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Abstract：
Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism\'s genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.
摘要：
生物学依赖于中心论点，即生物体中的基因编码分子机制，该机制与来自环境的刺激和原材料相结合，以创建代表基因组编程的最终表型表达。虽然概念简单，真核生物中基因型与表型的联系依赖于数千个基因与环境之间的相互作用,其复杂性水平可能不可知.现代生物学已经转向在系统生物学中使用网络，试图简化这种复杂性，以解码生物体的基因组是如何工作的。以前,生物网络是组织的基本方式，简化，并分析数据。然而,最近的进步使网络能够超越描述，成为自己的表型或假设。这篇综述讨论了这些努力，比如绘制跨生物尺度的反应，包括蜂窝实体之间的关系，以及直接使用网络作为特征或假设。
