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Entitymetrics: Measuring the Impact of Entities
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 netw...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756961/ https://www.ncbi.nlm.nih.gov/pubmed/24009660 http://dx.doi.org/10.1371/journal.pone.0071416 |
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author | Ding, Ying Song, Min Han, Jia Yu, Qi Yan, Erjia Lin, Lili Chambers, Tamy |
author_facet | Ding, Ying Song, Min Han, Jia Yu, Qi Yan, Erjia Lin, Lili Chambers, Tamy |
author_sort | Ding, Ying |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3756961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37569612013-09-05 Entitymetrics: Measuring the Impact of Entities Ding, Ying Song, Min Han, Jia Yu, Qi Yan, Erjia Lin, Lili Chambers, Tamy PLoS One Research Article 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. Public Library of Science 2013-08-29 /pmc/articles/PMC3756961/ /pubmed/24009660 http://dx.doi.org/10.1371/journal.pone.0071416 Text en © 2013 Ding et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ding, Ying Song, Min Han, Jia Yu, Qi Yan, Erjia Lin, Lili Chambers, Tamy Entitymetrics: Measuring the Impact of Entities |
title | Entitymetrics: Measuring the Impact of Entities |
title_full | Entitymetrics: Measuring the Impact of Entities |
title_fullStr | Entitymetrics: Measuring the Impact of Entities |
title_full_unstemmed | Entitymetrics: Measuring the Impact of Entities |
title_short | Entitymetrics: Measuring the Impact of Entities |
title_sort | entitymetrics: measuring the impact of entities |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756961/ https://www.ncbi.nlm.nih.gov/pubmed/24009660 http://dx.doi.org/10.1371/journal.pone.0071416 |
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