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Table 5 Performance of the SVM models using leave one out cross validation (LOOCV) method

From: VIRsiRNApred: a web server for predicting inhibition efficacy of siRNAs targeting human viruses

Predictive model no.

siRNA features

No. of siRNA features

Pearson correlation coefficient*

Training (T1380)

Validation (V345)

1

 

Mononucleotide frequency

4

0.32

0.29

2

Dinucleotide frequency

16

0.36

0.32

3

Trinucleotide frequency

64

0.45

0.41

4

Tetranucleotide frequency

256

0.48

0.44

5

Pentanucleotide frequency

1024

0.52

0.48

6

Binary

76

0.26

0.14

7

Thermodynamic features

21

0.29

0.24

8

Secondary structure

28

0.10

0.06

9

 

1 + 2 + 3 + 4 + 5

1364

0.52

0.49

10

6 + 9

1440

0.54

0.51

11

6 + 7 + 9

1461

0.58

0.55

12

 

6 + 7 + 8 + 9

1489

0.58

0.54

  1. *Pearson Correlation Coefficient (PCC) is the correlation between experimental and predicted viral siRNA efficacy.
  2. # T1380 is the training dataset of experimental viral siRNA. Predictive Models 1-8 were developed on individual siRNA features while models 9-12 were based on hybrid siRNA features.