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MSstatsTMT: Statistical detection of differentially abundant proteins in experiments with isobaric labeling and multiple mixtures

Overview of attention for article published in Molecular and Cellular Proteomics, July 2020
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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51 tweeters
Title
MSstatsTMT: Statistical detection of differentially abundant proteins in experiments with isobaric labeling and multiple mixtures
Published in
Molecular and Cellular Proteomics, July 2020
DOI 10.1074/mcp.ra120.002105
Pubmed ID
Authors

Ting Huang, Meena Choi, Manuel Tzouros, Sabrina Golling, Nikhil Janak Pandya, Balazs Banfai, Tom Dunkley, Olga Vitek

Twitter Demographics

The data shown below were collected from the profiles of 51 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 30 July 2020.
All research outputs
#666,404
of 15,606,535 outputs
Outputs from Molecular and Cellular Proteomics
#62
of 2,670 outputs
Outputs of similar age
#13,902
of 176,644 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#2
of 24 outputs
Altmetric has tracked 15,606,535 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 2,670 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one has done particularly well, scoring higher than 97% 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 176,644 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 92% of its contemporaries.
We're also able to compare this research output to 24 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 91% of its contemporaries.