Seed bioinformatics.
Seed bioinformatics.
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种子生物信息学。
DOI：
10.1007/978-1-61779-231-1_23
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Bassel GW
中科院分区：
文献类型：
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作者：
Bassel GW
基因表达数据集的分析是一个强有力的工具，基因功能预测，顺式元件的发现，和假设生成的模式植物拟南芥，最近为其他农业相关物种。在拟南芥的情况下，由个别研究人员进行的记录其转录组的实验已经导致了大量的数据集被公开，用于所谓的“电子北方”，共表达分析和其他方法的数据挖掘。鉴于大约50%的基因在“常规”同源性搜索中没有功能，只有大约10%的基因在实验室中通过实验确定了它们的功能，这些分析可以加速识别潜在的基因功能。本章介绍了生物信息学数据挖掘工具的使用，这些工具可在生物阵列资源（ http://www.bar.utoronto.ca ）和其他地方的假设产生的背景下，种子生物学。
Analysis of gene expression data sets is a potent tool for gene function prediction,cis-element discovery, and hypothesis generation for the model plantArabidopsis thaliana, and more recently for other agriculturally relevant species. In the case ofArabidopsis thaliana, experiments conducted by individual researchers to document its transcriptome have led to large numbers of data sets being made publicly available for data mining by the so-called “electronic northerns,” co-expression analysis and other methods. Given that approximately 50% of the genes inArabidopsishave no function ascribed to them by “conventional” homology searches, and that only around 10% of the genes have had their function experimentally determined in the laboratory, these analyses can accelerate the identification of potential gene function at the click of a mouse. This chapter covers the use of bioinformatic data mining tools available at the Bio-Array Resource ( http://www.bar.utoronto.ca ) and elsewhere for hypothesis generation in the context of seed biology.