Sentence examples for both datasets were used from inspiring English sources

Both datasets were used as an image that is interpreted using ancillary data from historical sources.

Both datasets were used to search for selective sweeps by evaluating the normalized relative heterozygosity between affected and unaffected individuals.

After preprocessing, 1101 antigens common in both datasets were used for further analysis.

Household characteristics and assets from both datasets were used to estimate an SES measure for each household in the two populations.

Replicate probes for each unigene were averaged and the 91,048 unigenes present in both datasets were used for the WGCNA consensus analysis.

Similarly, when misSEQ uel was ran on this same assembly, 69% (25/36) of locally misassembled contigs were identified, whereas this improved to 100% (36/36) when both datasets were used.

The combined error from both datasets was used to define a threshold of the minimum elevation difference that could be reliably attributed to erosion or deposition in the seven years separating the sUAS and LiDAR datasets.

In each iteration, m−1 faces (from both datasets) are used to learn the CCA transformation frontal-profile.

Overlapping SNPs in both datasets are used to determine the comprehensiveness of dataset.

Eight tissues and 222 TFs that are common to both datasets are used (Additional file 6).

The data analysis was done double blind and average of both datasets was used for comparison.