Sentence examples for all datasets were calculated from inspiring English sources

For correlation analysis, all datasets were calculated for correlation efficiency and were considered significant at p<0.05.

Phylogenies and 100 bootstrap supports for all datasets were calculated with PhyML v3.0 [ 80] with the LG [ 81] amino acid substitution model, estimated portions of invariable sites, estimated Γ distribution parameter, four rate categories, estimated amino acid frequencies, and an NJ starting tree.

First, the global mean of all intensities of all datasets is calculated.

Pearson correlation coefficients between genetic purity values obtained for all eight datasets were calculated using MINITAB v14.

Using the described selection criteria, the disorder indices of the proteins in all six independently constructed datasets were calculated.

KA/KS values for gene datasets were calculated by summing up over all non-synonymous and synonymous sites in each dataset as reported elsewhere [ 6].

Correlations between datasets were calculated by the Pearson product moment correlation coefficient in MATLAB.

Statistical significances of the correlations between datasets were calculated using Pearson's R values.

The lengths of the branches of the morphological datasets were calculated using a Euclidean distance matrix (SAS Procedure DISTANCE SASS version 9.1.3).

The co-clustering frequencies of sample pairs across the datasets were calculated.

The correlation between REGγ and every other gene in these datasets were calculated and evaluated statistically.