代谢组学
蛋白质组学
代谢组
计算生物学
生物
功能(生物学)
转录组
基因组学
系统生物学
生化工程
基因组
生物信息学
数据科学
计算机科学
电流(流体)
代谢工程
基因
遗传学
基因表达
作者
Katherine A. Hollywood,Daniel R. Brison,Royston Goodacre
出处
期刊:Proteomics
[Wiley]
日期:2006-08-25
卷期号:6 (17): 4716-4723
被引量:500
标识
DOI:10.1002/pmic.200600106
摘要
Abstract The ability to sequence whole genomes has taught us that our knowledge with respect to gene function is rather limited with typically 30–40% of open reading frames having no known function. Thus, within the life sciences there is a need for determination of the biological function of these so‐called orphan genes, some of which may be molecular targets for therapeutic intervention. The search for specific mRNA, proteins, or metabolites that can serve as diagnostic markers has also increased, as has the fact that these biomarkers may be useful in following and predicting disease progression or response to therapy. Functional analyses have become increasingly popular. They include investigations at the level of gene expression (transcriptomics), protein translation (proteomics) and more recently the metabolite network (metabolomics). This article provides an overview of metabolomics and discusses its complementary role with transcriptomics and proteomics, and within system biology. It highlights how metabolome analyses are conducted and how the highly complex data that are generated are analysed. Non‐invasive footprinting analysis is also discussed as this has many applications to in vitro cell systems. Finally, for studying biotic or abiotic stresses on animals, plants or microbes, we believe that metabolomics could very easily be applied to large populations, because this approach tends to be of higher throughput and generally lower cost than transcriptomics and proteomics, whilst also providing indications of which area of metabolism may be affected by external perturbation.
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