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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:

TAP 1.0: A robust immunoinformatic tool for the prediction of tumor T-cell antigens based on AAindex properties
Jesús Herrera‐Bravo, Lisandra Herrera Belén, Jorge G. Farías, et al.
Computational Biology and Chemistry (2021) Vol. 91, pp. 107452-107452
Closed Access | Times Cited: 22

Showing 22 citing articles:

Artificial intelligence applied in neoantigen identification facilitates personalized cancer immunotherapy
Yu Cai, Rui Chen, Shenghan Gao, et al.
Frontiers in Oncology (2023) Vol. 12
Open Access | Times Cited: 35
Advances in lipid nanoparticle mRNA therapeutics beyond COVID-19 vaccines
Yeung Wu, Sinuo Yu, Irene de Lázaro
Nanoscale (2024) Vol. 16, Iss. 14, pp. 6820-6836
Closed Access | Times Cited: 8
KSHVbook: An Information‐Sharing Database for Kaposi's Sarcoma‐Associated Herpesvirus
Yong Jiang, Danping Niu, Lei Yu, et al.
Journal of Medical Virology (2025) Vol. 97, Iss. 3
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
In Silico Methods for Assessing Cancer Immunogenicity—A Comparison Between Peptide and Protein Models
Stanislav Sotirov, Ivan Dimitrov
Applied Sciences (2025) Vol. 15, Iss. 8, pp. 4123-4123
Open Access
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
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
Sequence-Based Intelligent Model for Identification of Tumor T Cell Antigens Using Fusion Features
N. Bibi, Mukhtaj Khan, Salman Khan, et al.
IEEE Access (2024) Vol. 12, pp. 155040-155051
Open Access | Times Cited: 4
Vegvisir: Probabilistic Model (VAE) for Viral T-Cell Epitope Prediction
Lys Sanz Moreta, Ibel Carri, Heli M. Garcia Alvarez, et al.
Lecture notes in computer science (2025), pp. 112-130
Closed Access
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
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
MultiToxPred 1.0: a novel comprehensive tool for predicting 27 classes of protein toxins using an ensemble machine learning approach
Jorge F. Beltrán, Lisandra Herrera-Belén, Fernanda Parraguez-Contreras, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 2
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
T cell receptor gene repertoire profiles in subgroups of patients with chronic lymphocytic leukemia bearing distinct genomic aberrations
Elisavet Vlachonikola, Nikolaos Pechlivanis, Georgios Karakatsoulis, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 4
Beyond MHC binding: immunogenicity prediction tools to refine neoantigen selection in cancer patients
Ibel Carri, Erika Schwab, Enrique Podaza, et al.
Exploration of Immunology (2023), pp. 82-103
Open 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
VirVACPRED: A Web Server for Prediction of Protective Viral Antigens
Jesús Herrera‐Bravo, Jorge G. Farías, Fernanda Parraguez Contreras, et al.
International Journal of Peptide Research and Therapeutics (2021) Vol. 28, Iss. 1
Open Access | Times Cited: 10
Combined charge and hydrophobicity-guided screening of antibacterial peptides: two-level approach to predict antibacterial activity and efficacy
Ashwin Bale, Arnab Dutta, Debirupa Mitra
Amino Acids (2023) Vol. 55, Iss. 7, pp. 853-867
Closed Access | Times Cited: 3
PEP-PREDNa+: A web server for prediction of highly specific peptides targeting voltage-gated Na+ channels using machine learning techniques
Jesús Herrera‐Bravo, Jorge G. Farías, Fernanda Parraguez Contreras, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105414-105414
Closed Access | Times Cited: 5
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
Prediction of viral oncoproteins through the combination of generative adversarial networks and machine learning techniques
Jorge F. Beltrán, Lisandra Herrera-Belén, Alejandro J. Yáñez, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
AAindex-PPII: Predicting polyproline type II helix structure based on amino acid indexes with an improved BiGRU-TextCNN model
Jiasheng He, Shun Zhang, Chun Fang
Journal of Bioinformatics and Computational Biology (2023) Vol. 21, Iss. 05
Closed Access | Times Cited: 1
nAChR-PEP-PRED: A Robust Tool for Predicting Peptide Inhibitors of Acetylcholine Receptors Using the Random Forest Classifier
Jesús Herrera‐Bravo, Jorge G. Farías, Cristian Sandoval, et al.
International Journal of Peptide Research and Therapeutics (2022) Vol. 28, Iss. 5
Closed Access
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