Sentence examples for using a hierarchical cluster from inspiring English sources

However, when using a hierarchical cluster analysis, distinct profiles of coagulation were evidenced, defining 3 biological classes.

Based on historical maps and aerial photographs the LULC trends were determined using a hierarchical cluster analysis.

Global shark biogeographic units were identified by using a hierarchical cluster analysis, a standard method used to find structure in a multivariate dataset.

These candidate compounds were then clustered using a hierarchical cluster method based on both their two-dimensional compound structures and protein-ligand interactions [20], [21], similar to Jain's work [22].

This was done by using a hierarchical cluster analysis in order to identify clusters of individuals, and by taking into consideration the two DCt values corresponding to the ICCA.SRa and ICCA.SRb subregions, respectively.

Using a hierarchical cluster analysis on all cells and species occurring in those cells, we identified 93 biogeographic units, which we defined as areas characterized by a unique community of shark species, ranging in size from 2 to 9645 one-degree cells (mean = 311 cells, see Methods for details).

This was done using a hierarchical clustering algorithm that transformed the similarity matrix into a sequence of nested partitions.

The historical data of load, such as wind power data, are handled by using a hierarchical clustering algorithm and principal component feature extraction technology.

The R w wind power patterns is obtained using a hierarchical clustering algorithm combined with principal component-feature extraction technology with probability ( alpha_{{r_{w} }} ), denoted by ( (r_{w},alpha_{{r_{w} }} ) )((r_win {1,2,ldots,R_w})).

The microarray data (3072 spots) were analyzed using a hierarchical clustering analysis and focusing on two types of gene expression pattern.

The sample set of 148 healthy controls and 113 preT cases were then clustered over these 293 CpGs using a hierarchical clustering algorithm with Pearson correlation metric and average linkage.