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Entitymetrics: measuring the impact of entities.

Ding Y, Song M, Han J, Yu Q, Yan E, Lin L, Chambers T - PLoS ONE (2013)

Bottom Line: Entitymetrics highlight the importance of entities embedded in scientific literature for further knowledge discovery.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Information and Library Science, Indiana University, Bloomington, Indiana, USA.

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.

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Related in: MedlinePlus

From paper citation to entity citation.
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pone-0071416-g003: From paper citation to entity citation.

Mentions: In the next step, we built a bio-entity citation network based on the concept that if paper A cites paper B, then an entity in paper A will be considered to cite an entity in paper B. Entities in the citing paper are paired with entities in all the cited papers (see Figure 3). A hash table is used to store the entity citation associations and their occurance frequency.


Entitymetrics: measuring the impact of entities.

Ding Y, Song M, Han J, Yu Q, Yan E, Lin L, Chambers T - PLoS ONE (2013)

From paper citation to entity citation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3756961&req=5

pone-0071416-g003: From paper citation to entity citation.
Mentions: In the next step, we built a bio-entity citation network based on the concept that if paper A cites paper B, then an entity in paper A will be considered to cite an entity in paper B. Entities in the citing paper are paired with entities in all the cited papers (see Figure 3). A hash table is used to store the entity citation associations and their occurance frequency.

Bottom Line: Entitymetrics highlight the importance of entities embedded in scientific literature for further knowledge discovery.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Information and Library Science, Indiana University, Bloomington, Indiana, USA.

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.

Show MeSH
Related in: MedlinePlus