Sentence examples for centrality approach from inspiring English sources

Unlike existing methods, the betweenness centrality approach takes into account of both the fluxes between species and their relative positioning within the chemical network.

Our proposed approach ("using Katz broadcast centrality"), falls under the category of centrality approach and constraint-based mining as the user has control over the choice of threshold used for the first level filtering.

To compute the importance of genes that show differential co-expression or statistical interaction effects at the expression level (expression epistasis), we use a generalization of a centrality approach that we developed for epistasis networks from GWAS data, called SNPrank [ 9- 11].

Centrality approaches are generally classified into two types, classical centrality measures and parameterized centrality measures.

The independence of centrality approaches from a priori hypotheses, makes it a valuable methodological addition to the "model-free" analytic toolbox.

Therefore, although gene centrality approaches have shown to be useful to extract novel knowledge, important insights into the diversity of co-expression values and their statistical relevance may be missed.

Some strategies are the use of genetic algorithm or machine learning procedures [ 49, 50], however, the centrality approaches are by far the most applied procedures even by simplicity and because several studies had being pointed out its applicability [ 47, 51, 52].

By using a multi-centrality approach to identifying network hubs, we have detected vitamin-related proteins that are strongly embedded in the vitamin PPI network.

With our multi-centrality approach, the identified network hubs exhibit high centrality at the local, intermediate and global level, thus moving beyond a simple degree-based definition of protein centrality.

Our results show that both centrality modeling approaches achieved overall comparable performance, illustrating different advantages in terms of different metrics.

All of the networks except the ego network exhibit a power-law degree distribution, which seems to be a major influence on the ability of fragmenting the networks for centrality-based approaches.