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Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT

Overview of attention for article published in BMC Bioinformatics, January 2022
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users

Citations

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3 Dimensions

Readers on

mendeley
27 Mendeley
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Title
Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT
Published in
BMC Bioinformatics, January 2022
DOI 10.1186/s12859-021-04504-x
Pubmed ID
Authors

Aparna Elangovan, Yuan Li, Douglas E. V. Pires, Melissa J. Davis, Karin Verspoor

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 2 7%
Student > Ph. D. Student 2 7%
Other 1 4%
Lecturer 1 4%
Unspecified 1 4%
Other 3 11%
Unknown 17 63%
Readers by discipline Count As %
Computer Science 7 26%
Unspecified 1 4%
Business, Management and Accounting 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Unknown 17 63%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 September 2022.
All research outputs
#15,377,308
of 23,622,736 outputs
Outputs from BMC Bioinformatics
#5,143
of 7,410 outputs
Outputs of similar age
#268,569
of 514,094 outputs
Outputs of similar age from BMC Bioinformatics
#109
of 140 outputs
Altmetric has tracked 23,622,736 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,410 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% 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 514,094 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 140 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.