Resolution:
## Figure 7.
Clustering results used in the N-way HC-PLSR metamodelling with six clusters. A) Plot of the factors (Fac 1-Fac 3) from the global inverse metamodelling (=T_{Output,A,Inverse}). The observations are coloured according to cluster memberships. Cluster1=blue,
cluster2=red, cluster3=yellow, cluster4=green, cluster5=magenta, cluster6=cyan. is the 3-way state variable trajectory array, while XY is the parameters. The clustering was done on the factors explaining a significant amount of the variation in the state variable space,
that is the 19 first factors. B) Plot of the predicted Y-scores (see Additional file 1, eq. S12c) from the global classical metamodelling, colour coded according to the cluster memberships of the observations
found using T_{Output,A,Inverse}. The classification of the test set observations to be predicted in the classical
metamodelling was based on , predicted from using second order polynomial OLS regression. This OLS prediction model was calibrated
in the calibration step of the classical metamodelling, based on the factors from the inverse metamodelling (=, plotted in panel A) and calibration set (plotted here). C) Circadian clock state trajectories for the observations belonging to each cluster,
coloured according to cluster memberships from the inverse N-way HC-PLSR. Cluster1 = blue,
cluster2 = red, cluster3 = yellow, cluster4 = green, cluster5 = magenta, cluster6 = cyan.
All state variables are given in nM units.
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