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Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics

Overview of attention for article published in Nature Communications, June 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

twitter
56 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
31 Mendeley
Title
Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics
Published in
Nature Communications, June 2021
DOI 10.1038/s41467-021-23713-9
Pubmed ID
Authors

Mathias Wilhelm, Daniel P. Zolg, Michael Graber, Siegfried Gessulat, Tobias Schmidt, Karsten Schnatbaum, Celina Schwencke-Westphal, Philipp Seifert, Niklas de Andrade Krätzig, Johannes Zerweck, Tobias Knaute, Eva Bräunlein, Patroklos Samaras, Ludwig Lautenbacher, Susan Klaeger, Holger Wenschuh, Roland Rad, Bernard Delanghe, Andreas Huhmer, Steven A. Carr, Karl R. Clauser, Angela M. Krackhardt, Ulf Reimer, Bernhard Kuster

Twitter Demographics

The data shown below were collected from the profiles of 56 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 26%
Researcher 6 19%
Student > Bachelor 3 10%
Student > Master 3 10%
Student > Postgraduate 2 6%
Other 4 13%
Unknown 5 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 35%
Immunology and Microbiology 4 13%
Agricultural and Biological Sciences 3 10%
Engineering 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 5 16%
Unknown 4 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 31. 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 02 July 2021.
All research outputs
#869,443
of 18,883,809 outputs
Outputs from Nature Communications
#13,319
of 37,394 outputs
Outputs of similar age
#23,194
of 339,877 outputs
Outputs of similar age from Nature Communications
#1
of 2 outputs
Altmetric has tracked 18,883,809 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 37,394 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 53.2. This one has gotten more attention than average, scoring higher than 64% 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 339,877 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 93% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them