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NGmerge: merging paired-end reads via novel empirically-derived models of sequencing errors

Overview of attention for article published in BMC Bioinformatics, December 2018
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  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
31 Mendeley
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Title
NGmerge: merging paired-end reads via novel empirically-derived models of sequencing errors
Published in
BMC Bioinformatics, December 2018
DOI 10.1186/s12859-018-2579-2
Pubmed ID
Authors

John M. Gaspar

Twitter Demographics

The data shown below were collected from the profiles of 5 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 39%
Student > Ph. D. Student 7 23%
Student > Bachelor 4 13%
Student > Master 4 13%
Student > Doctoral Student 2 6%
Other 1 3%
Unknown 1 3%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 48%
Agricultural and Biological Sciences 8 26%
Environmental Science 1 3%
Computer Science 1 3%
Neuroscience 1 3%
Other 0 0%
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 02 April 2020.
All research outputs
#8,398,693
of 14,794,860 outputs
Outputs from BMC Bioinformatics
#3,175
of 5,491 outputs
Outputs of similar age
#187,140
of 377,266 outputs
Outputs of similar age from BMC Bioinformatics
#219
of 414 outputs
Altmetric has tracked 14,794,860 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,491 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 377,266 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 414 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.