The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed‐batch fermentations-Reference-Cited by-同舟云学术

The potential of random forest and neural networks for biomass and recombinant protein modeling in Escherichia coli fed‐batch fermentations

Published:2015-08-11 Issue:11 Volume:10 Page:1770-1782
ISSN:1860-6768
Container-title:Biotechnology Journal
language:en
Short-container-title:Biotechnology Journal

Author:

Melcher Michael¹²,Scharl Theresa¹,Spangl Bernhard¹²,Luchner Markus¹³,Cserjan Monika¹³,Bayer Karl¹³,Leisch Friedrich¹²,Striedner Gerald¹³

Affiliation:

1. Austrian Centre of Industrial Biotechnology, Graz, Austria

2. Institute of Applied Statistics and Computing, University of Natural Resources and Life Sciences, Vienna, Austria

3. Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria

Publisher

Wiley

Subject

Molecular Medicine,Applied Microbiology and Biotechnology,General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/biot.201400790

Reference32 articles.

1. International Conference on Harmonisation; guidance on Q8(R1) Pharmaceutical Development; addition of annex; availability. Notice.;Food and Drug Administration, H. H. S.;Fed. Regist.,2009

2. International Conference on Harmonisation; guidance on Q9 Quality Risk Management; availability. Notice.;Food and Drug Administration, H. H. S.;Fed. Regist.,2006

3. International Conference on Harmonisation; guidance on Q10 Pharmaceutical Quality System; availability. Notice.;Food and Drug Administration H. H. S.;Fed. Regist.,2009

4. Food and Drug Administration H. H. S. Guidance for Industry: PAT – A Framework for Innovative Pharmaceutical Development Manufacturing and Quality Assurance 2004. http://www.fda.gov/downloads/Drugs/Guidances/ucm070305.pdf [Oct 13 2014].

5. Roadmap for implementation of quality by design (QbD) for biotechnology products

Cited by 34 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. Development and validation of a hybrid model for prediction of viable cell density, titer and cumulative glucose consumption in a mammalian cell culture system;Computers & Chemical Engineering;2024-05

2. Explainable deep learning enhances robust and reliable real‐time monitoring of a chromatographic protein A capture step;Biotechnology Journal;2024-02

3. Online monitoring tools for vaccine production in bioreactors;Bioreactor Design Concepts for Viral Vaccine Production;2024

4. Sensors and chemometrics in downstream processing;Biotechnology and Bioengineering;2023-07-20

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