The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Data processing for mass spectrometry-based metabolomics
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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In the citing paper
“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]
In the citing paper
“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]
Citations
Cites
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Cited by
Sorted by citations
Pluskal, T., Castillo, S., Villar‐Briones, A., & Orešič, M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-395 · Cited by 3,852
“Several software packages have been developed for this purpose, and have been extensively reviewed by Katajamaa and Ore š i č [1].”
MethodGlobal metabolic profiling of animal and human tissues via UPLC-MS
Want, E. J., Masson, P., Michopoulos, F., Wilson, I. D., Theodoridis, G. A., Plumb, R. S., Shockcor, J. P., Loftus, N. J., Holmes, E. C., & Nicholson, J. K. (2012) · Nature Protocols · doi:10.1038/nprot.2012.135 · Cited by 1,647
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Kuhl, C., Tautenhahn, R., Böttcher, C., Larson, T. R., & Neumann, S. (2011) · Analytical Chemistry · doi:10.1021/ac202450g · Cited by 1,208
Highly sensitive feature detection for high resolution LC/MS
Tautenhahn, R., Böttcher, C., & Neumann, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-504 · Cited by 1,175
“3 Parameter optimisation Beside centWave, there are currently only two other feature detection algorithms available [9], which meet the following criteria: freely available, open source, and suited for feature detection in metabolomic LC/MS samples measured in centroid mode: matchedFilter- the originally implemented a…”
BackgroundMethod
Metadata
- Authors
- Katajamaa, M., & Orešič, M.
- Affiliations
- Turku Centre for Biotechnology (FI)
- VTT Technical Research Centre of Finland (FI)
- Corresponding author
- Katajamaa, Mikko
- Orešič, Matej
- ORCID
- 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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