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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:

scGMAI: a Gaussian mixture model for clustering single-cell RNA-Seq data based on deep autoencoder
Bin Yu, Chen Chen, Ren Qi, et al.
Briefings in Bioinformatics (2020)
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

Application of Deep Learning on Single-Cell RNA Sequencing Data Analysis: A Review
Matthew Brendel, Chang Su, Zilong Bai, et al.
Genomics Proteomics & Bioinformatics (2022) Vol. 20, Iss. 5, pp. 814-835
Open Access | Times Cited: 46
scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder
Xiaoxu Cui, Renkai Wu, Yinghao Liu, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access | Times Cited: 1
Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis
Mario Flores, Zhentao Liu, Tinghe Zhang, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Open Access | Times Cited: 46
scDCCA: deep contrastive clustering for single-cell RNA-seq data based on auto-encoder network
Jing Wang, Junfeng Xia, Haiyun Wang, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 36
Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network
Xiang Feng, Yu-Han Xiu, Haixia Long, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 22
A universal framework for single-cell multi-omics data integration with graph convolutional networks
Hongli Gao, Bin Zhang, Long Liu, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Open Access | Times Cited: 21
Self-supervised deep clustering of single-cell RNA-seq data to hierarchically detect rare cell populations
Tianyuan Lei, Ruoyu Chen, Shaoqiang Zhang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 6
Open Access | Times Cited: 18
Deep learning-based advances and applications for single-cell RNA-sequencing data analysis
Siqi Bao, Ke Li, Congcong Yan, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 30
A parameter-free deep embedded clustering method for single-cell RNA-seq data
Yuansong Zeng, Zhuoyi Wei, Fengqi Zhong, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Open Access | Times Cited: 20
scCAN: single-cell clustering using autoencoder and network fusion
Bang Tran, Duc Tran, Hung Nguyen, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 20
DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering
Qingyun Gao, Qing Ai
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
scDFN: enhancing single-cell RNA-seq clustering with deep fusion networks
Tianxiang Liu, Cangzhi Jia, Yue Bi, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 4
Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis
Zhenhao Zhang, Yuxi Liu, Meichen Xiao, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 4
Learning deep features and topological structure of cells for clustering of scRNA-sequencing data
Haiyue Wang, Xiaoke Ma
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 19
Application of Deep Learning for Single Cell Multi-Omics: A State-of-the-Art Review
Shahid Ahmad Wani, Sumeer Ahmad Khan, S. M. K. Quadri
Archives of Computational Methods in Engineering (2025)
Closed Access
scMUG: deep clustering analysis of single-cell RNA-seq data on multiple gene functional modules
De-Min Liang, Pu-Feng Du
Briefings in Bioinformatics (2025) Vol. 26, Iss. 2
Open Access
scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data
Lin Yuan, Zhijie Xu, Boyuan Meng, et al.
BMC Genomics (2025) Vol. 26, Iss. 1
Open Access
scASGC: An adaptive simplified graph convolution model for clustering single-cell RNA-seq data
Shudong Wang, Y. Zhang, Yulin Zhang, et al.
Computers in Biology and Medicine (2023) Vol. 163, pp. 107152-107152
Closed Access | Times Cited: 9
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder
Dayu Tan, Cheng Yang, Jing Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 3
Learning discriminative and structural samples for rare cell types with deep generative model
Haiyue Wang, Xiaoke Ma
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 14
scGMM-VGAE: a Gaussian mixture model-based variational graph autoencoder algorithm for clustering single-cell RNA-seq data
Eric Lin, Boyuan Liu, Leann Lac, et al.
Machine Learning Science and Technology (2023) Vol. 4, Iss. 3, pp. 035013-035013
Open Access | Times Cited: 8
Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data
Yansen Su, Rongxin Lin, Jing Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 6
Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity
Yuliangzi Sun, Woo Jun Shim, Sophie Shen, et al.
Nucleic Acids Research (2023) Vol. 51, Iss. 11, pp. e62-e62
Open Access | Times Cited: 6
A framework for scRNA-seq data clustering based on multi-view feature integration
Feng Li, Yang Liu, Jin‐Xing Liu, et al.
Biomedical Signal Processing and Control (2023) Vol. 89, pp. 105785-105785
Closed Access | Times Cited: 6
Graph attention autoencoder model with dual decoder for clustering single-cell RNA sequencing data
Shudong Wang, Y. Zhang, Yuanyuan Zhang, et al.
Applied Intelligence (2024) Vol. 54, Iss. 6, pp. 5136-5146
Closed Access | Times Cited: 2
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