Methods of Metabolite Identification Using MS/MS Data
Methods of Metabolite Identification Using MS/MS Data
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DOI：
10.1080/08874417.2019.1681328
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发表时间：
2019-11
影响因子：
2.8
通讯作者：
M. Kwak;Kyung-Woo Kang;Yingfeng Wang
中科院分区：
文献类型：
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作者：
M. Kwak;Kyung-Woo Kang;Yingfeng Wang
**摘要** 生物信息学和医学科学领域的研究人员一直在利用新兴技术开发各种创新的信息系统和软件工具。代谢物谱分析是生物信息学研究人员大力开发各种创新方法和软件工具的领域之一。代谢物是新陈代谢的中间产物和最终产物，新陈代谢是生物体内维持生命的一系列化学反应。准确和完整地识别代谢物能够通过提供一种观察代谢活动的直接方式来推动许多医学科学和生物信息学领域的发展。串联质谱（MS/MS）数据的分析一直是生物信息学中一个长期的计算难题。本研究考察了用于分析MS/MS数据以识别代谢物的各种现有和新兴的方法及软件工具，并讨论了这一重要的生物信息学研究领域所面临的挑战和未来展望。
ABSTRACT Researchers in bioinformatics and medical science fields have been developing various innovative information systems and software tools using emerging technologies. Metabolite profiling is one of the fields in which bioinformatics researchers are intensely developing various innovative methods and software tools. Metabolites are the intermediate and end products of metabolism, which is the set of life-sustaining chemical reactions in living organisms. Accurate and complete identification of metabolites can advance many medical science and bioinformatics fields by providing a direct way of observing metabolic activities. The analysis of tandem mass spectrometry (MS/MS) data has been a long-term computational challenge in bioinformatics. This study examines various existing and emerging methods and software tools for analyzing MS/MS data for metabolite identification and discusses challenges and future perspectives in this important bioinformatics research area.