同步、异步和最宽容语义下的布尔网络与反应系统的融合

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Natural Computing Pub Date : 2024-07-17 DOI:10.1007/s11047-024-09990-5
Roberto Bruni, Roberta Gori, Paolo Milazzo, Hélène Siboulet
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引用次数: 0

摘要

本文将两个众所周知的表示生物系统的计算框架紧密联系起来,以促进它们之间技术的无缝转移。布尔网络是生物学家采用的一种成熟的形式主义。人们根据不同的(同步和异步)更新语义对它们进行了研究,从而能够观察和描述系统行为的不同方面。最近,有人为布尔网络提出了一种新的语义,称为 "最允许语义"(most permissive semantics),可以更忠实地表达生物现象。反应系统提供了一种简化的形式主义,其灵感来自于活细胞中的生化反应。反应系统支持各种分析技术,有助于深入了解潜在的生物现象。我们的目标是利用现有的工具包,在布尔网络领域内预测和理解反应系统的行为。在本文中,我们首先将反应系统的行为扩展到几种异步语义,包括最宽松语义,然后证明布尔网络和反应系统在同步、一般/完全异步和最宽松语义下表现出同构行为。
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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Melding Boolean networks and reaction systems under synchronous, asynchronous and most permissive semantics

This paper forges a strong connection between two well known computational frameworks for representing biological systems, in order to facilitate the seamless transfer of techniques between them. Boolean networks are a well established formalism employed from biologists. They have been studied under different (synchronous and asynchronous) update semantics, enabling the observation and characterisation of distinct facets of system behaviour. Recently, a new semantics for Boolean networks has been proposed, called most permissive semantics, that enables a more faithful representation of biological phenomena. Reaction systems offer a streamlined formalism inspired by biochemical reactions in living cells. Reaction systems support a full range of analysis techniques that can help for gaining deeper insights into the underlying biological phenomena. Our goal is to leverage the available toolkit for predicting and comprehending the behaviour of reaction systems within the realm of Boolean networks. In this paper, we first extend the behaviour of reaction systems to several asynchronous semantics, including the most permissive one, and then we demonstrate that Boolean networks and reaction systems exhibit isomorphic behaviours under the synchronous, general/fully asynchronous and most permissive semantics.

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来源期刊
Natural Computing
Natural Computing Computer Science-Computer Science Applications
CiteScore
4.40
自引率
4.80%
发文量
49
审稿时长
3 months
期刊介绍: The journal is soliciting papers on all aspects of natural computing. Because of the interdisciplinary character of the journal a special effort will be made to solicit survey, review, and tutorial papers which would make research trends in a given subarea more accessible to the broad audience of the journal.
期刊最新文献
Real-time computing and robust memory with deterministic chemical reaction networks Integrated dynamic spiking neural P systems for fault line selection in distribution network Reaction mining for reaction systems Melding Boolean networks and reaction systems under synchronous, asynchronous and most permissive semantics Distinguishing genelet circuit input pulses via a pulse detector
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