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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)

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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
Subjects: Q Science
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Dominique Chu
Date Deposited: 03 Jan 2017 20:00 UTC
Last Modified: 09 Jul 2019 09:04 UTC
Resource URI: (The current URI for this page, for reference purposes)
Chu, Dominique:
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