May Patrick, Christian Nils, Ebenhöh Oliver, Weckwerth Wolfram, Walther Dirk
Max-Planck-Institute for Molecular Plant Physiology, Potsdam-Golm, Germany.
Methods Mol Biol. 2011;694:341-63. doi: 10.1007/978-1-60761-977-2_21.
The integrated analysis of different omics-level data sets is most naturally performed in the context of common process or pathway association. In this chapter, the two basic approaches for a metabolic pathway-centric integration of proteomics and metabolomics data are described: the knowledge-based approach relying on existing metabolic pathway information, and a data-driven approach that aims to deduce functional (pathway) associations directly from the data. Relevant algorithmic approaches for the generation of metabolic networks of model organisms, their functional analysis, database resources, visualization and analysis tools will be described. The use of proteomics data in the process of metabolic network reconstruction will be discussed.
不同组学水平数据集的综合分析最自然地是在常见过程或途径关联的背景下进行的。在本章中，描述了以代谢途径为中心整合蛋白质组学和代谢组学数据的两种基本方法：基于现有代谢途径信息的基于知识的方法，以及旨在直接从数据中推断功能（途径）关联的数据驱动方法。将描述用于生成模式生物代谢网络、其功能分析、数据库资源、可视化和分析工具的相关算法方法。还将讨论在代谢网络重建过程中蛋白质组学数据的使用。
