Evidence map›Paper›PMID 26320941›Full record

ArticleJournal of extracellular vesicles2015

Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies.

Sai Lakshmi Subramanian, Robert R Kitchen, Roger Alexander, Bob S Carter, Kei-Hoi Cheung, Louise C Laurent, Alexander Pico, Lewis R Roberts, Matthew E Roth, Joel S Rozowsky and 3 more

Abstract read
In one paragraph

Article in Journal of extracellular vesicles, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

35 citing papers in PubMed.

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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

13 authors.

Sai Lakshmi SubramanianBioinformatics Research Laboratory, Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Robert R KitchenDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
Roger AlexanderPacific Northwest Diabetes Research Institute, Seattle, WA, USA.
Bob S CarterDivision of Neurosurgery, UC San Diego School of Medicine, UC San Diego Health System, La Jolla, CA, USA.
Kei-Hoi CheungDepartment of Emergency Medicine, Yale Center for Medical Informatics, Yale University School of Medicine, New Haven, CT, USA.
Louise C LaurentDepartment of Reproductive Medicine, University of California, San Diego, La Jolla, CA, USA.
Alexander PicoGladstone Institutes, San Francisco, CA, USA.
Lewis R RobertsDivision of Gastroenterology and Hepatology, Mayo Clinic College of Medicine, Rochester, MN, USA.
Matthew E RothBioinformatics Research Laboratory, Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Joel S RozowskyDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
Andrew I SuDepartment of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA, USA.
Mark B GersteinDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
Aleksandar MilosavljevicBioinformatics Research Laboratory, Department of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, USA; amilosav@bcm.edu.

Funding

SOC CoreU54DA036134 · NIDA · BAYLOR COLLEGE OF MEDICINE · PI GALAS, DAVID J., GERSTEIN, MARK BENDER · 2013 to 2018
$15.0M
exRNA Biomarkers for Human GliomaUH3TR000931 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CARTER, BOB S, HOCHBERG, FRED H · 2015 to 2017
$3.0M
NCATS NIH HHS UH3 TR000931NIDA NIH HHS U54 DA036134
6 · The paper itself

Abstract

The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

Indexed as

DMRRERC ConsortiumexRNAexRNA AtlasexRNA Portal

Identifiers

PMID26320941
PMCPMC4553261

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.