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Computational approaches to systems biology: Applications in xenobiotic metabolism and cellular signaling.

机译：系统生物学的计算方法：在异生物代谢和细胞信号传导中的应用。

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摘要

Systems biology attempts to identify interactions between the components of biological systems and understand how these interactions give rise to the physiological function of the system. This thesis describes the application of computational tools to study, on a system-wide level, metabolic reaction networks describing the biodegradation of xenobiotic compounds and a cellular signaling network involved in coordinating the cell's immune response to intracellular pathogens.;Microorganisms provide a wealth of potential in the reduction and elimination of xenobiotic compounds in the environment. In order to explore their biodedegradative capabilities, computational methods are needed to predict xenobiotic metabolism. In Part I, a framework for predictive biodegradation called BNICE is described and applied to generate novel xenobiotic biodegradation pathways. A thermodynamic analysis was used to estimate the relative energetic feasibility of the degradation routes. Additionally, metabolic flux analysis and thermodynamics-based metabolic flux analysis provided an estimate of the feasibility within the context of the cellular environment, probing how implementation of the novel pathways influences the physiology of the cell in a genomescale model of cellular metabolism. This work demonstrates the utility of computational tools to design and evaluate novel biodegradation pathways.;Mathematical models of cell signaling pathways provide insight into the system-level behavior of cellular signaling networks. In particular, it is important to understand the regulatory features of this network in order to design effective therapeutic interventions. Part II of this thesis describes the development and application of a model of the Interleukin-12 pathway, a cellular signaling network involved in mediating the cell's immune response. Chemical kinetic modeling, parameter estimation, and time scale analysis were applied to infer the regulatory mechanisms that govern signaling in the pathway. These tools provided insight into the biology of the cell signaling pathway and revealed the kinetic events that largely influenced the cellular immune response.
机译：系统生物学试图识别生物系统各组成部分之间的相互作用，并了解这些相互作用如何引起系统的生理功能。本论文描述了计算工具在系统范围内研究代谢反应网络（描述异种生物化合物的生物降解）和参与协调细胞对细胞内病原体免疫应答的细胞信号网络的应用。微生物提供了巨大的潜力减少和消除环境中的异源化合物。为了探索它们的生物降解能力，需要计算方法来预测异源生物的代谢。在第一部分中，描述了一种称为BNICE的预测性生物降解框架，并将其应用于生成新型异源生物降解途径。使用热力学分析来估计降解途径的相对能量可行性。此外，代谢通量分析和基于热力学的代谢通量分析提供了在细胞环境中可行性的估计，并探讨了新途径的实施如何影响细胞代谢基因组规模模型中的细胞生理。这项工作证明了设计和评估新型生物降解途径的计算工具的实用性。细胞信号通路的数学模型提供了对细胞信号网络系统级行为的洞察力。特别是，重要的是要了解此网络的监管功能，以设计有效的治疗干预措施。本论文的第二部分描述了白介素12途径模型的开发和应用，白细胞介素12途径是一种介导细胞免疫应答的细胞信号网络。应用化学动力学建模，参数估计和时标分析来推断控制该途径中信号传导的调节机制。这些工具提供了对细胞信号通路生物学的深入了解，并揭示了在很大程度上影响细胞免疫反应的动力学事件。

著录项

  • 作者

    Finley, Stacey Deleria.;

  • 作者单位

    Northwestern University.;

  • 授予单位 Northwestern University.;
  • 学科 Biology Systematic.;Engineering Chemical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 191 p.
  • 总页数 191
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:26

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