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Editorial
, 2, 52

Global Systems Biology, Personalized Medicine and Molecular Epidemiology

Editorial

Global Systems Biology, Personalized Medicine and Molecular Epidemiology

Jeremy K Nicholson. Mol Syst Biol.

Figures

Figure 1
Figure 1
Relationships between systems biology, personalized healthcare and molecular epidemiology (dotted lines indicate indirect connections or influences).
Figure 2
Figure 2
Pharmaco-metabonomic modelling procedure: spectroscopic data on pre-dose metabolic fingerprints (X matrix) from biofluids such as urine and plasma are statistically linked to outcome (quantitative toxicity (Y1) drug metabolism (Y2) matrixes) of a drug intervention via multivariate statistics such as partial least squares methods. Typically, 20–50% of all data is used in the training set construction. The predictive power of the models is then tested using a test set or a cross-validation set to assess model robustness. It is also possible as an additional test to avoid overfitting of data, to deliberately permute the training set matrixes to induce a false model that should have a very low predictive capability.

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