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. 2016 Jun 6;10:40. doi: 10.1186/s12918-016-0283-2

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© The Author(s). 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 4 — Iterative replacement of Michaelis-Menten kinetics with measured properties by mass action kinetics. An increasing number of Michaelis-Menten kinetics rate laws with measured parameters were replaced by mass action kinetics, and the RT and MP of affected metabolites were calculated. The correlation of metabolite RT and MP between Michaelis-Menten kinetics and mass action kinetics fluctuated initially but gradually stabilized as more reactions were replaced with mass action kinetics. The black line is the average correlation of all nine perturbations performed. a Correlation of metabolite RTs between Michaelis-Menten and mass action model. b Correlation of metabolite MPs between Michaelis-Menten and mass action model. Spearman’s rho: Spearman’s rank correlation coefficient. The simulations were performed on the whole-cell kinetic model of erythrocyte constructed by Bordbar et al [33]