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Estimating sequencing error rates using families

Overview of attention for article published in BioData Mining, April 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Estimating sequencing error rates using families
Published in
BioData Mining, April 2021
DOI 10.1186/s13040-021-00259-6
Pubmed ID
Authors

Kelley Paskov, Jae-Yoon Jung, Brianna Chrisman, Nate T. Stockham, Peter Washington, Maya Varma, Min Woo Sun, Dennis P. Wall

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Student > Doctoral Student 1 14%
Other 1 14%
Student > Bachelor 1 14%
Researcher 1 14%
Other 0 0%
Unknown 1 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 29%
Mathematics 1 14%
Medicine and Dentistry 1 14%
Neuroscience 1 14%
Engineering 1 14%
Other 0 0%
Unknown 1 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 14 May 2021.
All research outputs
#14,219,854
of 21,172,126 outputs
Outputs from BioData Mining
#220
of 298 outputs
Outputs of similar age
#204,380
of 342,788 outputs
Outputs of similar age from BioData Mining
#1
of 1 outputs
Altmetric has tracked 21,172,126 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 298 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 20th percentile – i.e., 20% 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 342,788 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them