The cell as a semiotic system that realizes closure to efficient causation: The semiotic (M, R) system

IF 2 4区 生物学 Q2 BIOLOGY
Federico Vega
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引用次数: 0

Abstract

Robert Rosen defines organisms as material systems closed to efficient causation, and proposes the replicative (M, R) system as a model for them. Recently, we presented a cell model that realizes Rosen's formal model, based on Hofmeyr's analysis of the functional organization of cell biochemistry and on Rosen's construction of the replication function. In this article we propose a cell model that, starting from the same biochemical processes, replaces the replication function with a set of semiotic relations between some of the elements that participate in cellular processes. The result is a cell model that constitutes a semiotic system that realizes closure to efficient causation: a semiotic (M, R) system. We compare the models of closure that correspond to the replicative (M, R) system and the semiotic (M, R) system. Additionally, we discuss the role that the genetic code and protein synthesis play in the semiotic closure to efficient causation. Finally, we outline the method to extend this analysis to more complex organisms.

细胞是一个实现有效因果关系闭合的符号系统:符号(m, r)系统。
罗伯特-罗森将有机体定义为封闭于有效因果关系的物质系统,并提出复制(M,R)系统作为有机体的模型。维加(2023)基于霍夫迈尔(2017)对细胞生化功能组织的分析和罗森对复制功能的构建,提出了一个实现罗森形式模型的细胞模型。在本文中,我们提出了一种细胞模型,从相同的生化过程出发,用参与细胞过程的一些元素之间的一系列符号关系取代了复制功能。结果,细胞模型构成了一个实现有效因果关系闭合的符号学系统:一个符号学(M,R)系统。我们比较了与复制(M,R)系统和符号(M,R)系统相对应的封闭模型。此外,我们还讨论了遗传密码和蛋白质合成在有效因果关系的符号学闭合中扮演的角色。最后,我们概述了将这一分析扩展到更复杂生物体的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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