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De novo prediction of the elemental composition of peptides and proteins based on a single mass

机译:基于单块质量的肽和蛋白质元素组成的DE Novo预测

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Identification of peptides and proteins is a common task in mass spectrometry-based proteomics but often fails to deliver a comprehensive list of identifications. Downstream analysis, quantitative or qualitative, depends on the outcome of this process. Despite continuous improvement of computational methods, a large fraction of the screened peptides and/or proteins remains unidentified. We introduce here pacMASS, a method that de novo predicts the elemental composition of peptides and small proteins based on a single accurate mass, ie, the observed monoisotopic or average mass. This novel approach returns in a fast and memory efficient manner a limited number of elemental compositions per queried peptide or protein.
机译:肽和蛋白质的鉴定是基于质谱的蛋白质组学的常见任务,但通常不能提供全面的识别清单。 下游分析,定量或定性取决于该过程的结果。 尽管持续改善了计算方法,但大部分筛选的肽和/或蛋白质仍未识别。 我们在此介绍Pacmass,该方法是De Novo基于单一精确的质量来预测肽和小蛋白质的元素组成,即观察到的单同步体或平均质量。 该新颖方法以快速和记忆有效的方式返回每种肽或蛋白质的有限数量的元素组合物。

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