Sentence examples for density of interactions from inspiring English sources

Even if you don't accept the ecological metaphor, there's no doubt that our emerging information environment is more complex – in terms of numbers of participants, the density of interactions between them, and the pace of change – than anything that has gone before.

From the analysis of Δw dependence on blend composition we concluded that blends containing PVP of 10 000 g mol−1 exhibit a larger number of relaxations than blends containing high molecular weight PVP, indicating that the density of interactions is larger in the former.

In both datasets, the cluster we extracted had a significantly higher within-group density of interactions than what would be expected by chance (not shown), supporting our observations above.

Modularity is a measure of how much the network is structured in cohesive subgroups of vertices (modules), in which the density of interactions is higher within than among subgroups.

In order to test if the observed density of interactions among S3.7 proteins is expected by chance, we compared within-group interaction densities of the groups with those in 100 randomized instances of the network, and find that S3.7 proteins are significantly more inter-connected than what would be expected by chance (Fig. 2b).

One possible reason is that the size of modules depends on the parameter that scales the density of interactions.

By applying FICS, we characterized the area and density of interaction clusters between P-TEFb and RNAPII or histone H2A in single living cells.

If the "reinforcement" hypothesis, outlined above, is correct, therefore, the actions of an individual's neighbors ought to be dependent on the actions of their neighbors, and hence the experience of the focal individual will depend on the density of interaction between his or her immediate neighbors.

Using Bayes theorem [ 24] we can write the joint probability density of interaction variables as, (1) P (X | Y, V ) = P (Y | X, V, θ Y ) P (X | V, θ X ) ∑ X P (Y | X, V, θ Y ) P (X | V, θ X ) The first term in the numerator, P (Y | X, V, θ Y ), is the likelihood of the observed expression data given the interaction variables and gene network.

Values of b g greater than 1 indicate a density of internal interactions higher than interactions between the group and the rest of the network.

This is appropriate for the task of inferring ancestral interactions because we expect the density of such interactions to be relatively low, and because we care most about those inferred ancestral interactions in which we have high confidence.