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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:

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity
Wen Zhang, Peter G. Hawkins, Jing He, et al.
Science Advances (2021) Vol. 7, Iss. 20
Open Access | Times Cited: 88

Showing 1-25 of 88 citing articles:

Can we predict T cell specificity with digital biology and machine learning?
D. R. Hudson, Ricardo A. Fernandes, Mark Basham, et al.
Nature reviews. Immunology (2023) Vol. 23, Iss. 8, pp. 511-521
Open Access | Times Cited: 118
Benchmarking solutions to the T-cell receptor epitope prediction problem: IMMREP22 workshop report
Pieter Meysman, Justin Barton, Barbara Bravi, et al.
ImmunoInformatics (2023) Vol. 9, pp. 100024-100024
Open Access | Times Cited: 67
Development and use of machine learning algorithms in vaccine target selection
Barbara Bravi
npj Vaccines (2024) Vol. 9, Iss. 1
Open Access | Times Cited: 33
Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells
Giancarlo Croce, Sara Bobisse, Dana Léa Moreno, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 25
A guide to systems-level immunomics
Lorenzo Bonaguro, Jonas Schulte-Schrepping, Thomas Ulas, et al.
Nature Immunology (2022) Vol. 23, Iss. 10, pp. 1412-1423
Open Access | Times Cited: 53
Recent advances in T-cell receptor repertoire analysis: Bridging the gap with multimodal single-cell RNA sequencing
Sebastiaan Valkiers, Nicky de Vrij, Sofie Gielis, et al.
ImmunoInformatics (2022) Vol. 5, pp. 100009-100009
Open Access | Times Cited: 38
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
TEINet: a deep learning framework for prediction of TCR–epitope binding specificity
Yuepeng Jiang, Miaozhe Huo, Shuai Cheng Li
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Open Access | Times Cited: 34
Measures of epitope binding degeneracy from T cell receptor repertoires
Andreas Mayer, Curtis G. Callan
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 4
Open Access | Times Cited: 24
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
TCR-sequencing in cancer and autoimmunity: barcodes and beyond
Kristen E. Pauken, Kaitlyn A. Lagattuta, Benjamin Y. Lu, et al.
Trends in Immunology (2022) Vol. 43, Iss. 3, pp. 180-194
Open Access | Times Cited: 36
NetTCR-2.1: Lessons and guidance on how to develop models for TCR specificity predictions
Alessandro Montemurro, Leon Eyrich Jessen, Morten Nielsen
Frontiers in Immunology (2022) Vol. 13
Open Access | Times Cited: 35
The pitfalls of negative data bias for the T-cell epitope specificity challenge
Ceder Dens, Kris Laukens, Wout Bittremieux, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 10, pp. 1060-1062
Open Access | Times Cited: 19
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: 18
A comparison of clustering models for inference of T cell receptor antigen specificity
D. R. Hudson, Alexander L. R. Lubbock, Mark Basham, et al.
ImmunoInformatics (2024) Vol. 13, pp. 100033-100033
Open Access | Times Cited: 6
Improved T cell receptor antigen pairing through data-driven filtering of sequencing information from single cells
Helle Rus Povlsen, Amalie Kai Bentzen, Mohammad Kadivar, et al.
eLife (2023) Vol. 12
Open Access | Times Cited: 16
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
The pitfalls of negative data bias for the T-cell epitope specificity challenge
Ceder Dens, Kris Laukens, Wout Bittremieux, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 13
BERTrand—peptide:TCR binding prediction using Bidirectional Encoder Representations from Transformers augmented with random TCR pairing
Alexander Myronov, Giovanni Mazzocco, Paulina Król, et al.
Bioinformatics (2023) Vol. 39, Iss. 8
Open Access | Times Cited: 13
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: 5
T-cell receptor binding prediction: A machine learning revolution
Anna Weber, Aurélien Pélissier, María Rodríguez Martínez
ImmunoInformatics (2024) Vol. 15, pp. 100040-100040
Open Access | Times Cited: 5
Using the T Cell Receptor as a Biomarker in Type 1 Diabetes
Maki Nakayama, Aaron W. Michels
Frontiers in Immunology (2021) Vol. 12
Open Access | Times Cited: 31
Clonotype pattern in T-cell lymphomas map the cell of origin to immature lymphoid precursors
Aishwarya Iyer, Dylan Hennessey, Robert Gniadecki
Blood Advances (2022) Vol. 6, Iss. 7, pp. 2334-2345
Open Access | Times Cited: 21
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
EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddings
Dani Korpela, Emmi Jokinen, Alexandru Dumitrescu, et al.
Bioinformatics (2023) Vol. 39, Iss. 12
Open Access | Times Cited: 12
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