开发实验室和计算技术,以优化和定量理解细胞代谢网络

Xiao-Jiang Feng, J. Rabinowitz, H. Rabitz
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摘要

本文总结了实验室和计算技术的发展,以系统和可靠地了解代谢网络。通过结合基于过滤器的细胞培养系统和优化的代谢物提取方案,可以在营养和其他环境扰动后可靠地定量大量细胞代谢物。提出了一种非线性闭环辨识方法。计算插图和实验室应用清楚地证明了这些技术在理解细胞代谢方面的能力,特别是当它们以最佳方式集成时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of laboratory and computational techniques for optimal and quantitative understanding of cellular metabolic networks
This paper summarizes the development of laboratory and computational techniques for systematic and reliable understanding of metabolic networks. By combining a filter-based cell culture system and an optimized metabolite extraction protocol, a broad array of cellular metabolites can be reliably quantified following nutrient and other environment perturbations. A nonlinear closed-loop procedure was also developed for optimal bionetwork model identification. Computational illustrations and laboratory applications clearly demonstrate the capabilities of these techniques in understanding cellular metabolism, especially when they are integrated in an optimal fashion.
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