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MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

Overview of attention for article published in BMC Bioinformatics, July 2010
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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 (91st percentile)

Mentioned by

blogs
1 blog
twitter
4 tweeters
patent
2 patents

Citations

dimensions_citation
2550 Dimensions

Readers on

mendeley
1811 Mendeley
citeulike
7 CiteULike
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Title
MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
Published in
BMC Bioinformatics, July 2010
DOI 10.1186/1471-2105-11-395
Pubmed ID
Authors

Tomáš Pluskal, Sandra Castillo, Alejandro Villar-Briones, Matej Orešič

Abstract

Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 1,811 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 <1%
Germany 6 <1%
Brazil 5 <1%
Switzerland 4 <1%
Denmark 4 <1%
Netherlands 3 <1%
United Kingdom 3 <1%
Spain 3 <1%
South Africa 2 <1%
Other 16 <1%
Unknown 1756 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 431 24%
Researcher 315 17%
Student > Master 248 14%
Student > Bachelor 164 9%
Student > Doctoral Student 101 6%
Other 256 14%
Unknown 296 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 371 20%
Chemistry 368 20%
Biochemistry, Genetics and Molecular Biology 281 16%
Pharmacology, Toxicology and Pharmaceutical Science 61 3%
Medicine and Dentistry 57 3%
Other 277 15%
Unknown 396 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 May 2020.
All research outputs
#1,904,774
of 22,753,345 outputs
Outputs from BMC Bioinformatics
#472
of 7,269 outputs
Outputs of similar age
#6,845
of 94,084 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 56 outputs
Altmetric has tracked 22,753,345 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,269 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 93% 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 94,084 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 56 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 91% of its contemporaries.