De Keersmaecker Sigrid C J, Thijs Inge M V, Vanderleyden Jos, Marchal Kathleen
Centre of Microbial and Plant Genetics (CMPG) Katholieke Universiteit Leuven, Kasteelpark Arenberg 20, Belgium.
Mol Microbiol. 2006 Dec;62(5):1239-50. doi: 10.1111/j.1365-2958.2006.05453.x. Epub 2006 Oct 16.
In the current omics era, innovative high-throughput technologies allow measuring temporal and conditional changes at various cellular levels. Although individual analysis of each of these omics data undoubtedly results into interesting findings, it is only by integrating them that gaining a global insight into cellular behaviour can be aimed at. A systems approach thus is predicated on data integration. However, because of the complexity of biological systems and the specificities of the data-generating technologies (noisiness, heterogeneity, etc.), integrating omics data in an attempt to reconstruct signalling networks is not trivial. Developing its methodologies constitutes a major research challenge. Besides for their intrinsic value towards health care, environment and industry, prokaryotes are ideal model systems to further develop these methods because of their lower regulatory complexity compared with eukaryotes, and the ease with which they can be manipulated. Several successful examples outlined in this review already show the potential of the systems approach for both fundamental and industrial applications, which would be time-consuming or impossible to develop solely through traditional reductionist approaches.
在当前的组学时代，创新的高通量技术能够在各种细胞水平上测量时间和条件变化。虽然对这些组学数据中的每一个进行单独分析无疑会产生有趣的发现，但只有通过整合它们，才能旨在全面洞察细胞行为。因此，系统方法基于数据整合。然而，由于生物系统的复杂性和数据生成技术的特殊性（噪声、异质性等），整合组学数据以重建信号网络并非易事。开发其方法构成了一项重大研究挑战。除了对医疗保健、环境和工业具有内在价值外，原核生物因其与真核生物相比调控复杂性较低且易于操作，是进一步开发这些方法的理想模型系统。本综述中概述的几个成功例子已经展示了系统方法在基础和工业应用方面的潜力，而这些应用仅通过传统的还原论方法开发将耗时或不可能实现。
