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Table 5 Performance of the predictive models (M3 through M16), each with an individual or a combination of the newly added categories of features being excluded.

From: CpGIMethPred: computational model for predicting methylation status of CpG islands in human genome

  Features SP SE ACC CC
Histone Methylation Retained All retained 0.9405 0.9257 0.9313 0.8302
  Acetylation ( M 3 ) 0.9012 0.8965 0.9046 0.7852
  Functional role ( M 4 ) 0.9302 0.9265 0.9210 0.8038
  Nucleosome ( M 5 ) 0.9270 0.9250 0.9205 0.8024
  Acetylation+Functional ( M 6 ) 0.8791 0.8903 0.8897 0.7632
  Acetylation+Nucleosome ( M 7 ) 0.8698 0.8835 0.8826 0.7625
  Functional+Nucleosome ( M 8 ) 0.9186 0.9116 0.9186 0.8012
  All three ( M 9 ) 0.8685 0.8822 0.8786 0.7558
Histone Methylation Excluded All but histone methylation 0.9318 0.5932 0.8575 0.6404
  Acetylation ( M 10 ) 0.9670 0.2247 0.8001 0.3302
  Functional ( M 11 ) 0.9092 0.5670 0.8312 0.6124
  Nucleosome ( M 12 ) 0.9078 0.5660 0.8296 0.6076
  Acetylation+Functional ( M 13 ) 0.9320 0.2279 0.7862 0.3236
  Acetylation+Nucleosome ( M 14 ) 0.9266 0.2304 0.7641 0.3264
  Functional+Nucleosome ( M 15 ) 0.8990 0.5519 0.8232 0.5924
  All three ( M 16 ) 0.8972 0.2338 0.7352 0.3013
  1. Specificity (SP), sensitivity (SE) and accuracy (ACC) are evaluated for binary classification, and correlation coefficient (CC) for regression models.