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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:

Enzyme function prediction using contrastive learning
Tianhao Yu, Haiyang Cui, Jianan Canal Li, et al.
Science (2023) Vol. 379, Iss. 6639, pp. 1358-1363
Closed Access | Times Cited: 158

Showing 1-25 of 158 citing articles:

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: 168
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
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: 51
Discovering functionally important sites in proteins
Matteo Cagiada, Sandro Bottaro, Søren Lindemose, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 41
Functional annotation of enzyme-encoding genes using deep learning with transformer layers
Gi Bae Kim, Ji Yeon Kim, Jong An Lee, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 41
Genomic language model predicts protein co-regulation and function
Yunha Hwang, Andre Cornman, Elizabeth H. Kellogg, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 24
Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges
Manoj Kumar Goshisht
ACS Omega (2024) Vol. 9, Iss. 9, pp. 9921-9945
Open Access | Times Cited: 20
Drug target prediction through deep learning functional representation of gene signatures
Hao Chen, Frederick J. King, Bin Zhou, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 20
Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms
Jiwei Mao, Hongyu Zhang, Yu Chen, et al.
Biotechnology Advances (2024) Vol. 74, pp. 108401-108401
Open Access | Times Cited: 15
Discovery of Toxin-Degrading Enzymes with Positive Unlabeled Deep Learning
Dachuan Zhang, Huadong Xing, Dongliang Liu, et al.
ACS Catalysis (2024) Vol. 14, Iss. 5, pp. 3336-3348
Closed Access | Times Cited: 13
Structure-based self-supervised learning enables ultrafast protein stability prediction upon mutation
Jinyuan Sun, Tong Zhu, Yinglu Cui, et al.
The Innovation (2025) Vol. 6, Iss. 1, pp. 100750-100750
Open Access | Times Cited: 1
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: 1
Engineering extracellular electron transfer pathways of electroactive microorganisms by synthetic biology for energy and chemicals production
Junqi Zhang, Feng Li, Dingyuan Liu, et al.
Chemical Society Reviews (2023) Vol. 53, Iss. 3, pp. 1375-1446
Closed Access | Times Cited: 33
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: 29
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: 29
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: 28
Precision enzyme discovery through targeted mining of metagenomic data
Shohreh Ariaeenejad, Javad Gharechahi, Mehdi Foroozandeh Shahraki, et al.
Natural Products and Bioprospecting (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Prophage proteins alter long noncoding RNA and DNA of developing sperm to induce a paternal-effect lethality
Rupinder Kaur, Angelina McGarry, J. Dylan Shropshire, et al.
Science (2024) Vol. 383, Iss. 6687, pp. 1111-1117
Open Access | Times Cited: 8
Extremozymes: Challenges and opportunities on the road to novel enzymes production
Diego I.J. Salas-Bruggink, Jorge Sánchez-San Martín, Gabriel Leiva, et al.
Process Biochemistry (2024) Vol. 143, pp. 323-336
Closed Access | Times Cited: 8
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: 8
Bilingual language model for protein sequence and structure
Michael Heinzinger, Konstantin Weißenow, Joaquin Gomez Sanchez, et al.
NAR Genomics and Bioinformatics (2024) Vol. 6, Iss. 4
Open Access | Times Cited: 8
Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures
Anna Carbery, Martin Buttenschoen, R. Skyner, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 7
Characterization of a recombinant tannase from Pseudoduganella albidiflava with high substance affinity for propyl gallate
Dongfang Zhao, Huan Zeng, Shuang Xiao, et al.
Process Biochemistry (2024) Vol. 138, pp. 150-158
Closed Access | Times Cited: 6
BERT-TFBS: a novel BERT-based model for predicting transcription factor binding sites by transfer learning
Kai Wang, Xuan Zeng, Jingwen Zhou, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 6
Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering
Peng Cheng, Cong Mao, Jin Tang, et al.
Cell Research (2024) Vol. 34, Iss. 9, pp. 630-647
Open Access | Times Cited: 6
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