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Analyses of decision chains used by faculty highlight the idiosyncratic manner in which planning unfolds in practice, the centrality of existing artifacts, the role of contextual factors, and the absence of continuous improvement systems.
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The results from each of those were then compared to those obtained from random affiliation networks, or R-networks, in which individuals were unable to assess the centrality of their existing affiliations, and therefore dropped connections at random rather than dropping those perceived to be the least desirable partners.
Indeed, versions of existing centrality measures modified to take more local information into account are better at predicting which nodes are essential [ 131].
Actors with high betweenness centrality have a high probability of existing as a link on the shortest path (geodesic) between any two actors in a network.
In Table 3, |ION ∩ Mi | denotes the number of proteins detected by both ION and one of the eight other existing centrality methods Mi. {Mi ION} represents the set of proteins detected by Mi ignored by ION.
|ION ∩ Mi | denotes the number of proteins identified by both ION and one of the eight other existing centrality methods Mi. {Mi − ION} represents the set of proteins detected by Mi while ignored by ION.
All of these experimental result shows that the performance of ION in predicting essential proteins is better than that of the seven other existing centrality methods.
How the centrality of the most central node exceeds the centrality of all other nodes.
In summary, ION achieves comparable performance in finding essential proteins with high-connectivity with some of the eight other existing centrality methods.
In fact, for the top 100 of proteins, ION can detect 52 different essential proteins which can't be detected by anyone of the eight other existing centrality methods (see Additional file 2).
This added 4 measures of journal impact to our data set bringing the total number of retrieved, existing measures to 8. In [22] and [15] we describe methods to rank journals on the basis of various social network measures of centrality [13], e.g. betweenness centrality that is calculated from journal citation- and usage graphs.
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