Sentence examples for interaction distribution from inspiring English sources

In our study, the hub selection criterion was based on the position of a sharp turn (or inflection point) on an accumulative protein interaction distribution plot from each of the four species.

The outcome of spin organizations from a 2D Ising model simulation at three different T values is presented in Figure 2 after being projected on a 1015 parcellation of the brain [ 67] (notice that the relation between physical position in the brain and the 2D lattice is completely arbitrary, even if nearest neighbour interaction distribution is maintained).

Different topologies display different global utility and global strength of interaction distributions.

b Watts Strogatz network strength of interactions distribution is bimodal and highly skewed to the right.

c Barabási Albert network strength of interactions distribution is also a normal-like curve.

Regarding strength of interactions distribution, the Erdös Rényi random network displays a normal distribution of strength of interactions, as expected.

Fig. 7 Strength of interactions distribution on different topologies during Second Experiment. a Random, Erdös Rényi network displays a normal-like distribution.

Central to our argument are the differences in utility and strength of interactions distribution at the end of the simulation, for every topology.

However, in the Watts-Strogatz network topology (Fig. 7b), the strength of interactions distribution is a highly asymmetric bimodal, with a really low frequency mode of low strength of interactions and a high probability mode for high strength of interactions.

Analysing trophic interactions, distribution of individuals, migration, and relationships among populations is possible from samples that are small or even digested like feces, prey remains, shed skin cells, saliva or gut content [46 49].

For a given FDR α j and interaction degree distribution parameters Φ, the joint distribution of the total number of true interactions (k j ) and the number of false positives in the sampled interactions (f j ) is (1) in which ℕ is a normalization constant: (2) Pr k j |Φ) is the prior distribution of the protein interaction degree.