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The principal limitation of the CLUSTER methodology is that it has been explored in relation to one case study cluster.
The two techniques used in this study, Cluster Analysis (CA) and Multi-Criteria Decision Analysis (MCDA), are separately well-established.
In this study, cluster analysis was employed to detect similarity and dissimilarity groups between the water quality variables of the collected groundwater samples.
Horizontal gene transfer events were supported by the fact that the majority of the variable T3E genes in our study cluster within pathogenicity islands in their Xanthomonas host genomes [8], [64], [87].
For this retrospective case-control study, cluster sampling was used to generate a nationally representative sample while retaining operational feasibility of data collection; clusters were the basic TB programme management unit (tuberculosis unit–"TU") each covering ∼500,000 population.
In concordance with the MAQC established framework [38], designed to increase the consistency of microarray datasets, the majority of arrays in this study cluster within 2 standard deviations when assessed by quality metrics (Figure 8 A).
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The selected divisions were used as study clusters (first-stage cluster sampling).
The use of our method to study clusters with arbitrary point group symmetries is briefly discussed.
In this study, clustered events such as aftershocks and earthquake swarms are not removed.
Other clones of this study clustered with sequences from TAG-accumulating actinobacteria different to Rhodococcus.
In this study, clusters of 10 nanospacecraft are considered, leading to a mission based on a total of 30 nanospacecraft.
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