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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:

tFold-Ab: Fast and Accurate Antibody Structure Prediction without Sequence Homologs
Jiaxiang Wu, Fandi Wu, Biaobin Jiang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 17

Showing 17 citing articles:

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
A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation
Xiangru Tang, Howard Dai, Elizabeth Knight, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 7
Improved structure-related prediction for insufficient homologous proteins using MSA enhancement and pre-trained language model
Qiaozhen Meng, Fei Guo, Jijun Tang
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 17
AI models for protein design are driving antibody engineering
Michael Chungyoun, Jeffrey J. Gray
Current Opinion in Biomedical Engineering (2023) Vol. 28, pp. 100473-100473
Open 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
Potent human monoclonal antibodies targeting Epstein-Barr virus gp42 reveal vulnerable sites for virus infection
Gexin Zhao, Xin-Yan Fang, Guo‐Long Bu, et al.
Cell Reports Medicine (2024) Vol. 5, Iss. 5, pp. 101573-101573
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
Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Hedi Chen, Xiaoyu Fan, Shuqian Zhu, et al.
eLife (2024) Vol. 12
Open Access | Times Cited: 2
H3-OPT: Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Hedi Chen, Xiaoyu Fan, Shuqian Zhu, et al.
(2024)
Open Access
H3-OPT: Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Hedi Chen, Xiaoyu Fan, Shuqian Zhu, et al.
(2024)
Open Access
AI-accelerated therapeutic antibody development: practical insights
Luca Santuari, Marianne Bachmann Salvy, Ioannis Xénarios, et al.
Frontiers in Drug Discovery (2024) Vol. 4
Open Access
FvFold: A model to predict antibody Fv structure using protein language model with residual network and Rosetta minimization
Pasang Sherpa, Kil To Chong, Hilal Tayara
Computers in Biology and Medicine (2024) Vol. 182, pp. 109128-109128
Closed Access
Structural pre-training improves physical accuracy of antibody structure prediction using deep learning.
Jarosław Kończak, Bartosz Janusz, Jakub Młokosiewicz, et al.
ImmunoInformatics (2023) Vol. 11, pp. 100028-100028
Open Access | Times Cited: 1
Structural pre-training improves physical accuracy of antibody structure prediction using deep learning
Jarosław Kończak, Bartosz Janusz, Jakub Młokosiewicz, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 2
H3-OPT: Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Hedi Chen, Xiaoyu Fan, Shuqian Zhu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access
H3-OPT: Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Hedi Chen, Xiaoyu Fan, Shuqian Zhu, et al.
(2023)
Open Access
Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Hedi Chen, Xiaoyu Fan, Shuqian Zhu, et al.
eLife (2023) Vol. 12
Open Access
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