Probabilistic model by Bayesian network for the prediction of antibody glycosylation in perfusion and fed‐batch cell cultures-Reference-Cited by-同舟云学术

Probabilistic model by Bayesian network for the prediction of antibody glycosylation in perfusion and fed‐batch cell cultures

Published:2021-05-03 Issue:9 Volume:118 Page:3447-3459
ISSN:0006-3592
Container-title:Biotechnology and Bioengineering
language:en
Short-container-title:Biotechnol Bioeng

Author:

Zhang Liang¹²,Wang MingLiang²³,Castan Andreas⁴^ORCID,Hjalmarsson Håkan²³⁵^ORCID,Chotteau Veronique¹²⁵^ORCID

Affiliation:

1. Department of Industrial Biotechnology, School of Engineering Sciences in Chemistry, Biotechnology and Health KTH‐Royal Institute of Technology Stockholm Sweden

2. AdBIOPRO, VINNOVA Competence Centre for Advanced Bioproduction by Continuous Processing KTH Royal Institute of Technology Stockholm Sweden

3. Division of Decision and Control System, School of Electrical Engineering and Computer Science KTH‐Royal Institute of Technology Stockholm Sweden

4. Cytiva Uppsala Sweden

5. Digital Futures ‐ KTH Royal Institute of Technology Stockholm Sweden

Publisher

Wiley

Subject

Applied Microbiology and Biotechnology,Bioengineering,Biotechnology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/bit.27769

Reference47 articles.

1. Effects of nutrient levels and average culture pH on the glycosylation pattern of camelid-humanized monoclonal antibody

2. Effect of culture temperature on erythropoietin production and glycosylation in a perfusion culture of recombinant CHO cells

3. Getting Started in Probabilistic Graphical Models

4. Supplementing glycosylation: A review of applying nucleotide-sugar precursors to growth medium to affect therapeutic recombinant protein glycoform distributions

5. Investigation of the interactions of critical scale-up parameters (pH, pO2 and pCO2) on CHO batch performance and critical quality attributes

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A scoping review of supervised learning modelling and data-driven optimisation in monoclonal antibody process development;Digital Chemical Engineering;2023-06

2. Strategies for controlling afucosylation in monoclonal antibodies during upstream manufacturing;Biotechnology Journal;2023-04-19

3. An analytical study on the identification of N-linked glycosylation sites using machine learning model;PeerJ Computer Science;2022-09-21

4. Assessment of tissue toxicity risk in breast radiotherapy using Bayesian networks;Medical Physics;2022-04-28

5. Mathematical Modelling of Cell Culture Processes;Cell Engineering;2021