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Fig. 4 | BMC Bioinformatics

Fig. 4

From: LK-DFBA: a linear programming-based modeling strategy for capturing dynamics and metabolite-dependent regulation in metabolism

Fig. 4

Comparison of fitting performance when one metabolite time course is withheld from the fitting procedure. Solid lines represent the median penalized relative sum-of-square error (prSSE) for each modeling approach and dotted lines represent the median absolute deviation. a, b, c Performance when X1 is missing (X1-Missing). d, e, f X2-Missing. g, h, i X3-Missing. j, k, l X4-Missing. m, n, o XBM-Missing. nT is the number of time points used to fit each model. Generally, LK-DFBA (LR+) performs better than the compared methods, with the exception of decreased performance of LK-DFBA when the metabolite regulator X4 is missing, reflecting the importance of being able to measure regulatory molecules

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