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Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome

Overview of attention for article published in Genome Biology, March 2020
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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 (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
49 X users

Citations

dimensions_citation
92 Dimensions

Readers on

mendeley
194 Mendeley
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Title
Avocado: a multi-scale deep tensor factorization method learns a latent representation of the human epigenome
Published in
Genome Biology, March 2020
DOI 10.1186/s13059-020-01977-6
Pubmed ID
Authors

Jacob Schreiber, Timothy Durham, Jeffrey Bilmes, William Stafford Noble

X Demographics

X Demographics

The data shown below were collected from the profiles of 49 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 194 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 194 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 57 29%
Researcher 38 20%
Student > Bachelor 18 9%
Student > Master 15 8%
Student > Doctoral Student 8 4%
Other 22 11%
Unknown 36 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 57 29%
Computer Science 39 20%
Agricultural and Biological Sciences 24 12%
Engineering 10 5%
Physics and Astronomy 5 3%
Other 17 9%
Unknown 42 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 05 January 2024.
All research outputs
#1,464,647
of 25,473,687 outputs
Outputs from Genome Biology
#1,166
of 4,480 outputs
Outputs of similar age
#38,171
of 395,848 outputs
Outputs of similar age from Genome Biology
#33
of 77 outputs
Altmetric has tracked 25,473,687 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,480 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 gotten more attention than average, scoring higher than 73% 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 395,848 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 90% of its contemporaries.
We're also able to compare this research output to 77 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 58% of its contemporaries.