Imperial College London
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DrLudovicRenson

Faculty of Engineering, Department of Mechanical Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 7088l.renson

 
 
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Location

 

558City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{de:2022:10.1021/acssynbio.1c00632,
author = {de, Cesare I and Salzano, D and di, Bernardo M and Renson, L and Marucci, L},
doi = {10.1021/acssynbio.1c00632},
journal = {ACS Synthetic Biology},
pages = {2300--2313},
title = {Control-based continuation: a new approach to prototype synthetic gene networks.},
url = {http://dx.doi.org/10.1021/acssynbio.1c00632},
volume = {11},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Control-Based Continuation (CBC) is a general and systematic method to carry out the bifurcation analysis of physical experiments. CBC does not rely on a mathematical model and thus overcomes the uncertainty introduced when identifying bifurcation curves indirectly through modeling and parameter estimation. We demonstrate, in silico, CBC applicability to biochemical processes by tracking the equilibrium curve of a toggle switch, which includes additive process noise and exhibits bistability. We compare the results obtained when CBC uses a model-free and model-based control strategy and show that both can track stable and unstable solutions, revealing bistability. We then demonstrate CBC in conditions more representative of an in vivo experiment using an agent-based simulator describing cell growth and division, cell-to-cell variability, spatial distribution, and diffusion of chemicals. We further show how the identified curves can be used for parameter estimation and discuss how CBC can significantly accelerate the prototyping of synthetic gene regulatory networks.
AU  - de,Cesare I
AU  - Salzano,D
AU  - di,Bernardo M
AU  - Renson,L
AU  - Marucci,L
DO  - 10.1021/acssynbio.1c00632
EP  - 2313
PY  - 2022///
SN  - 2161-5063
SP  - 2300
TI  - Control-based continuation: a new approach to prototype synthetic gene networks.
T2  - ACS Synthetic Biology
UR  - http://dx.doi.org/10.1021/acssynbio.1c00632
UR  - https://www.ncbi.nlm.nih.gov/pubmed/35729740
UR  - https://pubs.acs.org/doi/10.1021/acssynbio.1c00632
UR  - http://hdl.handle.net/10044/1/98073
VL  - 11
ER  -
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