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Dynamic metabolomic data analysis: a tutorial review

In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic m...

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Detalles Bibliográficos
Autores principales: Smilde, A. K., Westerhuis, J. A., Hoefsloot, H. C. J., Bijlsma, S., Rubingh, C. M., Vis, D. J., Jellema, R. H., Pijl, H., Roelfsema, F., van der Greef, J.
Formato: Texto
Lenguaje:English
Publicado: Springer US 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2834778/
https://www.ncbi.nlm.nih.gov/pubmed/20339444
http://dx.doi.org/10.1007/s11306-009-0191-1
Descripción
Sumario:In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic metabolomic data. Moreover, some methods from other fields of science that may be of use to analyze such dynamic metabolomics data are described in some detail. The methods are put in a general framework after providing a formal definition on what constitutes a ‘dynamic’ method. Some of the methods are illustrated with real-life metabolomics examples.