Table 2 P-values using correlation and mutual information as measure of dependence. The p-values describe the probability of obtaining a higher correlation (third column) or mutual information (fourth column) than the one observed, assuming that the expression levels of genes encoding interacting proteins are independent. The values have been estimated using 1000 permutations.
From: Confirmation of human protein interaction data by human expression data
Number of dataset | Dataset | p-value (correlation) | p-value (mutual information) |
|---|---|---|---|
1 | Chi [12] | 0.067 | 0.243 |
2 | Higgins [13] | 0.008 | 0.277 |
3 | Pathan [15] | 0.004 | 0.150 |
4 | Zhang [16] | 0.016 | 0.264 |
5 | Zhao [17] | 0.019 | 0.368 |