Sentence examples for using the node weights from inspiring English sources

The sets-2 and 3 are also random sequences in which residues in certain positions are constrained based on conservation and on the topological rank (using the node weights on the basis of their primary and secondary connections [31]).

In the designed sequence sets (set 5 8), topology based ranking scheme (using the node weights on the basis of their primary and secondary connections) [31] was used to rank the residues sites and a sequence of reduced amino acid alphabet of five groups (labeled as A, B, C, D, and E) [34] as described in section (a) was generated.

The aggregation weights are identified using: the nodes control, the link state aggregation date, and the link states amount.

Microarray data was integrated into the network using the median intensity value as the node weights in the network.

Because Hubba cannot manipulate the node weights, we used only the gene names as an input for Hubba with the six different algorithms, as in the ERBB comparison case (see the "Methods" for the details).

Note that the MNM algorithm is independent of the node weights as the assortativity weight for an edge is measured simply to be the number of uncovered adjacent edges; thus, the maximal node matching obtained using the MNM algorithm for a given graph would be the same irrespective of the criterion used for node weights.

If AI (_{M}) is close to 1, it indicates that the end vertices of the edges in M are very much different from each other with respect to the node weight used in calculating the assortativty index.

If AI (_{M}) is close to 1, it indicates that the end vertices of the edges in M are similar to each other with respect to the node weight used in calculating the assortativity index.

If AI (_{M}) is close to 0, it indicates that the matching of the vertices is quite arbitrary with respect to the node weight used in calculating the assortativity index.

Figures 44, 45 and 46 present the results of the execution of the MDM and MAM algorithms on scale-free network graphs that evolve from the BA model (described in Sect. 6); the node degree is used as node weights for the assortativity calculations.

MeO designed the node weighting scheme.