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Quantitative mass spectrometry in proteomics: a critical review

Overview of attention for article published in Analytical & Bioanalytical Chemistry, August 2007
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
1 X user
patent
48 patents
wikipedia
5 Wikipedia pages

Citations

dimensions_citation
1349 Dimensions

Readers on

mendeley
2376 Mendeley
citeulike
13 CiteULike
connotea
2 Connotea
Title
Quantitative mass spectrometry in proteomics: a critical review
Published in
Analytical & Bioanalytical Chemistry, August 2007
DOI 10.1007/s00216-007-1486-6
Pubmed ID
Authors

Marcus Bantscheff, Markus Schirle, Gavain Sweetman, Jens Rick, Bernhard Kuster

Abstract

The quantification of differences between two or more physiological states of a biological system is among the most important but also most challenging technical tasks in proteomics. In addition to the classical methods of differential protein gel or blot staining by dyes and fluorophores, mass-spectrometry-based quantification methods have gained increasing popularity over the past five years. Most of these methods employ differential stable isotope labeling to create a specific mass tag that can be recognized by a mass spectrometer and at the same time provide the basis for quantification. These mass tags can be introduced into proteins or peptides (i) metabolically, (ii) by chemical means, (iii) enzymatically, or (iv) provided by spiked synthetic peptide standards. In contrast, label-free quantification approaches aim to correlate the mass spectrometric signal of intact proteolytic peptides or the number of peptide sequencing events with the relative or absolute protein quantity directly. In this review, we critically examine the more commonly used quantitative mass spectrometry methods for their individual merits and discuss challenges in arriving at meaningful interpretations of quantitative proteomic data.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 2,376 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 35 1%
Germany 27 1%
United Kingdom 22 <1%
Sweden 6 <1%
Netherlands 5 <1%
France 5 <1%
South Africa 5 <1%
Canada 4 <1%
India 4 <1%
Other 50 2%
Unknown 2213 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 748 31%
Researcher 380 16%
Student > Master 333 14%
Student > Bachelor 241 10%
Student > Doctoral Student 115 5%
Other 257 11%
Unknown 302 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 824 35%
Biochemistry, Genetics and Molecular Biology 475 20%
Chemistry 291 12%
Medicine and Dentistry 85 4%
Engineering 56 2%
Other 278 12%
Unknown 367 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 14 November 2023.
All research outputs
#1,633,633
of 25,837,817 outputs
Outputs from Analytical & Bioanalytical Chemistry
#87
of 9,764 outputs
Outputs of similar age
#2,942
of 77,167 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#1
of 53 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,764 research outputs from this source. They receive a mean Attention Score of 3.2. This one has done particularly well, scoring higher than 98% 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 77,167 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 95% of its contemporaries.
We're also able to compare this research output to 53 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 98% of its contemporaries.