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. 2016 May 23;17:109. doi: 10.1186/s13059-016-0968-2

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© Zhao et al. 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. 3 — Robustness of invFBA to noise. The maximal value of the biomass coefficient c_biomass, found by invFBA and subsequent objective variability analysis (OVA), is plotted as a function of the level of noise (σ ²) in FBA-simulated flux data for E. coli. These FBA-simulated fluxes are produced using maximization of biomass production as the objective function. Thus, a value of c_biomass close to unity in OVA indicates that invFBA recovers the original objective. As the level of noise increases, however, our ability to recover the original objective is highly reduced