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FluxFix: automatic isotopologue normalization for metabolic tracer analysis

Overview of attention for article published in BMC Bioinformatics, November 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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7 X users
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Citations

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Title
FluxFix: automatic isotopologue normalization for metabolic tracer analysis
Published in
BMC Bioinformatics, November 2016
DOI 10.1186/s12859-016-1360-7
Pubmed ID
Authors

Sophie Trefely, Peter Ashwell, Nathaniel W. Snyder

Abstract

Isotopic tracer analysis by mass spectrometry is a core technique for the study of metabolism. Isotopically labeled atoms from substrates, such as [(13)C]-labeled glucose, can be traced by their incorporation over time into specific metabolic products. Mass spectrometry is often used for the detection and differentiation of the isotopologues of each metabolite of interest. For meaningful interpretation, mass spectrometry data from metabolic tracer experiments must be corrected to account for the naturally occurring isotopologue distribution. The calculations required for this correction are time consuming and error prone and existing programs are often platform specific, non-intuitive, commercially licensed and/or limited in accuracy by using theoretical isotopologue distributions, which are prone to artifacts from noise or unresolved interfering signals. Here we present FluxFix ( http://fluxfix.science ), an application freely available on the internet that quickly and reliably transforms signal intensity values into percent mole enrichment for each isotopologue measured. 'Unlabeled' data, representing the measured natural isotopologue distribution for a chosen analyte, is entered by the user. This data is used to generate a correction matrix according to a well-established algorithm. The correction matrix is applied to labeled data, also entered by the user, thus generating the corrected output data. FluxFix is compatible with direct copy and paste from spreadsheet applications including Excel (Microsoft) and Google sheets and automatically adjusts to account for input data dimensions. The program is simple, easy to use, agnostic to the mass spectrometry platform, generalizable to known or unknown metabolites, and can take input data from either a theoretical natural isotopologue distribution or an experimentally measured one. Our freely available web-based calculator, FluxFix ( http://fluxfix.science ), quickly and reliably corrects metabolic tracer data for natural isotopologue abundance enabling faster, more robust and easily accessible data analysis.

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X Demographics

The data shown below were collected from the profiles of 7 X users 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 27%
Researcher 15 20%
Student > Bachelor 12 16%
Student > Doctoral Student 7 9%
Other 2 3%
Other 5 7%
Unknown 14 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 25%
Agricultural and Biological Sciences 14 19%
Chemistry 4 5%
Computer Science 3 4%
Engineering 3 4%
Other 11 15%
Unknown 21 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 24 May 2022.
All research outputs
#6,994,127
of 25,753,578 outputs
Outputs from BMC Bioinformatics
#2,398
of 7,741 outputs
Outputs of similar age
#114,325
of 418,524 outputs
Outputs of similar age from BMC Bioinformatics
#29
of 116 outputs
Altmetric has tracked 25,753,578 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,741 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 68% 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 418,524 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 72% of its contemporaries.
We're also able to compare this research output to 116 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.