Sentence examples for datasets are generated by from inspiring English sources

Two synthetic datasets are generated by the SSCA#2 generator [2] and the power-law generator R-MAT [3] respectively.

Increasingly elaborate and voluminous datasets are generated by the (bio pharmaceutical industry and are a major challenge for application of PAT and QbD principles.

All of the datasets are generated by the ms-series simulator [ 30].

The human datasets are generated by the simulator Hapsample (Wright et al., 2007), which is publicly accessible from the web site http://www.hapsample.org.org

From this 'ground truth' network a Bayesian network with CPTs drawn from a similar distribution to those learned from real data (see Methods for full details) is formed and synthetic datasets are generated by sampling the Bayesian network.

Additionally, all datasets are generated by the Illumina HiSeq 2000 sequencing platform with paired-end layout and are downloaded from the DNA Data Bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp/).

This over-head is incompatible with the size of the datasets being generated by next generation sequencing technologies.

The different reference datasets were generated by eliminating some cells or reads from the original scRNAseq.

MF datasets were generated by applying moderate perturbations to the basal activation levels of all genes in the network.

Tryptic glycopeptide datasets were generated by the addition of glycan mass increments to the masses of the two identified peptides.

The synthetic datasets were generated by drawing simulated case and control samples from lognormal distributions: control samples from a distribution with a lower mean, and case samples from either the control distribution or a case distribution with a higher mean.