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Improved workflows for high throughput library preparation using the transposome-based nextera system

Overview of attention for article published in BMC Biotechnology, November 2013
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

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7 X users
patent
50 patents

Citations

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141 Dimensions

Readers on

mendeley
246 Mendeley
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Title
Improved workflows for high throughput library preparation using the transposome-based nextera system
Published in
BMC Biotechnology, November 2013
DOI 10.1186/1472-6750-13-104
Pubmed ID
Authors

Sarah Lamble, Elizabeth Batty, Moustafa Attar, David Buck, Rory Bowden, Gerton Lunter, Derrick Crook, Bassam El-Fahmawi, Paolo Piazza

Abstract

The Nextera protocol, which utilises a transposome based approach to create libraries for Illumina sequencing, requires pure DNA template, an accurate assessment of input concentration and a column clean-up that limits its applicability for high-throughput sample preparation. We addressed the identified limitations to develop a robust workflow that supports both rapid and high-throughput projects also reducing reagent costs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 246 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 3 1%
Sweden 2 <1%
Chile 1 <1%
Ireland 1 <1%
France 1 <1%
Belgium 1 <1%
Argentina 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 229 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 65 26%
Student > Ph. D. Student 50 20%
Student > Master 22 9%
Student > Bachelor 21 9%
Other 14 6%
Other 46 19%
Unknown 28 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 116 47%
Biochemistry, Genetics and Molecular Biology 40 16%
Immunology and Microbiology 13 5%
Medicine and Dentistry 11 4%
Engineering 8 3%
Other 22 9%
Unknown 36 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 January 2024.
All research outputs
#2,632,879
of 24,527,858 outputs
Outputs from BMC Biotechnology
#72
of 964 outputs
Outputs of similar age
#29,732
of 312,867 outputs
Outputs of similar age from BMC Biotechnology
#2
of 18 outputs
Altmetric has tracked 24,527,858 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 964 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done particularly well, scoring higher than 92% 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 312,867 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 90% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.