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Automated peptide mapping and protein-topographical annotation of proteomics data

Overview of attention for article published in BMC Bioinformatics, June 2014
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Mentioned by

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2 tweeters

Citations

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8 Dimensions

Readers on

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23 Mendeley
Summary Twitter Dimensions citations
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Title
Automated peptide mapping and protein-topographical annotation of proteomics data
Published in
BMC Bioinformatics, June 2014
DOI 10.1186/1471-2105-15-207
Pubmed ID
24946880
Authors

Pavankumar Videm, Deepika Gunasekaran, Bernd Schröder, Bettina Mayer, Martin L Biniossek, Oliver Schilling

Abstract

In quantitative proteomics, peptide mapping is a valuable approach to combine positional quantitative information with topographical and domain information of proteins. Quantitative proteomic analysis of cell surface shedding is an exemplary application area of this approach.

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Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 30%
Student > Ph. D. Student 6 26%
Student > Bachelor 4 17%
Student > Master 2 9%
Other 1 4%
Other 2 9%
Unknown 1 4%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 39%
Computer Science 5 22%
Chemistry 2 9%
Engineering 2 9%
Neuroscience 1 4%
Other 3 13%
Unknown 1 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 November 2014.
All research outputs
#17,722,431
of 22,757,541 outputs
Outputs from BMC Bioinformatics
#5,926
of 7,272 outputs
Outputs of similar age
#155,696
of 228,247 outputs
Outputs of similar age from BMC Bioinformatics
#106
of 155 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,272 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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 228,247 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.

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