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Best-first search guided multistage mass spectrometry-based glycan identification

文献类型：期刊论文

作者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
出版日期2019-09-01
卷号35期号:17页码:2991-2997
ISSN号1367-4803
DOI10.1093/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
WOS记录号WOS:000487323400014
出版者OXFORD UNIV PRESS
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.

入库方式： OAI收割

来源：计算技术研究所

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