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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:

PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning
Phasit Charoenkwan, Chonlatip Pipattanaboon, Chanin Nantasenamat, et al.
Computers in Biology and Medicine (2022) Vol. 152, pp. 106368-106368
Closed Access | Times Cited: 14

Showing 14 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
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: 5
Advancing the Accuracy of Anti-MRSA Peptide Prediction Through Integrating Multi-Source Protein Language Models
Watshara Shoombuatong, Pakpoom Mookdarsanit, Lawankorn Mookdarsanit, et al.
Interdisciplinary Sciences Computational Life Sciences (2025)
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
Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing
Thi-Oanh Tran, Nguyen Quoc Khanh Le
Computers in Biology and Medicine (2024) Vol. 174, pp. 108408-108408
Closed Access | Times Cited: 4
PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, et al.
Computers in Biology and Medicine (2023) Vol. 158, pp. 106784-106784
Closed Access | Times Cited: 9
Tumor-Derived Antigenic Peptides as Potential Cancer Vaccines
Stanislav Sotirov, Ivan Dimitrov
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 9, pp. 4934-4934
Open Access | Times Cited: 3
Application of Machine Learning Algorithms for Prediction of Tumor T-Cell Immunogens
Stanislav Sotirov, Ivan Dimitrov
Applied Sciences (2024) Vol. 14, Iss. 10, pp. 4034-4034
Open Access | Times Cited: 2
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: 2
Pretoria: An effective computational approach for accurate and high-throughput identification of CD8+ t-cell epitopes of eukaryotic pathogens
Phasit Charoenkwan, Nalini Schaduangrat, Nhat Truong Pham, et al.
International Journal of Biological Macromolecules (2023) Vol. 238, pp. 124228-124228
Closed Access | Times Cited: 4
StackTTCA: a stacking ensemble learning-based framework for accurate and high-throughput identification of tumor T cell antigens
Phasit Charoenkwan, Nalini Schaduangrat, Watshara Shoombuatong
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 4
iTTCA-MVL: A multi-view learning model based on physicochemical information and sequence statistical information for tumor T cell antigens identification
Shulin Zhao, Shibo Huang, Mengting Niu, et al.
Computers in Biology and Medicine (2024) Vol. 170, pp. 107941-107941
Closed Access | Times Cited: 1
Accelerating the identification of the allergenic potential of plant proteins using a stacked ensemble-learning framework
Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, et al.
Journal of Biomolecular Structure and Dynamics (2024), pp. 1-13
Closed Access | Times Cited: 1
Empirical comparison and analysis of machine learning-based approaches for druggable protein identification.
Watshara Shoombuatong, Nalini Schaduangrat, Jaru Nikom
PubMed (2023) Vol. 22, pp. 915-927
Closed Access | Times Cited: 2
ENCAP: Computational prediction of tumor T cell antigens with ensemble classifiers and diverse sequence features
Jen-Chieh Yu, Kuan Ni, Ching-Tai Chen
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0307176-e0307176
Open Access
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