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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:

Identifying spatial domain by adapting transcriptomics with histology through contrastive learning
Yuansong Zeng, Rui Yin, Mai Luo, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

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: 22
Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism
Bo Wang, Jiawei Luo, Ying Liu, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 5
Closed Access | Times Cited: 21
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: 7
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
MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning
Yu Wang, Zaiyi Liu, Xiaoke Ma
Genome Medicine (2025) Vol. 17, Iss. 1
Open Access
xSiGra: explainable model for single-cell spatial data elucidation
Aishwarya Budhkar, Ziyang Tang, Xiang Liu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 5
Open Access | Times Cited: 3
MVST: Identifying spatial domains of spatial transcriptomes from multiple views using multi-view graph convolutional networks
Hao Duan, Qingchen Zhang, Feifei Cui, et al.
PLoS Computational Biology (2024) Vol. 20, Iss. 9, pp. e1012409-e1012409
Open Access | Times Cited: 3
Complete spatially resolved gene expression is not necessary for identifying spatial domains
Senlin Lin, Yan Cui, Fangyuan Zhao, et al.
Cell Genomics (2024) Vol. 4, Iss. 6, pp. 100565-100565
Open Access | Times Cited: 2
Multi-view Adaptive Fusion Network for Spatially Resolved Transcriptomics Data Clustering
Yanran Zhu, Xiao He, Chang Tang, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 12, pp. 8889-8900
Closed Access | Times Cited: 2
Spatial domain detection using contrastive self-supervised learning for spatial multi-omics technologies
Jianing Yao, Jinglun Yu, Brian Caffo, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Uncover Spatially Informed Variations for Single-Cell Spatial Transcriptomics with STew
N. Guo, Juan F. Vargas, Samantha Reynoso, et al.
Bioinformatics Advances (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 1
STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics.
Jiawen Chen, Muqing Zhou, Wenrong Wu, et al.
arXiv (Cornell University) (2024)
Open Access | Times Cited: 1
A review of recent advances in spatially resolved transcriptomics data analysis
Yue Gao, Ying-Lian Gao, Jing Jing, et al.
Neurocomputing (2024) Vol. 603, pp. 128283-128283
Closed Access | Times Cited: 1
A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis
Nan Chen, Xiao Yu, Weimin Li, et al.
Bioinformatics (2024) Vol. 40, Iss. 11
Open Access | Times Cited: 1
Spatial Omics Driven Crossmodal Pretraining Applied to Graph-based Deep Learning for Cancer Pathology Analysis
Zarif L. Azher, Michael Fatemi, Yunrui Lu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 3
Path-MGCN: a pathway activity based multi-view graph convolutional network for determining spatial domains with attention mechanism
Qirui Zhou, Chaowen Li, Chao Chen, et al.
Research Square (Research Square) (2024)
Open Access
MuCST: restoring and integrating heterogeneous morphology images and spatial transcriptomics data with contrastive learning
Yu Wang, Xiaoke Ma
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access
Accurately Deciphering Novel Cell Type in Spatially Resolved Single-Cell Data Through Optimal Transport
Mai Luo, Yuansong Zeng, Jianing Chen, et al.
Lecture notes in computer science (2024), pp. 107-118
Closed Access
AFSC: A Self-supervised Augmentation-Free Spatial Clustering Method Based on Contrastive Learning for Identifying Spatial Domains
Rui Han, Xu Wang, Xuan Wang, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 3358-3367
Open 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
Vispro improves imaging analysis for Visium spatial transcriptomics
Huifang Ma, Yilong Qu, Anru R. Zhang, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
A multi-modality and multi-granularity collaborative learning framework for identifying spatial domains and spatially variable genes
Xiao Liang, Pei Liu, Xueyan Li, et al.
Bioinformatics (2024) Vol. 40, Iss. 10
Open Access
A comprehensive review of approaches for spatial domain recognition of spatial transcriptomes
Ziyi Wang, Aoyun Geng, Hao Duan, et al.
Briefings in Functional Genomics (2024) Vol. 23, Iss. 6, pp. 702-712
Closed Access
Accurate Spatial Heterogeneity Dissection and Gene Regulation Interpretation for Spatial Transcriptomics using Dual Graph Contrastive Learning
Zhuohan Yu, Yuning Yang, Xingjian Chen, et al.
Advanced Science (2024)
Closed Access
Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle
Zhida Zhao, Qunhao Niu, Jiayuan Wu, et al.
Biology Direct (2024) Vol. 19, Iss. 1
Open Access
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