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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:

Graph attention network for link prediction of gene regulations from single-cell RNA-sequencing data
Guangyi Chen, Zhi‐Ping Liu
Bioinformatics (2022) Vol. 38, Iss. 19, pp. 4522-4529
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

STGRNS: an interpretable transformer-based method for inferring gene regulatory networks from single-cell transcriptomic data
Jing Xu, Aidi Zhang, Fang Liu, et al.
Bioinformatics (2023) Vol. 39, Iss. 4
Open Access | Times Cited: 29
GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference
Shuo Li, Yan Liu, Long-Chen Shen, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 11
scMGATGRN: a multiview graph attention network–based method for inferring gene regulatory networks from single-cell transcriptomic data
Lin Yuan, Ling Zhao, Yufeng Jiang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 8
Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data
Marco Stock, Corinna Losert, M Zambon, et al.
Molecular Systems Biology (2025)
Closed Access | Times Cited: 1
Predicting gene regulatory links from single-cell RNA-seq data using graph neural networks
Guo Mao, Zhengbin Pang, Ke Zuo, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Open Access | Times Cited: 20
Graph neural network approaches for single-cell data: a recent overview
Konstantinos Lazaros, Dimitrios E. Koumadorakis, Panagiotis Vlamos, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 17, pp. 9963-9987
Closed Access | Times Cited: 7
GCNGAT: Drug–disease association prediction based on graph convolution neural network and graph attention network
Runtao Yang, Yao Fu, Qian Zhang, et al.
Artificial Intelligence in Medicine (2024) Vol. 150, pp. 102805-102805
Closed Access | Times Cited: 5
scGREAT: Transformer-based deep-language model for gene regulatory network inference from single-cell transcriptomics
Yuchen Wang, Xingjian Chen, Zetian Zheng, et al.
iScience (2024) Vol. 27, Iss. 4, pp. 109352-109352
Open Access | Times Cited: 5
LogBTF: gene regulatory network inference using Boolean threshold network model from single-cell gene expression data
Lingyu Li, Liangjie Sun, Guangyi Chen, et al.
Bioinformatics (2023) Vol. 39, Iss. 5
Open Access | Times Cited: 12
Analysis of gene regulatory networks from gene expression using graph neural networks
Hakan T. Otal, Abdülhamit Subaşı, Furkan Kurt, et al.
Elsevier eBooks (2025), pp. 249-270
Closed Access
HGATLink: single-cell gene regulatory network inference via the fusion of heterogeneous graph attention networks and transformer
Yao Sun, Jing Gao
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
GCLink: a graph contrastive link prediction framework for gene regulatory network inference
Weiming Yu, Zerun Lin, Michael S. Lan, et al.
Bioinformatics (2025) Vol. 41, Iss. 3
Open Access
ChromoGAT: Precision chromosome segmentation through U-Net and GAT integration
A. G. Dinu, V. G. Biju, B. R. Vinod, et al.
International Journal of Information Technology (2025)
Closed Access
Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data
Junlin Xu, Changcheng Lu, Shuting Jin, et al.
Nucleic Acids Research (2025) Vol. 53, Iss. 5
Open Access
Inferring gene regulatory networks from time-series scRNA-seq data via GRANGER causal recurrent autoencoders
Liang Chen, Madison Dautle, Shuang Gao, et al.
Briefings in Bioinformatics (2025) Vol. 26, Iss. 2
Open Access
AnomalGRN: deciphering single-cell gene regulation network with graph anomaly detection
Zhecheng Zhou, Jinhang Wei, Mingzhe Liu, et al.
BMC Biology (2025) Vol. 23, Iss. 1
Open Access
Strategies to include prior knowledge in omics analysis with deep neural networks
Kisan Thapa, Meric Kinali, Shichao Pei, et al.
Patterns (2025) Vol. 6, Iss. 3, pp. 101203-101203
Open Access
Graph neural networks for single-cell omics data: a review of approaches and applications
Shiming Li, Heyang Hua, Shengquan Chen
Briefings in Bioinformatics (2025) Vol. 26, Iss. 2
Open Access
Inferring gene regulatory networks via directed graph contrastive representation learning
Kaifu Long, Luxuan Qu, Weiyiqi Wang, et al.
Knowledge-Based Systems (2025), pp. 113324-113324
Closed Access
Integrative network analysis reveals novel moderators of Aβ-Tau interaction in Alzheimer's disease
Akihiro Kitani, Yusuke Matsui
Alzheimer s Research & Therapy (2025) Vol. 17, Iss. 1
Open Access
scPRINT: pre-training on 50 million cells allows robust gene network predictions
Jérémie Kalfon, Jules Samaran, Gabriel Peyré, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data
Kai Wang, Yulong Li, Fei Liu, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
Link prediction by adversarial Nonnegative Matrix Factorization
Reza Mahmoodi, Seyed Amjad Seyedi, Fardin Akhlaghian Tab, et al.
Knowledge-Based Systems (2023) Vol. 280, pp. 110998-110998
Closed Access | Times Cited: 10
Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON
Peizhuo Wang, Wen Xiao, Han Li, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 10
Inference of Gene Regulatory Networks Based on Multi-view Hierarchical Hypergraphs
Songyang Wu, Kui Jin, Mingjing Tang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 2, pp. 318-332
Closed Access | Times Cited: 2
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