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Ions Classification in Peptide Tandem Mass Spectra

机译:肽串联质谱中的离子分类

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摘要

In computational proteomics, inferring the peptide sequence from its MS/MS data is an important issue and many algorithms have been proposed recently. Ions classification aiming at determining the type of ions provides a basis for most of the existing algorithms. However, no report on ions classification methods have been found to our knowledge. In this paper, a method extracting ion feature is first presented according to the analysis of the relationship among ions. To deal with ions with high overlap peaks and highdensity peaks in some mass interval, a method of filtering ''noise'' peaks is then proposed according to the information of the related ions. Moreover, a binary ions classification method, which takes some type of ions as one class and the rest ions as the other class, is proposed based on SVM witha novel kernel trick. In the experiments, classification for b-ions and y-ions are implemented. The results demonstratethat an accuracy level of 90% is achieved.
机译:在计算蛋白质组学中,从其MS / MS数据推断肽序列是一个重要的问题,并且最近提出了许多算法。旨在确定离子类型的离子分类为大多数现有算法提供了基础。但是,据我们所知,尚未找到有关离子分类方法的报告。通过对离子间关系的分析,提出了一种提取离子特征的方法。为了处理在一定质量间隔内具有高重叠峰和高密度峰的离子,根据相关离子的信息,提出了一种过滤“噪声”峰的方法。此外,提出了一种基于SVM的新颖的核技巧二元离子分类方法,该方法将某种类型的离子作为一类,其余的离子作为另一类。在实验中,对b离子和y离子进行了分类。结果表明,达到了90%的准确度。

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