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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:

Transformers in single-cell omics: a review and new perspectives
Artur Szałata, Karin Hrovatin, Sören Becker, et al.
Nature Methods (2024) Vol. 21, Iss. 8, pp. 1430-1443
Closed Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Deep learning-based predictions of gene perturbation effects do not yet outperform simple linear methods
Constantin Ahlmann-Eltze, Wolfgang Huber, Simon Anders
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 9
Simple controls exceed best deep learning algorithms and reveal foundation model effectiveness for predicting genetic perturbations
Daniel R. Wong, Abby S. Hill, Rocco Moccia
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access | Times Cited: 1
Embedding AI in biology

Nature Methods (2024) Vol. 21, Iss. 8, pp. 1365-1366
Open Access | Times Cited: 6
A joint analysis of single cell transcriptomics and proteomics using transformer
Yuanyuan Chen, Xiaodan Fan, Chaowen Shi, et al.
npj Systems Biology and Applications (2025) Vol. 11, Iss. 1
Open Access
CSI-GEP: A GPU-based unsupervised machine learning approach for recovering gene expression programs in atlas-scale single-cell RNA-seq data
Xueying Liu, Richard H. Chapple, D. W. Bennett, et al.
Cell Genomics (2025) Vol. 5, Iss. 1, pp. 100739-100739
Open Access
Machine Learning Methods in Clinical Flow Cytometry
Nicholas C. Spies, Alexandra E. Rangel, Paul English, et al.
Cancers (2025) Vol. 17, Iss. 3, pp. 483-483
Open Access
Small, Open-Source Text-Embedding Models as Substitutes to OpenAI Models for Gene Analysis
Dailin Gan, Jun Li
bioRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Adapting systems biology to address the complexity of human disease in the single-cell era
David S. Fischer, Martin Arreola Villanueva, Peter Winter, et al.
Nature Reviews Genetics (2025)
Closed Access
Transformers and genome language models
Micaela E. Consens, C Dufault, Michael Wainberg, et al.
Nature Machine Intelligence (2025)
Closed Access
A graph neural network that combines scRNA-seq and protein–protein interaction data

Nature Methods (2025)
Closed Access
A review of BioTree construction in the context of information fusion: Priors, methods, applications and trends
Zelin Zang, Yongjie Xu, Chenrui Duan, et al.
Information Fusion (2025), pp. 103108-103108
Closed Access
Transformer-based artificial intelligence on single-cell clinical data for homeostatic mechanism inference and rational biomarker discovery
Veronica Tozzo, Lily Zhang, Rajesh Ranganath, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Cellular mechanical memory: a potential tool for mesenchymal stem cell-based therapy
Sanjay Kumar Kureel, Rosario Maroto, Kristen C. Davis, et al.
Stem Cell Research & Therapy (2025) Vol. 16, Iss. 1
Open Access
Uncovering gene and cellular signatures of immune checkpoint response via machine learning and single-cell RNA-seq
Asaf Pinhasi, Keren Yizhak
npj Precision Oncology (2025) Vol. 9, Iss. 1
Open Access
Mapping Cell Identity from scRNA-seq: a primer on computational methods
Daniele Traversa, Matteo Chiara
Computational and Structural Biotechnology Journal (2025)
Open Access
Comprehensive benchmarking of large language models for RNA secondary structure prediction
Luciano I Zablocki, Leandro A. Bugnon, M. Gérard, et al.
Briefings in Bioinformatics (2025) Vol. 26, Iss. 2
Open Access
New horizons at the interface of artificial intelligence and translational cancer research
Josephine Yates, Eliezer M. Van Allen
Cancer Cell (2025) Vol. 43, Iss. 4, pp. 708-727
Closed Access
Small data methods in omics: the power of one
Kevin G. Johnston, Steven F. Grieco, Qing Nie, et al.
Nature Methods (2024) Vol. 21, Iss. 9, pp. 1597-1602
Closed Access | Times Cited: 2
The development of AI foundation models for single-cell transcriptomics
Haiyang Bian, Yixin Chen, Erpai Luo, et al.
National Science Review (2024) Vol. 11, Iss. 11
Open Access | Times Cited: 2
Multimodal learning of transcriptomes and text enables interactive single-cell RNA-seq data exploration with natural-language chats
Moritz Schaefer, Peter Peneder, Daniel Malzl, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
Considerations for building and using integrated single-cell atlases
Karin Hrovatin, Lisa Sikkema, Vladimir A. Shitov, et al.
Nature Methods (2024)
Closed Access | Times Cited: 2
VICTOR: Validation and Inspection of Cell Type Annotation through Optimal Regression
Chia-Jung Chang, Chih–Yuan Hsu, Qi Liu, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 3270-3280
Open Access
scGAA: a general gated axial-attention model for accurate cell-type annotation of single-cell RNA-seq data
T. Kong, T. Yu, Jiaxin Zhao, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
scPlantFormer: A Lightweight Foundation Model for Plant Single-Cell Omics Analysis
Xiujun Zhang, Jing Xu, Di Chen, et al.
Research Square (Research Square) (2024)
Open Access
A cross-species foundation model for single cells
Korbinian Traeuble, Matthias Heinig
Cell Research (2024)
Open Access
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