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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:

Machine learning in bioprocess development: from promise to practice
Laura M. Helleckes, Johannes Hemmerich, Wolfgang Wiechert, et al.
Trends in biotechnology (2022) Vol. 41, Iss. 6, pp. 817-835
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Big data and machine learning driven bioprocessing – Recent trends and critical analysis
Chao‐Tung Yang, Endah Kristiani, Yoong Kit Leong, et al.
Bioresource Technology (2023) Vol. 372, pp. 128625-128625
Closed Access | Times Cited: 39
A review on microbes mediated resource recovery and bioplastic (polyhydroxyalkanoates) production from wastewater
Vishal Ahuja, Pankaj Singh, Chandan Mahata, et al.
Microbial Cell Factories (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 7
Implementation of artificial intelligence (AI) and machine learning (ML) in microbiology
Prashant Tripathi, Akanksha Srivastava, Chetan Kumar Dubey, et al.
Methods in microbiology (2024), pp. 29-41
Closed Access | Times Cited: 7
Deep hybrid modeling of a HEK293 process: Combining long short‐term memory networks with first principles equations
João R. C. Ramos, José M. Pinto, Gil Poiares‐Oliveira, et al.
Biotechnology and Bioengineering (2024) Vol. 121, Iss. 5, pp. 1554-1568
Open Access | Times Cited: 6
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: 6
Advanced modeling techniques for predicting gas holdup in bubble columns using machine learning
Shabnam Shahhoseyni, Mohammad Rahmani, Abhishek Sivaram
Fuel (2025) Vol. 388, pp. 134449-134449
Closed Access
Machine Learning‐Powered Optimization of a CHO Cell Cultivation Process
Jannik Richter, Qimin Wang, Ferdinand Lange, et al.
Biotechnology and Bioengineering (2025)
Open Access
Machine Learning: A Suitable Method for Biocatalysis
Pedro Sampaio, Pedro Fernandes
Catalysts (2023) Vol. 13, Iss. 6, pp. 961-961
Open Access | Times Cited: 15
Data‐driven prediction models for forecasting multistep ahead profiles of mammalian cell culture toward bioprocess digital twins
Seo‐Young Park, S.H. Kim, C.-Y. Park, et al.
Biotechnology and Bioengineering (2023) Vol. 120, Iss. 9, pp. 2494-2508
Closed Access | Times Cited: 14
Bioreactors: Applications and Innovations for a Sustainable and Healthy Future—A Critical Review
Fernanda Palladino, Paulo Ricardo Franco Marcelino, Andersen Escobar Schlogl, et al.
Applied Sciences (2024) Vol. 14, Iss. 20, pp. 9346-9346
Open Access | Times Cited: 5
Bayesian Optimization for an ATP-Regenerating In Vitro Enzyme Cascade
Regine Siedentop, Maximilian Siska, Niklas Möller, et al.
Catalysts (2023) Vol. 13, Iss. 3, pp. 468-468
Open Access | Times Cited: 13
From genotype to phenotype: computational approaches for inferring microbial traits relevant to the food industry
Signe Tang Karlsen, Martin Holm Rau, Benjamín J. Sánchez, et al.
FEMS Microbiology Reviews (2023) Vol. 47, Iss. 4
Open Access | Times Cited: 13
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: 11
Industrial internet of things: What does it mean for the bioprocess industries?
Lidia Borgosz, Duygu Dikicioǧlu
Biochemical Engineering Journal (2023) Vol. 201, pp. 109122-109122
Open Access | Times Cited: 11
The Development and Opportunities of Predictive Biotechnology
Bettina M. Nestl, Bernd A. Nebel, Verena Resch, et al.
ChemBioChem (2024) Vol. 25, Iss. 13
Open Access | Times Cited: 3
Advances and opportunities in process analytical technologies for viral vector manufacturing
Sobhana A. Sripada, Mahshid Hosseini, Srivatsan Ramesh, et al.
Biotechnology Advances (2024) Vol. 74, pp. 108391-108391
Closed Access | Times Cited: 3
Current challenges and recent advances on the path towards continuous biomanufacturing
Miloš Drobnjaković, Roger A. Hart, Boonserm Kulvatunyou, et al.
Biotechnology Progress (2023) Vol. 39, Iss. 6
Closed Access | Times Cited: 9
Performance of removing aqueous contaminant by zirconium based adsorbents: a critical review
Dandan Zhao, Yi Yang, J. Paul Chen
Frontiers in Chemical Engineering (2024) Vol. 6
Open Access | Times Cited: 2
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: 6
Recent trends and perspectives of artificial intelligence-based machine learning from discovery to manufacturing in biopharmaceutical industry
Ravi Maharjan, Jae‐Chul Lee, Kyeong Lee, et al.
Journal of Pharmaceutical Investigation (2023) Vol. 53, Iss. 6, pp. 803-826
Closed Access | Times Cited: 6
Pushing the boundaries of phosphorylase cascade reaction for cellobiose production I: Kinetic model development
Alexander Sigg, Mario Klimacek, Bernd Nidetzky
Biotechnology and Bioengineering (2023) Vol. 121, Iss. 2, pp. 580-592
Open Access | Times Cited: 6
High-throughput process development from gene cloning to protein production
Manman Sun, Alex Xiong Gao, Xiuxia Liu, et al.
Microbial Cell Factories (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 5
Hybrid machine learning model based predictions for properties of poly(2-hydroxyethyl methacrylate)-poly(vinyl alcohol) composite cryogels embedded with bacterial cellulose
Jiawei Wu, Ruobing Wang, Yan Tan, et al.
Journal of Chromatography A (2024) Vol. 1727, pp. 464996-464996
Closed Access | Times Cited: 1
LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae
Zeyu Lu, Qianyi Shen, Naga Chandra Bandari, et al.
Nucleic Acids Research (2024) Vol. 52, Iss. 12, pp. 7367-7383
Open Access | Times Cited: 1
Active learning maps the emergent dynamics of enzymatic reaction networks.
‪Miglė Jakštaitė, Tao Zhou, Frank H. T. Nelissen, et al.
(2024)
Open Access | Times Cited: 1
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