(A) Average resource import and (B) Node Equilibrium Population (NEP) as a function of the closeness centrality of the 100 node network under two out of phase variability scenarios: low amplitude high frequency (LAHF) and high amplitude low frequency (HALF). (C) The coefficient of variation of NEP as a function of closeness centrality for the high amplitude low frequency scenario (HALF).</p
The increase in population in the shock node is deducted from this. The population loss in the rest ...
<p>With the exception of B-centrality in P-networks (labeled as <i>ns</i>), all affiliation preferen...
<p>Data points depict Pearson correlation coefficients between the rescaled eigenvalue centrality of...
GEP is higher under out of phase variability and within the variability scenarios higher under lower...
The decrease in NEP after a shock as a function of (A) the distance to the shock node and (B) the cl...
GEP is more stable over time in out of phase scenario’s and within the variability scenarios more st...
<p>(A) Closeness () distributions in human (green), yeast (blue), and fly (red). Heavy lines are the...
(A) Cumulative distribution of NEP in the 10 node and 100 node networks. The cumulative fraction (y-...
(a) shows the result for different subgraph sizes given the number of subgraphs m = 10; (b) shows th...
<p>(a) HT09 (b) SG-Infectious (c) FudanWIFI. All the temporal networks are the same as those in Fig....
Changes in node strength (A) and node closeness (B) for each duration-restricted travel network acco...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...
<p>(a) and (b) Temporal networks generated by the dataset of 'SG-Infectious' (c) and (d) Temporal ne...
Centrality indices for Betweenness, Closeness, and Strength centrality for all 33 nodes. For details...
Functional behaviour of networks; a-d) Participation coefficient in high η networks at a range of co...
The increase in population in the shock node is deducted from this. The population loss in the rest ...
<p>With the exception of B-centrality in P-networks (labeled as <i>ns</i>), all affiliation preferen...
<p>Data points depict Pearson correlation coefficients between the rescaled eigenvalue centrality of...
GEP is higher under out of phase variability and within the variability scenarios higher under lower...
The decrease in NEP after a shock as a function of (A) the distance to the shock node and (B) the cl...
GEP is more stable over time in out of phase scenario’s and within the variability scenarios more st...
<p>(A) Closeness () distributions in human (green), yeast (blue), and fly (red). Heavy lines are the...
(A) Cumulative distribution of NEP in the 10 node and 100 node networks. The cumulative fraction (y-...
(a) shows the result for different subgraph sizes given the number of subgraphs m = 10; (b) shows th...
<p>(a) HT09 (b) SG-Infectious (c) FudanWIFI. All the temporal networks are the same as those in Fig....
Changes in node strength (A) and node closeness (B) for each duration-restricted travel network acco...
In this paper, we seek to find a computationally light centrality metric that could serve as an alte...
<p>(a) and (b) Temporal networks generated by the dataset of 'SG-Infectious' (c) and (d) Temporal ne...
Centrality indices for Betweenness, Closeness, and Strength centrality for all 33 nodes. For details...
Functional behaviour of networks; a-d) Participation coefficient in high η networks at a range of co...
The increase in population in the shock node is deducted from this. The population loss in the rest ...
<p>With the exception of B-centrality in P-networks (labeled as <i>ns</i>), all affiliation preferen...
<p>Data points depict Pearson correlation coefficients between the rescaled eigenvalue centrality of...