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Pairwise efficiency: a new mathematical approach to qPCR data analysis increases the precision of the calibration curve assay

Overview of attention for article published in BMC Bioinformatics, May 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
1 news outlet
twitter
15 X users
facebook
2 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
54 Mendeley
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Title
Pairwise efficiency: a new mathematical approach to qPCR data analysis increases the precision of the calibration curve assay
Published in
BMC Bioinformatics, May 2019
DOI 10.1186/s12859-019-2911-5
Pubmed ID
Authors

Yulia Panina, Arno Germond, Brit G. David, Tomonobu M. Watanabe

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 20%
Student > Ph. D. Student 8 15%
Student > Doctoral Student 6 11%
Student > Master 6 11%
Student > Bachelor 5 9%
Other 4 7%
Unknown 14 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 24%
Biochemistry, Genetics and Molecular Biology 11 20%
Medicine and Dentistry 3 6%
Engineering 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 4 7%
Unknown 20 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 16 October 2020.
All research outputs
#2,097,847
of 24,995,564 outputs
Outputs from BMC Bioinformatics
#484
of 7,628 outputs
Outputs of similar age
#44,115
of 356,293 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 204 outputs
Altmetric has tracked 24,995,564 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,628 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 93% of its peers.
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 356,293 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 204 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.