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. 2018 Feb 26;8:3594. doi: 10.1038/s41598-018-21945-2

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© The Author(s) 2018

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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Searching for topologies that can differentially decode different transcription factor dynamics. (A) Possible direct links among three nodes (left) and the mathematical model (right). Each link can be in one of the three states: activation, inhibition, or no regulation. (B) AM and FM input dynamics of transcription factor (left) and Latin Hypercube sampling of the parameters of the model (right). (C) For AM, the steady-state output (a) is recorded. For FM, the asymptotic average output (schematically shown within the colored area) is recorded in the simulations (left). Illustration of the output analysis and the criterion for decoding AM- and FM-inputs (right), Red dot (b) represents the output from the example of the left panel.