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An automated model reduction tool to guide the design and analysis of synthetic biological circuits

View ORCID ProfileAyush Pandey, Richard M. Murray
doi: https://doi.org/10.1101/640276
Ayush Pandey
1Department of Electrical Engineering, California Institute of Technology
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  • For correspondence: apandey@caltech.edu
Richard M. Murray
2Department of Control and Dynamical Systems and Department of Bioengineering, California Institute of Technology, Pasadena, CA
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Abstract

We present an automated model reduction algorithm that uses quasi-steady state approximation based reduction to minimize the error between the desired outputs. Additionally, the algorithm minimizes the sensitivity of the error with respect to parameters to ensure robust performance of the reduced model in the presence of parametric uncertainties. We develop the theory for this model reduction algorithm and present the implementation of the algorithm that can be used to perform model reduction of given SBML models. To demonstrate the utility of this algorithm, we consider the design of a synthetic biological circuit to control the population density and composition of a consortium consisting of two different cell strains. We show how the model reduction algorithm can be used to guide the design and analysis of this circuit.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted May 17, 2019.
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An automated model reduction tool to guide the design and analysis of synthetic biological circuits
Ayush Pandey, Richard M. Murray
bioRxiv 640276; doi: https://doi.org/10.1101/640276
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An automated model reduction tool to guide the design and analysis of synthetic biological circuits
Ayush Pandey, Richard M. Murray
bioRxiv 640276; doi: https://doi.org/10.1101/640276

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