ArticlePloS one2013
Database citation in full text biomedical articles.
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.
- Beyond blast: enabling microbiologists to better extract literature, taxonomic distributions and gene neighbourhood information for protein families.Microbial genomics · 2024Article
- Beyond Blast: Enabling Microbiologists to Better Extract Literature, Taxonomic Distributions and Gene Neighborhood Information for Protein Families.bioRxiv : the preprint server for biology · 2024Article
- Quantitative monitoring of nucleotide sequence data from genetic resources in context of their citation in the scientific literature.GigaScience · 2021Article
- The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences.Bioinformatics (Oxford, England) · 2020Article
- Biomedical text mining for research rigor and integrity: tasks, challenges, directions.Briefings in bioinformatics · 2018Article
- U-Index, a dataset and an impact metric for informatics tools and databases.Scientific data · 2018Article
- Europe PMC in 2017.Nucleic acids research · 2018Article
- Patterns of database citation in articles and patents indicate long-term scientific and industry value of biological data resources.F1000Research · 2016Article
- The BioStudies database.Molecular systems biology · 2015Article
- ArrayExpress update--simplifying data submissions.Nucleic acids research · 2015Article
- Comment: Making data count.Scientific data · 2015Article
- Article
- Database citation in supplementary data linked to Europe PubMed Central full text biomedical articles.Journal of biomedical semantics · 2015Article
- Europe PMC: a full-text literature database for the life sciences and platform for innovation.Nucleic acids research · 2015Article
- PubServer: literature searches by homology.Nucleic acids research · 2014Article
- Mining locus tags in PubMed Central to improve microbial gene annotation.BMC bioinformatics · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Molecular biology and literature databases represent essential infrastructure for life science research. Effective integration of these data resources requires that there are structured cross-references at the level of individual articles and biological records. Here, we describe the current patterns of how database entries are cited in research articles, based on analysis of the full text Open Access articles available from Europe PMC. Focusing on citation of entries in the European Nucleotide Archive (ENA), UniProt and Protein Data Bank, Europe (PDBe), we demonstrate that text mining doubles the number of structured annotations of database record citations supplied in journal articles by publishers. Many thousands of new literature-database relationships are found by text mining, since these relationships are also not present in the set of articles cited by database records. We recommend that structured annotation of database records in articles is extended to other databases, such as ArrayExpress and Pfam, entries from which are also cited widely in the literature. The very high precision and high-throughput of this text-mining pipeline makes this activity possible both accurately and at low cost, which will allow the development of new integrated data services.
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.