Table 1 The improvement by incorporating network using CGI_Endeavour and CGI_RRA is significantly correlated with the number of training genes.
From: Network tuned multiple rank aggregation and applications to gene ranking
| Â | Â | CGI_Endeavour | CGI_RRA | ||
|---|---|---|---|---|---|
Expression | Network | correlation | p-value | correlation | p-value |
Compendium | BioGRID DIP MIPS | 0.6614(0.0943) 0.722(0.0796) 0.4212(0.1339) | 0.0041(0.0065) 0.0015(0.0040) 0.0668(0.0830) | 0.6581(0.0920) 0.7485(0.0855) 0.5232(0.0995) | 0.0041(0.0072) 0.0013(0.0046) 0.0217(0.0271) |
Stress | BioGRID DIP MIPS | 0.6313(0.0865) 0.6636(0.13300) 0.4620(0.1000) | 0.0060(0.0119) 0.0084(0.0212) 0.0387(0.0397) | 0.6387(0.0874) 0.7060(0.1333) 0.3961(0.1160) | 0.0055(0.0114) 0.0062(0.0162) 0.0725(0.0739) |
Cycle | BioGRID DIP MIPS | 0.7776(0.0894) 0.6497(0.1376) 0.5997(0.0823) | 0.0007(0.0019) 0.0104(0.0248) 0.0082(0.0131) | 0.6585(0.1071) 0.5645(0.1482) 0.5414(0.0890) | 0.0063(0.0151) 0.0227(0.0342) 0.0170(0.0233) |