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Computational mass spectrometry for small molecules

Overview of attention for article published in Journal of Cheminformatics, March 2013
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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 (82nd percentile)

Mentioned by

twitter
7 tweeters
patent
1 patent
googleplus
1 Google+ user

Citations

dimensions_citation
94 Dimensions

Readers on

mendeley
204 Mendeley
citeulike
2 CiteULike
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Title
Computational mass spectrometry for small molecules
Published in
Journal of Cheminformatics, March 2013
DOI 10.1186/1758-2946-5-12
Pubmed ID
Authors

Kerstin Scheubert, Franziska Hufsky, Sebastian Böcker

Abstract

: The identification of small molecules from mass spectrometry (MS) data remains a major challenge in the interpretation of MS data. This review covers the computational aspects of identifying small molecules, from the identification of a compound searching a reference spectral library, to the structural elucidation of unknowns. In detail, we describe the basic principles and pitfalls of searching mass spectral reference libraries. Determining the molecular formula of the compound can serve as a basis for subsequent structural elucidation; consequently, we cover different methods for molecular formula identification, focussing on isotope pattern analysis. We then discuss automated methods to deal with mass spectra of compounds that are not present in spectral libraries, and provide an insight into de novo analysis of fragmentation spectra using fragmentation trees. In addition, this review shortly covers the reconstruction of metabolic networks using MS data. Finally, we list available software for different steps of the analysis pipeline.

Twitter Demographics

The data shown below were collected from the profiles of 7 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 204 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 1%
Russia 3 1%
Germany 2 <1%
United States 2 <1%
Finland 1 <1%
Australia 1 <1%
South Africa 1 <1%
France 1 <1%
Czechia 1 <1%
Other 6 3%
Unknown 183 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 68 33%
Researcher 47 23%
Student > Master 17 8%
Student > Bachelor 15 7%
Professor > Associate Professor 12 6%
Other 31 15%
Unknown 14 7%
Readers by discipline Count As %
Chemistry 62 30%
Agricultural and Biological Sciences 50 25%
Biochemistry, Genetics and Molecular Biology 20 10%
Computer Science 14 7%
Engineering 7 3%
Other 30 15%
Unknown 21 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 05 August 2020.
All research outputs
#2,928,798
of 16,849,755 outputs
Outputs from Journal of Cheminformatics
#303
of 651 outputs
Outputs of similar age
#26,892
of 155,868 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 2 outputs
Altmetric has tracked 16,849,755 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 651 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.1. This one has gotten more attention than average, scoring higher than 53% 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 155,868 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 2 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