转录组学

后基因组学时代的基因组学、转录组学、蛋白质组学及代谢物组学等为代谢工程的发展提供了极好的机遇。

In the post-genomic era , genomics , transcriptomics , proteomics and metabolomics provide great opportunity for the development of metabolic engineering .

因此它被广泛地用作序列描述与注释、系统发生、基因组学、转录组学和蛋白质组学研究的一个起始步骤。

It is thus widely used as an initial step for sequence characterization and annotation , phylogeny , genomics , transcriptomics , and proteomics studies .

其次，利用双向电泳技术研究了水稻根中蛋白质对氮和CTK的响应。此外，还利用蛋白质组和转录组学技术分析了氮肥对水稻穗发育过程中基因表达的影响，并筛选差异表达基因。

In addition , the proteome of root response to nitrogen / CTK were studied by two-dimensional electrophoresis , and the differentially expressed genes response to nitrogen fertilizer were found by the techniques of proteome and transcriptome .

代谢组学是继基因组学、转录组学和蛋白质组学之后在学术界兴起的又一门新兴系统生物学分支。

Metabolomics is a rising branch of the systems biology methodology after genomics and proteomics .

完整的基因组注释可以为后续的比较基因组学、重测序和转录组学研究提供更可靠的信息。

A completed genome annotation would provide more reliable information for subsequent study of comparative genomics , resequencing , and transcriptomics .

代谢组学是一门在新陈代谢的动态进程中系统研究代谢产物的变化特征，揭示机体生命活动代谢本质的科学，是继基因组学、转录组学和蛋白质组学之后，系统生物学的重要组成部分。

Metabolomics is a science of the study of metabolite profiles of the organism in life activity process , is important component of systems biology .

一方面，基因组学、蛋白质组学、转录组学、代谢组学、生物信息学、系统生物学等新兴学科的崛起与发展，为药物发现提供更为广泛而深刻的理论基础；

On the one hand , the theoretics of drug discovery become more comprehensive and more profound as the development of numerous new disciplines such as genomics , proteomics , transcriptomics , metabonomics , bioinformatics and system biology ;

为了解释供氧水平与腺苷生产之间的关系，我们用转录组学方法系统地分析了供氧对枯草杆菌基因表达和代谢的影响。

Herein , for better understanding the relationship between oxygen supply and adenosine productivity in B. subtilis , we sought to systematically explore the effect of DO on genetic regulation and metabolism through transcriptome analysis by using gene microarray .

结构基因组学、蛋白质组学和转录物组学的研究产生了大量关于基因表达和蛋白质表达的数据，但同时，它们与功能基因组学的研究相比也显示出了局限性。

Although structural genomics , proteomics and transcriptomics yield vast amounts of date about the expression of genes and proteins , they are still under pressure to infer gene function .