Sentence examples for adjacency measures from inspiring English sources

The Adjacency measures the frequency of pairs of adjacent ascending or descending numbers, reflecting the habitual tendency to count forward or backward.

Future efforts may seek to compare the properties of sample networks using these and other adjacency measures.

In case of a soft threshold β = 1, we find the following corresponding weighted adjacency measures: and.

Our proposed sample adjacency measure (based on β = 2) also has several other advantages.

In Steps 1 and 2, the adjacency measure between genes is defined using the power transformation of correlation coefficients.

A major advantage of defining a network adjacency measure (as opposed to a general similarity measure) between samples is that it allows specification of network concepts (see below).

A major advantage of defining a network adjacency measure between samples (as opposed to a general similarity measure) is that it permits specification of network concepts.

These concepts are independent of the choice or use of clustering algorithms and depend only on the adjacency measure used to construct the network.

In light of these considerations, it can be helpful to have "targets" in mind, such as an expectation of what the mean ISA should approach for a given biological system, technology platform, and adjacency measure.

We find it useful to characterize sample networks using the mean (off-diagonal) adjacency measure, i.e. (9) m e a n A = ∑ i ∑ j ≠ i a ij n n − 1 where A = [ a ij ].

Third, while any other power β could be used, the choice of β = 2 results in an adjacency measure that is close to the correlation when the correlation is large (e.g. larger than 0.6, which is often the case among samples in microarray data).