Evidence map›Paper›PMID 29360933›Full record

ArticleBioinformatics (Oxford, England)2018

DExSI: a new tool for the rapid quantitation of 13C-labelled metabolites detected by GC-MS.

Michael J Dagley, Malcolm J McConville

Open access · hybridAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 54 citations in OpenAlex.

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  18. Oxidative desulfurization pathway for complete catabolism of sulfoquinovose by bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Michael J DagleyDepartment of Biochemistry and Molecular Biology, Bio21 Institute of Molecular Science and Biotechnology, University of Melbourne, Parkville, VIC 3010, Australia.
Malcolm J McConvilleDepartment of Biochemistry and Molecular Biology, Bio21 Institute of Molecular Science and Biotechnology, University of Melbourne, Parkville, VIC 3010, Australia.
University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Summary: Stable isotope directed metabolomics is increasingly being used to measure metabolic fluxes in microbial, plant and animal cells. Incorporation of 13C/15N isotopes into a wide range of metabolites is typically determined using gas chromatography-mass spectrometry (GC/MS) or other hyphenated mass spectrometry approaches. The DExSI (Data Extraction for Stable Isotope-labelled metabolites) pipeline is an interactive graphical software package which can be used to rapidly quantitate isotopologues for a wide variety of metabolites detected by GC/MS. DExSI performs automated metabolite annotation, mass and positional isotopomer abundance determination and natural isotope abundance correction. It provides a range of output options and is suitable for high throughput analyses. Availability and implementation: DExSI is available for non-commercial use from: https://github.com/DExSI/DExSI/. For Microsoft Windows 7 or higher (64-bit). Contact: malcolmm@unimelb.edu.au or michael.dagley@unimelb.edu.au. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

Carbon IsotopesSoftwareAnimalsBacteriaData VisualizationEukaryotaGas Chromatography-Mass SpectrometryIsotope LabelingMetabolomicsCarbon-13Carbon Isotopes

Identifiers

PMID29360933
PMCPMC5972663
OpenAlexW2792102657

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.