Sentence examples for extent of clusters from inspiring English sources

While this method protects against false positives, for modest effect sizes, the spatial extent of clusters may be reduced.

Comparison with icEEG and consideration of the surgical outcome suggests that in addition to the presence of IED-related clusters within the SOZ, the extent of clusters remote from the SOZ may also be important.

In contrary, in the clustering technique such as NNH, a threshold value, which determines the extent of clustering in the neighborhood, is pre-specified.

We study the effect that the extent of clustering has with the use of this heuristic as k varies and as (delta) is varied.

To us, these observations suggest that hDMPK A-induced fragmentation and clustering are at least partly uncoupled effects and that microtubular infrastructure only affects the extent of clustering.

Figure 2 shows the extent of clustering similar topologies using principal coordinates (PCoA) analysis, suggesting a coherent phylogenetic signal within some genes.

The methods and mathematical modeling of the translation of efficiency of FRET into extent of clustering have already been elucidated [30] and are explained briefly in Materials and Methods.

We used the exact same monoclonal antibody, L243, against DR1 as donor and acceptor, and added the reagent at well above saturating concentrations to ensure that the FRET measurements would accurately reflect the extent of clustering of that receptor.

In phenotype, the cells with the growth factors showed a progressive increase both in size and number, and particularly in extent of clustering (Fig. 1A) reaching a maximum by day 10 (Fig. 1C).

Plotting the FRET efficiency against the brightness of the acceptor before photobleaching, i.e. the density of acceptor labeled antibody bound to HLA-DR1, for all cells allows for the estimation of the extent of clustering of the HLA-DR1 for each group.

We have used the following network biology concepts to evaluate the topology and extent of clustering in the candidate sub-networks: Topological coefficient for node n1 is computed as TC (n1) = average (J n1, n2)/kn1), where J n1, n2) gives the value of the number of nodes shared by both n1 and n2 nodes and kn1 is the number of interactions of node n1.