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. 2017 Jun 27;79(7):1449–1486. doi: 10.1007/s11538-017-0277-2

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© The Author(s) 2017

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.

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Fig. 3 — Schematic depiction of sensitivity analysis versus optimisation. I Sensitivity analysis allows the ranking of the relative importance of the parameters on the outputs of interest. The least influential parameters can be fixed as constant lessening the burden of parameter fitting or can enable model reduction through the elimination of associated parameters. II The optimisation approaches differ in that they typically aim to eliminate the least influential state-variables by fixing them to be constant in time