Cited by 617Metabolomics and Mass Spectrometry StudiesAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Data processing for mass spectrometry-based metabolomics

Katajamaa, Mikko, Orešič, Matej·2007·Journal of Chromatography A

Abstract

Modern analytical technologies afford comprehensive and quantitative investigation of a multitude of different metabolites. Typical metabolomic experiments can therefore produce large amounts of data. Handling such complex datasets is an important step that has big impact on extent and quality at which the metabolite identification and quantification can be made, and thus on the ultimate biological interpretation of results. Increasing interest in metabolomics thus led to resurgence of interest in related data processing. A wide variety of methods and software tools have been developed for metabolomics during recent years, and this trend is likely to continue. In this paper we overview the key steps of metabolomic data processing and focus on reviewing recent literature related to this topic, particularly on methods for handling data from liquid chromatography mass spectrometry (LC-MS) experiments.

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Crossref · 10.1016/j.chroma.2007.04.021

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  • These steps include data preprocessing, alignment, normalization, and signal correction, followed by statistical analysis.

    “These include data preprocessing, data alignment, data normalization, and signal correction followed by the analysis through various statistical methods.”

    From The food metabolome: a window over dietary exposure (2014) · cites this paper as [119]

  • The metabolic profile of raw data from spectrometric analysis of biological samples can be analyzed in several steps.

    “The metabolic profile of raw data generated by the spectrometric analysis of biological samples can be analyzed in several steps (119, 120).”

    From The food metabolome: a window over dietary exposure (2014) · cites this paper as [119]

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Authors
Katajamaa, M., & Orešič, M.
Affiliations
  • Turku Centre for Biotechnology (FI)
  • VTT Technical Research Centre of Finland (FI)
Corresponding author
  • Katajamaa, Mikko
  • Orešič, Matej
Venue
Journal of Chromatography A
Publisher
Elsevier BV
Published
2007-07
Volume
1158
Issue
1-2
Pages
318-328
ISSN
0021-9673 (ISSN-L)
OpenAlex
W2075109094
Cited by
616
References
82
Citations by year
2026: 13 · 2025: 10 · 2024: 21 · 2023: 10 · 2022: 19 · 2021: 32 · 2020: 27 · 2019: 37 · 2018: 38 · 2017: 33 · 2016: 47 · 2015: 38 · 2014: 50 · 2013: 54 · 2012: 44
FWCI
2.56
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Chromatography A (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
Keywords
metabolomics data processing, mass spectrometry data, liquid chromatography-mass spectrometry, metabolite identification, metabolite quantification, data processing software
MeSH terms
Chromatography, Liquid, Mass Spectrometry

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