项目名称: 磷酸化肽质谱鉴定中的算法问题研究
项目编号: No.30800189
项目类型: 青年科学基金项目
立项/批准年度: 2009
项目学科: 金属学与金属工艺
项目作者: 孙世伟
作者单位: 中国科学院计算技术研究所
项目金额: 20万元
中文摘要: 蛋白质磷酸化修饰由于具有调控蛋白质活性和功能的重要作用而受到关注。质谱技术是大规模磷酸化蛋白鉴定主要手段。目前,基于质谱数据的磷酸化蛋白和肽段的专门搜索软件发展的并不完善。课题从蛋白质组水平上研究磷酸化肽大规模鉴定及分析的技术和方法。在肽段及磷酸化肽段的质谱鉴定过程中,主要有两个重要问题,第一是实验谱的噪音处理问题;第二是在鉴定过程中的理论谱生成问题,另外,为了提高准确率,还有多数据融合问题,本课题中,我们分别对这三个问题进行了研究,具体研究实验质谱预处理方法、磷酸化肽的判别分析、磷酸化位点的鉴定等方面的关键问题,建立一套高效可行的磷酸化肽的鉴定方法,开发出一套实用的分析算法和软件,为蛋白质组计划中磷酸化蛋白分析提供有利的技术保障。
中文关键词: 质谱技术;蛋白质组学;磷酸化修饰;算法
英文摘要: Protein post-translational modication plays an important role in organism. Phosphorylation is one of the most important PTMs(post-translational modications). Studying the fragmentation patterns of Phosphorylated peptides is helpful to phospho-peptide identication and validation. Nowdays, the search engines of peptide and PTM-peptide identification based on the MSMS is not satisfactory. We analysis the technology and method about large scale identification of phosphorylated peptides. During the process of identification, there are two major questions, the first is the deletion the noise peaks, the second is how to predict the theory spectrum for peptide correctly.How to use the data fusion method to improve the correctness of the identification. In this project, we research into these three questions, Concrete research content including following several aspects pretreatment of experimental spectrum, prediction of theory spectrum, phosphorylate site identification. We developed a Efficient and feasible model of identification of MSMS spectra and developed a software package named PI. This software provides a efficient platform for Phosphorylated peptides and proteins identification.
英文关键词: mass-spectrometric technique; proteomics;phosphorylated peptides; algorithm;