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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:

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: 28

Showing 1-25 of 28 citing articles:

Cancer Nanovaccines: Nanomaterials and Clinical Perspectives
Nimeet Desai, Vivek P. Chavda, Thakur Raghu Raj Singh, et al.
Small (2024) Vol. 20, Iss. 35
Open Access | Times Cited: 17
Neoantigen-targeted TCR-engineered T cell immunotherapy: current advances and challenges
Zhi Pang, Manman Lu, Yu Zhang, et al.
Biomarker Research (2023) Vol. 11, Iss. 1
Open Access | Times Cited: 23
Leveraging artificial intelligence in vaccine development: A narrative review
David B. Olawade, Jennifer Teke, Oluwaseun Fapohunda, et al.
Journal of Microbiological Methods (2024) Vol. 224, pp. 106998-106998
Open Access | Times Cited: 10
Artificial intelligence in Immuno-genetics
Raed Farzan
Bioinformation (2024) Vol. 20, Iss. 1, pp. 29-35
Open Access | Times Cited: 9
State-Of-The-Art Advancements on Cancer Vaccines and Biomarkers
Scott Strum, Mads Hald Andersen, Inge Marie Svane, et al.
American Society of Clinical Oncology Educational Book (2024) Vol. 44, Iss. 3
Closed Access | Times Cited: 6
An in-depth review of AI-powered advancements in cancer drug discovery
Le Huu Nhat Minh, P Nguyen, Nguyen Thi Trang, et al.
Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease (2025), pp. 167680-167680
Closed Access
Integrating AI into Cancer Immunotherapy—A Narrative Review of Current Applications and Future Directions
David B. Olawade, Aanuoluwapo Clement David-Olawade, Temitope Adereni, et al.
Diseases (2025) Vol. 13, Iss. 1, pp. 24-24
Open Access
The landscape of neoantigens and its clinical applications: From immunobiology to cancer vaccines
Chiranjib Chakraborty, Anirban Majumder, Manojit Bhattacharya, et al.
Current Research in Biotechnology (2024) Vol. 7, pp. 100177-100177
Open Access | Times Cited: 5
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
Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy
Alla Bulashevska, Zsófia Nacsa, Franziska Lang, et al.
Frontiers in Immunology (2024) Vol. 15
Open Access | Times Cited: 2
Harnessing Artificial Intelligence for the Detection and Management of Colorectal Cancer Treatment
Michael Jacob, Ruhananhad P. Reddy, Ricardo Isaiah Garcia, et al.
Cancer Prevention Research (2024) Vol. 17, Iss. 11, pp. 499-515
Closed Access | Times Cited: 1
mRNA-based cancer therapeutics
Anya M Hillery
Elsevier eBooks (2024), pp. 153-185
Closed Access | Times Cited: 1
Recent Progress in Cancer Vaccines and Nanovaccines
Kishwor Poudel, Tulasi Vithiananthan, Jong Oh Kim, et al.
Biomaterials (2024) Vol. 314, pp. 122856-122856
Closed Access | Times Cited: 1
Geometric deep learning improves generalizability of MHC-bound peptide predictions
Dario F. Marzella, Giulia Crocioni, Tadija Radusinović, et al.
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 1
Improving generalizability for MHC-I binding peptide predictions through geometric deep learning
Dario F. Marzella, Giulia Crocioni, Tadija Radusinović, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Advancements and hurdles in the development of a vaccine for triple-negative breast cancer: A comprehensive review of multi-omics and immunomics strategies
T Dhanushkumar, Santhosh Mukundan, Prasanna Kumar Selvam, et al.
Life Sciences (2023) Vol. 337, pp. 122360-122360
Closed Access | Times Cited: 2
Combination of multiple omics techniques for a personalized therapy or treatment selection
Chiara Massa, Barbara Seliger
Frontiers in Immunology (2023) Vol. 14
Open Access | Times Cited: 2
Improving generalizability and data efficiency for MHC-I binding peptide predictions through structure-based geometric deep learning
Li C. Xue, Dario F. Marzella, Giulia Crocioni, et al.
Research Square (Research Square) (2024)
Open Access
Cancer Vaccines
Dito Anurogo
Jurnal kedokteran dan kesehatan Indonesia (2024), pp. 1-2
Open Access
A look into the neighboring discipline: eHealth in oncology
Friedrich Overkamp
Deleted Journal (2024) Vol. 95, Iss. 6, pp. 451-458
Closed Access
Exploring the Potential of Neoantigen-Targeted Immunotherapies in Rare Cancers
Amir Ghaffari Jolfayi, Zahra Taheri, Soroush Khojasteh-Kaffash, et al.
Springer eBooks (2024), pp. 1-32
Closed Access
DeepNeoAG: Neoantigen epitope prediction from melanoma antigens using a synergistic deep learning model combining protein language models and multi-window scanning convolutional neural networks
Cheng-Che Chuang, Yuchen Liu, Yu‐Yen Ou
International Journal of Biological Macromolecules (2024), pp. 136252-136252
Closed Access
A new era with advanced immunotherapy
Claudia Badia Lopez, Elisabeth J. Ruijgrok, Casper H.J. van Eijck
Translational Gastroenterology and Hepatology (2024) Vol. 9, pp. 60-60
Open Access
Prospects and challenges of neoantigen applications in oncology
Ranran Shi, Ling Ran, Yuan Tian, et al.
International Immunopharmacology (2024) Vol. 143, pp. 113329-113329
Closed Access
Advances in mRNA LNP-Based Cancer Vaccines: Mechanisms, Formulation Aspects, Challenges, and Future Directions
Eslam Ramadan, Ali Ahmed Ali Ismeal, Youssef W. Naguib
Journal of Personalized Medicine (2024) Vol. 14, Iss. 11, pp. 1092-1092
Open Access
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