Table 5

Performance comparison of different approaches using five-fold cross-validation for the benchmark data sets.

Data set

Method

Spec. (%)

Sens. (%)

Acc (%)

MCC

Threshold


RBP86

Jeong 2006

91.04

43.4

80.2

0.39 (0.41)*

--

PPRint

89.55

53.05

81.16

0.45

--

RNAProB §

90.36

79.95

87.99

0.68

0.36

RNAProB #

90.01

79.64

87.65

0.67

0.36


RBP109

RNABindR

93.00

38.00

84.80

0.35

--

RNAProB §

93.88

64.62

89.70

0.58

0.35

RNAProB #

94.14

60.63

89.36

0.56

0.35


RBP107

BindN-PCP&

69.84

66.28

69.32

0.27

--

BindN-ALL&

75.70

65.78

74.25

--

--

PPRint

75.54

70.09

75.43

0.32

--

RNAProB §

80.87

77.14

80.44

0.42

0.11

RNAProB #

80.65

73.62

79.84

0.40

0.12


§ presents the performance by five-fold cross-validation.

# denotes the performance by a three-way data split procedure.

* indicates the performance of weighted profiles by Jeong and Miyano [7].

&BindN-PCP represents the results based only on physicochemical properties, while BindN-ALL shows the performance using physicochemical properties, relative solvent accessible surface area, and BLAST results.

Cheng et al. BMC Bioinformatics 2008 9(Suppl 12):S6   doi:10.1186/1471-2105-9-S12-S6

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