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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:

CPPred-FL: a sequence-based predictor for large-scale identification of cell-penetrating peptides by feature representation learning
Xiaoli Qiang, Chen Zhou, Xiucai Ye, et al.
Briefings in Bioinformatics (2018)
Closed Access | Times Cited: 121

Showing 26-50 of 121 citing articles:

Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines?
Akbar Hasanzadeh, Michael R. Hamblin, Jafar Kiani, et al.
Nano Today (2022) Vol. 47, pp. 101665-101665
Open Access | Times Cited: 40
Machine learning-driven multifunctional peptide engineering for sustained ocular drug delivery
Henry T. Hsueh, Renee Ti Chou, Usha Rai, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 35
Leveraging a meta-learning approach to advance the accuracy of Nav blocking peptides prediction
Watshara Shoombuatong, Nutta Homdee, Nalini Schaduangrat, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 12
Advancing the accuracy of tyrosinase inhibitory peptides prediction via a multiview feature fusion strategy
Watshara Shoombuatong, Nalini Schaduangrat, Nutta Homdee, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
B3Pred: A Random-Forest-Based Method for Predicting and Designing Blood–Brain Barrier Penetrating Peptides
Vinod Kumar, Sumeet Patiyal, Anjali Dhall, et al.
Pharmaceutics (2021) Vol. 13, Iss. 8, pp. 1237-1237
Open Access | Times Cited: 55
PreTP-EL: prediction of therapeutic peptides based on ensemble learning
Yichen Guo, Ke Yan, Hongwu Lv, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 48
Biological Membrane-Penetrating Peptides: Computational Prediction and Applications
Ewerton Cristhian Lima de Oliveira, Kauê Santana da Costa, Paulo Sérgio Taube, et al.
Frontiers in Cellular and Infection Microbiology (2022) Vol. 12
Open Access | Times Cited: 32
SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning
Xin Zhang, Lesong Wei, Xiucai Ye, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Open Access | Times Cited: 29
Stack-AVP: a stacked ensemble predictor based on multi-view information for fast and accurate discovery of antiviral peptides
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, et al.
Journal of Molecular Biology (2024), pp. 168853-168853
Closed Access | Times Cited: 8
M3S-ALG: Improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy
Phasit Charoenkwan, Nalini Schaduangrat, Le Thi Phan, et al.
Future Generation Computer Systems (2024) Vol. 162, pp. 107455-107455
Closed Access | Times Cited: 7
Prediction of Neuropeptides from Sequence Information Using Ensemble Classifier and Hybrid Features
Yannan Bin, Zhang We, Wending Tang, et al.
Journal of Proteome Research (2020) Vol. 19, Iss. 9, pp. 3732-3740
Closed Access | Times Cited: 50
ACEP: improving antimicrobial peptides recognition through automatic feature fusion and amino acid embedding
Haoyi Fu, Zicheng Cao, Mingyuan Li, et al.
BMC Genomics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 41
A comprehensive review of the imbalance classification of protein post-translational modifications
Lijun Dou, Fenglong Yang, Lei Xu, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 37
NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods
Mingming Jiang, Bowen Zhao, Shenggan Luo, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 36
PreTP-Stack: Prediction of Therapeutic Peptide Based on the Stacked Ensemble Learning
Ke Yan, Hongwu Lv, Jie Wen, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1337-1344
Closed Access | Times Cited: 27
Computational prediction and interpretation of druggable proteins using a stacked ensemble-learning framework
Phasit Charoenkwan, Nalini Schaduangrat, Píetro Lió, et al.
iScience (2022) Vol. 25, Iss. 9, pp. 104883-104883
Open Access | Times Cited: 25
Design of Protein Segments and Peptides for Binding to Protein Targets
Suchetana Gupta, Noora Azadvari, Parisa Hosseinzadeh
BioDesign Research (2022) Vol. 2022
Open Access | Times Cited: 23
Cell penetrating peptides: Highlighting points in cancer therapy
Akmal M. Asrorov, Huiyuan Wang, Meng Zhang, et al.
Drug Development Research (2023) Vol. 84, Iss. 6, pp. 1037-1071
Closed Access | Times Cited: 15
Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, et al.
Methods (2024)
Closed Access | Times Cited: 5
DeepCPPred: A Deep Learning Framework for the Discrimination of Cell-Penetrating Peptides and Their Uptake Efficiencies
Muhammad Arif, Muhammad Kabir, Saeed Ahmed, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 5, pp. 2749-2759
Closed Access | Times Cited: 31
Dual-manifold regularized regression models for feature selection based on hesitant fuzzy correlation
Mahla Mokhtia, Mahdi Eftekhari, Farid Saberi-Movahed
Knowledge-Based Systems (2021) Vol. 229, pp. 107308-107308
Closed Access | Times Cited: 28
CSM‐peptides: A computational approach to rapid identification of therapeutic peptides
Carlos H. M. Rodrigues, Anjali Garg, David W. Keizer, et al.
Protein Science (2022) Vol. 31, Iss. 10
Open Access | Times Cited: 22
PreTP-2L: identification of therapeutic peptides and their types using two-layer ensemble learning framework
Ke Yan, Yichen Guo, Bin Liu
Bioinformatics (2023) Vol. 39, Iss. 4
Open Access | Times Cited: 12
Pretraining model for biological sequence data
Bosheng Song, Zimeng Li, Xuan Lin, et al.
Briefings in Functional Genomics (2021) Vol. 20, Iss. 3, pp. 181-195
Open Access | Times Cited: 27
FEGS: a novel feature extraction model for protein sequences and its applications
Zengchao Mu, Ting Yu, Xiaoping Liu, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 27

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