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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:

Rapid assessment of T-cell receptor specificity of the immune repertoire
Xingcheng Lin, Jason T. George, Nicholas P. Schafer, et al.
Nature Computational Science (2021) Vol. 1, Iss. 5, pp. 362-373
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

epiTCR: a highly sensitive predictor for TCR–peptide binding
My-Diem Nguyen Pham, Thanh-Nhan Nguyen, Le Son Tran, et al.
Bioinformatics (2023) Vol. 39, Iss. 5
Open Access | Times Cited: 36
Characterizing the interaction conformation between T-cell receptors and epitopes with deep learning
Xingang Peng, Yipin Lei, Peiyuan Feng, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 4, pp. 395-407
Closed Access | Times Cited: 33
RACER-m leverages structural features for sparse T cell specificity prediction
Ailun Wang, Xingcheng Lin, Kevin Ng Chau, et al.
Science Advances (2024) Vol. 10, Iss. 20
Open Access | Times Cited: 10
Structure-based prediction of T cell receptor recognition of unseen epitopes using TCRen
В. К. Карнаухов, Dmitrii S. Shcherbinin, Anton O. Chugunov, et al.
Nature Computational Science (2024) Vol. 4, Iss. 7, pp. 510-521
Closed Access | Times Cited: 8
Breast cancer dormancy: need for clinically relevant models to address current gaps in knowledge
Grace G. Bushnell, Abhijeet Deshmukh, Petra den Hollander, et al.
npj Breast Cancer (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 46
DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis
Yu Zhao, Bing He, Fan Xu, et al.
Science Advances (2023) Vol. 9, Iss. 32
Open Access | Times Cited: 19
Mechanical forces amplify TCR mechanotransduction in T cell activation and function
Nicholas Jeffreys, Joshua M. Brockman, Yunhao Zhai, et al.
Applied Physics Reviews (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 6
Quantitative approaches for decoding the specificity of the human T cell repertoire
Zahra S. Ghoreyshi, Jason T. George
Frontiers in Immunology (2023) Vol. 14
Open Access | Times Cited: 15
BertTCR: a Bert-based deep learning framework for predicting cancer-related immune status based on T cell receptor repertoire.
Min Zhang, Qi Cheng, Zhenyu Wei, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 5
Open Access | Times Cited: 5
Defining and Studying B Cell Receptor and TCR Interactions
C. Garrett Rappazzo, Monica L. Fernández‐Quintero, Andreas Mayer, et al.
The Journal of Immunology (2023) Vol. 211, Iss. 3, pp. 311-322
Closed Access | Times Cited: 12
A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity
Barbara Bravi, Andrea Di Gioacchino, Jorge Fernández-de-Cossio-Díaz, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 12
Limits on inferring T cell specificity from partial information
James Henderson, Yuta Nagano, Martina Milighetti, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 42
Open Access | Times Cited: 4
Feature selection enhances peptide binding predictions for TCR-specific interactions
Hamid Teimouri, Zahra S. Ghoreyshi, Anatoly B. Kolomeisky, et al.
Frontiers in Immunology (2025) Vol. 15
Open Access
Interpretable Protein-DNA Interactions Captured by Structure-Sequence Optimization
Yafan Zhang, Irene Silvernail, Zhuyang Lin, et al.
(2025)
Open Access
Interpretable Protein-DNA Interactions Captured by Structure-Sequence Optimization
Yafan Zhang, Irene Silvernail, Zhuyang Lin, et al.
(2025)
Open Access
Implications of Tumor–Immune Coevolution on Cancer Evasion and Optimized Immunotherapy
Jason T. George, Herbert Levine
Trends in cancer (2021) Vol. 7, Iss. 4, pp. 373-383
Open Access | Times Cited: 24
Systems immunology of regulatory T cells: can one circuit explain it all?
Shubham Tripathi, John S. Tsang, Kyemyung Park
Trends in Immunology (2023) Vol. 44, Iss. 10, pp. 766-781
Open Access | Times Cited: 10
Interpretable Protein-DNA Interactions Captured by Structure-based Optimization
Yafan Zhang, Irene Silvernail, Zhuyang Lin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Predicting Antigen‐Specificities of Orphan T Cell Receptors from Cancer Patients with TCRpcDist
Marta A. S. Perez, Johanna Chiffelle, Sara Bobisse, et al.
Advanced Science (2024) Vol. 11, Iss. 40
Open Access | Times Cited: 3
A mutagenesis study of autoantigen optimization for potential T1D vaccine design
Yi Song, David R. Bell, Rizwan Ahmed, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 16
Open Access | Times Cited: 8
Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes
Martina Milighetti, John Shawe‐Taylor, Benny Chain
Frontiers in Physiology (2021) Vol. 12
Open Access | Times Cited: 17
Attention-aware contrastive learning for predicting T cell receptor–antigen binding specificity
Yiming Fang, Xuejun Liu, Hui Liu
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Open Access | Times Cited: 11
Computational Methods for Predicting Key Interactions in T Cell–Mediated Adaptive Immunity
Ryan Ehrlich, Eric Glynn, Mona Singh, et al.
Annual Review of Biomedical Data Science (2024) Vol. 7, Iss. 1, pp. 295-316
Closed Access | Times Cited: 2
Integration of Kinetic Data into Affinity-Driven Models for Improved T Cell-Antigen Specificity Prediction
Zahra S. Ghoreyshi, Hamid Teimouri, Anatoly B. Kolomeisky, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
Integration of Kinetic Data into Affinity-Based Models for Improved T Cell Specificity Prediction
Zahra S. Ghoreyshi, Hamid Teimouri, Anatoly B. Kolomeisky, et al.
Biophysical Journal (2024)
Closed Access | Times Cited: 2
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