A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]

Sensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows ho...

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Main Author: Steven A. Frank
Format: Article
Language:English
Published: F1000 Research Ltd 2018-04-01
Series:F1000Research
Online Access:https://f1000research.com/articles/7-200/v3
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spelling doaj-3aad331186564144a6554449981341262020-11-25T03:18:50ZengF1000 Research LtdF1000Research2046-14022018-04-01710.12688/f1000research.14016.315921A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]Steven A. Frank0Department of Ecology and Evolutionary Biology, University of California, Irvine, CA, 92697-2525, USASensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows how a biochemical logarithmic sensor can be constructed from the most basic principles of chemical reactions. Assuming that reactions follow the classic Michaelis-Menten kinetics of mass action or the more generalized and commonly observed Hill equation response, the summed output of several simple reactions with different sensitivities to the input will often give an aggregate output response that logarithmically transforms the input. The logarithmic response is robust to stochastic fluctuations in parameter values. This model emphasizes the simplicity and robustness by which aggregate chemical circuits composed of sloppy components can achieve precise response characteristics. Both natural and synthetic designs gain from the power of this aggregate approach.https://f1000research.com/articles/7-200/v3
collection DOAJ
language English
format Article
sources DOAJ
author Steven A. Frank
spellingShingle Steven A. Frank
A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
F1000Research
author_facet Steven A. Frank
author_sort Steven A. Frank
title A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
title_short A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
title_full A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
title_fullStr A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
title_full_unstemmed A biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
title_sort biochemical logarithmic sensor with broad dynamic range [version 3; referees: 2 approved]
publisher F1000 Research Ltd
series F1000Research
issn 2046-1402
publishDate 2018-04-01
description Sensory perception often scales logarithmically with the input level. Similarly, the output response of biochemical systems sometimes scales logarithmically with the input signal that drives the system. How biochemical systems achieve logarithmic sensing remains an open puzzle. This article shows how a biochemical logarithmic sensor can be constructed from the most basic principles of chemical reactions. Assuming that reactions follow the classic Michaelis-Menten kinetics of mass action or the more generalized and commonly observed Hill equation response, the summed output of several simple reactions with different sensitivities to the input will often give an aggregate output response that logarithmically transforms the input. The logarithmic response is robust to stochastic fluctuations in parameter values. This model emphasizes the simplicity and robustness by which aggregate chemical circuits composed of sloppy components can achieve precise response characteristics. Both natural and synthetic designs gain from the power of this aggregate approach.
url https://f1000research.com/articles/7-200/v3
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