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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:

Accurate prediction of protein-ATP binding residues using position-specific frequency matrix
Jun Hu, Linlin Zheng, Yansong Bai, et al.
Analytical Biochemistry (2021) Vol. 626, pp. 114241-114241
Closed Access | Times Cited: 16

Showing 16 citing articles:

Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network
Jia‐shun Wu, Yan Liu, Fang Ge, et al.
Computers in Biology and Medicine (2024) Vol. 172, pp. 108227-108227
Closed Access | Times Cited: 7
S-DCNN: prediction of ATP binding residues by deep convolutional neural network based on SMOTE
Sixi Hao, Caiyan Li, Xiuzhen Hu, et al.
Frontiers in Genetics (2025) Vol. 15
Open Access
Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models
Jia‐shun Wu, Yan Liu, Ying Zhang, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
ATP-Pred: Prediction of Protein-ATP Binding Residues via Fusion of Residue-Level Embeddings and Kolmogorov–Arnold Network
Lingrong Zhang, Taigang Liu
Journal of Chemical Information and Modeling (2025)
Closed Access
Improving Identification of Drug-Target Binding Sites Based on Structures of Targets Using Residual Graph Transformer Network
Shuang‐Qing Lv, Xin Zeng, Guang-Peng Su, et al.
Biomolecules (2025) Vol. 15, Iss. 2, pp. 221-221
Open Access
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: 9
Res-GCN: identification of protein phosphorylation sites using graph convolutional network and residual network
Minghui Wang, Jihua Jia, Fei Xu, et al.
Computational Biology and Chemistry (2024) Vol. 112, pp. 108183-108183
Closed Access | Times Cited: 2
Improving the prediction of DNA-protein binding by integrating multi-scale dense convolutional network with fault-tolerant coding
Yuhang Yin, Long-Chen Shen, Yuan-Hao Jiang, et al.
Analytical Biochemistry (2022) Vol. 656, pp. 114878-114878
Closed Access | Times Cited: 7
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 | Times Cited: 1
Support vector machine in drug design
Jose Isagani B. Janairo
Elsevier eBooks (2023), pp. 161-179
Closed Access | Times Cited: 2
A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond
Pengzhen Jia, Fuhao Zhang, Chaojin Wu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access
Unveiling the biosynthesis mechanism of novel lantibiotic homicorcin: an in silico analysis
Amzad Hossain, Md. Rakibul Islam, Omar Faruk, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
ATP_mCNN: Predicting ATP binding sites through pretrained language models and multi-window neural networks
Van‐The Le, Muhammad Shahid Malik, Yi-Jing Lin, et al.
Computers in Biology and Medicine (2024) Vol. 185, pp. 109541-109541
Closed Access
Residue-Level Multiview Deep Learning for ATP Binding Site Prediction and Applications in Kinase Inhibitors
Jae-Chan Lee, Dongmin Bang, Sun Kim
Journal of Chemical Information and Modeling (2024) Vol. 65, Iss. 1, pp. 50-61
Closed Access
A novel fusion technology utilizing complex network and sequence information for FAD-binding site identification
Lichao Zhang, Kang Xiao, Xueting Wang, et al.
Analytical Biochemistry (2023) Vol. 685, pp. 115401-115401
Closed Access | Times Cited: 1
A Deep Model for Species-Specific Prediction of Ribonucleic-Acid-Binding Protein with Short Motifs
Zhisen Wei, Jun Rao, Yaojin Lin
Applied Sciences (2023) Vol. 13, Iss. 14, pp. 8231-8231
Open Access
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