Figure 9(a) indicates the relationship between predicted sets M, C, and N. The three sets have 1186 predictions of PPIs.
The correspondence between our predicted set of Ectocarpus ESE hexamers and human ESEs is notable.
Given the expectation that in vivo substrates of Ste20p should share Ste20p's genetic interactions, the observed overlap between the predicted substrate set and the GINs of Ste20p's genetic interactors suggests that the in silico predictor exhibits in vivo relevance.
When the semantic score between the predicted GO term set and the annotated set of each protein was calculated with the online method G-sesame [ 45], the mean values correspondingly increased to 0.709, 0.678, and 0.638, respectively.
These were the correlation coefficient between the predicted and actual sets, ρ [ z * (u α, t α ), z (u α, t α ) ], the mean prediction error (ME): (10) ME = 1 n ∑ α = 1 n z * (u α, t α ) - z (u α, t α ) and the mean absolute prediction error (MAE) (Saito and Goovaerts, 2000): (11) MAE = 1 n ∑ α = 1 n | z * (u α, t α ) - z (u α, t α ) |.
Differences between the predicted profiles from setting non-identical C-values and friction factors for the swash phase, are believed to be linked to both the infiltration effects on the flow above the beachface and the more accelerated flow in the uprush.
PLS-DA maximizes the covariance between the predicting data set, which is X of the numerical value of the targeted steroids, and Y of the class assignment.
The correlation coefficient obtained between the predicted and training data set is 0.9657, indicating an accurate mapping of the data.
Comparisons between the predicted European seabass peptide data set and the zebrafish, medaka, stickleback, tetraodon and human proteomes were performed.
Accuracy was calculated as the correlation between the predicted EBVs of the validation set and the actual phenotypes divided by the square root of the heritability [ ~ r y 1,y 2 )/h] using all individuals.
