Sentence examples for the samples were classified using from inspiring English sources

The samples were classified using reported gene expression phenotype centroids as described [ 26].

The selected sample regarded is as an unknown one, and then the sample is classified using the model built with the rest training samples.

The metagenome sequences obtained from the different samples were classified using the BLASTx-approach of CARMA3 [ 24] in order to determine the prevalence of potentially human pathogenic bacteria.

The methylation proportion of each CpG site was obtained, M-scores were calculated, and the test set samples were classified using the threshold listed above.

After microscopic evaluation, OL samples were classified using the binary system [ 27].

Conversely, when ER+ FBC samples were classified using the MBC subgroup centroids, 151 samples (63%) were unclassified.

With the hope of applying laser-induced breakdown spectroscopy (LIBS) to the geological logging field, a series of cutting samples were classified using LIBS coupled with chemometric methods.

Haematoxylin and eosin slides were reassessed by a consultant upper gastrointestinal pathologist (SAP) to select the most suitable specimens for immunohistochemistry. Biopsy samples were classified using internationally agreed criteria (Ibrahim, 2000; Schlemper et al, 2000; Odze, 2006).

Groundwater samples were classified using cluster HCA.

In this analysis, samples were classified using K-means clustering based on candidate miRNAs expression levels into two groups which were defined as luminal-A trend or basal-like trend according to the proportion of two breast cancer subtype samples.

The expression of leptin and ObR in cancer samples was classified using a four-point scale: 0, < 10% stained cells; 1+, 10 50% cells with weak staining; 2+, >50% cells with weak staining; 3+, > 50% cells with strong staining.