Evidence map›Paper›PMID 22685160›Full record

ArticleDatabase : the journal of biological databases and curation2012

Improving links between literature and biological data with text mining: a case study with GEO, PDB and MEDLINE.

Aurélie Névéol, W John Wilbur, Zhiyong Lu

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. PubServer: literature searches by homology.Nucleic acids research · 2014
    Article
  7. Article
  8. BC4GO: a full-text corpus for the BioCreative IV GO task.Database : the journal of biological databases and curation · 2014
    Article
  9. Accessing biomedical literature in the current information landscape.Methods in molecular biology (Clifton, N.J.) · 2014
    Review
  10. Overview of the gene ontology task at BioCreative IV.Database : the journal of biological databases and curation · 2014
    Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Aurélie NévéolNational Center for Biotechnology Information, US National Library of Medicine, Bethesda, MD 20894, USA.
W John Wilbur
Zhiyong Lu

Funding

National Biomedical Information ServicesZIHLM200888 · NLM · NATIONAL LIBRARY OF MEDICINE · PI PALTOO, DINA · 2009 to 2025
$5200.7M
General and Semi-supervised Machine Learning Applied to BioinformaticsZIALM000089 · NLM · NATIONAL LIBRARY OF MEDICINE · PI WILBUR, WILLY · 2009 to 2015
$3.2M
Named Entity Recognition and Relationship Extraction in BiomedicineZIALM000002 · NLM · NATIONAL LIBRARY OF MEDICINE · PI LU, ZHIYONG · 2011 to 2012
$1.5M
Automatic Analysis and Annotation of Document Keywords in Biomedical LiteratureZIALM091711 · NLM · NATIONAL LIBRARY OF MEDICINE · PI WILBUR, WILLY · 2010 to 2015
$1.3M
NLM NIH HHS LM000002-01
6 · The paper itself

Abstract

High-throughput experiments and bioinformatics techniques are creating an exploding volume of data that are becoming overwhelming to keep track of for biologists and researchers who need to access, analyze and process existing data. Much of the available data are being deposited in specialized databases, such as the Gene Expression Omnibus (GEO) for microarrays or the Protein Data Bank (PDB) for protein structures and coordinates. Data sets are also being described by their authors in publications archived in literature databases such as MEDLINE and PubMed Central. Currently, the curation of links between biological databases and the literature mainly relies on manual labour, which makes it a time-consuming and daunting task. Herein, we analysed the current state of link curation between GEO, PDB and MEDLINE. We found that the link curation is heterogeneous depending on the sources and databases involved, and that overlap between sources is low, <50% for PDB and GEO. Furthermore, we showed that text-mining tools can automatically provide valuable evidence to help curators broaden the scope of articles and database entries that they review. As a result, we made recommendations to improve the coverage of curated links, as well as the consistency of information available from different databases while maintaining high-quality curation. Database URLs: http://www.ncbi.nlm.nih.gov/PubMed, http://www.ncbi.nlm.nih.gov/geo/, http://www.rcsb.org/pdb/

Indexed as

Databases, BibliographicDatabases, GeneticMEDLINEAbstracting and IndexingDatabase Management SystemsData Mining

Identifiers

PMID22685160
PMCPMC3371192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.