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SMILE: systems metabolomics using interpretable learning and evolution

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

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
13 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
44 Mendeley
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Title
SMILE: systems metabolomics using interpretable learning and evolution
Published in
BMC Bioinformatics, May 2021
DOI 10.1186/s12859-021-04209-1
Pubmed ID
Authors

Chengyuan Sha, Miroslava Cuperlovic-Culf, Ting Hu

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 16%
Student > Master 5 11%
Researcher 4 9%
Unspecified 3 7%
Student > Bachelor 2 5%
Other 7 16%
Unknown 16 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 14%
Computer Science 5 11%
Engineering 4 9%
Unspecified 3 7%
Business, Management and Accounting 1 2%
Other 7 16%
Unknown 18 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 04 June 2022.
All research outputs
#6,744,715
of 25,390,970 outputs
Outputs from BMC Bioinformatics
#2,326
of 7,689 outputs
Outputs of similar age
#133,652
of 442,094 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 179 outputs
Altmetric has tracked 25,390,970 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,689 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 69% 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 442,094 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 69% of its contemporaries.
We're also able to compare this research output to 179 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 72% of its contemporaries.