title: Features-based deisotoping method for tandem mass spectra.
abstract: 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.
authors.affiliation: Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N5A9.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Yuan
authors.forename: Jinhong
authors.initials: J
authors.lastname: Shi
authors.forename: Wenjun
authors.initials: W
authors.lastname: Lin
authors.forename: Bolin
authors.initials: B
authors.lastname: Chen
authors.forename: Fang-Xiang
authors.initials: FX
authors.lastname: Wu