Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future.
Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future.
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DOI：
10.1002/jms.3780
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发表时间：
2016-08
期刊：
影响因子：
--
通讯作者：
Tiwari HK
中科院分区：
文献类型：
--
作者：
Barnes S;Benton HP;Casazza K;Cooper SJ;Cui X;Du X;Engler J;Kabarowski JH;Li S;Pathmasiri W;Prasain JK;Renfrow MB;Tiwari HK
代谢组学是一门系统生物学学科，代表了对已知和未知代谢途径的分析，在过去的20年里发展迅速。由于其综合性，代谢组学需要仔细考虑所提出的问题，回答问题所需的规模，样本标本的收集和储存，从生物基质中提取代谢物的方法，所采用的分析方法和分析的质量控制，收集的数据如何相互关联，统计学方法，以确定代谢物发生重大变化，代谢物的推定鉴定，并使用稳定同位素，以帮助验证代谢物的身份和建立途径连接和流量。代谢组学方法的全面描述的第二部分集中在数据分析，代谢组学的新兴方法和这门学科的未来。
Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline.
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