Applications of graph theory in protein structure identification

被引:19
|
作者
Yan, Yan [1 ,2 ]
Zhang, Shenggui [2 ]
Wu, Fang-Xiang [1 ]
机构
[1] Univ Saskatchewan, Div Biomed Engn, Saskatoon, SK S7N 5A9, Canada
[2] Northwestern Polytech Univ, Dept Appl Math, Xian 710072, Shaanxi, Peoples R China
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
TANDEM MASS-SPECTROMETRY; SEQUENCE DATABASES; PEPTIDES; PROTEOMICS; ALGORITHM; CLIQUES; SPECTRA; COMPLEX;
D O I
10.1186/1477-5956-9-S1-S17
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
There is a growing interest in the identification of proteins on the proteome wide scale. Among different kinds of protein structure identification methods, graph-theoretic methods are very sharp ones. Due to their lower costs, higher effectiveness and many other advantages, they have drawn more and more researchers' attention nowadays. Specifically, graph-theoretic methods have been widely used in homology identification, side-chain cluster identification, peptide sequencing and so on. This paper reviews several methods in solving protein structure identification problems using graph theory. We mainly introduce classical methods and mathematical models including homology modeling based on clique finding, identification of side-chain clusters in protein structures upon graph spectrum, and de novo peptide sequencing via tandem mass spectrometry using the spectrum graph model. In addition, concluding remarks and future priorities of each method are given.
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页数:10
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