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. 2010 May 13;38(18):5959–5969. doi: 10.1093/nar/gkq353

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© The Author(s) 2010. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 4. — Evaluating the statistical significance of the differences in the correlations between measures of protein evolution and regulatory in-degree for TFs and generic proteins. The probability distribution of the expected Spearman’s rank correlation coefficients was generated by considering 10⁵ samples of 174 proteins randomly selected from the 5861 total yeast proteins. The position of the observed correlation coefficient for the actual 174 yeast TFs is highlighted. (a) The correlation between K_A/K_S and regulatory in-degree is significantly more positive for TFs than it is for generic proteins (P = 0.0019). (b) The correlation between inverse expression level and regulatory in-degree is not significantly more positive for TFs than it is for generic proteins (P = 0.39).