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Table 3 Comparing mGOASVM with state-of-the-art multi-label predictors based on leave-one-out cross validation (LOOCV) using (a) the virus dataset and (b) the plant dataset

From: mGOASVM: Multi-label protein subcellular localization based on gene ontology and support vector machines

(a) Performance on the viral protein dataset

Label

Subcellular location

LOOCV locative accuracy

  

Virus-mPLoc [[37]]

KNN-SVM [[39]]

iLoc-Virus [[33]]

mGOASVM

1

Viral capsid

8/8 = 100.0%

8/8 = 100.0%

8/8 = 100.0%

8/8 = 100.0%

2

Host cell membrane

19/33 = 57.6%

27/33 = 81.8%

25/33 = 75.8%

32/33 = 97.0%

3

Host ER

13/20 = 65.0%

15/20 = 75.0%

15/20 = 75.0%

17/20 = 85.0%

4

Host cytoplasm

52/87 = 59.8%

86/87 = 98.8%

64/87 = 73.6%

85/87 = 97.7%

5

Host nucleus

51/84 = 60.7%

54/84 = 65.1%

70/84 = 83.3%

82/84 = 97.6%

6

Secreted

9/20 = 45.0%

13/20 = 65.0%

15/20 = 75.0%

20/20 = 100.0%

Overall Locative Accuracy

152/252 = 60.3%

203/252 = 80.7%

197/252 = 78.2%

244/252 = 96.8%

Overall Actual Accuracy

155/207 =74.8%

184/207 = 88.9%

(b) Performance on the plant protein dataset

Label

Subcellular location

LOOCV locative accuracy

 
  

Plant-mPLoc [[41]]

iLoc-Plant [[42]]

mGOASVM

 

1

Cell membrane

24/56 = 42.9%

39/56 = 69.6%

53/56 = 94.6%

 

2

Cell wall

8/32 = 25.0%

19/32 = 59.4%

27/32 = 84.4%

 

3

Chloroplast

248/286 = 86.7%

252/286 = 88.1%

272/286 = 95.1%

 

4

Cytoplasm

72/182 = 39.6%

114/182 = 62.6%

174/182 = 95.6%

 

5

Endoplasmic reticulum

17/42 = 40.5%

21/42 = 50.0%

38/42 = 90.5%

 

6

Extracellular

3/22 = 13.6%

2/22 = 9.1%

22/22 = 100.0%

 

7

Golgi apparatus

6/21 = 28.6%

16/21 = 76.2%

19/21 = 90.5%

 

8

Mitochondrion

114/150 = 76.0%

112/150 = 74.7%

150/150 = 100.0%

 

9

Nucleus

136/152 = 89.5%

140/152 = 92.1%

151/152 = 99.3%

 

10

Peroxisome

14/21 = 66.7%

6/21 = 28.6%

21/21 = 100.0%

 

11

Plastid

4/39 = 10.3%

7/39 = 17.9%

39/39 = 100.0%

 

12

Vacuole

26/52 = 50.0%

28/52 = 53.8%

49/52 = 94.2%

 

Overall Locative Accuracy

672/1055 = 63.7%

756/1055 = 71.7%

1015/1055 =96.2%

 

Overall Actual Accuracy

666/978 = 68.1%

855/978 = 87.4%

 
  1. “–” means the corresponding references do not provide the overall actual accuracy. KNN-SVM: the KNN-SVM ensemble classifier proposed in[39]. Host ER: Host endoplasmic reticulum.