ArticleAdvances in bioinformatics2011
Features-based deisotoping method for tandem mass spectra.
Article in Advances in bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Exploring novel secondary metabolites from natural products using pre-processed mass spectral data.Scientific reports · 2019Article
- Approximating Isotope Distributions of Biomolecule Fragments.ACS omega · 2018Article
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Authors and funding
5 authors.
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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.
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