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Table 1 The statistics of network properties for SGI vs. non-SGI gene pairs

From: A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

Gene pair characteristic

KSStat

P-value

  

Binary

Network

Weighted

Network

Binary

Network

Weighted

Network

Average

Degree

0.0364

0.0261

0.9

0.0011

 

Closeness

0.0212

0.0385

0.0108

1.48E-07

 

Betweenness

0.0319

0.0529

1.55E-05

7.05E-14

 

Clustering Coefficient

0.0679

0.0691

1.41E-23

2.365E-24

Absolute

Difference

Degree

0.0587

0.0715

1.00E-17

5.71E-25

 

Closeness

0.0587

0.0441

1.00E-17

9.365E-10

 

Betweenness

0.0313

0.0414

2.35E-05

1.56E-08

 

Clustering Coefficient

0.0615

0.0571

1.97E-19

4.435E-26

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BMC Bioinformatics

ISSN: 1471-2105

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