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  What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics

Hamzeiy, H., & Cox, J. (2017). What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics. Current Opinion in Biotechnology, 43, 141-146. doi:10.1016/j.copbio.2016.11.014.

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1-s2.0-S0958166916302749-main.pdf (Publisher version), 2MB
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© 2016 The Author(s). Under a Creative Commons license
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 Creators:
Hamzeiy, Hamid1, Author              
Cox, Jürgen1, Author              
Affiliations:
1Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              

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Free keywords: PROTEIN IDENTIFICATION; CELL-LINE; QUANTIFICATION; ACCURACY; DATABASE; ORBITRAP; TANDEM; PLATFORM; BIOLOGY; SEARCHBiochemistry & Molecular Biology; Biotechnology & Applied Microbiology;
 Abstract: Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification.

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Language(s): eng - English
 Dates: 2016-12-282017-02
 Publication Status: Published in print
 Pages: 6
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 Table of Contents: -
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 Degree: -

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Project name : -
Grant ID : 686547
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Current Opinion in Biotechnology
  Other : Curr. Opin. Biotechnol.
Source Genre: Journal
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Publ. Info: London : Elsevier Current Trends
Pages: - Volume / Issue: 43 Sequence Number: - Start / End Page: 141 - 146 Identifier: ISSN: 0958-1669
CoNE: https://pure.mpg.de/cone/journals/resource/954925577053