Sentence examples for data were clustered from inspiring English sources

Transcriptome data were clustered using weighted gene coexpression network analysis (WGCNA), a tailored method for identification of highly coexpressed gene sets23.

Considering the varying phases of moorsh-forming process, bulk densities and water retention data were clustered according to horizon category by applying the k-means method.

Due to the small-scale landscape heterogeneity, pixel-based classifiers were applied and training data were clustered according to their spectral signatures.

The data were clustered into 4 substantive themes that included: life is scattered; trying to make sense of it; learning to live with it; and getting settled.

The results suggest that using multiple data sources with the spatio-temporal simple cokriging method effectively improves the imputation accuracy if the missing data were clustered, or in blocks.

The data were clustered by Ward's clustering with the Euclidean distance.

Interview data were clustered around main themes as detailed on a value proposition canvas (Jobs, Gains, Pains, see below).

Array data were clustered using Cluster 3.0.

All sequences that accounted for less than five percent of the data were clustered together.

Data were clustered with different algorithms, and functions of the known DE genes were further defined by Gene Ontology.

Expression microarrays (normalized data) were clustered by a hierarchical clustering algorithm by using an average linkage method in GeneSpring.