PT  - JOURNAL ARTICLE
AU  - Frederick Starkey
AU  - Filippo Menolascina
TI  - Optimization for Predictive Gene Circuit Design Automation
AID  - 10.1101/2022.06.21.497000
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.06.21.497000
4099  - http://biorxiv.org/content/early/2022/06/21/2022.06.21.497000.short
4100  - http://biorxiv.org/content/early/2022/06/21/2022.06.21.497000.full
AB  - Synthetic Biology aims to rationally engineer biological systems. Current methods often employ an initial human designed circuit topology and utilise iterative approaches, e.g. directed evolution, to fine-tune part function. This approach can be extremely time consuming and resource intensive whilst often reaching sub-optimal solutions. A design workflow in which circuits and parts are designed in silico can overcome such limitations. Here we describe a method to automatically design synthetic gene circuits with user-specified dynamics; unlike some previous contributions our algorithm is able to design circuits with analog, not just digital behaviours. We demonstrate the capabilities of our approach benchmarking it on a number of different gene circuits design tasks. We review and compare the performance of our method against state of the art and outline future opportunities for development. Finally, to foster adoption, we make our algorithm available through a web app.Competing Interest StatementThe authors have declared no competing interest.