Use this URL to cite or link to this record in EThOS: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.770269 |
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Title: | An in silico approach to predict alterations in the Golgi N-glycosylation machinery | ||||||
Author: | Fisher, Peter |
ISNI:
0000 0004 7651 8463
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Awarding Body: | University of York | ||||||
Current Institution: | University of York | ||||||
Date of Award: | 2018 | ||||||
Availability of Full Text: |
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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.
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Supervisor: | Ungar, Daniel ; Wood, Jamie ; Thomas-Oates, Jane | Sponsor: | Not available | ||||
Qualification Name: | Thesis (Ph.D.) | Qualification Level: | Doctoral | ||||
EThOS ID: | uk.bl.ethos.770269 | DOI: | Not available | ||||
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