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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:

H2Opred: a robust and efficient hybrid deep learning model for predicting 2’-O-methylation sites in human RNA
Nhat Truong Pham, Rajan Rakkiyapan, Jongsun Park, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 21

Showing 21 citing articles:

DOGpred: A Novel Deep Learning Framework for Accurate Identification of Human O-linked Threonine Glycosylation Sites
Ki Wook Lee, Nhat Truong Pham, Hye Jung Min, et al.
Journal of Molecular Biology (2025), pp. 168977-168977
Closed Access | Times Cited: 1
ac4C-AFL: A high-precision identification of human mRNA N4-acetylcytidine sites based on adaptive feature representation learning
Nhat Truong Pham, Annie Terrina Terrance, Young-Jun Jeon, et al.
Molecular Therapy — Nucleic Acids (2024) Vol. 35, Iss. 2, pp. 102192-102192
Open Access | Times Cited: 9
AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus
Shaherin Basith, Balachandran Manavalan, Gwang Lee
Methods (2025)
Closed 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
PMPred-AE: a computational model for the detection and interpretation of pathological myopia based on artificial intelligence
Hongqi Zhang, Muhammad Arif, Maha A. Thafar, et al.
Frontiers in Medicine (2025) Vol. 12
Open Access
DrugPred: An ensemble learning model based on ESM2 for predicting potential druggable proteins
Hongqi Zhang, Shanghua Liu, Jun-Wen Yu, et al.
Future Generation Computer Systems (2025), pp. 107801-107801
Closed Access
Computational prediction of phosphorylation sites of SARS-CoV-2 infection using feature fusion and optimization strategies
Mumdooh J. Sabir, Majid Rasool Kamli, Ahmed Atef, et al.
Methods (2024) Vol. 229, pp. 1-8
Closed Access | Times Cited: 4
SEP-AlgPro: An efficient allergen prediction tool utilizing traditional machine learning and deep learning techniques with protein language model features
Shaherin Basith, Nhat Truong Pham, Balachandran Manavalan, et al.
International Journal of Biological Macromolecules (2024) Vol. 273, pp. 133085-133085
Closed Access | Times Cited: 4
E-MuLA: An Ensemble Multi-Localized Attention Feature Extraction Network for Viral Protein Subcellular Localization
Grace-Mercure Bakanina Kissanga, Hasan Zulfiqar, Shenghan Gao, et al.
Information (2024) Vol. 15, Iss. 3, pp. 163-163
Open Access | Times Cited: 2
Attention mechanism models for precision medicine
Liang Cheng
Briefings in Bioinformatics (2024) Vol. 25, Iss. 4
Open Access | Times Cited: 2
Meta-2OM: A multi-classifier meta-model for the accurate prediction of RNA 2′-O-methylation sites in human RNA
Md. Harun-Or-Roshid, Nhat Truong Pham, Balachandran Manavalan, et al.
PLoS ONE (2024) Vol. 19, Iss. 6, pp. e0305406-e0305406
Open Access | Times Cited: 2
mHPpred: Accurate identification of peptide hormones using multi-view feature learning
Shaherin Basith, Vinoth Kumar Sangaraju, Balachandran Manavalan, et al.
Computers in Biology and Medicine (2024) Vol. 183, pp. 109297-109297
Closed Access | Times Cited: 2
METnet: A novel deep learning model predicting MET dysregulation in non-small-cell lung cancer on computed tomography images
Yige Sun, Jirui Guo, Yang Liu, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108136-108136
Closed Access | Times Cited: 1
RDscan: Extracting RNA-disease relationship from the literature based on pre-training model
Yang Zhang, Yu Yang, Liping Ren, et al.
Methods (2024) Vol. 228, pp. 48-54
Closed Access | Times Cited: 1
DeepIRES: a hybrid deep learning model for accurate identification of internal ribosome entry sites in cellular and viral mRNAs
Jian Zhao, Zhewei Chen, Meng Zhang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 5
Open Access | Times Cited: 1
MST-m6A: A Novel Multi-Scale Transformer-based Framework for Accurate Prediction of m6A Modification Sites Across Diverse Cellular Contexts
Qiaosen Su, Le Thi Phan, Nhat Truong Pham, et al.
Journal of Molecular Biology (2024), pp. 168856-168856
Closed Access | Times Cited: 1
Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration
Xinxin Wang, Can Yu, Yucheng Sun, et al.
Computers in Biology and Medicine (2024) Vol. 172, pp. 108253-108253
Closed Access
Prediction of cell-type-specific cohesin-mediated chromatin loops based on chromatin state
Li Liu, Ranran Jia, Rui Hou, et al.
Methods (2024) Vol. 226, pp. 151-160
Closed Access
A protein pre-trained model-based approach for the identification of the liquid-liquid phase separation (LLPS) proteins
Zahoor Ahmed, Kiran Shahzadi, Sebu Aboma Temesgen, et al.
International Journal of Biological Macromolecules (2024) Vol. 277, pp. 134146-134146
Closed Access
Bioinformatics for Inosine: Tools and Approaches to Trace This Elusive RNA Modification
Enrico Bortoletto, Umberto Rosani
Genes (2024) Vol. 15, Iss. 8, pp. 996-996
Open Access
Deciphering the Complex Characterization of Coding LncRNA
Tianyuan Liu, Xiucai Ye, Tetsuya Sakurai
2022 International Joint Conference on Neural Networks (IJCNN) (2024), pp. 1-8
Closed Access
Nmix: a hybrid deep learning model for precise prediction of 2’-O-methylation sites based on multi-feature fusion and ensemble learning
Yuqing Geng, Fei-Liao Lai, Hao Luo, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access
AISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules
Subathra Selvam, Priya Dharshini Balaji, Honglae Sohn, et al.
Pharmaceuticals (2024) Vol. 17, Iss. 12, pp. 1693-1693
Open Access
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