Misra Biswapriya B
Department of Internal Medicine, Section of Molecular Medicine, Medical Center Boulevard, Winston-Salem, NC, USA.
Electrophoresis. 2018 Apr;39(7):909-923. doi: 10.1002/elps.201700441. Epub 2018 Jan 25.
Rapid advances in mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based platforms for metabolomics have led to an upsurge of data every single year. Newer high-throughput platforms, hyphenated technologies, miniaturization, and tool kits in data acquisition efforts in metabolomics have led to additional challenges in metabolomics data pre-processing, analysis, interpretation, and integration. Thanks to the informatics, statistics, and computational community, new resources continue to develop for metabolomics researchers. The purpose of this review is to provide a summary of the metabolomics tools, software, and databases that were developed or improved during 2016-2017, thus, enabling readers, developers, and researchers access to a succinct but thorough list of resources for further improvisation, implementation, and application in due course of time.
基于质谱(MS)和核磁共振(NMR)的代谢组学平台的迅速发展,使得每年产生的数据量激增。代谢组学数据采集工作中更新的高通量平台、联用技术、小型化和工具包,给代谢组学数据的预处理、分析、解释和整合带来了更多挑战。得益于信息学、统计学和计算领域,代谢组学研究人员不断有新资源可供使用。本综述的目的是总结2016年至2017年期间开发或改进的代谢组学工具、软件和数据库,从而使读者、开发者和研究人员能够获取一份简洁而全面的资源列表,以便在未来适时进一步改进、实施和应用。