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组学与网络的结合——利用系统方法推断植物中的调控网络。

Omics meet networks - using systems approaches to infer regulatory networks in plants.

机构信息

Duke University, Department of Biology and Center for Systems Biology, USA.

出版信息

Curr Opin Plant Biol. 2010 Apr;13(2):126-31. doi: 10.1016/j.pbi.2009.11.005. Epub 2009 Dec 28.

Abstract

Many genomic-scale datasets in plants have been generated over the last few years. This substantial achievement has led to impressive progress, including some of the most detailed molecular maps in any multicellular organism. Networks and pathways have been reconstructed using transcriptome, genome-wide transcription factor binding, proteome and metabolome data, and subsequently used to infer functional interactions among genes, proteins, and metabolites. However, more sophisticated systems biology approaches are needed to integrate different omics datasets. Ultimately, the integration of diverse and massive datasets into coherent models will improve our understanding of the molecular networks that underlie biological processes.

摘要

近年来,植物领域产生了许多基因组规模的数据集。这一巨大的成就带来了令人瞩目的进展,包括在任何多细胞生物中最详细的分子图谱之一。使用转录组、全基因组转录因子结合、蛋白质组和代谢组数据重建了网络和途径,随后用于推断基因、蛋白质和代谢物之间的功能相互作用。然而,需要更复杂的系统生物学方法来整合不同的组学数据集。最终,将不同的大规模数据集整合到一致的模型中,将提高我们对生物过程背后的分子网络的理解。

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