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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Hybrid deep modeling of a CHO-K1 fed-batch process: combining first-principles with deep neural networks
José M. Pinto, João R. C. Ramos, Rafael S. Costa, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 12

Showing 12 citing articles:

Roles of mechanistic, data-driven, and hybrid modeling approaches for pharmaceutical process design and operation
Mohamed Rami Gaddem, Junu Kim, Kensaku Matsunami, et al.
Current Opinion in Chemical Engineering (2024) Vol. 44, pp. 101019-101019
Closed Access | Times Cited: 12
Hybrid Physics-Informed Metabolic Cybergenetics: Process Rates Augmented with Machine-Learning Surrogates Informed by Flux Balance Analysis
Sebastián Espinel‐Ríos, José L. Avalos‬
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 15, pp. 6685-6700
Open Access | Times Cited: 9
Bioprocessing 4.0: A Pragmatic Review and Future Perspectives
Kesler Isoko, Joan Cordiner, Zoltán Kis, et al.
Digital Discovery (2024) Vol. 3, Iss. 9, pp. 1662-1681
Open Access | Times Cited: 7
Neural ordinary differential equation‐based model predictive controller for regulating glucose concentration in a fed‐batch CHO cell bioreactor
Kuo‐Chun Chiu, Dongping Du
The Canadian Journal of Chemical Engineering (2025)
Closed Access
From Shallow to Deep Bioprocess Hybrid Modeling: Advances and Future Perspectives
Roshanak Agharafeie, João R. C. Ramos, Jorge M. Mendes, et al.
Fermentation (2023) Vol. 9, Iss. 10, pp. 922-922
Open Access | Times Cited: 9
Advances on hybrid modelling for bioprocesses engineering: insights into research trends and future directions from a bibliometric approach
Juan Federico Herrera-Ruiz, Javier Fontalvo, Oscar Andrés Prado-Rúbio
Results in Engineering (2024), pp. 103548-103548
Open Access | Times Cited: 3
A multiscale hybrid modelling methodology for cell cultures enabled by enzyme-constrained dynamic metabolic flux analysis under uncertainty
Oliver Pennington, Sebastián Espinel‐Ríos, Mauro Torres Sebastian, et al.
Metabolic Engineering (2024) Vol. 86, pp. 274-287
Open Access | Times Cited: 2
Machine Learning and Deep Learning Strategies for Chinese Hamster Ovary Cell Bioprocess Optimization
Tiffany-Marie D. Baako, S Kulkarni, Jerome McClendon, et al.
Fermentation (2024) Vol. 10, Iss. 5, pp. 234-234
Open Access | Times Cited: 1
Modeling and simulation of the enzymatic kinetics for the production of Galactooligosaccharides (GOS) using an Artificial Neural Network hybrid model
Juan D. Hoyos, M.A. Noriega, Carlos A.M. Riascos
Digital Chemical Engineering (2023) Vol. 9, pp. 100132-100132
Open Access | Times Cited: 2
A neural ordinary differential equation model for predicting the growth of Chinese Hamster Ovary cell in a bioreactor system
Kuo‐Chun Chiu, Dongping Du
Biotechnology and Bioprocess Engineering (2024)
Closed Access
Hybrid modeling for in silico optimization of a dynamic perfusion cell culture process
Piyush Agarwal, Chris McCready, Say Kong Ng, et al.
Biotechnology Progress (2024)
Open Access
From Shallow to Deep Bioprocess Hybrid Modeling: Advances and Future Perspectives
Roshanak Agharafeie, João R. C. Ramos, Jorge M. Mendes, et al.
(2023)
Open Access
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