Department of Plant Biology and Genome Center, University of California, Davis, Davis, CA, USA.
Department of Cell & Systems Biology/Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, ON, Canada.
Methods Mol Biol. 2021;2200:25-89. doi: 10.1007/978-1-0716-0880-7_2.
Bioinformatic tools are now an everyday part of a plant researcher's collection of protocols. They allow almost instantaneous access to large data sets encompassing genomes, transcriptomes, proteomes, epigenomes, and other "-omes," which are now being generated with increasing speed and decreasing cost. With the appropriate queries, such tools can generate quality hypotheses, sometimes without the need for new experimental data. In this chapter, we will investigate some of the tools used for examining gene expression and coexpression patterns, performing promoter analyses and functional classification enrichment for sets of genes, and exploring protein-protein and protein-DNA interactions in Arabidopsis. We will also cover additional tools that allow integration of data from several sources for improved hypothesis generation.
生物信息学工具现在是植物研究人员实验方案中不可或缺的一部分。它们可以几乎即时地访问包含基因组、转录组、蛋白质组、表观基因组和其他“组学”的大型数据集,这些数据集现在正在以越来越快的速度和越来越低的成本生成。通过适当的查询,这些工具可以生成高质量的假设,有时甚至不需要新的实验数据。在本章中,我们将研究一些用于检查基因表达和共表达模式、进行启动子分析和功能分类富集的工具,以及探索拟南芥中的蛋白质-蛋白质和蛋白质-DNA 相互作用。我们还将介绍其他允许整合来自多个来源的数据以提高假设生成能力的工具。