Austrian Centre of Industrial Biotechnology, Vienna, Austria; Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria.
Biotechnol J. 2013 Sep;8(9):1009-16. doi: 10.1002/biot.201200269. Epub 2013 Jun 21.
Elementary flux mode (EFM) analysis allows the unbiased decomposition of a metabolic network into minimal functional units, making it a powerful tool for metabolic engineering. While the use of EFM analysis (EFMA) is still limited by the size of the models it can handle, EFMA has been successfully applied to solve real-world metabolic engineering problems. Here we provide a user-oriented introduction to EFMA, provide examples of recent applications, analyze current research strategies to overcome the computational restrictions and give an overview over current approaches, which aim to identify and calculate only biologically relevant EFMs.
基本通量模式(EFM)分析可以将代谢网络无偏地分解为最小的功能单元,是代谢工程的有力工具。尽管 EFM 分析(EFMA)的使用仍然受到其能够处理的模型大小的限制,但 EFMA 已成功应用于解决实际的代谢工程问题。在这里,我们提供了一个面向用户的 EFMA 介绍,提供了最近应用的例子,分析了克服计算限制的当前研究策略,并概述了当前的方法,这些方法旨在仅识别和计算生物学上相关的 EFMs。