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Optimal Experiment Design and Leveraging Competition for Shared Resources in Cell-free Extracts
Abstract The fact that genes compete for shared cel
The fact that genes compete for shared cellular resources poses a fundamental challenge when identifying pa- rameters of synthetic gene circuits. A recently developed model of gene expression tackles this problem by explicitly accounting for resource competition. In addition to accurately describing experimental data, this model only depends on a handful of easily identifiable parameters with clear physical interpretation. Based on this model, we outline a procedure how to select the optimal set of experiments to characterize biomolecular parts in synthetic biology. Additionally, we reveal the role competition for shared resources plays, provide guidelines how to minimize its detrimental effects, and how to leverage this phenomenon to extract the most information about unknown parameters. To illustrate the results, we consider the case of part characterization in cell-free extracts, treat plasmid DNA concentrations as decision variables, and demonstrate the significant performance difference between na ̈ıve and optimal experiment design.
een na ̈ıve and optimal experiment design.  +
Authors Wolfgang Halter, Frank Allgower, Richard M. Murray and Andras Gyorgy  +
Funding Molecular Programming Architectures, Abstractions, Algorithms, and Applications +
ID 2018b  +
Source To appear, 2018 Conference on Decision and Control (CDC)  +
Tag hamg18-cdc  +
Title Optimal Experiment Design and Leveraging Competition for Shared Resources in Cell-free Extracts +
Type Conference paper  +
Categories Papers
Modification date
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19 June 2018 05:31:09  +
URL
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https://www.cds.caltech.edu/~murray/preprints/hamg18-cdc.pdf  +
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Optimal Experiment Design and Leveraging Competition for Shared Resources in Cell-free Extracts + Title
 

 

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