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Application of an interpretable classification model on Early Folding Residues during protein folding

Overview of attention for article published in BioData Mining, January 2019
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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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19 Dimensions

Readers on

mendeley
38 Mendeley
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Title
Application of an interpretable classification model on Early Folding Residues during protein folding
Published in
BioData Mining, January 2019
DOI 10.1186/s13040-018-0188-2
Pubmed ID
Authors

Sebastian Bittrich, Marika Kaden, Christoph Leberecht, Florian Kaiser, Thomas Villmann, Dirk Labudde

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 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 %
Unspecified 10 26%
Student > Master 8 21%
Student > Ph. D. Student 3 8%
Student > Bachelor 2 5%
Researcher 2 5%
Other 2 5%
Unknown 11 29%
Readers by discipline Count As %
Unspecified 10 26%
Computer Science 9 24%
Engineering 5 13%
Mathematics 1 3%
Chemistry 1 3%
Other 1 3%
Unknown 11 29%
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 10 January 2019.
All research outputs
#13,945,718
of 23,122,481 outputs
Outputs from BioData Mining
#196
of 310 outputs
Outputs of similar age
#222,190
of 435,934 outputs
Outputs of similar age from BioData Mining
#5
of 7 outputs
Altmetric has tracked 23,122,481 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 310 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 36th percentile – i.e., 36% 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 435,934 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.