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Probabilistic model applied to ion abundances in product-ion spectra: quantitative analysis of aspartic acid isomerization in peptides

Overview of attention for article published in Analytical & Bioanalytical Chemistry, November 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
2 X users
patent
1 patent

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
10 Mendeley
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Title
Probabilistic model applied to ion abundances in product-ion spectra: quantitative analysis of aspartic acid isomerization in peptides
Published in
Analytical & Bioanalytical Chemistry, November 2019
DOI 10.1007/s00216-019-02174-6
Pubmed ID
Authors

Daniil G. Ivanov, Maria I. Indeykina, Stanislav I. Pekov, Adel E. Iusupov, Anna E. Bugrova, Alexey S. Kononikhin, Eugene N. Nikolaev, Igor A. Popov

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

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 20%
Student > Master 2 20%
Student > Doctoral Student 1 10%
Lecturer 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 3 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 30%
Chemistry 2 20%
Physics and Astronomy 1 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 10%
Unknown 3 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 07 April 2022.
All research outputs
#7,994,699
of 25,462,162 outputs
Outputs from Analytical & Bioanalytical Chemistry
#1,867
of 9,646 outputs
Outputs of similar age
#140,265
of 380,517 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#29
of 158 outputs
Altmetric has tracked 25,462,162 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 9,646 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 79% 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 380,517 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 62% of its contemporaries.
We're also able to compare this research output to 158 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.