.2 -
SIFT [7] Genome-wide 68.3 66.1 56.5 0.3
  1. Summary of the performance of other state-of-the-art classifiers of mutations, either general or kinase-specific. Performance was measured in terms of overall accuracy recall and the Matthews correlation coefficient. General methods with which the prediction corresponds to our dataset are marked with †. The remaining results for the classifiers displayed here were taken directly from their original publications