Results 1 to 10 of about 572,176 (269)
Clustering coefficient reflecting pairwise relationships within hyperedges [PDF]
Scientific ReportsHypergraphs are generalizations of simple graphs that allow for the representation of complex group interactions beyond pairwise relationships. Clustering coefficients quantify local link density in networks and have been widely studied for both simple ...
Rikuya Miyashita +2 more
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Overlapping Structures Detection in Protein-Protein Interaction Networks Using Community Detection Algorithm Based on Neighbor Clustering Coefficient [PDF]
Frontiers in Genetics, 2021 With the rapid development of bioinformatics, researchers have applied community detection algorithms to detect functional modules in protein-protein interaction (PPI) networks that can predict the function of unknown proteins at the molecular level and ...
Yan Wang +7 more
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Corrigendum: Overlapping Structures Detection in Protein-Protein Interaction Networks Using Community Detection Algorithm Based on Neighbor Clustering Coefficient [PDF]
Frontiers in Genetics, 2021 Yan Wang +7 more
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The Clustering Coefficient for Graph Products
Axioms, 2023 The clustering coefficient of a vertex v, of degree at least 2, in a graph Γ is obtained using the formula C(v)=2t(v)deg(v)(deg(v)−1), where t(v) denotes the number of triangles of the graph containing v as a vertex, and the clustering coefficient of Γ ...
Jhon J. Aguilar-Alarcón +2 more
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Scientific Annals of Economics and Business, 2023 In this paper we deal with a network analysis of interconnected cabinets in Greece for an extended time period. In parallel, we present a small review of the economic crises that have occurred in Greece over this period.
Dimitrios Kydros +1 more
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Study of Information Dissemination in Hypernetworks with Adjustable Clustering Coefficient
Applied Sciences, 2023 The structure of a model has an important impact on information dissemination. Many information models of hypernetworks have been proposed in recent years, in which nodes and hyperedges represent the individuals and the relationships between the ...
Pengyue Li +4 more
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A Novel Centrality of Influential Nodes Identification in Complex Networks
IEEE Access, 2020 Influential nodes identification in complex networks is vital for understanding and controlling the propagation process in complex networks. Some existing centrality measures ignore the impacts of neighbor node.
Yuanzhi Yang +4 more
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IEEE Access, 2021 Mental workload has been widely estimated based on electroencephalography (EEG) in the frequency domain. However, simple frequency features are not entirely accurate indicators of the cognitive load because surface EEG signals are weak, nonstationary and
Guohun Zhu +4 more
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Evolutionary aspect of protein sequence network based on the 2D representation of amino acids [PDF]
Network Biology, 2022 For the comparative analysis of proteins, their proper clustering, and evolutionary relationships require analysis of their sequences. We used a mathematical parameter termed a similar factor to create a similar degree matrix of ND6 protein sequences ...
Sanjay Sharma +2 more
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Brain Sciences, 2021 We aimed to evaluate diffusion tensor imaging (DTI) in infants born extremely preterm, to determine the effect of erythropoietin (Epo) on DTI, and to correlate DTI with neurodevelopmental outcomes at 2 years of age for infants in the Preterm ...
Janessa B. Law +7 more
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