Sentence examples for datasets was assumed from inspiring English sources

The BLASTp RBH between the GRS and CCDS datasets was assumed to be robust and so if a contig was wrongly assigned to a CCDS (via the GRS dataset), it is likely that BLASTx is the source of error.

However, all the datasets are assumed to be subject to the same selective reporting bias, i.e. the parameters w =  (w1,.., wk) are the same for all datasets.

These datasets were assumed to be representative of standard qPCR data because they are included as example datasets in the qpcR package for the purpose of demonstrating various model-fitting procedures for quantification of qPCR data.

In fixed effects models, the true effect of risk allele is assumed to be the same value in each dataset, whereas in random effects models the risk allele effects for the individual datasets are assumed to vary around some overall average effect.

To simplify the data import all datasets are assumed to be preprocessed and being in tab-delimited ASCII form.

For binary classifications, candidate input datasets are assumed to be two sets of vectors in an n-dimensional space.

All reads mapping to annotated genes in the Otto et al. and Bartfai et al. datasets were assumed to originate from the annotated sense mRNA, whereas only the mapped sense-strand reads from total RNA libraries (libraries #1 4) were used for the Siegel et al. dataset.

It should be noted that in the estimation of confidence limits for translation rates, the protein half-life dataset was assumed not to have a significant location error.

In order to evaluate the performance of the different methods, we now run a simulation where parameters obtained from the Iris dataset are assumed to be the "true model".

The results of TF on this dataset are assumed to be accurate.

Missing continuous infusion durations (for two occasions in the model development dataset) were assumed to be 16 h, per protocol.