The need to investigate the atomic constituents of biological network has led to increasing popularity of topological studies. A biological network is a graphical representation of the interactome with nodes and edges. Therefore, graph theoretic measures can be applied to such networks. We have performed an empirical study comparing a number of centrality measures, viz., betweenness centrality, eigenvector centrality, pagerank centrality, closeness centrality and radiality associated with a graph in the context of PPI networks. This empirical study shows the superiority of pagerank and radiality measure. We believe that their superiority can be leveraged in the analysis of other networks such as gene networks or metabolic networks.
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Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USAUniv Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
Martin, Travis
Zhang, Xiao
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Univ Michigan, Dept Phys, Ann Arbor, MI 48109 USAUniv Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
Zhang, Xiao
Newman, M. E. J.
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Univ Michigan, Dept Phys, Ann Arbor, MI 48109 USA
Univ Michigan, Ctr Study Complex Syst, Ann Arbor, MI 48109 USAUniv Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA