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Glycobioinformatics: Current strategies and tools for data mining in MS ‐based glycoproteomics
Author(s) -
Li Feng,
Glinskii Olga V.,
Glinsky Vladislav V.
Publication year - 2013
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201200149
Subject(s) - glycoproteomics , computer science , glycan , field (mathematics) , data science , chemistry , glycoprotein , mathematics , pure mathematics , biochemistry
Glycobioinformatics is a rapidly developing field providing a vital support for MS ‐based glycoproteomics research. Recent advances in MS greatly increased technological capabilities for high throughput glycopeptide analysis. However, interpreting MS output, in terms of identifying glycan structures, attachment sites and glycosylation linkages still presents multiple challenges. Here, we discuss current strategies used in MS ‐based glycoproteomics and bioinformatics tools available for MS‐based glycopeptide and glycan analysis. We also provide a brief overview of recent efforts in glycobioinformatics such as the new initiative U ni C arb KB directed toward developing more comprehensive and unified glycobioinformatics platforms. With regards to glycobioinformatics tools and applications, we do not express our personal preferences or biases, but rather focus on providing a concise description of main features and functionalities of each application with the goal of assisting readers in making their own choices and identifying and locating glycobioinformatics tools most suitable for achieving their experimental objectives.