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美国卫生研究院文献>BMC Systems Biology
>A correction method for systematic error in 1H-NMR time-course data validated through stochastic cell culture simulation
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A correction method for systematic error in 1H-NMR time-course data validated through stochastic cell culture simulation
BackgroundThe growing ubiquity of metabolomic techniques has facilitated high frequency time-course data collection for an increasing number of applications. While the concentration trends of individual metabolites can be modeled with common curve fitting techniques, a more accurate representation of the data needs to consider effects that act on more than one metabolite in a given sample. To this end, we present a simple algorithm that uses nonparametric smoothing carried out on all observed metabolites at once to identify and correct systematic error from dilution effects. In addition, we develop a simulation of metabolite concentration time-course trends to supplement available data and explore algorithm performance. Although we focus on nuclear magnetic resonance (NMR) analysis in the context of cell culture, a number of possible extensions are discussed.
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