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系统生物学作为一个集成平台,融合了生物信息学、系统综合生物学和系统代谢工程。

Systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

机构信息

Laborotary of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, HsinChu 30013, Taiwan.

出版信息

Cells. 2013 Oct 11;2(4):635-88. doi: 10.3390/cells2040635.

Abstract

Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

摘要

系统生物学旨在实现对生物体的系统水平理解,并将这一知识应用于合成生物学、代谢工程和医学等各个领域。对生物体的系统水平理解可以通过深入了解以下方面来获得:(i)系统结构和生物网络的机制,如基因调控、蛋白质相互作用、信号转导和代谢途径;(ii)生物网络的系统动态,通过系统识别和系统分析方法来理解稳定性、鲁棒性和转导能力;(iii)生物网络不同层次的系统控制方法,为稳健控制系统状态、最小化故障提供了系统机制的理解,并为疾病治疗提供了潜在的治疗靶点;(iv)具有期望行为的生物网络的修改和构建的系统设计方法,为合成生物学设计和系统代谢工程提供了系统设计原则和系统模拟。本文综述了系统生物学、系统合成生物学和系统代谢工程在工程和生物学研究中的最新进展。我们还讨论了系统生物学的挑战和未来展望,以及系统生物学作为生物信息学、系统合成生物学和系统代谢工程的综合平台的概念。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/768f/3972654/c4814bafe54f/cells-02-00635-g001.jpg

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