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multiplierz: an extensible API based desktop environment for proteomics data analysis

Overview of attention for article published in BMC Bioinformatics, October 2009
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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 (96th percentile)

Mentioned by

blogs
3 blogs
twitter
1 X user

Citations

dimensions_citation
64 Dimensions

Readers on

mendeley
49 Mendeley
citeulike
4 CiteULike
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Title
multiplierz: an extensible API based desktop environment for proteomics data analysis
Published in
BMC Bioinformatics, October 2009
DOI 10.1186/1471-2105-10-364
Pubmed ID
Authors

Jignesh R Parikh, Manor Askenazi, Scott B Ficarro, Tanya Cashorali, James T Webber, Nathaniel C Blank, Yi Zhang, Jarrod A Marto

Abstract

Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge.

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

Geographical breakdown

Country Count As %
United States 1 2%
Russia 1 2%
Italy 1 2%
Austria 1 2%
Unknown 45 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 27%
Researcher 12 24%
Other 5 10%
Professor > Associate Professor 5 10%
Student > Bachelor 3 6%
Other 6 12%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 39%
Chemistry 7 14%
Biochemistry, Genetics and Molecular Biology 6 12%
Computer Science 5 10%
Engineering 5 10%
Other 2 4%
Unknown 5 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 04 September 2017.
All research outputs
#1,442,485
of 22,708,120 outputs
Outputs from BMC Bioinformatics
#264
of 7,256 outputs
Outputs of similar age
#4,344
of 94,165 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 64 outputs
Altmetric has tracked 22,708,120 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 7,256 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 96% 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 94,165 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 64 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 96% of its contemporaries.