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Efficient discovery of abundant post-translational modifications and spectral pairs using peptide mass and retention time differences

机译:利用肽质量和保留时间差异,高效发现丰富的翻译后修饰和光谱对

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Background: Peptide identification via tandem mass spectrometry is the basic task of current proteomics research. Due to the complexity of mass spectra, the majority of mass spectra cannot be interpreted at present. The existence of unexpected or unknown protein posttranslational modifications is a major reason.Results: This paper describes an efficient and sequence database-independent approach to detecting abundant post-translational modifications in high-accuracy peptide mass spectra. The approach is based on the observation that the spectra of a modified peptide and its unmodified counterpart are correlated with each other in their peptide masses and retention time. Frequently occurring peptide mass differences in a data set imply possible modifications,while small and consistent retention time differences provide orthogonal supporting evidence.We propose to use a bivariate Gaussian mixture model to discriminate modification-related spectral pairs from random ones. Due to the use of two-dimensional information, accurate modification masses and confident spectral pairs can be determined as well as the quantitative influences of modifications on peptide retention time.Conclusions: Experiments on two glycoprotein data sets demonstrate that our method can effectively detect abundant modifications and spectral pairs. By including the discovered modifications into database search or by propagating peptide assignments between paired spectra, an average of 10% more spectra are interpreted.
机译:背景:通过串联质谱鉴定肽是当前蛋白质组学研究的基本任务。由于质谱的复杂性,目前大多数质谱无法解释。结果:本文描述了一种高效且独立于序列数据库的方法,可在高精度肽段质谱中检测大量的翻译后修饰。该方法基于以下观察结果:修饰的肽及其未修饰的对应物的光谱在其肽质量和保留时间上相互关联。数据集中经常出现的肽质量差异意味着可能存在修饰,而较小且一致的保留时间差异提供了正交的支持证据。我们建议使用双变量高斯混合模型来区分与修饰相关的光谱对与随机光谱对。由于使用了二维信息,因此可以确定准确的修饰质量和可信的光谱对,以及修饰对肽保留时间的定量影响。结论:对两个糖蛋白数据集进行的实验表明,我们的方法可以有效地检测大量的修饰和光谱对。通过将发现的修饰包括到数据库搜索中或通过在配对光谱之间传播肽分配,可以解释平均多出10%的光谱。

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  • 会议地点 Beijing(CN);Beijing(CN)
  • 作者单位

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China Key Lab of Intelligent Information Processing, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    State Key Laboratory of Proteomics-Beijing Proteome Research Center-Beijing Institute of Radiation Medicine, Beijing 102206, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China Key Lab of Intelligent Information Processing, Chinese Academy of Sciences, Beijing 100190, China;

    State Key Laboratory of Proteomics-Beijing Proteome Research Center-Beijing Institute of Radiation Medicine, Beijing 102206, China;

    State Key Laboratory of Proteomics-Beijing Proteome Research Center-Beijing Institute of Radiation Medicine, Beijing 102206, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;

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