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Virtual terminator nucleotides for next-generation DNA sequencing

Overview of attention for article published in Nature Methods, July 2009
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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 (85th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

patent
30 patents
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
86 Dimensions

Readers on

mendeley
185 Mendeley
citeulike
4 CiteULike
connotea
2 Connotea
Title
Virtual terminator nucleotides for next-generation DNA sequencing
Published in
Nature Methods, July 2009
DOI 10.1038/nmeth.1354
Pubmed ID
Authors

Jayson Bowers, Judith Mitchell, Eric Beer, Philip R Buzby, Marie Causey, J William Efcavitch, Mirna Jarosz, Edyta Krzymanska-Olejnik, Li Kung, Doron Lipson, Geoffrey M Lowman, Subramanian Marappan, Peter McInerney, Adam Platt, Atanu Roy, Suhaib M Siddiqi, Kathleen Steinmann, John F Thompson

Abstract

We synthesized reversible terminators with tethered inhibitors for next-generation sequencing. These were efficiently incorporated with high fidelity while preventing incorporation of additional nucleotides, and we used them to sequence canine bacterial artificial chromosomes in a single-molecule system that provided even coverage for over 99% of the region sequenced. This single-molecule approach generated high-quality sequence data without the need for target amplification and thus avoided concomitant biases.

Mendeley readers

The data shown below were compiled from readership statistics for 185 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
United Kingdom 2 1%
Brazil 2 1%
India 2 1%
Italy 2 1%
Indonesia 1 <1%
Chile 1 <1%
Mexico 1 <1%
Finland 1 <1%
Other 7 4%
Unknown 162 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 28%
Researcher 48 26%
Student > Master 19 10%
Student > Bachelor 18 10%
Unspecified 10 5%
Other 38 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 92 50%
Biochemistry, Genetics and Molecular Biology 24 13%
Chemistry 14 8%
Medicine and Dentistry 12 6%
Unspecified 12 6%
Other 31 17%

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 29 September 2019.
All research outputs
#1,716,771
of 13,605,565 outputs
Outputs from Nature Methods
#1,801
of 3,838 outputs
Outputs of similar age
#39,820
of 282,128 outputs
Outputs of similar age from Nature Methods
#47
of 94 outputs
Altmetric has tracked 13,605,565 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,838 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.1. This one has gotten more attention than average, scoring higher than 51% 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 282,128 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 85% of its contemporaries.
We're also able to compare this research output to 94 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 50% of its contemporaries.