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A multitask transfer learning framework for the prediction of virus-human protein–protein interactions

Overview of attention for article published in BMC Bioinformatics, November 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
38 Mendeley
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Title
A multitask transfer learning framework for the prediction of virus-human protein–protein interactions
Published in
BMC Bioinformatics, November 2021
DOI 10.1186/s12859-021-04484-y
Pubmed ID
Authors

Thi Ngan Dong, Graham Brogden, Gisa Gerold, Megha Khosla

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 13%
Researcher 5 13%
Unspecified 2 5%
Student > Doctoral Student 2 5%
Student > Bachelor 2 5%
Other 4 11%
Unknown 18 47%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 13%
Computer Science 5 13%
Medicine and Dentistry 3 8%
Unspecified 2 5%
Agricultural and Biological Sciences 1 3%
Other 2 5%
Unknown 20 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 30 November 2021.
All research outputs
#8,131,204
of 25,097,836 outputs
Outputs from BMC Bioinformatics
#3,030
of 7,651 outputs
Outputs of similar age
#172,606
of 516,854 outputs
Outputs of similar age from BMC Bioinformatics
#69
of 171 outputs
Altmetric has tracked 25,097,836 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 7,651 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 58% 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 516,854 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 66% of its contemporaries.
We're also able to compare this research output to 171 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 57% of its contemporaries.