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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:

DEEP-EP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery
Farman Ali, Abdullah Almuhaimeed, Majdi Khalid, et al.
Methods (2024) Vol. 226, pp. 49-53
Closed Access | Times Cited: 11

Showing 11 citing articles:

IP-GCN: A Deep Learning Model for Prediction of Insulin using Graph Convolutional Network for Diabetes Drug Design
Farman Ali, Majdi Khalid, Abdullah Almuhaimeed, et al.
Journal of Computational Science (2024) Vol. 81, pp. 102388-102388
Closed Access | Times Cited: 7
VEGF-ERCNN: A Deep Learning-based Model for Prediction of Vascular Endothelial Growth Factor using Ensemble Residual CNN
Farman Ali, Majdi Khalid, Atef Masmoudi, et al.
Journal of Computational Science (2024), pp. 102448-102448
Closed Access | Times Cited: 5
Advances in Machine Learning for Epigenetics and Biomedical Applications
Hao Lin, Hao Lv, Fanny Dao
Methods (2025) Vol. 235, pp. 53-54
Closed Access
Comprehensive Analysis of Computational Models for Prediction of Anticancer Peptides Using Machine Learning and Deep Learning
Farman Ali, Norazlin Ibrahim, Raed Alsini, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
Conotoxins: Classification, Prediction, and Future Directions in Bioinformatics
Rui Li, Junwen Yu, Dong-Xin Ye, et al.
Toxins (2025) Vol. 17, Iss. 2, pp. 78-78
Open Access
Leveraging deep learning for epigenetic protein prediction: a novel approach for early lung cancer diagnosis and drug discovery
Farman Ali, Abdullah Almuhaimeed, Wajdi Alghamdi, et al.
Health Information Science and Systems (2025) Vol. 13, Iss. 1
Closed Access
A comprehensive review and evaluation of machine learning-based approaches for identifying tumor T cell antigens
Watshara Shoombuatong, Saeed Ahmed, Sakib Mahmud, et al.
Computational Biology and Chemistry (2025), pp. 108440-108440
Closed Access
An omics-driven computational model for angiogenic protein prediction: Advancing therapeutic strategies with Ens-deep-AGP
Naif Almusallam, Farman Ali, Atef Masmoudi, et al.
International Journal of Biological Macromolecules (2024), pp. 136475-136475
Closed Access | Times Cited: 3
Multi-headed Ensemble Residual CNN: A Powerful Tool for Fibroblast Growth Factor Prediction
Naif Almusallam, Farman Ali, Harish Kumar, et al.
Results in Engineering (2024) Vol. 24, pp. 103348-103348
Open Access | Times Cited: 2
TriStack enables accurate identification of antimicrobial and anti-inflammatory peptides by combining machine learning and deep learning approaches
Jiyun Han, Qixuan Chen, J. T. Su, et al.
Future Generation Computer Systems (2024) Vol. 161, pp. 259-268
Closed Access | Times Cited: 1
Identification of CCR7 and CBX6 as key biomarkers in abdominal aortic aneurysm: Insights from multi‐omics data and machine learning analysis
Xi Yong, Xuerui Hu, Tengyao Kang, et al.
IET Systems Biology (2024)
Closed Access
Empirical Comparison and Analysis of Artificial Intelligence-Based Methods for Identifying Phosphorylation Sites of SARS-CoV-2 Infection
Hongyan Lai, Tao Zhu, Sijia Xie, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 24, pp. 13674-13674
Open Access
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