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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:

De novo design of luciferases using deep learning
Hsien‐Wei Yeh, Christoffer Norn, Yakov Kipnis, et al.
Nature (2023) Vol. 614, Iss. 7949, pp. 774-780
Open Access | Times Cited: 256

Showing 1-25 of 256 citing articles:

De novo design of protein structure and function with RFdiffusion
Joseph L. Watson, David Juergens, Nathaniel R. Bennett, et al.
Nature (2023) Vol. 620, Iss. 7976, pp. 1089-1100
Open Access | Times Cited: 736
From nature to industry: Harnessing enzymes for biocatalysis
Rebecca Buller, Stefan Lutz, Romas J. Kazlauskas, et al.
Science (2023) Vol. 382, Iss. 6673
Open Access | Times Cited: 204
Soil microbiome engineering for sustainability in a changing environment
Janet Jansson, Ryan McClure, Robert G. Egbert
Nature Biotechnology (2023) Vol. 41, Iss. 12, pp. 1716-1728
Open Access | Times Cited: 102
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: 90
Machine learning for functional protein design
Pascal Notin, Nathan Rollins, Yarin Gal, et al.
Nature Biotechnology (2024) Vol. 42, Iss. 2, pp. 216-228
Closed Access | Times Cited: 84
Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering
Jason Yang, Francesca-Zhoufan Li, Frances H. Arnold
ACS Central Science (2024) Vol. 10, Iss. 2, pp. 226-241
Open Access | Times Cited: 67
A new age in protein design empowered by deep learning
Hamed Khakzad, Ilia Igashov, Arne Schneuing, et al.
Cell Systems (2023) Vol. 14, Iss. 11, pp. 925-939
Open Access | Times Cited: 47
Atomic context-conditioned protein sequence design using LigandMPNN
Justas Dauparas, Gyu Rie Lee, Robert Pecoraro, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 46
Opportunities and challenges in design and optimization of protein function
Dina Listov, Casper A. Goverde, Bruno E. Correia, et al.
Nature Reviews Molecular Cell Biology (2024) Vol. 25, Iss. 8, pp. 639-653
Closed Access | Times Cited: 41
Sparks of function by de novo protein design
Alexander E. Chu, Tianyu Lu, Po‐Ssu Huang
Nature Biotechnology (2024) Vol. 42, Iss. 2, pp. 203-215
Closed Access | Times Cited: 31
Automated in vivo enzyme engineering accelerates biocatalyst optimization
Enrico Orsi, Lennart Schada von Borzyskowski, Stephan Noack, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 26
AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery
Yue Xu, Shihao Ma, Haotian Cui, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 23
Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development
Kwangho Nam, Yihan Shao, Dan Thomas Major, et al.
ACS Omega (2024)
Open Access | Times Cited: 22
Navigating the landscape of enzyme design: from molecular simulations to machine learning
Jiahui Zhou, Meilan Huang
Chemical Society Reviews (2024) Vol. 53, Iss. 16, pp. 8202-8239
Open Access | Times Cited: 21
Rapid and automated design of two-component protein nanomaterials using ProteinMPNN
Robbert J. de Haas, Natalie Brunette, Alex Goodson, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 13
Open Access | Times Cited: 17
Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities
Connor D. Flynn, Dingran Chang
Diagnostics (2024) Vol. 14, Iss. 11, pp. 1100-1100
Open Access | Times Cited: 17
Computational design of serine hydrolases
Anna Lauko, Samuel J. Pellock, Kiera H. Sumida, et al.
Science (2025)
Open Access | Times Cited: 7
Accelerated enzyme engineering by machine-learning guided cell-free expression
Grant M. Landwehr, Jonathan W. Bogart, Carol Magalhaes, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access | Times Cited: 6
Protein codes promote selective subcellular compartmentalization
Henry R. Kilgore, Itamar Chinn, Peter G. Mikhael, et al.
Science (2025)
Closed Access | Times Cited: 4
Protein Engineering of Substrate Specificity toward Nitrilases: Strategies and Challenges
Shi-Qian Bian, Zi-Kai Wang, Jin‐Song Gong, et al.
Journal of Agricultural and Food Chemistry (2025)
Closed Access | Times Cited: 2
Iminium catalysis in natural Diels–Alderase
Zuodong Sun, Xin Zang, Qingyang Zhou, et al.
Nature Catalysis (2025)
Closed Access | Times Cited: 2
Structure‐Based Drug Discovery with Deep Learning**
Rıza Özçelik, Derek van Tilborg, José Jiménez-Luna, et al.
ChemBioChem (2023) Vol. 24, Iss. 13
Open Access | Times Cited: 37
Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design
Braun Markus, Gruber Christian C, Krassnigg Andreas, et al.
ACS Catalysis (2023) Vol. 13, Iss. 21, pp. 14454-14469
Open Access | Times Cited: 33
AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design
Guillem Casadevall, Cristina Duran, Sílvia Osuna
JACS Au (2023) Vol. 3, Iss. 6, pp. 1554-1562
Open Access | Times Cited: 32
Building Enzymes through Design and Evolution
Euan J. Hossack, Florence J. Hardy, Anthony P. Green
ACS Catalysis (2023) Vol. 13, Iss. 19, pp. 12436-12444
Open Access | Times Cited: 31
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