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In silico proteome analysis to facilitate proteomics experiments using mass spectrometry

Overview of attention for article published in Proteome Science, August 2003
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About this Attention Score

  • Among the highest-scoring outputs from this source (#36 of 208)
  • Good Attention Score compared to outputs of the same age (66th percentile)

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1 X user
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1 patent

Citations

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85 Dimensions

Readers on

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106 Mendeley
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1 Connotea
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Title
In silico proteome analysis to facilitate proteomics experiments using mass spectrometry
Published in
Proteome Science, August 2003
DOI 10.1186/1477-5956-1-5
Pubmed ID
Authors

Gerard Cagney, Shiva Amiri, Thanuja Premawaradena, Micheal Lindo, Andrew Emili

Abstract

Proteomics experiments typically involve protein or peptide separation steps coupled to the identification of many hundreds to thousands of peptides by mass spectrometry. Development of methodology and instrumentation in this field is proceeding rapidly, and effective software is needed to link the different stages of proteomic analysis. We have developed an application, proteogest, written in Perl that generates descriptive and statistical analyses of the biophysical properties of multiple (e.g. thousands) protein sequences submitted by the user, for instance protein sequences inferred from the complete genome sequence of a model organism. The application also carries out in silico proteolytic digestion of the submitted proteomes, or subsets thereof, and the distribution of biophysical properties of the resulting peptides is presented. proteogest is customizable, the user being able to select many options, for instance the cleavage pattern of the digestion treatment or the presence of modifications to specific amino acid residues. We show how proteogest can be used to compare the proteomes and digested proteome products of model organisms, to examine the added complexity generated by modification of residues, and to facilitate the design of proteomics experiments for optimal representation of component proteins.

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

Geographical breakdown

Country Count As %
Switzerland 1 <1%
Netherlands 1 <1%
France 1 <1%
Brazil 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Croatia 1 <1%
Unknown 99 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 24%
Student > Ph. D. Student 23 22%
Student > Master 13 12%
Professor 7 7%
Student > Bachelor 6 6%
Other 15 14%
Unknown 17 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 43%
Biochemistry, Genetics and Molecular Biology 20 19%
Chemistry 10 9%
Medicine and Dentistry 4 4%
Computer Science 4 4%
Other 4 4%
Unknown 18 17%
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 06 June 2017.
All research outputs
#7,363,939
of 25,394,764 outputs
Outputs from Proteome Science
#36
of 208 outputs
Outputs of similar age
#16,902
of 53,446 outputs
Outputs of similar age from Proteome Science
#1
of 1 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 208 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done well, scoring higher than 82% 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 53,446 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 66% of its contemporaries.
We're also able to compare this research output to 1 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