Once TF activities are calculated in this manner, the linear (Pearson) correlation is calculated for all possible gene-TF pairs. This serves as a score used to construct probability distributions for the training set (known gene/TF interactions) and random set (all possible gene/TF pairs). Comparison of these probability distributions gives an idea about the fitness of the preliminary TRN and expression data, and to which degree we can rely on the predictions of FTF. If the preliminary TRN is too small or of poor quality, or if there are too few expression datasets, the training versus random set probability distributions are difficult to distinguish. The scores can also be used to rank genes that are more likely to have expression data which is inconsistent with the preliminary TRN.