The use of graph theory models is widespread in biological pathway analyses as it is often desired to evaluate the position of genes and proteins in their interaction networks of the biological systems. In this article, we argue that the common standard graph centrality measures do not sufficiently capture the informative topological organizations of the pathways, and thus, limit the biological inference. While key pathway elements may appear both upstream and downstream in pathways, standard directed graph centralities attribute significant topological importance to the upstream elements and evaluate the downstream elements as having no importance.
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