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# Rapid prototyping a Example module for characterization (strain yCL109; β-est: β-estradiol; aTc: anhydrotetracyclin). b, c Characterization experiments, citrine fluorescence measured by flow cytometry. All flow cytometry measurements include at least 4000 cells after gating. Symbols show experimental means, ±standard deviation, and lines simulations of the maximum likelihood parameter set estimated with all seven modules. 5 μM β-estradiol were added at time 0, together with varying concentrations of α-factor (dose response at 18 h (b), dynamics after α addition (c)), or varying concentrations of aTc with 0 or 1 μM α (aTc dose response at 6 h (b)). For α-factor release (c), we removed α from the medium 18 h after induction. d Illustration of the second step of TopoDesign to infer the posterior distribution p(θ∣D)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p({\mathbf{\theta }}|D)$$\end{document} of the 20 parameters θi for parts in Fig. 1b by approximate Bayesian computation (ABC) using the likelihood p(D∣θ)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p(D|{\mathbf{\theta }})$$\end{document} for data D. e Projection of the joint posterior parameter distribution on two pairs of parameters; bright contour lines indicate high probability density.

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Cells can encode information about their environment by modulating signaling dynamics and responding accordingly. Yet, the mechanisms cells use to decode these dynamics remain unknown when cells respond exclusively to transient signals. Here, we approach design principles underlying such decoding by rationally engineering a synthetic short-pulse de...

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... Correlation between the pulses of NF-jB and differential gene expression patterns have been identified in the recent past (Lane et al., 2017;Zambrano et al., 2016). Subsequently, mathematical model studies revealed the topology of network motifs that are capable of generating pulses (Gao et al., 2018;Lormeau et al., 2021;Martinez-Corral et al., 2018;Zhang et al., 2016). Therefore, it is important to gain a systematic quantitative understanding of how various network motifs process pulsatile signals such that regulatory units process it as a true signal leaving out the small amplitude noisy signals. ...
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