Fürtauer Lisa, Weiszmann Jakob, Weckwerth Wolfram, Nägele Thomas
Department of Ecogenomics and Systems Biology, Faculty of Life Sciences, University of Vienna, Vienna, Austria.
Vienna Metabolomics Center, University of Vienna, Vienna, Austria.
Methods Mol Biol. 2018;1778:329-347. doi: 10.1007/978-1-4939-7819-9_24.
The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.
对植物代谢组进行实验分析通常会产生一个全面的多维数据集。为了在生化调控和环境波动的背景下解读代谢组学数据，人们已经开发出各种数学建模方法，且已证明这些方法很有用。在本章中，将对数学建模进行一般性介绍，并结合植物代谢进行讨论。特别关注数学方法在功能上整合植物代谢组学数据于代谢网络中并将其与其他生化或生理参数相结合的适用性。
