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Model Reduction Tools For Phenomenological Modeling of Input-Controlled Biological Circuits

Pandey, Ayush and Murray, Richard M. (2020) Model Reduction Tools For Phenomenological Modeling of Input-Controlled Biological Circuits. . (Unpublished)

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We present a Python-based software package to automatically obtain phenomenological models of input-controlled synthetic biological circuits that guide the design using chemical reaction-level descriptive models. From the parts and mechanism description of a synthetic biological circuit, it is easy to obtain a chemical reaction model of the circuit under the assumptions of mass-action kinetics using various existing tools. However, using these models to guide design decisions during an experiment is difficult due to a large number of reaction rate parameters and species in the model. Hence, phenomenological models are often developed that describe the effective relationships among the circuit inputs, outputs, and only the key states and parameters. In this paper, we present an algorithm to obtain these phenomenological models in an automated manner using a Python package for circuits with inputs that control the desired outputs. This model reduction approach combines the common assumptions of time-scale separation, conservation laws, and species' abundance to obtain the reduced models that can be used for design of synthetic biological circuits. We consider an example of a simple gene expression circuit and another example of a layered genetic feedback control circuit to demonstrate the use of the model reduction procedure.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemData/Code
Pandey, Ayush0000-0003-3590-4459
Murray, Richard M.0000-0002-5785-7481
Additional Information: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. Posted February 20, 2020. We would like to thank Chelsea Hu for her help with the modeling of the layered feedback controller example. This research is sponsored in part by the National Science Foundation under grant number: CBET-1903477 and the Defense Advanced Research Projects Agency (Agreement HR0011-17-2-0008). The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR0011-17-2-0008
Record Number:CaltechAUTHORS:20200220-154511531
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Official Citation:Model Reduction Tools For Phenomenological Modeling of Input-Controlled Biological Circuits. Ayush Pandey, Richard M Murray. bioRxiv 2020.02.15.950840; doi:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101437
Deposited By: Tony Diaz
Deposited On:20 Feb 2020 23:50
Last Modified:03 Aug 2020 21:01

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