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Understanding the causes of errors in eukaryotic protein-coding gene prediction: a case study of primate proteomes

Overview of attention for article published in BMC Bioinformatics, November 2020
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
9 X users

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Understanding the causes of errors in eukaryotic protein-coding gene prediction: a case study of primate proteomes
Published in
BMC Bioinformatics, November 2020
DOI 10.1186/s12859-020-03855-1
Pubmed ID
Authors

Corentin Meyer, Nicolas Scalzitti, Anne Jeannin-Girardon, Pierre Collet, Olivier Poch, Julie D. Thompson

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 26%
Student > Bachelor 3 11%
Student > Ph. D. Student 3 11%
Student > Postgraduate 2 7%
Student > Master 2 7%
Other 1 4%
Unknown 9 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 30%
Agricultural and Biological Sciences 4 15%
Computer Science 3 11%
Engineering 1 4%
Unknown 11 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 20 September 2023.
All research outputs
#6,787,528
of 25,169,746 outputs
Outputs from BMC Bioinformatics
#2,374
of 7,658 outputs
Outputs of similar age
#135,114
of 423,755 outputs
Outputs of similar age from BMC Bioinformatics
#55
of 162 outputs
Altmetric has tracked 25,169,746 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,658 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 68% 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 423,755 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 67% of its contemporaries.
We're also able to compare this research output to 162 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 66% of its contemporaries.