From data processing to multivariate validation - essential steps in extracting interpretable information from metabolomics data
2011 (English)In: Current Pharmaceutical Biotechnology, ISSN 1389-2010, Vol. 12, no 7, 996-1004(9) p.Article in journal (Refereed) Published
In metabolomics studies there is a clear increase of data. This indicates the necessity of both having a battery of suitable analysis methods and validation procedures able to handle large amounts of data. In this review, an overview of the metabolomics data processing pipeline is presented. A selection of recently developed and most cited data processing methods is discussed. In addition, commonly used chemometric and machine learning analysis methods as well as validation approaches are described.
Place, publisher, year, edition, pages
Bentham Science Publishers , 2011. Vol. 12, no 7, 996-1004(9) p.
multivariate data analysis, data processing, chemometrics, metabolomics, statistical validation, validation procedures, chemometric and machine learning analysis, NMR, downstream data analysis, Filtration, non-linear regression method
IdentifiersURN: urn:nbn:se:umu:diva-44567DOI: 10.2174/138920111795909041PubMedID: 21466461OAI: oai:DiVA.org:umu-44567DiVA: diva2:421438