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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:

Deep learning guided optimization of human antibody against SARS-CoV-2 variants with broad neutralization
Sisi Shan, Shitong Luo, Ziqing Yang, et al.
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 11
Open Access | Times Cited: 96

Showing 1-25 of 96 citing articles:

Efficient evolution of human antibodies from general protein language models
Brian Hie, Varun R. Shanker, Duo Xu, et al.
Nature Biotechnology (2023) Vol. 42, Iss. 2, pp. 275-283
Open Access | Times Cited: 203
Computational and artificial intelligence-based methods for antibody development
Ji‐Sun Kim, Matthew McFee, Qiao Fang, et al.
Trends in Pharmacological Sciences (2023) Vol. 44, Iss. 3, pp. 175-189
Open Access | Times Cited: 84
Development of therapeutic antibodies for the treatment of diseases
Zeng Wang, Guoqing Wang, Huaqing Lu, et al.
Molecular Biomedicine (2022) Vol. 3, Iss. 1
Open Access | Times Cited: 73
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: 66
Deep-learning-enabled protein–protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution
Guangyu Wang, Xiaohong Liu, Kai Wang, et al.
Nature Medicine (2023) Vol. 29, Iss. 8, pp. 2007-2018
Closed Access | Times Cited: 40
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
Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries
Lin Li, Esther Gupta, John Spaeth, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 37
PLMSearch: Protein language model powers accurate and fast sequence search for remote homology
Wei Liu, Ziye Wang, Ronghui You, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 17
Unlockingde novoantibody design with generative artificial intelligence
Amir Shanehsazzadeh, Matt McPartlon, George W. Kasun, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 33
Recent advances in predicting and modeling protein–protein interactions
Jesse Durham, Jing Zhang, Ian R. Humphreys, et al.
Trends in Biochemical Sciences (2023) Vol. 48, Iss. 6, pp. 527-538
Closed Access | Times Cited: 27
Modeling the competitive transmission of the Omicron strain and Delta strain of COVID-19
Youming Guo, Tingting Li
Journal of Mathematical Analysis and Applications (2023) Vol. 526, Iss. 2, pp. 127283-127283
Open Access | Times Cited: 24
Protein Engineering with Lightweight Graph Denoising Neural Networks
Bingxin Zhou, Lirong Zheng, Banghao Wu, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 9, pp. 3650-3661
Open Access | Times Cited: 8
Advancing Antibody Engineering through Synthetic Evolution and Machine Learning
Edward B. Irvine, Sai T. Reddy
The Journal of Immunology (2024) Vol. 212, Iss. 2, pp. 235-243
Closed Access | Times Cited: 7
Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions
Doo Nam Kim, Andrew McNaughton, Neeraj Kumar
Bioengineering (2024) Vol. 11, Iss. 2, pp. 185-185
Open Access | Times Cited: 7
De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model
Haohuai He, Bing He, Lei Guan, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
Single-cell spatiotemporal analysis reveals alveolar dendritic cell–T cell immunity hubs defending against pulmonary infection
Boyi Cong, Xuan Dong, Zongheng Yang, et al.
Cell Discovery (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
Predicting Antibody Affinity Changes upon Mutation Based on Unbound Protein Structures
Zhengshan Chen, Song He, Xiangyang Chi, et al.
International Journal of Molecular Sciences (2025) Vol. 26, Iss. 3, pp. 1343-1343
Open Access
Efficient evolution of human antibodies from general protein language models and sequence information alone
Brian Hie, Duo Xu, Varun R. Shanker, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 26
Deep learning in preclinical antibody drug discovery and development
Yuwei Zhou, Ziru Huang, Wenzhen Li, et al.
Methods (2023) Vol. 218, pp. 57-71
Closed Access | Times Cited: 16
Fast and accurate modeling and design of antibody-antigen complex using tFold
Fandi Wu, Yu Zhao, Jiaxiang Wu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 5
Pretrainable geometric graph neural network for antibody affinity maturation
Huiyu Cai, Zuobai Zhang, Mingkai Wang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Antibody design using deep learning: from sequence and structure design to affinity maturation
Sara Joubbi, Alessio Micheli, Paolo Milazzo, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 4
Pulse dipolar EPR for determining nanomolar binding affinities
Katrin Ackermann, Joshua L. Wort, Bela E. Bode
Chemical Communications (2022) Vol. 58, Iss. 63, pp. 8790-8793
Open Access | Times Cited: 18
Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer
Cheng Tan, Zhangyang Gao, Lirong Wu, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 14, pp. 15222-15230
Open Access | Times Cited: 3
Learned features of antibody-antigen binding affinity
Nathaniel L. Miller, Thomas A. Clark, Rahul Raman, et al.
Frontiers in Molecular Biosciences (2023) Vol. 10
Open Access | Times Cited: 9
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