Skip to main content

Table 1 Values of modularity for E. coli and Buchnera networks

From: Modular organization in the reductive evolution of protein-protein interaction networks

Dataset Modules and validation Qreal Qrand Qnorm (Qreal - Qrand)
Newman algorithm     
   E. coli, Butland dataset 12 (5/10) 0.346 0.244 0.102
   Buchnera, Butland dataset 7 (3/7) 0.259 0.232 0.027
   Buchnera constrained, Butland dataset 7 (2/6) 0.182 0.168 0.014
   E. coli, Arifuzzaman dataset 15 (8/13) 0.409 0.329 0.080
   Buchnera, Arifuzzaman dataset 10 (4/9) 0.460 0.423 0.037
   Buchnera constrained, Arifuzzaman dataset 12 (4/10) 0.274 0.265 0.009
   E. coli, STRING 33 (32/32) 0.670 0.209 0.461
   Buchnera, STRING 12 (11/11) 0.581 0.272 0.309
   Buchnera constrained, STRING 14 (11/11) 0.493 0.210 0.283
Guimerá algorithm     
   E. coli, Butland dataset 10 (7/10) 0.357 0.248 0.109
   Buchnera, Butland dataset 6 (3/5) 0.263 0.237 0.026
   Buchnera constrained, Butland dataset 8 (2/7) 0.192 0.179 0.013
   E. coli, Arifuzzaman dataset 12 (6/11) 0.413 0.332 0.081
   Buchnera, Arifuzzaman dataset 8 (4/8) 0.461 0.432 0.029
   Buchnera constrained, Arifuzzaman dataset 11 (2/8) 0.266 0.242 0.024
   E. coli, STRING 19 (17/17) 0.669 0.211 0.458
   Buchnera, STRING 11(10/10) 0.566 0.277 0.289
   Buchnera constrained, STRING 9 (7/7) 0.489 0.231 0.258
  1. Modularity is calculated using different algorithms as described in the text for the E. coli and Buchnera networks. The module validation is indicated between parentheses after the number of modules for each network and this provides information on the number of modules that are statistically significant with regards to the STRING data (see text for details). For instance, 5/10 means that five out of ten modules are significant in terms of STRING interactions. The number of modules validated is sometimes different to the total number of modules, since some modules are too small to be statistically assessed. When using STRING-derived networks, all modules can be validated since the same information was used to construct the network. The table also shows the modularity coefficient (Q) for real and randomized networks, and the normalized modularity coefficient, resulting from the subtraction of the modularity coefficients for real and random modules.