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Author Liang Dong ♦ Bing Shi ♦ Guangdong Tian ♦ YanBo Li ♦ Bing Wang ♦ MengChu Zhou
Sponsorship IEEE Computer Society
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2004
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science ♦ Technology ♦ Medicine & health ♦ Engineering & allied operations
Subject Keyword Couplings ♦ Proteins ♦ Databases ♦ Computational biology ♦ algorithm ♦ MS/MS ♦ glycan topology interpretation ♦ Denovo ♦ optimization ♦ Tandem mass spectrometry (MS/MS) ♦ mass spectra ♦ glycan topology interpretation ♦ de novo algorithm
Abstract 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.
Description Author affiliation :: Inst. of Syst. Eng., Macau Univ. of Sci. & Technol., Macau, China
Author affiliation :: Dept. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Author affiliation :: Transp. Coll., Northeast Forestry Univ., Harbin, China
Author affiliation :: Inst. of Comput. Technol., Beijing, China
ISSN 15455963
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-05-01
Publisher Place U.S.A.
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Volume Number 12
Issue Number 3
Size (in Bytes) 761.41 kB
Page Count 11
Starting Page 568
Ending Page 578

Source: IEEE Xplore Digital Library