利用高解析度质谱数据开展定量分析，是基于质谱数据进行后续研究的重要内容。然而，现有流程中仍然存在几个问题：首先，从肽段定量到蛋白定量，业内尚未形成一套统一的准则，其方法仍存在一定争议。其次，定性分析和定量程序产出的结果中，无论是肽段还是蛋白，往往都无法完全匹配，从而在定性研究和定量之间产生了难以逾越的鸿沟。另外，鉴于质谱数据的谱图利用率，很多中低丰度蛋白得不到鉴定，更无法进行定量分析。而生物学上往往这些中低丰度蛋白的变化会给出重要的提示。因此，寻找到可靠的自动判读和计算中低丰度肽段信号的方法，可以更大程度地提高谱图利用率，挖掘出更多的信息。本研究的目的在于建立肽段离子流色谱峰面积、质谱仪参数与实际蛋白量之间的关系，并确立适于定量的质谱参数条件。特别是通过色谱保留时间锚定和回归，提高中低丰度蛋白的定量率。本项目将为开展利用基于高精度质谱数据进行蛋白无标定量的生物学研究，提供坚实而准确的保证。

Currently, Mass spectrometry is a routine technique with wide applications in biology. The increases in sensitivity and resolution of the instruments have opened new dimensions in analyses of biological research. However there are several problems needing to be solved in current process. First, there are no unified criteria for protein quantification based on peptide quantity; and sample volume, concentration, as well as gradient will affect the quantitative result. Second, mismatch appears to a certain extent between qualitative analysis and quantitative procedure. Both peptide list and protein list are not exactly the same, leading to a gap between the qualitative and quantitative proteomics. In addition, a large number of low abundance proteins cannot be identified or be quantified because of the feature of spectrum. However, these low abundance proteins often represent some biological hints of importance. Therefore, more information will be extracted if there is a reliable, automatic identify signals of low-abundance peptides and calculated extracted ion chromatography peak area, and consequently it will improve spectrum utilization greatly. .Our study will establish the relationship among peak area of peptide extracted ion chromatography, mass spectrometer parameters and actual amount of protein. Then we will establish the suitable parameters of the mass spectrum for quantitative research. Especially, we will improve the quantification of low-abundance protein based on retention time alignment and regression. It will be applied as an intuitive and accurate way to interpret MS data, and will be a useful tool for precise quantification of protein. And the process for label free quantification of low-abundance protein based on high-resolution mass spectrum will be helpful to biological research.