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A spectrum graph-based protein sequence filtering algorithm for proteoform identification by top-down mass spectrometry

机译:基于谱图的蛋白质序列滤波算法,用于通过自上而下的质谱法识别

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Database search is the main approach for identifying proteoforms using top-down tandem mass spectra. However, it is extremely slow to align a query spectrum against all protein sequences in a large database when the target proteoform that produced the spectrum contains post-translational modifications and/or mutations. As a result, efficient and sensitive protein sequence filtering algorithms are essential for speeding up database search. In this paper, we propose a novel filtering algorithm, which generates spectrum graphs from subspectra of the query spectrum and searches them against the protein database to find good candidates. Compared with the sequence tag and gaped tag approaches, the proposed method circumvents the step of tag extraction, thus simplifying data processing. Experimental results on real data showed that the proposed method achieved both high speed and high sensitivity in protein sequence filtration.
机译:数据库搜索是使用自上而下的串联质谱来识别蛋白质ord的主要方法。然而,当产生频谱的目标蛋白质包含后翻译后修改和/或突变时,将查询谱对准对大型数据库中的所有蛋白质序列的查询频谱非常慢。结果,高效敏感的蛋白质序列过滤算法对于加速数据库搜索至关重要。在本文中,我们提出了一种新颖的滤波算法,其从查询频谱的子谱产生频谱图,并将它们针对蛋白质数据库来寻找良好的候选者。与序列标签和差距标签接近相比,所提出的方法避免标签提取的步骤,从而简化数据处理。实验结果对真实数据显示,该方法在蛋白质序列过滤中实现了高速和高灵敏度。

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