Journal
PLOS ONE
Volume 8, Issue 8, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0071416
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Funding
- National Research Foundation of Korea Grant
- Korean Government [NRF-2012-2012S1A3A2033291]
- Bio & Medical Technology Development Program of the National Research Foundation (NRF)
- Korean government (MEST) [2012048758]
- National Research Foundation of Korea [2012S1A3A2033291] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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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.
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