中文摘要：

随着蛋白质组学研究的不断深入，基于质谱的选择反应监测技术（SRM）已经成为以发现生物标志物为代表的定向蛋白质组学研究的重要手段．SRM技术根据假设信息，特异性地获取符合假设条件的质谱信号，去除不符合条件的离子信号干扰，从而得到特定蛋白质的定量信息．SRM技术具有更高的灵敏度和精确性、更大的动态范围等优势．该技术可分为实验设计、数据获取和数据分析三个步骤．在这几个步骤中，最重要的是利用生物信息学手段总结当前实验数据的结果，并用机器学习方法和总结的经验规则进行SRM实验的母离子和子离子对的预测．针对数据质控和定量的生物信息学方法研究在提高SRM数据可靠性方面具有重要作用．此外，为方便SRM的研究，本文还收集、汇总了SRM技术相关的软件、工具和数据库资源．随着质谱仪器的不断发展，新的SRM实验策略以及分析方法、计算工具也应运而生．结合更优化的实验策略、方法，采用更精准的生物信息学算法和工具，SRM在未来蛋白质组学的发展中将发挥更加重要的作用．

英文摘要：

Selected reaction monitoring（SRM） is one of the major approaches in targeted proteomics researches which mainly focus on the discovery of biomarkers. According to the research purpose, the specific proteins and peptides are selected before an SRM experiment. SRM increases the sensitivity, the accuracy and the dynamic range during the analysis especially in the detection capabilities of low abundance proteins and peptides. A typical SRM experiment includes three steps： experiment design; MS data acquisition; data validation and quantification. Among the three steps, it is vital to predict the special peptides and fragment ions using bioinformatics methods. The validation and quantification of the SRM data are also important to SRM data analysis. Meanwhile, the corresponding sottwares, tools and databases are summarized. New experiments strategies and new bioinformatics tools are generated along with the developments of SRM instruments. Using improved experiment strategies, parameters and better quantitative algorithms as well as more sophisticated bioinformatics tools, SRM will play a more important role in the future ofproteomics research.