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Data acquisition, analysis, and mining: Integrative tools for discerning metabolic function in Saccharomyces cerevisiae

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Metabolomics

Part of the book series: Topics in Current Genetics ((TCG,volume 18))

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Abstract

The well defined genetic architecture and metabolic network of Saccharomycescerevisiae make this organism a cornerstone for metabolomics research. Recent effortshave focused on robust sample preparation techniques, analytical tools to quantitatively identifyhundreds of metabolites at the same time, and elegant approaches for analyzing and interpreting thedata. While equally important, we focus here on approaches for extracting useful information fromthe data itself. We outline several statistical and mathematical methods that can be used to digestand validate the most important features in the data. These multivariate approaches are from eitherthe well established standard portfolio of statistical methods, or can be adapted from other areaswhere similar problems can be identified and where statistical and mathematical methods exist. Lookingforward, we also describe approaches for fusing metabolome data with other cellular measurements andnetwork structure to elucidate biosynthetic control mechanisms.

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  1. Center for Microbial Biotechnology, BioCentrum-DTU, Technical University of Denmark, Søltofts Plads, DK-2800, Kgs. Lyngby, Denmark

    Michael C. Jewett, Michael A. E. Hansen & Jens Nielsen

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Jewett, M.C., Hansen, M.A.E., Nielsen, J. (2007). Data acquisition, analysis, and mining: Integrative tools for discerning metabolic function in Saccharomyces cerevisiae . In: Nielsen, J., Jewett, M.C. (eds) Metabolomics. Topics in Current Genetics, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/4735_2007_0222

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