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Table 6 The performance of data augmentation on the SignalP dataset

From: SigUNet: signal peptide recognition based on semantic segmentation

Comp

Eukaryotes

Gram-positive

Gram-negative

Train

MCC (%)

FPRTM (%)

MCC (%)

FPRTM (%)

MCC (%)

FPRTM (%)

SigUNet

 As compa

90.2

4.0

76.1

5.1

80.6

1.5

 All organismsb

89.9

3.2

80.9

3.1

82.1

3.6

 Bacteriac

79.3

1.9

83.5

0.3

SigUNet-light

 As comp

89.4

4.3

77.7

5.1

82.9

1.9

 All organisms

88.9

3.9

82.5

3.1

81.4

3.5

 Bacteria

80.2

1.9

83.9

2.7

  1. aThe model is trained using the same organism as the comparison dataset. bThe model is trained using all organisms. cThe model is trained using all of the bacteria data. The best performance is highlighted in bold