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SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing

Overview of attention for article published in BMC Genomics, August 2014
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
32 Mendeley
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Title
SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing
Published in
BMC Genomics, August 2014
DOI 10.1186/1471-2164-15-664
Pubmed ID
Authors

Yukuto Sato, Kaname Kojima, Naoki Nariai, Yumi Yamaguchi-Kabata, Yosuke Kawai, Mamoru Takahashi, Takahiro Mimori, Masao Nagasaki

Abstract

Next-generation sequencers (NGSs) have become one of the main tools for current biology. To obtain useful insights from the NGS data, it is essential to control low-quality portions of the data affected by technical errors such as air bubbles in sequencing fluidics.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
United Kingdom 1 3%
Sweden 1 3%
France 1 3%
Unknown 28 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 25%
Student > Ph. D. Student 5 16%
Other 4 13%
Student > Master 4 13%
Student > Bachelor 1 3%
Other 5 16%
Unknown 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 47%
Biochemistry, Genetics and Molecular Biology 6 19%
Environmental Science 2 6%
Unspecified 1 3%
Psychology 1 3%
Other 2 6%
Unknown 5 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 24 August 2014.
All research outputs
#13,410,980
of 22,759,618 outputs
Outputs from BMC Genomics
#4,987
of 10,637 outputs
Outputs of similar age
#109,648
of 230,503 outputs
Outputs of similar age from BMC Genomics
#75
of 186 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 50% 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 230,503 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 186 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 57% of its contemporaries.