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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 embedding and Gaussian mixture variational autoencoder network for end-to-end analysis of single-cell RNA sequencing data
Junlin Xu, Jielin Xu, Yajie Meng, et al.
Cell Reports Methods (2023) Vol. 3, Iss. 1, pp. 100382-100382
Open Access | Times Cited: 69

Showing 26-50 of 69 citing articles:

KRN-DTI: Towards accurate drug-target interaction prediction with Kolmogorov-Arnold and residual networks
Zhen Li, Juyuan Huang, Xinxin Liu, et al.
Methods (2025) Vol. 240, pp. 137-144
Closed Access
Exploring RNA-Seq Data Analysis Through Visualization Techniques and Tools: A Systematic Review of Opportunities and Limitations for Clinical Applications
Farhana Manzoor, Cyruss A. Tsurgeon, Vibhuti Gupta
Bioengineering (2025) Vol. 12, Iss. 1, pp. 56-56
Open Access
Cancer Drug Sensitivity Prediction Based on Deep Transfer Learning
Weilin Meng, Xinyu Xu, Zhichao Xiao, et al.
International Journal of Molecular Sciences (2025) Vol. 26, Iss. 6, pp. 2468-2468
Open Access
An adaptive network construction for single-cell clustering
Tianyu Yang, Yanmei Hu, Yihang Wu, et al.
The Journal of Supercomputing (2025) Vol. 81, Iss. 6
Closed Access
Prediction of small molecule drug-miRNA associations based on GNNs and CNNs
Zheyu Niu, Xin Gao, Zhaozhi Xia, et al.
Frontiers in Genetics (2023) Vol. 14
Open Access | Times Cited: 9
The Power of Two: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis
Mehrshad Sadria, Anita T. Layton
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 8
Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network
Lihong Peng, Liangliang Huang, Geng Tian, et al.
Frontiers in Microbiology (2023) Vol. 14
Open Access | Times Cited: 8
Excavation of gene markers associated with pancreatic ductal adenocarcinoma based on interrelationships of gene expression
Zhao‐Yue Zhang, Zi‐Jie Sun, Dong Gao, et al.
IET Systems Biology (2024)
Open Access | Times Cited: 3
CFCN: An HLA-peptide Prediction Model based on Taylor Extension Theory and Multi-view Learning
Bing Rao, Bing Han, Leyi Wei, et al.
Current Bioinformatics (2024) Vol. 19, Iss. 10, pp. 977-990
Closed Access | Times Cited: 3
Inferring gene regulatory networks by hypergraph variational autoencoder
Guangxin Su, H. Wang, Ying Zhang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
MGDDI: A multi-scale graph neural networks for drug–drug interaction prediction
Guannan Geng, Lizhuang Wang, Yanwei Xu, et al.
Methods (2024) Vol. 228, pp. 22-29
Closed Access | Times Cited: 3
AtML: An Arabidopsis thaliana root cell identity recognition tool for medicinal ingredient accumulation
Shicong Yu, Lijia Liu, Hao Wang, et al.
Methods (2024)
Open Access | Times Cited: 3
Machine learning-based predictive model for abdominal diseases using physical examination datasets
Chen Wei, Yujie Zhang, Weili Wu, et al.
Computers in Biology and Medicine (2024) Vol. 173, pp. 108249-108249
Closed Access | Times Cited: 2
Advancing cancer driver gene detection via Schur complement graph augmentation and independent subspace feature extraction
Xinqian Ma, Zhen Li, Zhenya Du, et al.
Computers in Biology and Medicine (2024) Vol. 174, pp. 108484-108484
Closed Access | Times Cited: 2
Computational approaches for predicting drug-disease associations: a comprehensive review
Zhaoyang Huang, Zhichao Xiao, Chunyan Ao, et al.
Frontiers of Computer Science (2024) Vol. 19, Iss. 5
Closed Access | Times Cited: 2
Analyzing scRNA-seq data by CCP-assisted UMAP and tSNE
Yuta Hozumi, Guo‐Wei Wei
PLoS ONE (2024) Vol. 19, Iss. 12, pp. e0311791-e0311791
Open Access | Times Cited: 2
SAELGMDA: Identifying human microbe–disease associations based on sparse autoencoder and LightGBM
Feixiang Wang, Huandong Yang, Yan Wu, et al.
Frontiers in Microbiology (2023) Vol. 14
Open Access | Times Cited: 6
A new integrated framework for the identification of potential virus–drug associations
Jia Qu, Zihao Song, Xiaolong Cheng, et al.
Frontiers in Microbiology (2023) Vol. 14
Open Access | Times Cited: 6
Integrating single-cell RNA-seq datasets with substantial batch effects
Karin Hrovatin, Amir Ali Moinfar, Luke Zappia, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Single-cell biclustering for cell-specific transcriptomic perturbation detection in AD progression
Yuqiao Gong, Jingsi Xu, Maoying Wu, et al.
Cell Reports Methods (2024) Vol. 4, Iss. 4, pp. 100742-100742
Open Access | Times Cited: 1
scDMAE: A Generative Denoising Model Adopted Mask Strategy for scRNA-Seq Data Recovery
Wei Liu, Youze Pan, Zhijie Teng, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 6, pp. 3772-3780
Closed Access | Times Cited: 1
scDM: A deep generative method for cell surface protein prediction with diffusion model
Hanlei Yu, Yuanjie Zheng, Xinbo Yang
Journal of Molecular Biology (2024) Vol. 436, Iss. 12, pp. 168610-168610
Closed Access | Times Cited: 1
CVGAE: A Self-Supervised Generative Method for Gene Regulatory Network Inference Using Single-Cell RNA Sequencing Data
Wei Liu, Zhijie Teng, Zejun Li, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 4, pp. 990-1004
Closed Access | Times Cited: 1
Prediction of miRNAs and diseases association based on sparse autoencoder and MLP
Si-Lin Sun, Bingwei Zhou, Sheng-Zheng Liu, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 1
ML-NPI: Predicting Interactions between Noncoding RNA and Protein Based on Meta-Learning in a Large-Scale Dynamic Graph
Tao Wang, Wentao Wang, Xin Jiang, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2912-2920
Closed Access | Times Cited: 3

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