The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents the latest authors’ achievements regarding the analysis of the networks of proteins (interactome networks), by computing more efficiently the betweenness centrality measure. The pa...

background and objectives: while social network analysis has left a remarkable practical impact in the healthcare field, the potential implication of this methodology in the primary health domain is poorly researched. hence, this study aimed to explore the use and usefulness social network analysis in the context of primary health care. methods: the health volunteers of imam ali health center i...

Abstract Betweenness centrality quantifies the importance of a vertex for information flow in network. The standard betweenness applies to static single-layer networks, but many real world networks are both dynamic and made several layers. We propose definition temporal multiplexes. This accounts topological structure duration paths determination shortest paths. an algorithm compute new metric ...

In this paper, we propose a method for rapid computation of group betweenness centrality whose running time (after preprocessing) does not depend on network size. The calculation of group betweenness centrality is computationally demanding and, therefore, it is not suitable for applications that compute the centrality of many groups in order to identify new properties. Our method is based on th...

Betweenness centrality of a vertex in a graph measures the fraction of shortest paths going through the vertex. This is a basic notion for determining the importance of a vertex in a network. The kbetweenness centrality of a vertex is defined similarly, but only considers shortest paths of length at most k. The sequence of k-betweenness centralities for all possible values of k forms the betwee...

This paper presents a centrality measurement and analysis of the social networks for tracking online community. The tracking of single community in social networks is commonly done using some of the centrality measures employed in social network community tracking. The ability that centrality measures have to determine the relative position of a node within a network has been used in previous r...

Betweenness centrality of a vertex (edge) in a graph is a measure for the relative participation of the vertex (edge) in the shortest paths in the graph. Betweenness centrality is widely used in various areas such as biology, transportation, and social networks. In this paper, we study the update problem of betweenness centrality in fully dynamic graphs. The proposed update algorithm substantia...