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植物转录网络图谱绘制:新型生物学机制的数据驱动式发现。

Mapping Transcriptional Networks in Plants: Data-Driven Discovery of Novel Biological Mechanisms.

机构信息

Department of Plant Biology and Genome Center, University of California, Davis, California 95616; email:

出版信息

Annu Rev Plant Biol. 2016 Apr 29;67:575-94. doi: 10.1146/annurev-arplant-043015-112205. Epub 2016 Jan 25.

Abstract

In plants, systems biology approaches have led to the generation of a variety of large data sets. Many of these data are created to elucidate gene expression profiles and their corresponding transcriptional regulatory mechanisms across a range of tissue types, organs, and environmental conditions. In an effort to map the complexity of this transcriptional regulatory control, several types of experimental assays have been used to map transcriptional regulatory networks. In this review, we discuss how these methods can be best used to identify novel biological mechanisms by focusing on the appropriate biological context. Translating network biology back to gene function in the plant, however, remains a challenge. We emphasize the need for validation and insight into the underlying biological processes to successfully exploit systems approaches in an effort to determine the emergent properties revealed by network analyses.

摘要

在植物中,系统生物学方法已经产生了各种大型数据集。其中许多数据旨在阐明各种组织类型、器官和环境条件下的基因表达谱及其相应的转录调控机制。为了绘制这种转录调控控制的复杂性图谱,已经使用了几种类型的实验测定来绘制转录调控网络。在这篇综述中,我们通过关注适当的生物学背景,讨论了如何最好地利用这些方法来识别新的生物学机制。然而,将网络生物学转化回植物中的基因功能仍然是一个挑战。我们强调需要对基础生物学过程进行验证和深入了解,以便成功利用系统方法来确定网络分析所揭示的新兴特性。

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