用 SysML 分析细菌趋化控制过程

James D. Johansen
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摘要

本文利用系统建模语言(SysML)对细菌趋化控制过程进行研究,利用定义明确、经过验证的工程工具对复杂系统进行架构、分析和改进。它提出了一种称为逆向工程面向对象系统工程方法(RE-OOSEM)的新方法,可将描述性生物学研究信息转换为描述性系统工程信息。它利用 SysML 和基于模型的系统工程(MBSE)从生物系统知识中捕捉系统结构,并将其输入系统工程工具。从工程学的角度来看,这样可以更深入地了解生物系统是如何运行的,并提出需要多少模型细节来揭示自上而下的系统理解。RE-OOSEM 方法为 SysML 趋化控制捕捉过程提供指导。使用 SysML 语法代替生物语法,便于从工程系统的角度分析生物趋化控制系统。该模型可作为脚手架,帮助揭示系统功能、系统组件和过程的关系以及生物信息表型和基因型的相关性。其中包括一个基于 SysML 架构模型的可执行 MathWorks Stateflow 趋化控制过程模型。结果显示了以下工程角度的观察结果。(1) 有几个控制组件不是专用的,而是在需要时可用和利用的。(2) 单个化学感受器作为传感器阵列共同发挥作用。(3) 磷酸盐基团是一种信号机制。(4) 通过化学感受器的 CH3 基团进行甲基化,导致敏感性适应。(5) 利用配体键、磷酸化和甲基化协同进行闭环控制。(6) 通过控制子过程的时间关系,可以了解系统的结构。
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Bacterial chemotaxis control process analysis with SysML
This paper looks at the bacteria chemotaxis control process utilizing the System Modeling Language (SysML) to leverage well‐defined and proven engineering tools for architecting, analyzing, and refining complex systems. It proposes a new methodology called reverse‐engineering object‐oriented systems engineering method (RE‐OOSEM) that converts descriptive biology research information into descriptive systems engineering information. It utilizes SysML and model‐based systems engineering (MBSE) to capture system architecture from biological system knowledge and inputs them into systems engineering tools. From an engineering point of view, this allows greater insight into how biological systems operate and suggests how much model detail is required to uncover a top‐down system understanding. RE‐OOSEM methodology guides the SysML chemotaxis control capture process. SysML syntax is used instead of biological syntax to facilitate biological chemotaxis control system analysis from an engineered system point of view. The model can act as a scaffolding to help uncover system function, the relationships of system components and processes, and bioinformatic phenotype and genotype correlation. An executable MathWorks Stateflow chemotaxis control process model based on the SysML architectural model is included. The results show the following engineering perspective observations. (1) Several control components are not dedicated but are available and utilized when needed. (2) Individual chemoreceptors act together as a sensor array. (3) Phosphate groups act as a signaling mechanism. (4) Methylation via CH3 groups of the chemoreceptor results in sensitivity adaptation. (5) Closed‐loop control collaboratively utilizes ligand bonding, phosphorylation, and methylation. (6) Timing relationships of the control subprocesses give insight into the system's architecture.
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