ArticlePloS one2013
Entitymetrics: measuring the impact of entities.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 91 citations in OpenAlex.
- Issues about entitymetrics and paper-entity citation network.Scientometrics · 2022Article
- Analyzing knowledge entities about COVID-19 using entitymetrics.Scientometrics · 2021Article
- Using the full-text content of academic articles to identify and evaluate algorithm entities in the domain of natural language processing.Journal of informetrics · 2020Article
- Understanding Drug Repurposing From the Perspective of Biomedical Entities and Their Evolution: Bibliographic Research Using Aspirin.JMIR medical informatics · 2020Article
- Tracking and Mining the COVID-19 Research Literature.Frontiers in research metrics and analytics · 2020Article
- Using Entity Metrics to Understand Drug Repurposing.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020Article
- A systematic review on literature-based discovery workflow.PeerJ. Computer science · 2019Article
- Application of Ferulic Acid for Alzheimer's Disease: Combination of Text Mining and Experimental Validation.Frontiers in neuroinformatics · 2018Article
- Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.Journal of data and information science (Warsaw, Poland) · 2017Article
- Analyzing the field of bioinformatics with the multi-faceted topic modeling technique.BMC bioinformatics · 2017Article
- Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach.PloS one · 2016Article
- Comment: Making data count.Scientific data · 2015Article
- Article
- A chemo-centric view of human health and disease.Nature communications · 2014Article
- Article
- A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.Database : the journal of biological databases and curation · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.