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Analysis of primitive genetic interactions for the design of a genetic signal differentiator
Author(s) -
Wolfgang Halter,
Richard M. Murray,
Frank Allgöwer
Publication year - 2019
Publication title -
synthetic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.769
H-Index - 8
ISSN - 2397-7000
DOI - 10.1093/synbio/ysz015
Subject(s) - differentiator , computer science , signal (programming language) , genetic algorithm , filter (signal processing) , machine learning , computer vision , programming language
We study the dynamic and static input–output behavior of several primitive genetic interactions and their effect on the performance of a genetic signal differentiator. In a simplified design, several requirements for the linearity and time-scales of processes like transcription, translation and competitive promoter binding were introduced. By experimentally probing simple genetic constructs in a cell-free experimental environment and fitting semi-mechanistic models to these data, we show that some of these requirements can be verified, while others are only met with reservations in certain operational regimes. Analyzing the linearized model of the resulting genetic network, we conclude that it approximates a differentiator with relative degree one. Taking also the discovered nonlinearities into account and using a describing function approach, we further determine the particular frequency and amplitude ranges where the genetic differentiator can be expected to behave as such.

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