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Mendeley readers
Attention Score in Context
| Title |
A statistical approach to quantification of genetically modified organisms (GMO) using frequency distributions
|
|---|---|
| Published in |
BMC Bioinformatics, December 2014
|
| DOI | 10.1186/s12859-014-0407-x |
| Pubmed ID | |
| Authors |
Lars Gerdes, Ulrich Busch, Sven Pecoraro |
| Abstract |
BackgroundAccording to Regulation (EU) No 619/2011, trace amounts of non-authorised genetically modified organisms (GMO) in feed are tolerated within the EU if certain prerequisites are met. Tolerable traces must not exceed the so-called `minimum required performance limit¿ (MRPL), which was defined according to the mentioned regulation to correspond to 0.1% mass fraction per ingredient. Therefore, not yet authorised GMO (and some GMO whose approvals have expired) have to be quantified at very low level following the qualitative detection in genomic DNA extracted from feed samples. As the results of quantitative analysis can imply severe legal and financial consequences for producers or distributors of feed, the quantification results need to be utterly reliable.ResultsWe developed a statistical approach to investigate the experimental measurement variability within one 96-well PCR plate. This approach visualises the frequency distribution as zygosity-corrected relative content of genetically modified material resulting from different combinations of transgene and reference gene Cq values. One application of it is the simulation of the consequences of varying parameters on measurement results. Parameters could be for example replicate numbers or baseline and threshold settings, measurement results could be for example median (class) and relative standard deviation (RSD). All calculations can be done using the built-in functions of Excel without any need for programming. The developed Excel spreadsheets are available (see section `Availability of supporting data¿ for details). In most cases, the combination of four PCR replicates for each of the two DNA isolations already resulted in a relative standard deviation of 15% or less.ConclusionsThe aims of the study are scientifically based suggestions for minimisation of uncertainty of measurement especially in ¿but not limited to¿ the field of GMO quantification at low concentration levels. Four PCR replicates for each of the two DNA isolations seem to be a reasonable minimum number to narrow down the possible spread of results. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Norway | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Members of the public | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 4% |
| Russia | 1 | 4% |
| Singapore | 1 | 4% |
| Unknown | 21 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 29% |
| Student > Ph. D. Student | 5 | 21% |
| Student > Bachelor | 3 | 13% |
| Student > Master | 3 | 13% |
| Lecturer | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 4 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 38% |
| Social Sciences | 4 | 17% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Computer Science | 1 | 4% |
| Arts and Humanities | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 5 | 21% |
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 23 December 2014.
All research outputs
#13,418,483
of 22,774,233 outputs
Outputs from BMC Bioinformatics
#4,192
of 7,276 outputs
Outputs of similar age
#174,171
of 354,985 outputs
Outputs of similar age from BMC Bioinformatics
#66
of 152 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,276 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 38th percentile – i.e., 38% 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 354,985 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 152 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.