Evidence map›Paper›PMID 19753098›Full record

ArticleFrontiers in neuroscience2009

Ontologies for Neuroscience: What are they and What are they Good for?

Stephen D Larson, Maryann E Martone

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Molecular ontology of the parabrachial nucleus.The Journal of comparative neurology · 2022
    Article
  8. Article
  9. Article
  10. Article
  11. Best behaviour? Ontologies and the formal description of animal behaviour.Mammalian genome : official journal of the International Mammalian Genome Society · 2015
    Review
  12. Terminology development towards harmonizing multiple clinical neuroimaging research repositories.Data integration in the life sciences : ... International Workshop, DILS ... : proceedings. DILS (Conference) · 2015
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

2 authors.

Stephen D LarsonDepartment of Neurosciences, University of California San Diego, CA, USA.
Maryann E Martone

Funding

VOLUMETRIC CONTOUR-BASED SURFACE RECONSTRUCTIONP41RR004050 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PASQUALE, ELENA B · 1989 to 2011
$28.0M
A Resource for Biomedical Ontologies and Knowledge BasesP41LM007885 · NLM · STANFORD UNIVERSITY · PI MUSEN, MARK A · 2003 to 2010
$6.4M
DEVELOPMENT OF A 3-D CELL-CENTERED NEURONAL DATABASER01DA016602 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MARTONE, MARYANN E · 2003 to 2007
$3.4M
Ontology-based multiscale investigation of human neurological disease modelsR01NS058296 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MARTONE, MARYANN E · 2007 to 2010
$2.1M
NCRR NIH HHS P41 RR004050NIDA NIH HHS HHSN271200577531CNIDA NIH HHS R01 DA016602NINDS NIH HHS R01 NS058296NLM NIH HHS P41 LM007885
6 · The paper itself

Abstract

Current information technology practices in neuroscience make it difficult to understand the organization of the brain across spatial scales. Subcellular junctional connectivity, cytoarchitectural local connectivity, and long-range topographical connectivity are just a few of the relevant data domains that must be synthesized in order to make sense of the brain. However, due to the heterogeneity of the data produced within these domains, the landscape of multiscale neuroscience data is fragmented. A standard framework for neuroscience data is needed to bridge existing digital data resources and to help in the conceptual unification of the multiple disciplines of neuroscience. Using our efforts in building ontologies for neuroscience as an example, we examine the benefits and limits of ontologies as a solution for this data integration problem. We provide several examples of their application to problems of image annotation, content-based retrieval of structural data, and integration of data across scales and researchers.

Indexed as

databasesdata integrationneuroanatomyneuroinformaticssubcellular anatomy

Identifiers

PMID19753098
PMCPMC2695392

What OpenQuestion holds

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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.