Sentence examples for multiple datasets for from inspiring English sources

For privacy advocates, this is a long-fought victory; recognition that there is something uniquely intrusive about mass surveillance, and the ability to cross-reference and analyse multiple datasets for patterns and correlations, that cannot and should not be weighed by reference to traditional notions of targeted interception.

Analysis was done using the t-test method for determining significance of CRX expression across multiple datasets for normal and cancer cell lines.

Analysis of multiple datasets, for example combined analysis of microarray gene expression datasets addressing similar biological questions conducted at an interpretational level by meta-analysis, can enable more accurate results.

There are many natural population datasets available from previous studies and there is a strong precedent for comparing multiple datasets for such studies even when only small numbers of samples are available (e.g. [17], [28]).

These conflicting trees are likely due less to differences in analytical methods than variance in the sampled taxa, thus highlighting that taxon sampling is just as important as concatenating multiple datasets for estimating a robust phylogeny of rickettsiae.

This shows the importance of using multiple datasets for testing to get a fair comparison between methods; for example, WS had a better average ROC-50 score than PWM-based BBLS due to the good score on NRSF, but overall, BBLS PWM is slightly better than WS (p-value 0.064).

The enrichment zone thresholds for multiple datasets of a given TF were averaged to select one threshold value per TF.

For the multiple datasets used for illustration here, goodness-of-fit and −2×log-likelihood were used to compare models.

Several non-parametric statistical tests [27], [28] have been recently recommended for comparing different classifiers on multiple datasets (accounting for the effects of multiple comparisons) [29].

Finally, real-time updating and auto integration of multiple datasets allow for quick and seamless operations without the time overhead associated with traditional RDBMS-style approaches [23].

Further work will be needed to reveal whether similar relationships between biological importance and preservation of ChIP peaks in multiple datasets exists for other nuclear receptors and transcription factors.