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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:

EquiPNAS: improved protein–nucleic acid binding site prediction using protein-language-model-informed equivariant deep graph neural networks
Rahmatullah Roche, Bernard Moussad, Md Hossain Shuvo, et al.
Nucleic Acids Research (2024) Vol. 52, Iss. 5, pp. e27-e27
Open Access | Times Cited: 18

Showing 18 citing articles:

RNA Sequence Analysis Landscape: A Comprehensive Review of Task Types, Databases, Datasets, Word Embedding Methods, and Language Models
Muhammad Nabeel Asim, Muhammad Ali Ibrahim, Tayyaba Asif, et al.
Heliyon (2025) Vol. 11, Iss. 2, pp. e41488-e41488
Open Access
MVGNN-PPIS: A novel multi-view graph neural network for protein-protein interaction sites prediction based on Alphafold3-predicted structures and transfer learning
Meng Lu, Wei Lu, Rina Wu
International Journal of Biological Macromolecules (2025), pp. 140096-140096
Closed Access
Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR
Ahtisham Fazeel Abbasi, Muhammad Nabeel Asim, Andreas Dengel
Journal of Translational Medicine (2025) Vol. 23, Iss. 1
Open Access
Interpretable Protein-DNA Interactions Captured by Structure-Sequence Optimization
Yafan Zhang, Irene Silvernail, Zhuyang Lin, et al.
(2025)
Open Access
Interpretable Protein-DNA Interactions Captured by Structure-Sequence Optimization
Yafan Zhang, Irene Silvernail, Zhuyang Lin, et al.
(2025)
Open Access
Structure-based prediction of protein-nucleic acid binding using graph neural networks
Jared M. Sagendorf, Raktim Mitra, Jiawei Huang, et al.
Biophysical Reviews (2024) Vol. 16, Iss. 3, pp. 297-314
Open Access | Times Cited: 5
Improving prediction performance of general protein language model by domain-adaptive pretraining on DNA-binding protein
Wenwu Zeng, Yutao Dou, Liangrui Pan, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 3
Interpretable Protein-DNA Interactions Captured by Structure-based Optimization
Yafan Zhang, Irene Silvernail, Zhuyang Lin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
EGPDI: identifying protein–DNA binding sites based on multi-view graph embedding fusion
Mengxin Zheng, Guicong Sun, Xueping Li, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 2
PDNAPred: Interpretable prediction of protein-DNA binding sites based on pre-trained protein language models
Lingrong Zhang, Taigang Liu
International Journal of Biological Macromolecules (2024), pp. 136147-136147
Closed Access | Times Cited: 1
Hybrid protein-ligand binding residue prediction with protein language models: Does the structure matter?
Hamza Gamouh, Marián Novotný, David Hoksza
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Single-sequence protein-RNA complex structure prediction by geometric attention-enabled pairing of biological language models
Rahmatullah Roche, Sumit Tarafder, Debswapna Bhattacharya
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Advances in the Application of Protein Language Modeling for Nucleic Acid Protein Binding Site Prediction
Bo Wang, Wenjin Li
Genes (2024) Vol. 15, Iss. 8, pp. 1090-1090
Open Access
GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning
Jiyun Han, Shizhuo Zhang, Mingming Guan, et al.
Structure (2024)
Closed Access
Nanobody–antigen interaction prediction with ensemble deep learning and prompt-based protein language models
Juntao Deng, Miao Gu, Pengyan Zhang, et al.
Nature Machine Intelligence (2024)
Closed Access
Accurate nucleic acid-binding residue identification based on domain-adaptive protein language model and explainable geometric deep learning
Wenwu Zeng, Liangrui Pan, Boya Ji, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
EquiRank: Improved protein-protein interface quality estimation using protein language-model-informed equivariant graph neural networks
Md Hossain Shuvo, Debswapna Bhattacharya
Computational and Structural Biotechnology Journal (2024) Vol. 27, pp. 160-170
Open Access
Twenty years of advances in prediction of nucleic acid-binding residues in protein sequences
Sushmita Basu, Jing Yu, Daisuke Kihara, et al.
Briefings in Bioinformatics (2024) Vol. 26, Iss. 1
Open Access
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