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JRC GMO-Matrix: a web application to support Genetically Modified Organisms detection strategies

Overview of attention for article published in BMC Bioinformatics, December 2014
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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3 tweeters

Citations

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30 Dimensions

Readers on

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44 Mendeley
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1 CiteULike
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Title
JRC GMO-Matrix: a web application to support Genetically Modified Organisms detection strategies
Published in
BMC Bioinformatics, December 2014
DOI 10.1186/s12859-014-0417-8
Pubmed ID
Authors

Alexandre Angers-Loustau, Mauro Petrillo, Laura Bonfini, Francesco Gatto, Sabrina Rosa, Alexandre Patak, Joachim Kreysa

Abstract

BackgroundThe polymerase chain reaction (PCR) is the current state of the art technique for DNA-based detection of Genetically Modified Organisms (GMOs). A typical control strategy starts by analyzing a sample for the presence of target sequences (GM-elements) known to be present in many GMOs. Positive findings from this ¿screening¿ are then confirmed with GM (event) specific test methods. A reliable knowledge of which GMOs are detected by combination of GM-detection methods is thus crucial to minimize the verification efforts.DescriptionIn this article, we describe a novel platform that links the information of two unique databases built and maintained by the European Union Reference Laboratory for Genetically Modified Food and Feed (EU-RL GMFF) at the Joint Research Centre (JRC) of the European Commission, one containing the sequence information of known GM-events and the other validated PCR-based detection and identification methods. The new platform compiles in silico determinations of the detection of a wide range of GMOs by the available detection methods using existing scripts that simulate PCR amplification and, when present, probe binding. The correctness of the information has been verified by comparing the in silico conclusions to experimental results for a subset of forty-nine GM events and six methods.ConclusionsThe JRC GMO-Matrix is unique for its reliance on DNA sequence data and its flexibility in integrating novel GMOs and new detection methods. Users can mine the database using a set of web interfaces that thus provide a valuable support to GMO control laboratories in planning and evaluating their GMO screening strategies. The platform is accessible at http://gmo-crl.jrc.ec.europa.eu/jrcgmomatrix/

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 30%
Student > Bachelor 10 23%
Student > Ph. D. Student 5 11%
Other 2 5%
Student > Master 2 5%
Other 2 5%
Unknown 10 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 39%
Biochemistry, Genetics and Molecular Biology 9 20%
Nursing and Health Professions 1 2%
Environmental Science 1 2%
Computer Science 1 2%
Other 4 9%
Unknown 11 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 January 2015.
All research outputs
#2,096,207
of 4,691,823 outputs
Outputs from BMC Bioinformatics
#1,600
of 2,706 outputs
Outputs of similar age
#64,718
of 155,197 outputs
Outputs of similar age from BMC Bioinformatics
#86
of 150 outputs
Altmetric has tracked 4,691,823 research outputs across all sources so far. This one has received more attention than most of these and is in the 52nd percentile.
So far Altmetric has tracked 2,706 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 36th percentile – i.e., 36% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 155,197 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.