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But we find no difference in heterogeneity between proper and improper module networks.
Similarly in the unweighted yeast gene co-expression network, the mean factorizability of proper modules equals 0.62 while it is only 0.11 for the improper module.
In the weighted yeast gene co-expression network, the mean factorizability of proper modules equals 0.73 while it is only 0.18 for the improper module.
Of the 2292 proteins in the yeast PPI network, 2050 were clustered into 44 proper modules, and the remaining proteins grouped into an improper module.
Based on our theoretical derivations, it comes as no surprise that proper modules also have a high average clustering coefficient and a high centralization when compared to the improper module.
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Our empirical data also highlight how network concepts differ between subnetworks of 'proper' modules and the subnetwork comprised of improper (grey) module nodes, see Table 1.
Non-module genes were grouped into a single (improper) grey module.
Of the 1371 proteins in the Drosophila PPI network, 862 were clustered into 28 modules, and the remaining proteins grouped into an improper (grey) module.
The fourth module discerns correct from improper attachments, preventing the stabilization of the latter and allowing the selective stabilization of the former.
For example, when a predetermined level is used, only the value of the gradient module is concerned, thus an improper predetermined level will break the boundaries of objects.
However, since the conventional weighting functions are designed to adapt to the RGB images processed by the image processing module such as the gamma correction, they are improper for the BP-LDR images.
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