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再锁:代谢网络中的相对最优性解释了对干扰的稳健代谢和调节响应。

RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations.

机构信息

Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, USA.

出版信息

Genome Biol. 2012 Jul 5;13(9):R78. doi: 10.1186/gb-2012-13-9-r78.

Abstract

Predicting cellular responses to perturbations is an important task in systems biology. We report a new approach, RELATCH, which uses flux and gene expression data from a reference state to predict metabolic responses in a genetically or environmentally perturbed state. Using the concept of relative optimality, which considers relative flux changes from a reference state, we hypothesize a relative metabolic flux pattern is maintained from one state to another, and that cells adapt to perturbations using metabolic and regulatory reprogramming to preserve this relative flux pattern. This constraint-based approach will have broad utility where predictions of metabolic responses are needed.

摘要

预测细胞对扰动的反应是系统生物学中的一项重要任务。我们报告了一种新方法 RELATCH,它使用参考状态下的通量和基因表达数据来预测遗传或环境扰动状态下的代谢反应。我们使用相对最优性的概念,即考虑从参考状态的相对通量变化,假设从一个状态到另一个状态保持相对代谢通量模式,并且细胞通过代谢和调控重编程来适应扰动,以保持这种相对通量模式。这种基于约束的方法将在需要预测代谢反应的情况下具有广泛的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e66/3506949/dbccee281569/gb-2012-13-9-r78-1.jpg

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