Sentence examples for large set of metrics from inspiring English sources

Rudnick et al. (2010) described a large set of metrics for the quantitative assessment of system performance and evaluation of technical variability among inter- and intra-laboratory LC-MS/MS proteomics experiments.

Multivariate ANOVA analysis is a possible way to overcome this no-direction problem; however, with a large set of metrics to examine simultaneously, it is computationally and methodologically more challenging, and the estimates may involve a large magnitude of uncertainty.

From the earliest development of landscape metrics to quantify spatial pattern, analysts have used principal components analysis or related data reduction techniques (e.g., Cushman and others 2008; Riitters and others 1995) to aid interpretation by compressing a large set of metrics to a statistically independent smaller set of meta-metrics.

Users should not be expected to manually parse and analyse large sets of metrics or graphs.

The assessment was conducted by using a metrics suite, metrics thresholds derived from a large set of open source metadata-based frameworks, a process for automatic detection of design disharmonies and manual source code analysis.

A larger set of related metrics need to be developed.

This paper reports a systematic exploration of existing ontology metrics from a large set of ontologies extracted from the Swoogle search engine.

This paper reports a preliminary exploration of ontology metrics from a large set of ontologies extracted from the Open Biomedical Ontologies (OBO) repository.

The visualizer evaluates a large set of gene set enrichment profiles using a variety of comparison metrics and presents these metrics in an understandable manner.

More specifically, future research could focus on studying the behavior of social tagging systems and tag vocabulary evolution in additional LORs (beyond the OSR repository) with large sets of tags, using the extended set of metrics adopted in this paper.

Biological models typically contain numerous output metrics resulting from large sets of coupled equations, and complex covariance patterns often exist between the outputs.