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Estimation of sequencing error rates in short reads

Overview of attention for article published in BMC Bioinformatics, January 2012
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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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

blogs
1 blog
twitter
8 tweeters
q&a
1 Q&A thread

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
178 Mendeley
citeulike
9 CiteULike
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Title
Estimation of sequencing error rates in short reads
Published in
BMC Bioinformatics, January 2012
DOI 10.1186/1471-2105-13-185
Pubmed ID
Authors

Xin Victoria, Natalie Blades, Jie Ding, Razvan Sultana, Giovanni Parmigiani

Abstract

Short-read data from next-generation sequencing technologies are now being generated across a range of research projects. The fidelity of this data can be affected by several factors and it is important to have simple and reliable approaches for monitoring it at the level of individual experiments.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 5%
United Kingdom 5 3%
Spain 2 1%
Sweden 2 1%
Germany 2 1%
India 1 <1%
Brazil 1 <1%
Australia 1 <1%
Poland 1 <1%
Other 0 0%
Unknown 154 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 53 30%
Researcher 38 21%
Student > Master 23 13%
Student > Bachelor 15 8%
Professor > Associate Professor 11 6%
Other 34 19%
Unknown 4 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 95 53%
Biochemistry, Genetics and Molecular Biology 30 17%
Computer Science 28 16%
Mathematics 7 4%
Environmental Science 3 2%
Other 9 5%
Unknown 6 3%

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 06 July 2016.
All research outputs
#1,011,202
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#374
of 4,576 outputs
Outputs of similar age
#10,030
of 121,368 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 36 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. 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 121,368 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 91% of its contemporaries.
We're also able to compare this research output to 36 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 94% of its contemporaries.