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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:

Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning
Ziyi Zhou, Liang Zhang, Yuanxi Yu, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 16

Showing 16 citing articles:

Biophysics-based protein language models for protein engineering
Sam Gelman, Bryce Johnson, Chase R. Freschlin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 9
Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein–Protein Interactions
Yang Yue, Yihua Cheng, CĂ©line Marquet, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
SaprotHub: Making Protein Modeling Accessible to All Biologists
Jin Su, Zhikai Li, Chenchen Han, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Integrating Computational Design and Experimental Approaches for Next-Generation Biologics
Ahrum Son, Jongham Park, Woojin Kim, et al.
(2024)
Open Access | Times Cited: 1
Synergizing sequence and structure representations to predict protein variants
Tong Chen, Pranam Chatterjee
Cell Research (2024) Vol. 34, Iss. 9, pp. 597-598
Open Access
Integrating Computational Design and Experimental Approaches for Next-Generation Biologics
Ahrum Son, Jongham Park, Woojin Kim, et al.
Biomolecules (2024) Vol. 14, Iss. 9, pp. 1073-1073
Open Access
AI-enabled Alkaline-resistant Evolution of Protein to Apply in Mass Production
Liqi Kang, Banghao Wu, Bingxin Zhou, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Prediction and design of transcriptional repressor domains with large-scale mutational scans and deep learning
Raeline Valbuena, AkshatKumar Nigam, Josh Tycko, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access
Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence
Ahrum Son, Jongham Park, Woojin Kim, et al.
Molecules (2024) Vol. 29, Iss. 19, pp. 4626-4626
Open Access
Enhancing Enzyme Activity with Mutation Combinations Guided by Few-shot Learning and Causal Inference
Boxue Tian, Lin Guo, Xiaoguang Yan, et al.
Research Square (Research Square) (2024)
Open Access
AI-enabled Alkaline-resistant Evolution of Protein to Apply in Mass Production
Liqi Kang, Banghao Wu, Bingxin Zhou, et al.
(2024)
Open Access
AI-enabled Alkaline-resistant Evolution of Protein to Apply in Mass Production
Liqi Kang, Banghao Wu, Bingxin Zhou, et al.
(2024)
Open Access
An explainable few-shot learning model for the directed evolution of antimicrobial peptides
Qiandi Gao, Liangjun Ge, Yihan Wang, et al.
International Journal of Biological Macromolecules (2024) Vol. 285, pp. 138272-138272
Closed Access
BindingGYM: A Large-Scale Mutational Dataset Toward Deciphering Protein-Protein Interactions
Wei Lu, Jixian Zhang, Ming Gu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Protein engineering in the deep learning era
Bingxin Zhou, Yang Tan, Yutong Hu, et al.
mLife (2024) Vol. 3, Iss. 4, pp. 477-491
Open Access
Discovery of highly active kynureninases for cancer immunotherapy through protein language model
Hyunuk Eom, Sukhwan Park, Kye Soo Cho, et al.
Nucleic Acids Research (2024) Vol. 53, Iss. 1
Open Access
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