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Mass Spectrometry, Proteomics, Data Mining Strategies and Their Applications in Infectious Disease Research

机译:质谱,蛋白质组学,数据挖掘策略及其在传染病研究中的应用

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摘要

The ultimate goal of proteome research is the comprehensive description of all proteins present in a given sample using qualitative, quantitative and functional metrics. Traditionally, protein mixtures were first separated by two-dimensional gel electrophoresis and spots of interest were excised, in-gel digested and analyzed by mass spectrometry (MS). In most cases, protein identification was done by MALDI-TOF-MS (matrix-assisted laser desorption/ionization time-of-flight). The methodology is time consuming and rarely leads to a comprehensive description of the analyzed proteome. Over the last years shot-gun expression profiling methodologies were developed and can identify thousands of proteins in complex biological samples in a single experiment. We will provide a short historic overview of proteome research and mass spectrometry technologies currently used in the systems biology community. In particular, we will summarize the developments and applications of shot-gun proteomics and allied computational data mining tools to medical research and infectious disease research.
机译:蛋白质组学研究的最终目标是使用定性,定量和功能指标对给定样品中存在的所有蛋白质进行全面描述。传统上,首先通过二维凝胶电泳分离蛋白质混合物,然后切下感兴趣的斑点,进行凝胶内消化,并通过质谱(MS)分析。在大多数情况下,蛋白质鉴定是通过MALDI-TOF-MS(基质辅助激光解吸/电离飞行时间)进行的。该方法耗时且很少导致对所分析蛋白质组的全面描述。在过去的几年中,开发了shot弹枪表达谱分析方法,可在一次实验中鉴定出复杂生物样品中的数千种蛋白质。我们将提供系统生物学界当前使用的蛋白质组研究和质谱技术的简短历史概述。特别是,我们将总结of弹蛋白质组学和相关的计算数据挖掘工具在医学研究和传染病研究中的发展和应用。

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