Sentence examples for datasets less from inspiring English sources

Extremely low coverage datasets (less than ≈ 10×) and datasets with very high error rates (>5%) contain insufficient sampling of the true k-mers to support numerical inferences.

Currently the vast majority of expression data from numerous labs is not being used to its highest potential as independent labs continue to move to more expansive array platforms rendering older datasets less informative in the context of new data.

In the case of small datasets (less than a few hundred training sequences), we find it advantageous to smooth each row of V independently, maintaining the total counts across the entire row (for real or artificial data).

In both datasets, less substantial changes in these markers were observed in the golimumab monotherapy treatment group as compared with the golimumab plus MTX groups, indicating a stronger modulation of the overall biomarker response for golimumab treatment in combination with MTX compared with golimumab monotherapy.

This is of course the best way to conduct a controlled experiment, where any uncertainty renders the dataset less useful.

Out of 25347 annotated entities in the testing dataset less than 0.19% spanned the same token, which is truly negligible.

Dose volume histograms (DVH), D50, D70, D90, D avg, and V100 were recomputed using the same 3D dosimetric dataset (less ablated tissue) to compare 90Y radioembolization with adjuvant PET/CT-guided ablation to radioembolization alone in this patient cohort.

For the slightly larger 89 taxa dataset, less iterations are needed until support values become comparably saturated.

However, no enrichment of somatic mutations was observed in this dataset (less than 1% of TSRs have somatic mutations in the splicing sites).

For some datasets, out of all correlation coefficients calculated for the dataset, less than 1% are statistically significant, while for others datasets, more than 40% of the correlation coefficients are statistically significant.

For example, ppp-values close to zero indicate that most of the replicated datasets were less extreme than the observed datasets, and hence the model shows less discrepancy from predicted values, compared to the real data.