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Table 3 A prediction performance comparison to show the effectiveness of incorporating neighbourhood information

From: A method to improve protein subcellular localization prediction by integrating various biological data sources

 

No NI(*)

NI(*)

Prediction coverage (%)

60

84

Measure-I (k = 3) (%)

86.14

87.50

Measure-II (%)

63.52

67.76

   Mitochondrion

35.12

57.85

   Vacuole

31.58

15.30

   Spindle pole

38.89

60.00

   Cell periphery

34.92

30.34

   Punctate composite

19.67

16.50

   Vacuolar membrane

8.11

22.73

   ER

53.02

51.89

   Nuclear periphery

50.00

48.98

   Endosome

40.74

44.12

   Bud neck

36.11

52.73

   Microtubule

45.46

31.58

   Golgi

23.81

42.86

   Late Golgi

21.74

29.03

   Peroxisome

33.33

65.00

   Actin

52.94

58.62

   Nucleolus

32.91

58.62

   Cytoplasm

79.88

80.68

   ER to Golgi

100.00

66.67

   Early Golgi

26.67

48.87

   Lipid particle

9.09

6.67

   Nucleus

77.91

80.59

   Bud

7.69

23.81

Measure-III (%)

39.07

45.15

  1. (*) Note: No NI: Prediction without incorporating neighbourhood information; NI: Prediction with neighbourhood information.