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Article: Chemometric methods in data processing of mass spectrometry-based metabolomics: A review

TitleChemometric methods in data processing of mass spectrometry-based metabolomics: A review
Authors
KeywordsMetabolomics
Chemometrics
Biomarker
Identification of metabolites
Data preprocessing
Modeling
Issue Date2016
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/aca
Citation
Analytica Chimica Acta, 2016, v. 914, p. 17-34 How to Cite?
AbstractThis review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets.
Persistent Identifierhttp://hdl.handle.net/10722/267530
ISSN
2017 Impact Factor: 5.123
2015 SCImago Journal Rankings: 1.548
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYi, L-
dc.contributor.authorDong, N-
dc.contributor.authorYun, Y-
dc.contributor.authorDeng, B-
dc.contributor.authorRen, D-
dc.contributor.authorLiu, S-
dc.contributor.authorLiang, Y-
dc.date.accessioned2019-02-20T01:07:09Z-
dc.date.available2019-02-20T01:07:09Z-
dc.date.issued2016-
dc.identifier.citationAnalytica Chimica Acta, 2016, v. 914, p. 17-34-
dc.identifier.issn0003-2670-
dc.identifier.urihttp://hdl.handle.net/10722/267530-
dc.description.abstractThis review focuses on recent and potential advances in chemometric methods in relation to data processing in metabolomics, especially for data generated from mass spectrometric techniques. Metabolomics is gradually being regarded a valuable and promising biotechnology rather than an ambitious advancement. Herein, we outline significant developments in metabolomics, especially in the combination with modern chemical analysis techniques, and dedicated statistical, and chemometric data analytical strategies. Advanced skills in the preprocessing of raw data, identification of metabolites, variable selection, and modeling are illustrated. We believe that insights from these developments will help narrow the gap between the original dataset and current biological knowledge. We also discuss the limitations and perspectives of extracting information from high-throughput datasets.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/aca-
dc.relation.ispartofAnalytica Chimica Acta-
dc.subjectMetabolomics-
dc.subjectChemometrics-
dc.subjectBiomarker-
dc.subjectIdentification of metabolites-
dc.subjectData preprocessing-
dc.subjectModeling-
dc.titleChemometric methods in data processing of mass spectrometry-based metabolomics: A review-
dc.typeArticle-
dc.identifier.emailDong, N: npdong@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.aca.2016.02.001-
dc.identifier.pmid26965324-
dc.identifier.scopuseid_2-s2.0-84977744133-
dc.identifier.hkuros296841-
dc.identifier.volume914-
dc.identifier.spage17-
dc.identifier.epage34-
dc.identifier.isiWOS:000371348100003-
dc.publisher.placeNetherlands-

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