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Automated reduction and interpretation of

Overview of attention for article published in Journal of the American Society for Mass Spectrometry, April 2000
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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4 X users
patent
14 patents

Citations

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510 Dimensions

Readers on

mendeley
167 Mendeley
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1 CiteULike
Title
Automated reduction and interpretation of
Published in
Journal of the American Society for Mass Spectrometry, April 2000
DOI 10.1016/s1044-0305(99)00157-9
Pubmed ID
Authors

David M. Horn, Roman A. Zubarev, Fred W. McLafferty

Abstract

Here a fully automated computer algorithm is applied to complex mass spectra of peptides and proteins. This method uses a subtractive peak finding routine to locate possible isotopic clusters in the spectrum, subjecting these to a combination of the previous Fourier transform/Patterson method for primary charge determination and the method for least-squares fitting to a theoretically derived isotopic abundance distribution for m/z determination of the most abundant isotopic peak, and the statistical reliability of this determination. If a predicted protein sequence is available, each such m/z value is checked for assignment as a sequence fragment. A new signal-to-noise calculation procedure has been devised for accurate determination of baseline and noise width for spectra with high peak density. In 2 h, the program identified 824 isotopic clusters representing 581 mass values in the spectrum of a GluC digest of a 191 kDa protein; this is >50% more than the number of mass values found by the extremely tedious operator-applied methodology used previously. The program should be generally applicable to classes of large molecules, including DNA and polymers. Thorough high resolution analysis of spectra by Horn (THRASH) is proposed as the program's verb.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Netherlands 1 <1%
Belgium 1 <1%
United Kingdom 1 <1%
Russia 1 <1%
Poland 1 <1%
Unknown 159 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 31%
Researcher 42 25%
Student > Master 15 9%
Student > Doctoral Student 11 7%
Student > Bachelor 10 6%
Other 21 13%
Unknown 16 10%
Readers by discipline Count As %
Chemistry 49 29%
Agricultural and Biological Sciences 41 25%
Biochemistry, Genetics and Molecular Biology 20 12%
Computer Science 16 10%
Engineering 4 2%
Other 16 10%
Unknown 21 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 19 February 2022.
All research outputs
#3,138,657
of 25,374,647 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#169
of 3,834 outputs
Outputs of similar age
#3,113
of 40,972 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#1
of 10 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,834 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 95% 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 40,972 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 10 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