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. 2017 Dec 5;7:17018. doi: 10.1038/s41598-017-17072-z

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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The optimal experimental design for accurate and precise estimation with the tQ model. (a) When the scatter plot of posterior samples from the first experiment is horizontal, E _T and S _T need to be decreased to obtain the nonhorizontal scatter plot in the next experiment. Then, using the combination of the two experiments leads to accurate and precise estimation (red scatter plots). (b) When the scatter plot from the first experiment is nonhorizontal, E _T or S _T need to be increased in the next experiment to obtain a horizontal scatter plot. (c) Inference with a single progress curve from the low E _T (0.1 K _M) and the high E _T (10 K _M) leads to nonhorizontal and horizontal scatter plots, respectively, for chymotrypsin, urease, and fumarase (gray scatter plots). When both data sets were used together, accurate estimates were obtained for all enzymes (red scatter plots). Here, low S _T (0.1 K _M) is used. Here, green triangles represent the true values of the parameters.