Table of Contents
Processes, Volume 6, Issue 9 (September 2018)
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Cover Story (view full-size image) Despite a booming Synthetic Biology community and some notable successes, engineering biomolecular [...] Read more. Despite a booming Synthetic Biology community and some notable successes, engineering biomolecular circuits with quantitatively predictable behavior remains extremely time-consuming. Mathematical models are uniquely suited to address this problem. Synthetic Biology has so far made limited use of mathematical models, mostly because inferring them is perceived as expensive and/or difficult. For Synthetic Biology to progress, model inference must be simpler, faster and ultimately cheaper. In this issue, we propose an iterative in-vivo Optimal Experimental Design approach that fully automates model calibration. We compare it with current model identification methods for biological parts and we show how this can lead to a reliable model much faster. View this paper.