Harnessing the potential of artificial neural networks for predicting protein glycosylation-Reference-Cited by-同舟云学术

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Harnessing the potential of artificial neural networks for predicting protein glycosylation

Published:2020-06 Issue: Volume:10 Page:e00131
ISSN:2214-0301
Container-title:Metabolic Engineering Communications
language:en
Short-container-title:Metabolic Engineering Communications

Author:

Kotidis Pavlos,Kontoravdi Cleo

Funder

Department of Chemical Engineering, Imperial College London

Publisher

Elsevier BV

Subject

Biomedical Engineering,Endocrinology, Diabetes and Metabolism

Reference77 articles.

1. N-linked protein glycosylation in the ER;Aebi;Biochim. Biophys. Acta Mol. Cell Res.,2013

2. Mechanistic reconstruction of glycoprotein secretion through monitoring of intracellular N-glycan processing;Arigoni-Affolter;Sci. Adv.,2019

3. Supplementing glycosylation: a review of applying nucleotide-sugar precursors to growth medium to affect therapeutic recombinant protein glycoform distributions;Blondeel;Biotechnol. Adv.,2018

4. The contributions of individual galactosyltransferases to protein specific N-glycan processing in Chinese Hamster Ovary cells;Bydlinski;J. Biotechnol.,2018

5. Emerging principles for the therapeutic exploitation of glycosylation;Dalziel;Science,2014

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