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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...

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Detalles Bibliográficos
Autores principales: Ding, Ying, Song, Min, Han, Jia, Yu, Qi, Yan, Erjia, Lin, Lili, Chambers, Tamy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
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.
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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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