Computational approaches to define a human milk metaglycome.

ABSTRACT:

Motivation

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.

Results

We present a novel computational approach to automate the sequencing of glycans using metadata-assisted glycan sequencing, which combines MS analyses with glycan structural information from glycan microarray technology. Succes

SUBMITTER: Agravat SB 

PROVIDER: S-EPMC4907376 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature