Best-first search guided multistage mass spectrometry-based glycan identification | |
Wang, Yaojun2,3; Bu, Dongbo2; Huang, Chuncui4; Wang, Hui1,2; Zhou, Jinyu1,4; Dong, Junchuan1,2; Pan, Weiyi1,2; Zhang, Jingwei1,2; Zhang, Qi1,2; Li, Yan4 | |
刊名 | BIOINFORMATICS |
2019-09-01 | |
卷号 | 35期号:17页码:2991-2997 |
ISSN号 | 1367-4803 |
DOI | 10.1093/bioinformatics/btz056 |
英文摘要 | Motivation: Glycan identification has long been hampered by complicated branching patterns and various isomeric structures of glycans. Multistage mass spectrometry (MSn) is a promising glycan identification technique as it generates multiple-level fragments of a glycan, which can be explored to deduce branching pattern of the glycan and further distinguish it from other candidates with identical mass. However, the automatic glycan identification still remains a challenge since it mainly relies on expertise to guide a MSn instrument to generate spectra. Results: Here, we proposed a novel method, named bestFSA, based on a best-first search algorithm to guide the process of spectrum producing in glycan identification using MSn. BestFSA is able to select the most appropriate peaks for next round of experiments and complete the identification using as few experimental rounds. Our analysis of seven representative glycans shows that bestFSA correctly distinguishes actual glycans efficiently and suggested bestFSA could be used in practical glycan identification. The combination of the MSn technology coupled with bestFSA should greatly facilitate the automatic identification of glycan branching patterns, with significantly improved identification sensitivity, and reduce time and cost of MSn experiments. |
资助项目 | National Key Research and Development Program of China[2018YFC0910405] ; National Natural Science Foundation of China[31671369] ; National Natural Science Foundation of China[31600650] ; National Natural Science Foundation of China[31770775] ; International Partnership Program of Chinese Academy of Sciences[153311KYSB20150012] |
WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics |
语种 | 英语 |
出版者 | OXFORD UNIV PRESS |
WOS记录号 | WOS:000487323400014 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/4609] |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Li, Yan; Sun, Shiwei |
作者单位 | 1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp & Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 3.Peking Univ, Guanghua Sch Management, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Biophys, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Yaojun,Bu, Dongbo,Huang, Chuncui,et al. Best-first search guided multistage mass spectrometry-based glycan identification[J]. BIOINFORMATICS,2019,35(17):2991-2997. |
APA | Wang, Yaojun.,Bu, Dongbo.,Huang, Chuncui.,Wang, Hui.,Zhou, Jinyu.,...&Sun, Shiwei.(2019).Best-first search guided multistage mass spectrometry-based glycan identification.BIOINFORMATICS,35(17),2991-2997. |
MLA | Wang, Yaojun,et al."Best-first search guided multistage mass spectrometry-based glycan identification".BIOINFORMATICS 35.17(2019):2991-2997. |
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