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An in silico MS/MS library for automatic annotation of novel FAHFA lipids

Overview of attention for article published in Journal of Cheminformatics, November 2015
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  • Above-average Attention Score compared to outputs of the same age (56th percentile)
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4 tweeters

Citations

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38 Dimensions

Readers on

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50 Mendeley
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Title
An in silico MS/MS library for automatic annotation of novel FAHFA lipids
Published in
Journal of Cheminformatics, November 2015
DOI 10.1186/s13321-015-0104-4
Pubmed ID
Authors

Yan Ma, Tobias Kind, Arpana Vaniya, Ingrid Gennity, Johannes F. Fahrmann, Oliver Fiehn

Abstract

A new lipid class named 'fatty acid esters of hydroxyl fatty acids' (FAHFA) was recently discovered in mammalian adipose tissue and in blood plasma and some FAHFAs were found to be associated with type 2 diabetes. To facilitate the automatic annotation of FAHFAs in biological specimens, a tandem mass spectra (MS/MS) library is needed. Due to the limitation of the commercial available standard compounds, we proposed building an in silico MS/MS library to extend the coverage of molecules. We developed a computer-generated library with 3267 tandem mass spectra (MS/MS) for 1089 FAHFA species. FAHFA spectra were generated based on authentic standards with negative mode electrospray ionization and 10, 20, and 40 V collision induced dissociation at 4 spectra/s as used in in ultra-high performance liquid chromatography-QTOF mass spectrometry studies. However, positional information of the hydroxyl group is only obtained either at lower QTOF spectra acquisition rates of 1 spectrum/s or at the MS(3) level in ion trap instruments. Therefore, an additional set of 4290 fragment-rich MS/MS spectra was created to enable distinguishing positional FAHFA isomers. The library was generated based on ion fragmentations and ion intensities of FAHFA external reference standards, developing a heuristic model for fragmentation rules and extending these rules to large swaths of computer-generated structures of FAHFAs with varying chain lengths, degrees of unsaturation and hydroxyl group positions. Subsequently, we validated the new in silico library by discovering several new FAHFA species in egg yolk, showing that this library enables high-throughput screening of FAHFA lipids in various biological matrices. The developed library and templates are freely available for commercial or noncommercial use at http://fiehnlab.ucdavis.edu/staff/yanma/fahfa-lipid-library. This in silico MS/MS library allows users to annotate FAHFAs from accurate mass tandem mass spectra in an easy and fast manner with NIST MS Search or PepSearch software. The developing template is provided for advanced users to modify the parameters and export customized libraries according to their instrument features. Graphical abstractExample of experimental and in silico MS/MS spectra for FAHFA lipids.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
Austria 1 2%
Brazil 1 2%
Unknown 46 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 30%
Researcher 12 24%
Student > Master 9 18%
Student > Doctoral Student 3 6%
Professor 2 4%
Other 3 6%
Unknown 6 12%
Readers by discipline Count As %
Chemistry 11 22%
Agricultural and Biological Sciences 10 20%
Biochemistry, Genetics and Molecular Biology 7 14%
Pharmacology, Toxicology and Pharmaceutical Science 3 6%
Earth and Planetary Sciences 2 4%
Other 9 18%
Unknown 8 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 June 2018.
All research outputs
#7,510,587
of 13,104,802 outputs
Outputs from Journal of Cheminformatics
#407
of 527 outputs
Outputs of similar age
#152,749
of 353,819 outputs
Outputs of similar age from Journal of Cheminformatics
#29
of 51 outputs
Altmetric has tracked 13,104,802 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 527 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one is in the 21st percentile – i.e., 21% 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 353,819 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 56% of its contemporaries.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.