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Highly sensitive amplicon-based transcript quantification by semiconductor sequencing

Overview of attention for article published in BMC Genomics, July 2014
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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 (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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4 X users
patent
2 patents
wikipedia
1 Wikipedia page

Citations

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27 Dimensions

Readers on

mendeley
56 Mendeley
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Title
Highly sensitive amplicon-based transcript quantification by semiconductor sequencing
Published in
BMC Genomics, July 2014
DOI 10.1186/1471-2164-15-565
Pubmed ID
Authors

Jitao David Zhang, Tobias Schindler, Erich Küng, Martin Ebeling, Ulrich Certa

Abstract

In clinical and basic research custom panels for transcript profiling are gaining importance because only project specific informative genes are interrogated. This approach reduces costs and complexity of data analysis and allows multiplexing of samples. Polymerase-chain-reaction (PCR) based TaqMan assays have high sensitivity but suffer from a limited dynamic range and sample throughput. Hence, there is a gap for a technology able to measure expression of large gene sets in multiple samples.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Brazil 1 2%
South Africa 1 2%
Denmark 1 2%
Japan 1 2%
United States 1 2%
Unknown 50 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 32%
Student > Ph. D. Student 10 18%
Student > Bachelor 6 11%
Student > Master 6 11%
Student > Postgraduate 3 5%
Other 7 13%
Unknown 6 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 54%
Biochemistry, Genetics and Molecular Biology 11 20%
Medicine and Dentistry 2 4%
Engineering 2 4%
Physics and Astronomy 1 2%
Other 3 5%
Unknown 7 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 12 February 2020.
All research outputs
#3,725,418
of 22,758,248 outputs
Outputs from BMC Genomics
#1,484
of 10,637 outputs
Outputs of similar age
#37,053
of 227,325 outputs
Outputs of similar age from BMC Genomics
#24
of 189 outputs
Altmetric has tracked 22,758,248 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 85% 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 227,325 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 83% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.