Morgenthal K, Weckwerth W, Steuer R
Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, 14476 Postdam, Germany.
Biosystems. 2006 Feb-Mar;83(2-3):108-17. doi: 10.1016/j.biosystems.2005.05.017. Epub 2005 Nov 21.
Nowadays techniques for non-targeted metabolite profiling allow for the generation of huge amounts of relevant data essential for the construction of dynamic metabolomic networks. Thus, metabolomics, besides transcriptomics or proteomics, provides a major tool for the characterization of postgenomic processes. In this work, we introduce comparative correlation analysis as a complementary approach to characterize the physiological states of various organs of diverse plant species with focus on specific participation of metabolites in different reaction networks. The correlations observed are induced by diminutive fluctuations in environmental conditions, which propagate through the system and induce specific patterns depending on the genomic background. In order to examine this hypothesis, numeric examples of such fluctuations are computed and compared with experimentally obtained metabolite data.
如今，非靶向代谢物谱分析技术能够生成大量对于构建动态代谢组网络至关重要的相关数据。因此，代谢组学除了转录组学或蛋白质组学之外，还为后基因组过程的表征提供了一个主要工具。在这项工作中，我们引入比较相关性分析作为一种补充方法，以表征不同植物物种各种器官的生理状态，重点关注代谢物在不同反应网络中的特定参与情况。观察到的相关性是由环境条件的微小波动引起的，这些波动通过系统传播，并根据基因组背景诱导特定模式。为了检验这一假设，计算了此类波动的数值示例，并与实验获得的代谢物数据进行了比较。
