Sentence examples for a considerable dataset from inspiring English sources

We identified a considerable dataset of STR and SNP markers that can be used as raw material in future population genetics, broodstock management, QTL mapping and Marker Assisted Selection (MAS) in sharpsnout seabream and other phylogenetically close sparid species.

This considerable dataset can certainly be generalizable to a population of children with ADHD, however, it may not be entirely generalizable to a non-ADHD, healthy pediatric population.

This study utilized considerable datasets, from different sources including the remotely sensed systems (e.g. TRMM).

Although Method 4 performed very well, Methods 2 and 3 should not be neglected because for a considerable number of datasets the maximum objective function values were obtained by these methods.

A considerable portion of our dataset represents the longer distance range (>100 m), which has been underrepresented in the literature so far.

In all three metagenomic datasets, a considerable fraction of cassettes were adjacent to putative cas genes.

Our analysis reveals a considerable overlap between our datasets and that of Lolas et al., as 71% of the mouse targets are included in the human datasets (Fig. 7A).

It can be seen that in both datasets a considerable fraction of data is censored across some dimensions (genes), whereas for other dimensions no censoring occurred (i.e. expression of the respective gene could be detected with a Ct number below the LOD for all cells).

Overlap between target prediction datasets: there was a considerable difference between the predictions from different datasets (Fig. 1A).

The predicted target sites for miRNAs miR-124, miR-135, miR-30, miR-19 and miR-130 (Fig. 1C and Fig. S1) were considered to be best-supported based on the following criteria: (1) Overlap between target prediction datasets: there was a considerable difference between the predictions from different datasets (Fig. 1 A).

We referred to two GEO datasets, GSE11151, and GSE15641, because both datasets contain a considerable number of renal tumors with various histologic subtypes (n > 60) as well as normal kidney tissue samples.