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后基因组时代的网络热力学。

Network thermodynamics in the post-genomic era.

机构信息

Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

出版信息

Curr Opin Microbiol. 2010 Jun;13(3):350-7. doi: 10.1016/j.mib.2010.03.001. Epub 2010 Apr 6.

Abstract

Network models have been used to study the underlying processes and principles of biological systems for decades, providing many insights into the complexity of life. Biological systems require a constant flow of free energy to drive these processes that operate away from thermodynamic equilibrium. With the advent of high-throughput omics technologies, more and more thermodynamic knowledge about the biological components, processes and their interactions are surfacing that we can integrate using large-scale biological network models. This allows us to ask many fundamental questions about these networks, such as, how far away from equilibrium must the reactions in a network be displaced in order to allow growth, or what are the possible thermodynamic objectives of the cell.

摘要

网络模型已被用于研究生物系统的基础过程和原理数十年,为理解生命的复杂性提供了许多洞见。生物系统需要不断的自由能流动来驱动这些远离热力学平衡的过程。随着高通量组学技术的出现,越来越多关于生物组分、过程及其相互作用的热力学知识逐渐浮现,我们可以利用大规模的生物网络模型来整合这些知识。这使我们能够对这些网络提出许多基本问题,例如,为了允许生长,网络中的反应必须偏离平衡多远,或者细胞的可能热力学目标是什么。

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