Sentence examples for datasets has proven from inspiring English sources
An extensive evaluation of Merkurion in real-world datasets has proven its effectiveness and broad applicability to many data domains.
Despite the inefficiency of the current parallelization strategy, the 40X speedup for the largest datasets has proven sufficient for clinical applicability of the ℓ1-SPIRiT technique.
Experiments on several datasets have proven that the combined use of both techniques improves the classification accuracy on 3-class sentiment analysis.
So far, this dataset has proven fairly resistant to heavy tuning and over-fitting and it is a striking observation that ProbCons, the only package explicitly trained on BaliBase is not the most accurate (as shown on Table 1).
Time-series of normalized difference vegetation index (NDVI) datasets, such as the pathfinder AVHRR land (PAL) NDVI dataset, have proven to be appropriate for the detection of long-term vegetation cover changes.
The dataset presented here has proven very valuable for studying this important group of protists.
Along with the accumulation of microarray datasets, transcriptome co-expression analysis has proven to be a powerful tool for identifying regulatory relationships in the transcriptional networks of model organisms, including Escherichia coli [16], yeast [17] and Arabidopsis [18].
Motivation: The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs).
The visualization of datasets in form of quasi-median networks has proven a powerful tool to unmask data idiosyncrasies that could represent such errors [16].
Resolving the early diversification of animal lineages has proven difficult, even using genome-scale datasets.
Adding new data to existing datasets and bringing in multiple sources of other data has proven challenging from a data management point of view.
