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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.