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Performance limits and trade-offs in entropy-driven biochemical computers

Chu, Dominique (2018) Performance limits and trade-offs in entropy-driven biochemical computers. Journal of Theoretical Biology, 443 . pp. 1-9. ISSN 0022-5193. (doi:10.1016/j.jtbi.2018.01.022) (KAR id:59768)

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Official URL:
https://doi.org/10.1016/j.jtbi.2018.01.022

Abstract

The properties and fundamental limits of chemical computers have recently attracted significant interest as a model of computation, an unifying principle of cellular organisation and in the context of bio-engineering. As of yet, research in this topic is based on case-studies. There exists no generally accepted criterion to distinguish between chemical processes that compute and those that do not. Here, the concept of entropy driven computer (EDC) is proposed as a general model of chemical computation. It is found that entropy driven computation is subject to a trade-off between accuracy and entropy production, but unlike many biological systems, there are no trade-offs involving time. The latter only arise when it is taken into account that the observation of the state of the EDC is not energy neutral, but comes at a cost. The significance of this conclusion in relation to biological systems is discussed. Three examples of biological computers, including an implementation of a neural network as an EDC are given.

Item Type: Article
DOI/Identification number: 10.1016/j.jtbi.2018.01.022
Uncontrolled keywords: Biological computing, Information thermodynamics, Cost of computation, Linear noise approximation
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Dominique Chu
Date Deposited: 03 Jan 2017 20:00 UTC
Last Modified: 16 Feb 2021 13:41 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/59768 (The current URI for this page, for reference purposes)
Chu, Dominique: https://orcid.org/0000-0002-3706-2905
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