Buecherl, Lukas;
Myers, Chris J;
Fontanarrosa, Pedro;
(2024)
Evaluating the Contribution of Model Complexity in Predicting Robustness in Synthetic Genetic Circuits.
ACS Synthetic Biology
, 13
(9)
pp. 2742-2752.
10.1021/acssynbio.3c00708.
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Abstract
The design-build-test-learn workflow is pivotal in synthetic biology as it seeks to broaden access to diverse levels of expertise and enhance circuit complexity through recent advancements in automation. The design of complex circuits depends on developing precise models and parameter values for predicting the circuit performance and noise resilience. However, obtaining characterized parameters under diverse experimental conditions is a significant challenge, often requiring substantial time, funding, and expertise. This work compares five computational models of three different genetic circuit implementations of the same logic function to evaluate their relative predictive capabilities. The primary focus is on determining whether simpler models can yield conclusions similar to those of more complex ones and whether certain models offer greater analytical benefits. These models explore the influence of noise, parametrization, and model complexity on predictions of synthetic circuit performance through simulation. The findings suggest that when developing a new circuit without characterized parts or an existing design, any model can effectively predict the optimal implementation by facilitating qualitative comparison of designs' failure probabilities (e.g., higher or lower). However, when characterized parts are available and accurate quantitative differences in failure probabilities are desired, employing a more precise model with characterized parts becomes necessary, albeit requiring additional effort.
| Type: | Article |
|---|---|
| Title: | Evaluating the Contribution of Model Complexity in Predicting Robustness in Synthetic Genetic Circuits |
| Location: | United States |
| DOI: | 10.1021/acssynbio.3c00708 |
| Publisher version: | http://dx.doi.org/10.1021/acssynbio.3c00708 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Genetic regulatory networks; synthetic genetic circuits; extrinsic and intrinsic noise in gene expression; synthetic biology; genetic circuit simulation and modeling; comparative analysis of genetic models |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10200876 |
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