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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:

ACP-GBDT: An improved anticancer peptide identification method with gradient boosting decision tree
Yanjuan Li, Ma Di, Dong Chen, et al.
Frontiers in Genetics (2023) Vol. 14
Open Access | Times Cited: 12

Showing 12 citing articles:

ACP-ESM: A novel framework for classification of anticancer peptides using protein-oriented transformer approach
Zeynep Hilal Kilimci, Mustafa Yalçın
Artificial Intelligence in Medicine (2024) Vol. 156, pp. 102951-102951
Open Access | Times Cited: 7
Trends and Determinants of Global Infectious Disease Burden from 1990 to 2021: Insights from Machine Learning Models
Hengliang Lv, Longhao Wang, Xueli Zhang, et al.
(2025)
Closed Access
ANNprob-ACPs: A novel anticancer peptide identifier based on probabilistic feature fusion approach
Tasmin Karim, Md. Shazzad Hossain Shaon, Md. Fahim Sultan, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107915-107915
Closed Access | Times Cited: 13
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
Source identification of mine water inrush based on GBDT-RS-SHAP
Zhenwei Yang, Han Li, Xinyi Wang, et al.
Environmental Earth Sciences (2025) Vol. 84, Iss. 4
Closed Access
Mining Bovine Milk Proteins for DPP-4 Inhibitory Peptides Using Machine Learning and Virtual Proteolysis
Yiyun Zhang, Yiqing Zhu, Xin Bao, et al.
Research (2024) Vol. 7
Open Access | Times Cited: 3
ACP-ESM2: The prediction of anticancer peptides based on pre-trained classifier
Huijia Song, Xiaozhu Lin, Huainian Zhang, et al.
Computational Biology and Chemistry (2024) Vol. 110, pp. 108091-108091
Closed Access | Times Cited: 3
Discovery of anticancer peptides from natural and generated sequences using deep learning
Jianda Yue, Tingting Li, Jiawei Xu, et al.
International Journal of Biological Macromolecules (2024) Vol. 290, pp. 138880-138880
Closed Access | Times Cited: 1
Prediction of SO2, NOx and PM in the sintering process based on deep learning
Baorong Wang, Xiaoming Li, Yize Ren, et al.
Ironmaking & Steelmaking Processes Products and Applications (2024)
Closed Access
Cancer pharmacoinformatics: Databases and analytical tools
Pradnya Kamble, Prinsa R. Nagar, Kaushikkumar A. Bhakhar, et al.
Functional & Integrative Genomics (2024) Vol. 24, Iss. 5
Closed 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
A Stacking Machine Learning Method for IL-10-Induced Peptide Sequence Recognition Based on Unified Deep Representation Learning
Jiayu Li, Jici Jiang, Hongdi Pei, et al.
Applied Sciences (2023) Vol. 13, Iss. 16, pp. 9346-9346
Open Access
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