Department of Chemistry, University of Kansas, 1251 Wescoe Hall Drive, Lawrence, KS 66045, USA.
J Neuroimmune Pharmacol. 2010 Mar;5(1):18-30. doi: 10.1007/s11481-009-9157-3. Epub 2009 May 7.
Metabolomics is the characterization, identification, and quantitation of metabolites resulting from a wide range of biochemical processes in living systems. Its rapid development over the past few years has increased the demands for bioinformatics and cheminformatics resources that span from data processing tools, comprehensive databases, statistical tools, and computational tools for modeling metabolic networks. With the wealth of information that is being amassed, new types of metabolomic databases are emerging that are not only designed to store, manage, and analyze metabolomic data but are also designed to serve as gateways to the vast information space of metabolism in living systems. At present, metabolomics is underpinned by a number of freely and commercially available databases that provide information on the chemical structures, physicochemical and pharmacological properties, spectral profiles, experimental workflows, and biological functions of metabolites. This review provides an overview of the recent progress in databases employed in metabolomics.
代谢组学是对生物系统中广泛的生化过程产生的代谢物进行特征描述、鉴定和定量的科学。在过去几年中，代谢组学的快速发展增加了对生物信息学和化学信息学资源的需求，这些资源涵盖了从数据处理工具、综合数据库、统计工具到代谢网络建模的计算工具。随着信息的积累，出现了新的代谢组学数据库类型，这些数据库不仅旨在存储、管理和分析代谢组学数据，而且还旨在作为通往生物系统代谢广阔信息空间的门户。目前，代谢组学有许多免费和商业可用的数据库作为支撑，这些数据库提供了关于代谢物的化学结构、物理化学和药理学特性、光谱特征、实验工作流程以及生物学功能的信息。本文综述了代谢组学中使用的数据库的最新进展。
