<p>For each measure of centrality sets of folds with high and low centralities are identified as described in the Methods. These sets are shown projected onto the network. Low centralities are coloured in blue. High centralities are shaded from red (lowest) to yellow (highest). Nodes with intermediate centralities which are not counted as either central or peripheral are shown in grey. Also shown is a cumulative percentile plot for the fold ages of central and peripheral nodes. These graphs show a preference for central nodes to be older than peripheral folds. a) Node centrality by degree. b) Node centrality by closeness. c) Node centrality by betweenness.</p
In network analysis, it is useful to identify important vertices in a network. Based on the varying ...
International audienceFinding nodes occupying interesting positions in a graph is useful to extract ...
<p>Each column corresponds to a specific network (all species or by single species) Each line relate...
International audienceWe show that prominent centrality measures in network analysis are all based o...
Abstract—Estimating influential nodes in large scale networks including but not limited to social ne...
Living systems are associated with Social networks — networks made up of nodes, some of which may be...
The roles of different nodes within a network are often understood through centrality analysis, whic...
The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance...
Subgraph centrality measure characterizes the participation of each node in all subgraphs in a netwo...
Many scholars have tried to address the identification of critical nodes in complex networks from di...
The roles of different nodes within a network are often understood through centrality analysis, whic...
An important problem in network analysis is understanding how much nodes are important in order to \...
<p>(A) Distribution of protein nodes among the network topological features. Rich-club in red, rich-...
BACKGROUND: Living systems are associated with Social networks - networks made up of nodes, some of ...
Recent developments in network theory have allowed for the study of the structure and function of th...
In network analysis, it is useful to identify important vertices in a network. Based on the varying ...
International audienceFinding nodes occupying interesting positions in a graph is useful to extract ...
<p>Each column corresponds to a specific network (all species or by single species) Each line relate...
International audienceWe show that prominent centrality measures in network analysis are all based o...
Abstract—Estimating influential nodes in large scale networks including but not limited to social ne...
Living systems are associated with Social networks — networks made up of nodes, some of which may be...
The roles of different nodes within a network are often understood through centrality analysis, whic...
The centrality of an edge in a graph is proposed to be the degree of sensitivity of a graph distance...
Subgraph centrality measure characterizes the participation of each node in all subgraphs in a netwo...
Many scholars have tried to address the identification of critical nodes in complex networks from di...
The roles of different nodes within a network are often understood through centrality analysis, whic...
An important problem in network analysis is understanding how much nodes are important in order to \...
<p>(A) Distribution of protein nodes among the network topological features. Rich-club in red, rich-...
BACKGROUND: Living systems are associated with Social networks - networks made up of nodes, some of ...
Recent developments in network theory have allowed for the study of the structure and function of th...
In network analysis, it is useful to identify important vertices in a network. Based on the varying ...
International audienceFinding nodes occupying interesting positions in a graph is useful to extract ...
<p>Each column corresponds to a specific network (all species or by single species) Each line relate...