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Computational approaches to define a human milk metaglycome
Author(s) -
Sanjay Agravat,
Xuezheng Song,
Teerapat Rojsajjakul,
Richard D. Cummings,
David F. Smith
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw048
Subject(s) - glycome , glycan , computational biology , glycomics , biology , computer science , biochemistry , glycoprotein
The goal of deciphering the human glycome has been hindered by the lack of high-throughput sequencing methods for glycans. Although mass spectrometry (MS) is a key technology in glycan sequencing, MS alone provides limited information about the identification of monosaccharide constituents, their anomericity and their linkages. These features of individual, purified glycans can be partly identified using well-defined glycan-binding proteins, such as lectins and antibodies that recognize specific determinants within glycan structures.

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