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Further Research Topics
Large-Scale Data Analysis and Interpretation of Metabolomics Data
Metabolomic measurements provide a wealth of information about the biochemical status of cells, tissues and organs and play an important role to elucidate the function of novel genes. A remarkable inherent feature of cellular metabolism is that the concentrations of a small but significant number of metabolites are strongly correlated when measurements of biological replicates are performed. Drawing upon concepts of Nonlinear Dynamics and Computer Science, our work seeks to elucidate how comparative correlation analysis offers a way to exploit the intrinsic variability of metabolic networks to obtain significant additional information about the physiological state of the system.
Further reading:
- Morgenthal K., Weckwerth W., Steuer R. (2006) Metabolomic networks in plants: Transitions from pattern recognition to biological interpretation. Biosystems. 83(2-3):108-17.
- R. Steuer, J. Kurths, O. Fiehn and W. Weckwerth (2003) Observing and interpreting correlations in metabolomic networks. Bioinformatics, Vol. 19 (8), 1019-1026