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Automated feature engineering improves prediction of protein–protein interactions

Overview of attention for article published in Amino Acids, July 2019
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Mentioned by

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2 X users

Citations

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19 Dimensions

Readers on

mendeley
36 Mendeley
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Title
Automated feature engineering improves prediction of protein–protein interactions
Published in
Amino Acids, July 2019
DOI 10.1007/s00726-019-02756-9
Pubmed ID
Authors

Neven Sumonja, Branislava Gemovic, Nevena Veljkovic, Vladimir Perovic

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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 22%
Researcher 7 19%
Student > Bachelor 5 14%
Student > Master 4 11%
Student > Doctoral Student 3 8%
Other 1 3%
Unknown 8 22%
Readers by discipline Count As %
Computer Science 7 19%
Biochemistry, Genetics and Molecular Biology 5 14%
Mathematics 2 6%
Agricultural and Biological Sciences 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 6 17%
Unknown 12 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 July 2019.
All research outputs
#18,024,509
of 23,151,828 outputs
Outputs from Amino Acids
#1,121
of 1,531 outputs
Outputs of similar age
#243,063
of 347,684 outputs
Outputs of similar age from Amino Acids
#4
of 7 outputs
Altmetric has tracked 23,151,828 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,531 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 23rd percentile – i.e., 23% 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 347,684 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% 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 3 of them.