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• W2053403152 abstract "This paper proposes entitymetrics to measure the impact of knowledge units. Entitymetrics highlight the importance of entities embedded in scientific literature for further knowledge discovery. In this paper, we use Metformin, a drug for diabetes, as an example to form an entity-entity citation network based on literature related to Metformin. We then calculate the network features and compare the centrality ranks of biological entities with results from Comparative Toxicogenomics Database (CTD). The comparison demonstrates the usefulness of entitymetrics to detect most of the outstanding interactions manually curated in CTD." @default.
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• W2053403152 date "2013-08-29" @default.
• W2053403152 modified "2023-10-11" @default.
• W2053403152 title "Entitymetrics: Measuring the Impact of Entities" @default.
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• W2053403152 doi "https://doi.org/10.1371/journal.pone.0071416" @default.
• W2053403152 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3756961" @default.
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