文章基本信息

标题：Features-Based Deisotoping Method for Tandem Mass Spectra
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作者：Zheng Yuan ; Jinhong Shi ; Wenjun Lin 等
期刊名称：Advances in Bioinformatics
印刷版ISSN：1687-8027
电子版ISSN：1687-8035
出版年度：2011
卷号：2011
DOI：10.1155/2011/210805
出版社：Hindawi Publishing Corporation
摘要：For high-resolution tandem mass spectra, the determination of monoisotopic masses of fragment ions plays a key role in the subsequent peptide and protein identification. In this paper, we present a new algorithm for deisotoping the bottom-up spectra. Isotopic-cluster graphs are constructed to describe the relationship between all possible isotopic clusters. Based on the relationship in isotopic-cluster graphs, each possible isotopic cluster is assessed with a score function, which is built by combining nonintensity and intensity features of fragment ions. The non-intensity features are used to prevent fragment ions with low intensity from being removed. Dynamic programming is adopted to find the highest score path with the most reliable isotopic clusters. The experimental results have shown that the average Mascot scores and 𝐹-scores of identified peptides from spectra processed by our deisotoping method are greater than those by YADA and MS-Deconv software.