Sentence examples for datasets were selected and from inspiring English sources

Previously reported gene expression datasets were selected and downloaded from the Gene Expression Omnibus database.

As case of study, the most common 26 of 48 species from the Snapshot Serengeti (SSe) dataset were selected and the potential of the Very Deep Convolutional neural networks framework for the species identification task was analyzed.

To confirm the expression of RNAseq only sequences, 25 RNAseq transcripts never identified in any other dataset were selected and all were successfully amplified by RT-PCR.

The putative ceRNA pairs satisfying the optimal states of essential factors in the GBM dataset were selected and defined as the "optimal ceRNA pairs".

The top ten genes with lowest p-values of the microwave dataset were selected and their fold changes were compared to the fold changes of the same genes in the Genevestigator datasets.

A subset of 83 query proteins belonging to the four main SCOP categories with certain features such as having the sequence identity of less than 10%, without missing residues and having at least two family members in the dataset, were selected and subtracted from the dataset (additional details about the dataset are available at Lo et al. [ 22]).

To create the first series in the benchmark, the first assay in the dataset was selected and an attempt was made to find a set of 5 molecules whose activities differ by at least 0.38 log units (this attempt involved iterating randomly over all possible selections of 5 molecules from the assay several thousand times).

For GWE data analysis, the GSE5281 dataset was selected and analyzed using GEO2R tool accessed from GEO web server [ 45].

The Homo sapiens genes dataset is selected, and filters selected by clicking on the Filter bar again but this time the ID list limit filter in the GENE section is chosen.

For the outgroup in our tree, a consensus sequence representing the most common nucleotide at each position for each subtype represented in the Zaire/DRC dataset was selected, and then an overall DRC consensus sequence (DRCcons) was inferred.

Then the two datasets were selected to detect site-specific positive selection and purifying selection.