Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/139646
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Type: | Journal article |
Title: | GlycoMinestruct : A new bioinformatics tool for highly accurate mapping of the human N-linked and O-linked glycoproteomes by incorporating structural features |
Author: | Li, F. Li, C. Revote, J. Zhang, Y. Webb, G.I. Li, J. Song, J. Lithgow, T. |
Citation: | Scientific Reports, 2016; 6(1):1-16 |
Publisher: | Springer Science and Business Media LLC |
Issue Date: | 2016 |
ISSN: | 2045-2322 2045-2322 |
Statement of Responsibility: | Fuyi Li, Chen Li, Jerico Revote, Yang Zhang, Geoffrey I.Webb, Jian Li, Jiangning Song, Trevor Lithgow |
Abstract: | Glycosylation plays an important role in cell-cell adhesion, ligand-binding and subcellular recognition. Current approaches for predicting protein glycosylation are primarily based on sequence-derived features, while little work has been done to systematically assess the importance of structural features to glycosylation prediction. Here, we propose a novel bioinformatics method called GlycoMine<sup>struct</sup>(http://glycomine.erc.monash.edu/Lab/GlycoMine_Struct/) for improved prediction of human N- and O-linked glycosylation sites by combining sequence and structural features in an integrated computational framework with a two-step feature-selection strategy. Experiments indicated that GlycoMine<sup>struct</sup> outperformed NGlycPred, the only predictor that incorporated both sequence and structure features, achieving AUC values of 0.941 and 0.922 for N- and O-linked glycosylation, respectively, on an independent test dataset. We applied GlycoMine<sup>struct</sup> to screen the human structural proteome and obtained high-confidence predictions for N- and O-linked glycosylation sites. GlycoMinestruct can be used as a powerful tool to expedite the discovery of glycosylation events and substrates to facilitate hypothesis-driven experimental studies. |
Keywords: | Glycosylation; protein structure predictions |
Rights: | © The Author(s) 2016. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
DOI: | 10.1038/srep34595 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/1092262 |
Published version: | http://dx.doi.org/10.1038/srep34595 |
Appears in Collections: | Medicine publications |
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hdl_139646.pdf | Published version | 2.12 MB | Adobe PDF | View/Open |
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