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Table 1 Performance evaluation of the new version of our method HMM-ModE on ‘gold standard’ dataset and comparison with HMM-ModE/HMMER2 [9]

From: HMM-ModE: implementation, benchmarking and validation with HMMER3

SuperFamily Family # Seq HMM-d HMM-ModE with HMMER3 (HMMER2)
Se Sp Se Sp
AminoHydrolase AMP deaminase 28 1 0.90 1(1) 1(1)
urease 100 1 0.50 1(1) 1(1)
D-hydantoinase 10 1 0.05 1(1) 1(1)
Dihydroorotase 2 13 1 0.14 1(1) 1(1)
Guanine deaminase 11 1 0.22 1(1) 1(1)
Adenosine deaminase 10 1 0.35 1(1) 1(1)
Enolase Enolase 215 1 0.88 1(1) 1(1)
Glucarate dehydratase 26 1 0.20 1(1) 1(1)
Muconate cycloisomerase 14 1 0.09 1(1) 1(1)
Chloromuconate cycloisomerase 10 1 0.05 1(1) 1(1)
Crotonase Enoyl-CoA hydratase 54 1 0.23 1(1) 1(1)
Histone acetyltransferase 11 11 0.09 1(1) 1(1)
Haloacid Dehydrogenase P-type atpase 91 1 0.77 1(1) 1(1)
Vicinal Oxygen chelate Catechol 2,3-dioxygenase 32 1 0.28 1(1) 0.88 (0.88)
4-Hydroxyphenylpyruvate dioxygenase 26 1 0.60 1(1) 1(1)
2,3-Dihydroxybiphenyl dioxygenase 23 1 0.20 0.95 (1) 0.71(0.63)
Glyoxalase 1 12 1 0.20 1(1) 1(1)
  1. HMM-d stands for default HMMER and # Seq stands for number of sequences in each family. Se is Sensitivity and Sp is Specificity. Sn is the sensitivity value calculated as TP/(TP + FN), and Sp is the specificity calculated as TP/(TP + FP). As shown here, there is a significant improvement in the specificity of the predictions with small compromise in the respective sensitivity using HMM-ModE.
  2. The corresponding values of Se and Sp using HMM-ModE with HMMER2 is written in parenthesis.