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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:

STGNNks: Identifying cell types in spatial transcriptomics data based on graph neural network, denoising auto-encoder, and k-sums clustering
Lihong Peng, Xianzhi He, Xinhuai Peng, et al.
Computers in Biology and Medicine (2023) Vol. 166, pp. 107440-107440
Closed Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Deep learning in spatially resolved transcriptomics: a comprehensive technical view
Roxana Zahedi, Mohammad Reza Eftekhariyan Ghamsari, Ahmadreza Argha, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 15
CellDialog: A Computational Framework for Ligand-Receptor-Mediated Cell-Cell Communication Analysis
Lihong Peng, Wei Xiong, Chendi Han, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 1, pp. 580-591
Closed Access | Times Cited: 24
LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine
Lihong Peng, Liangliang Huang, Qiongli Su, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 24
Identifying potential ligand–receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis
Lihong Peng, Pengfei Gao, Wei Xiong, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108110-108110
Closed Access | Times Cited: 11
Spatial transcriptomics data and analytical methods: An updated perspective
Mohd Danishuddin, Shawez Khan, Jong-Joo Kim
Drug Discovery Today (2024) Vol. 29, Iss. 3, pp. 103889-103889
Closed Access | Times Cited: 8
Drug repositioning based on tripartite cross-network embedding and graph convolutional network
Pan Zeng, Bofei Zhang, Aohang Liu, et al.
Expert Systems with Applications (2024) Vol. 252, pp. 124152-124152
Closed Access | Times Cited: 7
GEnDDn: An lncRNA–Disease Association Identification Framework Based on Dual-Net Neural Architecture and Deep Neural Network
Lihong Peng, Mengnan Ren, Liangliang Huang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 2, pp. 418-438
Closed Access | Times Cited: 7
Finding potential lncRNA–disease associations using a boosting-based ensemble learning model
Liqian Zhou, Xinhuai Peng, Lijun Zeng, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 5
SCPLPA: An miRNA–disease association prediction model based on spatial consistency projection and label propagation algorithm
Min Chen, Yingwei Deng, Zejun Li, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 9
Open Access | Times Cited: 5
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
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
Unveiling patterns in spatial transcriptomics data: a novel approach utilizing graph attention autoencoder and multiscale deep subspace clustering network
Liqian Zhou, Xinhuai Peng, Min Chen, et al.
GigaScience (2025) Vol. 14
Open Access
Graph-based 3D spatial gene neighborhood networks of single cells in gels and tissues
Zhou Fang, Kelsey Krusen, Henry D. Priest, et al.
BME Frontiers (2025) Vol. 6
Open Access
Predicting protein–protein interactions in microbes associated with cardiovascular diseases using deep denoising autoencoders and evolutionary information
Sichang Zhou, Jian Luo, Mei Tang, et al.
Frontiers in Pharmacology (2025) Vol. 16
Open Access
Exploring the Role of T‐Cell Metabolism in Modulating Immunotherapy Efficacy for Non‐Small Cell Lung Cancer Based on Clustering
Hua Guo, Liangyu Zhang, Tang Hu, et al.
Journal of Clinical Laboratory Analysis (2025)
Open Access
scGIR: deciphering cellular heterogeneity via gene ranking in single-cell weighted gene correlation networks
Fei Xu, Huan Hu, Hai Lin, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 3
Microbiota-induced inflammatory responses in bladder tumors promote epithelial-mesenchymal transition and enhanced immune infiltration
Qiang Li, Yichao Sun, Kun Zhai, et al.
Physiological Genomics (2024) Vol. 56, Iss. 8, pp. 544-554
Closed Access | Times Cited: 3
SEnSCA: Identifying possible ligand‐receptor interactions and its application in cell–cell communication inference
Liqian Zhou, Xiwen Wang, Lihong Peng, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 9
Open Access | Times Cited: 2
HHGNN: Hyperbolic Hypergraph Convolutional Neural Network based on variational autoencoder
Zhangyu Mei, Xiao Bi, Yating Wen, et al.
Neurocomputing (2024) Vol. 601, pp. 128225-128225
Closed Access | Times Cited: 2
Deep learning-based multimodal spatial transcriptomics analysis for cancer
Pankaj Rajdeo, Bruce J. Aronow, V. B. Surya Prasath
Advances in cancer research (2024), pp. 1-38
Open Access | Times Cited: 2
DenoiseST: A dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomics
Yaxuan Cui, Ruheng Wang, Xin Zeng, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
MRDPDA: A multi‐Laplacian regularized deepFM model for predicting piRNA‐disease associations
Yajun Liu, Fan Zhang, Yulian Ding, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 17
Open Access | Times Cited: 1
DenoiseST: A dual-channel unsupervised deep learning-based denoising method to identify spatial domains and functionally variable genes in spatial transcriptomics
Yaxuan Cui, Ruheng Wang, Xin Zeng, et al.
Research Square (Research Square) (2024)
Open Access
Supervised Analysis of Alternative Polyadenylation from Single-Cell and Spatial Transcriptomics Data with spvAPA
Qinglong Zhang, Liping Kang, Haoran Yang, et al.
(2024)
Closed Access
SpaGRA: graph augmentation facilitates domain identification for spatially resolved transcriptomics
Xue Sun, Wei Zhang, Wenrui Li, et al.
Journal of genetics and genomics/Journal of Genetics and Genomics (2024)
Closed Access
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