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  • 标题:Biomolecular mechanisms for signal differentiation
  • 本地全文:下载
  • 作者:Emmanouil Alexis ; Carolin C.M. Schulte ; Luca Cardelli
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2021
  • 卷号:24
  • 期号:12
  • 页码:1-32
  • DOI:10.1016/j.isci.2021.103462
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryCells can sense temporal changes of molecular signals, allowing them to predict environmental variations and modulate their behavior. This paper elucidates biomolecular mechanisms of time derivative computation, facilitating the design of reliable synthetic differentiator devices for a variety of applications, ultimately expanding our understanding of cell behavior. In particular, we describe and analyze three alternative biomolecular topologies that are able to work as signal differentiators to input signals around their nominal operation. We propose strategies to preserve their performance even in the presence of high-frequency input signal components which are detrimental to the performance of most differentiators. We find that the core of the proposed topologies appears in natural regulatory networks and we further discuss their biological relevance. The simple structure of our designs makes them promising tools for realizing derivative control action in synthetic biology.Graphical abstractDisplay OmittedHighlights•Calculating the speed or higher derivatives of molecular signals has been a challenge•Biomolecular topologies acting as signal differentiators are studied•High performance and insensitivity to high-frequency input signals can be achieved•Natural circuits and synthetic realizations for signal differentiation are describedMathematical biosciences; Systems biology; Synthetic biology
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