2021
DOI: 10.1016/j.molstruc.2021.130980
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Eigenvector centrality based algorithm for finding a maximal common connected vertex induced molecular substructure of two chemical graphs

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Cited by 7 publications
(3 citation statements)
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“…In recent years, centrality measures have found several applications in chemistry. For example, eigenvector centrality has been applied to the study of certain molecular substructures in [53], whereas closeness and betweenness centrality have been used to show that osmolytes act as hubs in the hydrogen-bond network of the solution [60].…”
Section: Centrality Measuresmentioning
confidence: 99%
“…In recent years, centrality measures have found several applications in chemistry. For example, eigenvector centrality has been applied to the study of certain molecular substructures in [53], whereas closeness and betweenness centrality have been used to show that osmolytes act as hubs in the hydrogen-bond network of the solution [60].…”
Section: Centrality Measuresmentioning
confidence: 99%
“…Eigenvector centrality (EC). Eigenvector centrality (EC) 77 scores correspond to the values of the first eigenvector of the graph adjacency matrix. The EC score of u is defined as:…”
Section: Benchmarking Quantification and Statisticsmentioning
confidence: 99%
“…Eigenvector centrality has been utilized for assessing heterogeneity and damage in proteins based on polymer networks [7], for finding a maximal common connected vertex induced molecular substructure of two chemical graphs [12], and for functional importance and diversity of yeast proteins in the context of a protein-protein interaction network [13]. A molecule can be visualized as a graph and also represented as an undirected, labeled graph in which atoms are nodes and bonds are the edges of the graph.…”
Section: Conclusion and Remarksmentioning
confidence: 99%