化学网络中的路径可实现性。

IF 1.4 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Journal of Computational Biology Pub Date : 2025-02-01 Epub Date: 2025-02-03 DOI:10.1089/cmb.2024.0521
Jakob L Andersen, Sissel Banke, Rolf Fagerberg, Christoph Flamm, Daniel Merkle, Peter F Stadler
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引用次数: 0

摘要

探索具有特定功能的途径和替代途径在许多化学环境中都很有趣。以前已经开发了一个用于指定和搜索路径的框架,但是缺乏对许多路径解决方案中哪些是可实现的或可以实现的关注。可实现的意思是,实际上存在一些反应的顺序,这些反应将执行该途径。提出了一种基于Petri网可达性问题的路径可实现性分析方法。对于可实现的路径,我们的方法还提供了一个编码反应顺序的证书,从而实现了该路径。我们提出了途径可实现性的两个扩展概念,其中一个与网络催化剂的概念有关。我们举例说明了我们在戊糖磷酸途径上的发现。此外,我们讨论了我们的概念的相关性,以阐明在描绘路径时通常隐含地做出的选择。最后,为可变现性的数学理论奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pathway Realizability in Chemical Networks.

The exploration of pathways and alternative pathways that have a specific function is of interest in numerous chemical contexts. A framework for specifying and searching for pathways has previously been developed, but a focus on which of the many pathway solutions are realizable, or can be made realizable, is missing. Realizable here means that there actually exists some sequencing of the reactions of the pathway that will execute the pathway. We present a method for analyzing the realizability of pathways based on the reachability question in Petri nets. For realizable pathways, our method also provides a certificate encoding an order of the reactions, which realizes the pathway. We present two extended notions of realizability of pathways, one of which is related to the concept of network catalysts. We exemplify our findings on the pentose phosphate pathway. Furthermore, we discuss the relevance of our concepts for elucidating the choices often implicitly made when depicting pathways. Lastly, we lay the foundation for the mathematical theory of realizability.

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来源期刊
Journal of Computational Biology
Journal of Computational Biology 生物-计算机:跨学科应用
CiteScore
3.60
自引率
5.90%
发文量
113
审稿时长
6-12 weeks
期刊介绍: Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics. Journal of Computational Biology coverage includes: -Genomics -Mathematical modeling and simulation -Distributed and parallel biological computing -Designing biological databases -Pattern matching and pattern detection -Linking disparate databases and data -New tools for computational biology -Relational and object-oriented database technology for bioinformatics -Biological expert system design and use -Reasoning by analogy, hypothesis formation, and testing by machine -Management of biological databases
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