Sentence examples for strength of clusters from inspiring English sources

The strength of clusters was evaluated with confidence intervals calculated from 10 000 multiscale bootstrap resampling.

Calculate the clustering strength of cluster C k based on the assortative mixing equations (Equations 9 and 10); this step iterates through each C k adjacency list, thus it has a time complexity of O |E|+|V|)  .

An estimate of the "strength of clustering" is obtained by calculating S = O - E E × 100.

The strength of clustering is that it uncovers structure within biological networks, even when nothing is known about individual proteins.

In addition, we computed the monophyletic clade (MC) statistic that measures the strength of clustering within individual geographic regions.

For PNETs, the strength of clustering (calculated using the geographical distance version of the Knox method) was positive for most critical values.

Furthermore, its application requires that the expected age distributions of HGT events are similar between compared methods, as the strength of clustering likely decreases with increasing age.

The strength of clustering (S) of PNET was summed over all 225 combinations of space and time (∑ i = 1 225 S ) and was calculated as 13819 using the geographical distance and 17177 using the NN versions of the Knox test, respectively.

In addition, the maximum clade statistic was used to compare the strength of clustering at each location by calculating the expected and observed mean clade size from each of the 4 study locations.

To enable comparisons to be made between the geographical distance and nearest neighbour (NN) metrics (see below), an overall indicator of the strength of clustering was obtained using ∑ i = 1 225 S (where i refers to the i th combination of s and t).

The terminal.pen2 dataset is expected to contain less false-positive HGT candidates than terminal.pen1 (due to the increased gain/loss penalty ratio, stronger support is required before a gene is considered to result from HGT): as the fraction of false positives decreases, the strength of clustering grows.