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MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra

Overview of attention for article published in Journal of Cheminformatics, October 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

twitter
34 X users

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
123 Mendeley
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Title
MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra
Published in
Journal of Cheminformatics, October 2021
DOI 10.1186/s13321-021-00558-4
Pubmed ID
Authors

Florian Huber, Sven van der Burg, Justin J. J. van der Hooft, Lars Ridder

X Demographics

X Demographics

The data shown below were collected from the profiles of 34 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 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 123 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 15%
Researcher 18 15%
Student > Bachelor 11 9%
Student > Master 10 8%
Unspecified 8 7%
Other 12 10%
Unknown 45 37%
Readers by discipline Count As %
Chemistry 19 15%
Biochemistry, Genetics and Molecular Biology 9 7%
Unspecified 8 7%
Agricultural and Biological Sciences 7 6%
Computer Science 6 5%
Other 21 17%
Unknown 53 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 18 November 2021.
All research outputs
#1,921,393
of 25,163,238 outputs
Outputs from Journal of Cheminformatics
#154
of 946 outputs
Outputs of similar age
#43,361
of 435,222 outputs
Outputs of similar age from Journal of Cheminformatics
#4
of 33 outputs
Altmetric has tracked 25,163,238 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 946 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has done well, scoring higher than 83% 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 435,222 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.