Sentence examples for both sets were then from inspiring English sources

Both sets were then asked to do the odd-man-out test again.Among the Ballancers, there was no change in the ability to pick out the unusual.

Both sets were then compared.

MASCOT results for both sets were then merged to get the final set of ORFs that had at least one peptide matching spectra.

Metabolites derived from both sets were then reconstituted in 0.1% formic acid/50% methanol and subjected to a static nanoelectrospray ionization coupled to an LTQ orbitrap XL hybrid fourier transform mass spectrometer (FTMS).

DNA yield was not associated with genotype for those cases included in set 1 or set 2. SNPs showing a positive association with survival after a diagnosis of breast cancer (P trend < 0.05) were genotyped in set 2. Data from both sets were then combined (n = 4,470) to jointly analyze the SNPs with positive associations.

A combined assembly using all the 454 data from both sets was then constructed in the same way to generate the best possible reference transcriptome for further analysis.

Both data sets were then filtered (as described), yielding a single "best" Danio alignment for each informative query.

The themes that overlapped or were common to both data sets were then integrated to undertake a second level of analysis.

Both data sets were then compared by one team member (SJ) to identify explanatory theories and data which supported these theories.

Both data sets were then normalized to library size with DESeq, and to contrast the two subtypes, the DESeq parameterized negative binomial model was used to obtained the P-values for each BR or gene (Anders and Huber 2010).

Both training and test sets were then confirmed for the inclusion of all the atom types present in FSD.