标题:An Accurate de novo Algorithm for Glycan Topology Determination from Mass Spectra
作者:Dong, Liang; Shi, Bing; Tian, Guangdong; Li, YanBo; Wang, Bing; Zhou, MengChu
作者机构:[Dong, Liang; Shi, Bing] Shandong Univ, Dept Comp Sci & Technol, Jinan, Shandong, Peoples R China.; [Tian, Guangdong] Northest Forestry Univ, Transp 更多
会议名称:8th Brazilian Symposium on Bioinformatics (BSB)
会议日期:NOV 03-07, 2013
来源:IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
出版年:2015
卷:12
期:3
页码:568-578
DOI:10.1109/TCBB.2014.2368981
关键词:Tandem mass spectrometry (MS/MS); mass spectra; glycan topology; interpretation; de novo algorithm; optimization
摘要:Determining the glycan topology automatically from mass spectra represents a great challenge. Existing methods fall into approximate and exact ones. The former including greedy and heuristic ones can reduce the computational complexity, but suffer from information lost in the procedure of glycan interpretation. The latter including dynamic programming and exhaustive enumeration are much slower than the former. In the past years, nearly all emerging methods adopted a tree structure to represent a glycan. They share such problems as repetitive peak counting in reconstructing a candidate structure. Besides, tree-based glycan representation methods often have to give different computational formulas for binary and ternary glycans. We propose a new directed acyclic graph structure for glycan representation. Based on it, this work develops a de novo algorithm to accurately reconstruct the tree structure iteratively from mass spectra with logical constraints and some known biosynthesis rules, by a single computational formula. The experiments on multiple complex glycans extracted from human serum show that the proposed algorithm can achieve higher accuracy to determine a glycan topology than prior methods without increasing computational burden.
收录类别:CPCI-S;EI;SCOPUS;SCIE
WOS核心被引频次:11
Scopus被引频次:11
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940396725&doi=10.1109%2fTCBB.2014.2368981&partnerID=40&md5=9516ed3686160bda0be707bbdad693cf
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