Sentence examples for datasets were then from inspiring English sources

The CT datasets were then resampled to match the resolution of the MR images.

Multiple datasets were then integrated to obtain a list of taxa that are harvested by recreational fishers within the AR area.

These datasets were then used in the slope stability analysis and, simultaneously, the random variables of friction angle were generated to be coupled in the analysis.

The farmer interview and collar datasets were then combined to generate a final integrated RSF map summarizing the probability of elk cattle comingling and were contrasted over each of four cattle grazing seasons (spring, early summer, late summer, and autumn).

Genes that lacked orthologs in both datasets were then removed from each of the two networks.

Predicted ancestral sequences for both bacterial and archaeal/eukaryal datasets were then aligned using M-coffee.

By the jackknife cross-validation, the prediction accuracies for the two datasets were then calculated.

The transformed datasets were then hierarchically clustered using Cluster 2.11 and the results displayed using Treeview 1.60 [69].

The high resolution environmental datasets were then used to predict potential habitat suitability for five species of framework-forming scleractinians.

The two datasets were then matched in a gene-specific manner to find CVs concurrent in the two databases.

Microarray expression data for sulfur amino acid pathway-affected cells (see Microarray Datasets) were then averaged for the top 30 genes in our ranking.