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An Overview of Metabolomics Data Analysis: Current Tools and Future Perspectives
Turku Centre for Biotechnology, University of Turku, Turku, Finland; Åbo Akademi University, Turku, Finland.
Turku Centre for Biotechnology, University of Turku, Turku, Finland; Åbo Akademi University, Turku, Finland.
Turku Centre for Biotechnology, University of Turku, Turku, Finland; Åbo Akademi University, Turku, Finland.
Örebro University, School of Science and Technology.ORCID iD: 0000-0002-4382-4355
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2018 (English)In: Data Analysis for Omic Sciences: Methods and Applications / [ed] Joaquim Jaumot; Carmen Bedia; Romà Tauler, Elsevier, 2018, Vol. 82, p. 387-413Chapter in book (Refereed)
Abstract [en]

Metabolomics is a study of small molecules in the body and the associated metabolic pathways and is considered to provide a close link between organism's genotype and phenotype. As with other ‘omics’ techniques, metabolomic analysis generates large-scale and complex datasets. Therefore, various data analysis tools are needed to extract biologically relevant information. The data analysis workflows in metabolomics studies are generally complex and involve several steps. In this chapter, we highlight the concept of metabolomics workflow and discuss the data analysis strategies for metabolomics experiments. We also discuss the available tools that can assist in biological interpretation of metabolomics data. We also present an emerging approach of developing genome-scale metabolic models to study cellular metabolism.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 82, p. 387-413
Series
Comprehensive Analytical Chemistry, ISSN 0166-526X, E-ISSN 1875-788X
Keywords [en]
Genome-scale metabolic models, Metabolic models, Metabolite set analysis, Metabolomics, Multivariate, Pathways, Univariate data analysis
National Category
Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:oru:diva-71466DOI: 10.1016/bs.coac.2018.07.001Scopus ID: 2-s2.0-85051717444ISBN: 978-0-444-64044-4 (print)OAI: oai:DiVA.org:oru-71466DiVA, id: diva2:1278471
Available from: 2019-01-14 Created: 2019-01-14 Last updated: 2019-03-04Bibliographically approved

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Hyötyläinen, TuuliaOrešič, Matej

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