Evidence map›Paper›PMID 21918645›Full record

ArticleWeb semantics (Online)2011

NCBO Resource Index: Ontology-Based Search and Mining of Biomedical Resources.

Clement Jonquet, Paea Lependu, Sean Falconer, Adrien Coulet, Natalya F Noy, Mark A Musen, Nigam H Shah

Abstract read
In one paragraph

Article in Web semantics (Online), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Data integration in biological research: an overview.Journal of biological research (Thessalonike, Greece) · 2015
    Review
  9. Article
  10. Article
  11. Article
  12. Ontology-Based Querying with Bio2RDF's Linked Open Data.Journal of biomedical semantics · 2013
    Article
  13. NCBO Technology: Powering semantically aware applications.Journal of biomedical semantics · 2013
    Article
  14. The HUPO proteomics standards initiative- mass spectrometry controlled vocabulary.Database : the journal of biological databases and curation · 2013
    Article
  15. Article
  16. Article
  17. Using ontology-based annotation to profile disease research.Journal of the American Medical Informatics Association : JAMIA · 2012
    Article
  18. Review
  19. Enabling enrichment analysis with the Human Disease Ontology.Journal of biomedical informatics · 2011
    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

7 authors.

Clement JonquetStanford Center for Biomedical Informatics Research, Stanford University, 251 Campus Drive, Stanford, CA 94305-5479, USA.
Paea Lependu
Sean Falconer
Adrien Coulet
Natalya F Noy
Mark A Musen
Nigam H Shah

Funding

STANFORD COMPOSITE(RMI)U54HG004028 · NHGRI · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2005 to 2014
$36.2M
NHGRI NIH HHS U54 HG004028
6 · The paper itself

Abstract

The volume of publicly available data in biomedicine is constantly increasing. However, these data are stored in different formats and on different platforms. Integrating these data will enable us to facilitate the pace of medical discoveries by providing scientists with a unified view of this diverse information. Under the auspices of the National Center for Biomedical Ontology (NCBO), we have developed the Resource Index-a growing, large-scale ontology-based index of more than twenty heterogeneous biomedical resources. The resources come from a variety of repositories maintained by organizations from around the world. We use a set of over 200 publicly available ontologies contributed by researchers in various domains to annotate the elements in these resources. We use the semantics that the ontologies encode, such as different properties of classes, the class hierarchies, and the mappings between ontologies, in order to improve the search experience for the Resource Index user. Our user interface enables scientists to search the multiple resources quickly and efficiently using domain terms, without even being aware that there is semantics "under the hood."

Identifiers

PMID21918645
PMCPMC3170774

What OpenQuestion holds

Textmetadata
LicenceTDM
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.