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基于数据依赖性采集模式(DDA)的质谱分析是进行规模化蛋白质组学研究的常用方法。由于这类方法往往是液相色谱与质谱联用,因此肽段分离及其质量鉴定是该方法的核心指标。对于复杂肽段混合物而言,混合质谱图是广泛存在的;它们给肽段定性和定量都带来严重的问题。在当前的技术条件下,开发用于识别和分析混合质谱图的生物信息学工具是解决这一问题的可行方案。本文主要介绍了混合质谱图产生的原因和影响因素,以及识别和分析混合谱图的相关生物信息学工具的最新开发进展。
Mass spectrometry based on data-dependent acquisition mode (DDA) is a common method for conducting large-scale proteomics research. Due to the fact that such methods are often used in conjunction with LC / MS, the separation of peptides and their identification of quality are the key indicators of this method. For complex peptide mixtures, mixed mass spectra are widespread; they pose serious problems for both qualitative and quantitative peptide quantitation. Under current technical conditions, the development of bioinformatics tools for identifying and analyzing mixed-mass spectra is a viable solution to this problem. This article describes the causes and influencing factors of mixed mass spectrometry and the recent developments in bioinformatics tools that identify and analyze mixed spectra.