Sentence examples for enormous number of data from inspiring English sources

Based on an enormous number of data stored in the Dortmund Data Bank, the SRK parameters of components in petroleum fluids have been fitted to a large number of experimental data including 4170 saturated liquid density data and 8097 PVT data at supercritical conditions.

The system incorporates a number of proprietary technologies for the specialized demands of processing an enormous number of concurrent tasks and data while analyzing information in real time.

The enormous number of protein primary structure data resulting from genomic sequencing efforts of the past 25 years provide compelling evidence that enzyme recruitment is pervasive in extant metabolic pathways.

Fully automation will be useful for processing enormous numbers of wave data.

The analysis of the human and macaque data was done for two purposes: (A) to show that the enormous number of AG mismatches in the squid data is real and not an artefact of the analysis pipeline, and (B) to demonstrate that our pipeline could identify RNA editing sites established by previous studies.

The enormous number of lexical decision trials in this data set featured a commensurate amount of errors; across all participants, 118,566 trials (i.e., 10.80%) contained errors.

These controls demonstrate that the enormous number of AG mismatches in the squid data is not an artefact of our analysis pipeline.

Because of the problems in searching for data on events that were often not considered as primary, secondary or even adverse event outcomes, and the enormous number of reports that could potentially contain relevant data, we did not feel able to call this review systematic.

The enormous number of indicators found in the literature generates too much data that often provide no additional knowledge on the environmental sustainability of a system.

Assembly of the sequence data were aided by condensing the enormous number of paired-end reads into a much smaller set of longer "super-reads," rendering subsequent assembly with an overlap-based assembly algorithm computationally feasible.

However, the very large number of SNPs checked in a typical GWAS (more than 10 million) and the enormous number of possible SNP combinations make detecting high-order epistatic interactions from GWAS data statistically and computationally challenging [ 6, 7].