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:

The Development of Machine Learning Methods in Cell-Penetrating Peptides Identification: A Brief Review
Huanhuan Wei, Wuritu Yang, Hua Tang, et al.
Current Drug Metabolism (2018) Vol. 20, Iss. 3, pp. 217-223
Closed Access | Times Cited: 14

Showing 14 citing articles:

The role of cell‐penetrating peptides in potential anti‐cancer therapy
Meiling Zhou, Zou Xi, Kexin Cheng, et al.
Clinical and Translational Medicine (2022) Vol. 12, Iss. 5
Open Access | Times Cited: 81

Cell Penetrating Peptides: Classification, Mechanisms, Methods of Study, and Applications
Alessandro Gori, Giulia Lodigiani, Stella Garcia Colombarolli, et al.
ChemMedChem (2023) Vol. 18, Iss. 17
Open Access | Times Cited: 57

Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools
Ran Su, Jie Hu, Quan Zou, et al.
Briefings in Bioinformatics (2018) Vol. 21, Iss. 2, pp. 408-420
Closed Access | Times Cited: 148

AI-Driven Innovations in Smart Multifunctional Nanocarriers for Drug and Gene Delivery: A Mini-Review
H. Noury, Abbas Rahdar, Luiz Fernando Romanholo Ferreira, et al.
Critical Reviews in Oncology/Hematology (2025), pp. 104701-104701
Closed Access | Times Cited: 1

Cell-Penetrating Peptides Derived from Animal Venoms and Toxins
Gandhi Rádis‐Baptista
Toxins (2021) Vol. 13, Iss. 2, pp. 147-147
Open Access | Times Cited: 54

Prediction of Amphiphilic Cell-Penetrating Peptide Building Blocks from Protein-Derived Amino Acid Sequences for Engineering of Drug Delivery Nanoassemblies
Guillaume Feger, Borislav Angelov, Angelina Angelova
The Journal of Physical Chemistry B (2020) Vol. 124, Iss. 20, pp. 4069-4078
Open Access | Times Cited: 53

Uptake pathways of cell-penetrating peptides in the context of drug delivery, gene therapy, and vaccine development
Moataz Dowaidar
Cellular Signalling (2024) Vol. 117, pp. 111116-111116
Closed Access | Times Cited: 7

CPPCGM: A Highly Efficient Sequence-Based Tool for Simultaneously Identifying and Generating Cell-Penetrating Peptides
Qiufen Chen, Yuewei Zhang, Jiali Gao, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access

A bird’s-eye view of the biological mechanism and machine learning prediction approaches for cell-penetrating peptides
Maduravani Ramasundaram, Honglae Sohn, Thirumurthy Madhavan
Frontiers in Artificial Intelligence (2025) Vol. 7
Open Access

"Computational Approaches for Identifying Neuropeptides: A Comprehensive Review"
Roger Rahmani, Leila R Kalankesh, Reza Ferdousi
Molecular Therapy — Nucleic Acids (2024) Vol. 36, Iss. 1, pp. 102409-102409
Open Access | Times Cited: 2

Application of machine learning for ancestry inference using multi-InDel markers
Kuan Sun, Yining Yao, Libing Yun, et al.
Forensic Science International Genetics (2022) Vol. 59, pp. 102702-102702
Closed Access | Times Cited: 12

In silico identification and experimental validation of cellular uptake and intracellular labeling by a new cell penetrating peptide derived from CDN1
Xiangli Guo, Linlin Chen, Lidan Wang, et al.
Drug Delivery (2021) Vol. 28, Iss. 1, pp. 1722-1736
Open Access | Times Cited: 11

Predicting Cell-Penetrating Peptides: Building and Interpreting Random Forest based prediction Models
Shilpa Yadahalli, Chandra Verma
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 5

Methods for CPP Selection, Prediction and in Silico Analysis
Ülo Langel
Springer eBooks (2023), pp. 83-94
Closed Access

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