Evidence map›Paper›PMID 20006477›Full record

ArticleArtificial intelligence in medicine2010

Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

Matthias Samwald, Huajun Chen, Alan Ruttenberg, Ernest Lim, Luis Marenco, Perry Miller, Gordon Shepherd, Kei-Hoi Cheung

Abstract read
In one paragraph

Article in Artificial intelligence in medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Matthias SamwaldCenter for Medical Informatics, Yale University School of Medicine, New Haven, CT 06520-8009, USA. samwald@gmx.at
Huajun Chen
Alan Ruttenberg
Ernest Lim
Luis Marenco
Perry Miller
Gordon Shepherd
Kei-Hoi Cheung

Funding

SENSELAB: INTEGRATION OF MULTIDISCIPLINARY SENSORY DATAP01DC004732 · NIDCD · YALE UNIVERSITY · PI SHEPHERD, GORDON · 2000 to 2008
$10.2M
SenseLab: Integration of Multidisciplinary Sensory DataR01DC009977 · NIDCD · YALE UNIVERSITY · PI HINES, MICHAEL L, MCDOUGAL, ROBERT A. · 2009 to 2018
$6.7M
NIDCD NIH HHS P01 DC004732NIDCD NIH HHS P01 DC04732NIDCD NIH HHS R01 DC009977
6 · The paper itself

Abstract

objectiveIntegrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases.

methodsBased on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources.

conclusionWe demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/.

Indexed as

Information DisseminationInternetNeurosciencesSemanticsBrain MappingHumansNerve NetTranslational Research, Biomedical

Identifiers

PMID20006477
PMCPMC3131218

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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.