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Table 2 Performance test of P2CS

From: P2CS: a two-component system resource for prokaryotic signal transduction research

Species

Manually defined TCS proteins

P2CS Predicted TCS proteins

Sensitivity (%)

Specificity (%)

Precision (%)

Reference

Anaeromyxobacter dehalogenans 2CP-C

174

188 (185+3)

100

99.67

92.55

[15]

Bacillus anthracis str. Ames

102 (94+8)

104 (94+10)

100

99.96

97.9

[18]

Bacillus anthracis str. Sterne

102

103

99.02

99.96

98.06

[18]

Bacillus cereus ATCC 14579

101 (99+2)

102 (99+3)

100

99.98

99.02

[18]

Bacillus cereus ATCC 10987

101 (100+1)

99 (98+1)

98.02

100

100

[18]

Bacillus cereus E33L

107

107

100

100

100

[18]

Bacillus subtilis

70

70

100

100

100

[18]

Bacillus thuringiensis serovar konkukian str. 97-27

109

109

100

100

100

[18]

Escherichia coli str. K-12 substr. MG1655

62

62 (61+1)

100

100

100

[15]

Myxococcus xanthus DK1622

278 (276+2)

283 (281+2)

99.28

99.91

97.53

[15]

Nitrosospira multiformis ATCC 25196 chromosome 1

62

59

93.55

99.96

98.31

[19]

Pseudomonas syringae pv. syringae B728a

142

143

97.89

99.92

97.2

[11]

Pseudomonas syringae pv. tomato str. DC3000

143 (140+3)

144 (139+5)

97.2

99.92

96.53

[11]

Pseudomonas syringae pv. phaseolicola 1448A

139 (137+2)

141 (138+3)

97.84

99.87

96.45

[11]

Sorangium cellulosum So ce56

267

273

98.88

99.92

96.70

[15]

Streptomyces coelicolor A3(2)

164

187

99.39

99.68

87.17

[17]

Xanthomonas campestris pv. campestris ATCC 33913

106

110

100

99.9

96.36

[20]

X. campestris pv. campestris 8004

106

110

100

99.9

96.36

[20]

X. axonopodis pv. citri 306

114

120

100

99.86

95

[20]

X. campestris pv. vesicatoria 85-10

121

126

100

99.86

95

[20]

X. oryzae pv. oryzae KACC10331

92 (91+1)

96 (95+1)

100

99.9

95.83

[20]

X. oryzae pv. oryzae MAFF 311018

93

95

100

99.95

97.89

[20]

  1. Comparison to manually detected TCS proteins (numbers in parentheses are the details of predicted and mis-predicted TCS proteins). Parameters calculation: Sensitivity = TP/TP+TN, Specificity = TN/TN+FP, Precision = TP/TP+FP.
  2. TP. True positive, TN. True negative, FP. False positive, FN. False negative.