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Decreasing miRNA sequencing bias using a single adapter and circularization approach

Overview of attention for article published in Genome Biology, September 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
24 news outlets
twitter
15 X users
patent
6 patents

Citations

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51 Dimensions

Readers on

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101 Mendeley
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Title
Decreasing miRNA sequencing bias using a single adapter and circularization approach
Published in
Genome Biology, September 2018
DOI 10.1186/s13059-018-1488-z
Pubmed ID
Authors

Sergio Barberán-Soler, Jenny M. Vo, Ryan E. Hogans, Anne Dallas, Brian H. Johnston, Sergei A. Kazakov

Abstract

The ability to accurately quantify all the microRNAs (miRNAs) in a sample is important for understanding miRNA biology and for development of new biomarkers and therapeutic targets. We develop a new method for preparing miRNA sequencing libraries, RealSeq®-AC, that involves ligating the miRNAs with a single adapter and circularizing the ligation products. When compared to other methods, RealSeq®-AC provides greatly reduced miRNA sequencing bias and allows the identification of the largest variety of miRNAs in biological samples. This reduced bias also allows robust quantification of miRNAs present in samples across a wide range of RNA input levels.

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 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 101 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 28 28%
Student > Ph. D. Student 20 20%
Student > Bachelor 10 10%
Student > Master 6 6%
Other 4 4%
Other 9 9%
Unknown 24 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 32 32%
Agricultural and Biological Sciences 21 21%
Chemistry 6 6%
Medicine and Dentistry 5 5%
Neuroscience 3 3%
Other 9 9%
Unknown 25 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 206. 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 25 June 2023.
All research outputs
#190,165
of 25,385,509 outputs
Outputs from Genome Biology
#53
of 4,468 outputs
Outputs of similar age
#3,830
of 345,580 outputs
Outputs of similar age from Genome Biology
#2
of 71 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done particularly well, scoring higher than 98% 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 345,580 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 71 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 97% of its contemporaries.