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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 Enzyme Engineering
Stanislav Mazurenko, Zbyněk Prokop, Jiřı́ Damborský
ACS Catalysis (2019) Vol. 10, Iss. 2, pp. 1210-1223
Open Access | Times Cited: 328

Showing 1-25 of 328 citing articles:

The Crucial Role of Methodology Development in Directed Evolution of Selective Enzymes
Ge Qu, Aitao Li, Carlos G. Acevedo‐Rocha, et al.
Angewandte Chemie International Edition (2019) Vol. 59, Iss. 32, pp. 13204-13231
Closed Access | Times Cited: 386
Power of Biocatalysis for Organic Synthesis
Christoph K. Winkler, Joerg H. Schrittwieser, Wolfgang Kroutil
ACS Central Science (2021) Vol. 7, Iss. 1, pp. 55-71
Open Access | Times Cited: 266
Recent trends in biocatalysis
Dong Yi, Thomas Bayer, Christoffel P. S. Badenhorst, et al.
Chemical Society Reviews (2021) Vol. 50, Iss. 14, pp. 8003-8049
Open Access | Times Cited: 264
Embracing Nature’s Catalysts: A Viewpoint on the Future of Biocatalysis
Bernhard Hauer
ACS Catalysis (2020) Vol. 10, Iss. 15, pp. 8418-8427
Closed Access | Times Cited: 231
Enzyme discovery and engineering for sustainable plastic recycling
Baotong Zhu, Dong Wang, Na Wei
Trends in biotechnology (2021) Vol. 40, Iss. 1, pp. 22-37
Open Access | Times Cited: 223
The road to fully programmable protein catalysis
Sarah L. Lovelock, Rebecca Crawshaw, Sophie Basler, et al.
Nature (2022) Vol. 606, Iss. 7912, pp. 49-58
Closed Access | Times Cited: 217
Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction
Feiran Li, Le Yuan, Hongzhong Lu, et al.
Nature Catalysis (2022) Vol. 5, Iss. 8, pp. 662-672
Open Access | Times Cited: 211
Synthetic biology 2020–2030: six commercially-available products that are changing our world
Christopher A. Voigt
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 208
Current progress and open challenges for applying deep learning across the biosciences
Nicolae Sapoval, Amirali Aghazadeh, Michael Nute, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 206
Multistep enzyme cascades as a route towards green and sustainable pharmaceutical syntheses
Ana I. Benítez‐Mateos, David Roura Padrosa, Francesca Paradisi
Nature Chemistry (2022) Vol. 14, Iss. 5, pp. 489-499
Closed Access | Times Cited: 175
Mechanism-Based Design of Efficient PET Hydrolases
Ren Wei, Gerlis von Haugwitz, Lara Pfaff, et al.
ACS Catalysis (2022) Vol. 12, Iss. 6, pp. 3382-3396
Open Access | Times Cited: 169
Informed training set design enables efficient machine learning-assisted directed protein evolution
Bruce J. Wittmann, Yisong Yue, Frances H. Arnold
Cell Systems (2021) Vol. 12, Iss. 11, pp. 1026-1045.e7
Open Access | Times Cited: 151
Protein sequence design with deep generative models
Zachary Wu, Kadina E. Johnston, Frances H. Arnold, et al.
Current Opinion in Chemical Biology (2021) Vol. 65, pp. 18-27
Open Access | Times Cited: 127
Advances in machine learning for directed evolution
Bruce J. Wittmann, Kadina E. Johnston, Zachary Wu, et al.
Current Opinion in Structural Biology (2021) Vol. 69, pp. 11-18
Open Access | Times Cited: 125
ProteInfer, deep neural networks for protein functional inference
Theo Sanderson, Maxwell L. Bileschi, David Belanger, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 97
Biocatalysed synthesis planning using data-driven learning
Daniel Probst, Matteo Manica, Yves Gaëtan Nana Teukam, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 89
Elimination of Fusarium mycotoxin deoxynivalenol (DON) via microbial and enzymatic strategies: Current status and future perspectives
Ye Tian, Dachuan Zhang, Pengli Cai, et al.
Trends in Food Science & Technology (2022) Vol. 124, pp. 96-107
Open Access | Times Cited: 66
Carbonic anhydrase for CO2 capture, conversion and utilization
Sachin Talekar, Byung Hoon Jo, Jonathan S. Dordick, et al.
Current Opinion in Biotechnology (2022) Vol. 74, pp. 230-240
Closed Access | Times Cited: 65
Machine Learning-Guided Protein Engineering
Petr Kouba, Pavel Kohout, Faraneh Haddadi, et al.
ACS Catalysis (2023) Vol. 13, Iss. 21, pp. 13863-13895
Open Access | Times Cited: 65
Machine learning-enabled retrobiosynthesis of molecules
Tianhao Yu, Aashutosh Girish Boob, Michael Volk, et al.
Nature Catalysis (2023) Vol. 6, Iss. 2, pp. 137-151
Closed Access | Times Cited: 61
Machine‐Learning‐Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes
Jie Zhuang, Adam C. Midgley, Yonghua Wei, et al.
Advanced Materials (2023) Vol. 36, Iss. 10
Closed Access | Times Cited: 58
Rational design of enzyme activity and enantioselectivity
Zhongdi Song, Qunfeng Zhang, Wenhui Wu, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 53
Ultrahigh-Throughput Enzyme Engineering and Discovery in In Vitro Compartments
Maximilian Gantz, Stefanie Neun, Elliot J. Medcalf, et al.
Chemical Reviews (2023) Vol. 123, Iss. 9, pp. 5571-5611
Open Access | Times Cited: 46
Artificial intelligence-aided protein engineering: from topological data analysis to deep protein language models
Yuchi Qiu, Guo‐Wei Wei
Briefings in Bioinformatics (2023) Vol. 24, Iss. 5
Open Access | Times Cited: 38
Recent progress in the synthesis of advanced biofuel and bioproducts
Brian F. Pfleger, Ralf Takors
Current Opinion in Biotechnology (2023) Vol. 80, pp. 102913-102913
Closed Access | Times Cited: 37
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