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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:

GeoBind: segmentation of nucleic acid binding interface on protein surface with geometric deep learning
Pengpai Li, Zhi–Ping Liu
Nucleic Acids Research (2023) Vol. 51, Iss. 10, pp. e60-e60
Open Access | Times Cited: 23

Showing 23 citing articles:

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: 21
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Qianmu Yuan, Chong Tian, Yuedong Yang
eLife (2024) Vol. 13
Open Access | Times Cited: 10
GPSFun: geometry-aware protein sequence function predictions with language models
Qianmu Yuan, Chong Tian, Yidong Song, et al.
Nucleic Acids Research (2024) Vol. 52, Iss. W1, pp. W248-W255
Open Access | Times Cited: 8
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: 6
NesT-NABind: a Nested Transformer for Nucleic Acid-Binding Site Prediction on Protein Surface
Xinyue Ma, Fenglei Li, Qianyu Chen, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Deep Learning for Predicting Biomolecular Binding Sites of Proteins
Minjie Mou, Zhichao Zhang, Ziqi Pan, et al.
Research (2025) Vol. 8
Open Access
UMPPI: Unveiling Multilevel Protein–Peptide Interaction Prediction via Language Models
Shuwen Xiong, Jiajie Cai, Hua Shi, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Predicting Small Molecule Binding Nucleotides in RNA Structures Using RNA Surface Topography
Jiaming Gao, Haoquan Liu, Zhuo Chen, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 18, pp. 6979-6992
Closed Access | Times Cited: 4
E2EATP: Fast and High-Accuracy Protein–ATP Binding Residue Prediction via Protein Language Model Embedding
B. Dharma Rao, Xuan Yu, Jie Bai, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 1, pp. 289-300
Closed Access | Times Cited: 8
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Qianmu Yuan, Chong Tian, Yuedong Yang
eLife (2024) Vol. 13
Open Access | Times Cited: 2
m6A-modified cenRNA stabilizes CENPA to ensure centromere integrity in cancer cells
Zihong Kang, Ruimeng Li, Chang Liu, et al.
Cell (2024) Vol. 187, Iss. 21, pp. 6035-6054.e27
Closed Access | Times Cited: 2
MuToN Quantifies Binding Affinity Changes upon Protein Mutations by Geometric Deep Learning
Pengpai Li, Zhi–Ping Liu
Advanced Science (2024)
Open Access | Times Cited: 2
Protein–protein and protein–nucleic acid binding site prediction via interpretable hierarchical geometric deep learning
Shizhuo Zhang, Jiyun Han, Juntao Liu
GigaScience (2024) Vol. 13
Open 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
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Qianmu Yuan, Chong Tian, Yuedong Yang
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Qianmu Yuan, Chong Tian, Yuedong Yang
(2024)
Open Access
PNAbind: Structure-based prediction of protein-nucleic acid binding using graph neural networks
Jared M. Sagendorf, Raktim Mitra, Jiawei Huang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Genome-scale annotation of protein binding sites via language model and geometric deep learning
Qianmu Yuan, Chong Tian, Yuedong Yang
(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
Deep Learning Methods for Binding Site Prediction in Protein Structures
Elizaveta Geraseva
Biochemistry (Moscow) Supplement Series B Biomedical Chemistry (2024) Vol. 18, Iss. 2, pp. 103-117
Closed 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
MERIT: Accurate prediction of multi ligand-binding residues with hybrid deep transformer network, evolutionary couplings and transfer learning
Jian Zhang, Sushmita Basu, Fuhao Zhang, et al.
Journal of Molecular Biology (2024), pp. 168872-168872
Closed Access
Structure-Based Prediction of lncRNA–Protein Interactions by Deep Learning
Pengpai Li, Zhi–Ping Liu
Methods in molecular biology (2024), pp. 363-376
Closed 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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