Genome scale data on biological systems has increasingly become available by sequencing of DNA and RNA, and by mass spectrometric quantification of proteins and metabolites. The cellular components from which these -omics regimes are derived act as one integrated system in vivo; thus, there is a natural instinct to integrate -omics data types. Statistical analyses, the use of previous knowledge in the form of networks, and the use of time-resolved measurements are three key design elements for life scientists to consider in planning integrated -omics studies. These design elements are reviewed in the context of multiple recent systems biology studies that leverage data from different types of -omics analyses. While most of these studies rely on well-established model organisms, the concepts for integrating -omics data that were developed in these studies can help to enable systems research in the field of cancer biology.

中文翻译：

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组学的整合：不仅仅是各部分的总和

通过 DNA 和 RNA 测序以及蛋白质和代谢物的质谱定量，生物系统的基因组规模数据越来越可用。衍生出这些组学机制的细胞成分在体内充当一个集成系统；因此，有一种自然的本能来整合 -omics 数据类型。统计分析、以网络形式使用先前知识以及使用时间分辨测量是生命科学家在规划集成组学研究时要考虑的三个关键设计要素。这些设计元素在最近多项系统生物学研究的背景下进行了审查，这些研究利用了来自不同类型组学分析的数据。虽然大多数这些研究依赖于完善的模式生物，