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Table 3 Application of HMM-d, HMM-t, HMM-ModE and HMM-Sub for function-specific classification of the S/T-Y kinase/atypical kinase/lipid kinase/ATP-grasp fold family

From: HMM-ModE – Improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences

  HMM-d HMM-t HMM-ModE HMM-Sub
2.7.1.100 19 16(0) * *
2.7.1.116 43 43(4) * *
2.7.1.117 103 103(8) * *
2.7.1.123 3392 529(120) 934(203) 3264
2.7.1.125 295 11(4) 11(4) 259
2.7.1.126 96 34(2) 34(2) 37
2.7.1.129 5 5(0) * *
2.7.1.137 135 135(29) * *
2.7.1.32 93 64(23) * *
2.7.1.38 2634 22(4) 22(4) 109
2.7.1.39 260 260(54) * *
2.7.1.67 57 57(15) * *
2.7.1.68 36 36(15) * *
2.7.1.82 45 31(10) * *
2.7.1.95 19 19(3) * *
2.7.9.1 171 169(55) * *
2.7.9.2 111 107(10) * *
  1. The numbers in the parentheses for HMM-ModE and HMM-t are the total counts of sequences annotated as hypothetical, putative, unknown and unnamed which have been classified by the two protocols. A "*" in the HMM-ModE and HMM-Sub columns indicates that the number of false positive sequences picked up by the HMMER profile from the negative training data were not sufficient to build a false positive profile.