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Erratum to: DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning

Overview of attention for article published in Genome Biology, May 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
6 news outlets
twitter
1 X user

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
13 Mendeley
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Title
Erratum to: DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning
Published in
Genome Biology, May 2017
DOI 10.1186/s13059-017-1233-z
Pubmed ID
Authors

Christof Angermueller, Heather J. Lee, Wolf Reik, Oliver Stegle

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 31%
Student > Master 2 15%
Researcher 2 15%
Professor 1 8%
Student > Ph. D. Student 1 8%
Other 0 0%
Unknown 3 23%
Readers by discipline Count As %
Unspecified 4 31%
Computer Science 3 23%
Biochemistry, Genetics and Molecular Biology 1 8%
Agricultural and Biological Sciences 1 8%
Unknown 4 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 52. 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 17 May 2017.
All research outputs
#814,852
of 25,382,440 outputs
Outputs from Genome Biology
#540
of 4,468 outputs
Outputs of similar age
#16,606
of 324,616 outputs
Outputs of similar age from Genome Biology
#14
of 65 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 87% 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 324,616 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 94% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.