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An in silico approach to predict alterations in the Golgi N-glycosylation machinery

Fisher, Peter (2018) An in silico approach to predict alterations in the Golgi N-glycosylation machinery. PhD thesis, University of York.

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PETER FISHER PHD THESIS 2019.pdf - Examined Thesis (PDF)
Restricted until 15 February 2024.

Abstract

Protein glycosylation is responsible for modulating the numerous properties of secreted and membrane proteins. The glycan structures that are produced by the cell in the Golgi apparatus are only partially a result of the transcriptome of the enzymes responsible. The organisation of glycosylation enzymes, including levels and localizations within the Golgi apparatus has only been accessible with advanced microscopy techniques and is limited to a small number of enzymes. In this work a computational model capable of predicting changes in Golgi enzyme localizations and activities informed by glycan profiles has been developed. This model is used to predict the localization of N-linked glycan-modifying enzymes in three human cell lines and then to predict changes in enzyme homeostasis in Cog4-deficient cell lines and upon osteogenic differentiation.

Item Type: Thesis (PhD)
Academic Units: The University of York > Biology (York)
Depositing User: MR Peter Fisher
Date Deposited: 15 Mar 2019 16:12
Last Modified: 15 Mar 2019 16:12
URI: http://etheses.whiterose.ac.uk/id/eprint/22970

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