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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:

SGCNCMI: A New Model Combining Multi-Modal Information to Predict circRNA-Related miRNAs, Diseases and Genes
Chang-Qing Yu, Xinfei Wang, Liping Li, et al.
Biology (2022) Vol. 11, Iss. 9, pp. 1350-1350
Open Access | Times Cited: 23

Showing 23 citing articles:

Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA–miRNA associations
Lu-Xiang Guo, Lei Wang, Zhu‐Hong You, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 17
Biolinguistic graph fusion model for circRNA–miRNA association prediction
Lu-Xiang Guo, Lei Wang, Zhu‐Hong You, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 10
A feature extraction method based on noise reduction for circRNA-miRNA interaction prediction combining multi-structure features in the association networks
Xinfei Wang, Chang-Qing Yu, Zhu‐Hong You, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 3
Closed Access | Times Cited: 22
KS-CMI: A circRNA-miRNA interaction prediction method based on the signed graph neural network and denoising autoencoder
Xinfei Wang, Chang-Qing Yu, Zhu‐Hong You, et al.
iScience (2023) Vol. 26, Iss. 8, pp. 107478-107478
Open Access | Times Cited: 20
BCMCMI: A Fusion Model for Predicting circRNA-miRNA Interactions Combining Semantic and Meta-path
Meng-Meng Wei, Chang-Qing Yu, Liping Li, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 16, pp. 5384-5394
Closed Access | Times Cited: 18
BEROLECMI: a novel prediction method to infer circRNA-miRNA interaction from the role definition of molecular attributes and biological networks
Xinfei Wang, Chang-Qing Yu, Zhu‐Hong You, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 5
An efficient circRNA-miRNA interaction prediction model by combining biological text mining and wavelet diffusion-based sparse network structure embedding
Xinfei Wang, Chang-Qing Yu, Zhu‐Hong You, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107421-107421
Closed Access | Times Cited: 12
DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions
Chao Cao, Mengli Li, Chunyu Wang, et al.
BMC Biology (2025) Vol. 23, Iss. 1
Open Access
Leveraging explainable multi-scale features for fine-grained circRNA-miRNA interaction prediction
Li Peng, Wang Wang, Zhiyuan Yang, et al.
BMC Biology (2025) Vol. 23, Iss. 1
Open Access
Identifying circRNA-miRNA interaction based on multi-biological interaction fusion
Dunwei Yao, Lidan Nong, Minzhen Qin, et al.
Frontiers in Microbiology (2022) Vol. 13
Open Access | Times Cited: 16
Predicting circRNA-miRNA interactions utilizing transformer-based RNA sequential learning and high-order proximity preserved embedding
Ji-Ren Zhou, Xinfei Wang, Rui Niu, et al.
iScience (2023) Vol. 27, Iss. 1, pp. 108592-108592
Open Access | Times Cited: 9
RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous Network Embedding
Chang-Qing Yu, Xinfei Wang, Liping Li, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 18, pp. 7163-7172
Closed Access | Times Cited: 3
Prediction of circRNA–miRNA Interaction Using Graph Attention Network Based on Molecular Attributes and Biological Networks
Abdullah Almotilag, Murtada K. Elbashir, Mahmood A. Mahmood, et al.
Processes (2025) Vol. 13, Iss. 5, pp. 1318-1318
Open Access
LMGATCDA: Graph Neural Network With Labeling Trick for Predicting circRNA-Disease Associations
Wenjing Wang, Pengyong Han, Zhengwei Li, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 2, pp. 289-300
Closed Access | Times Cited: 2
BJLD-CMI: a predictive circRNA-miRNA interactions model combining multi-angle feature information
Yixin Zhao, Chang-Qing Yu, Liping Li, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 2
Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome
Sonet Daniel Thomas, Krithika Vijayakumar, Levin John, et al.
OMICS A Journal of Integrative Biology (2024) Vol. 28, Iss. 5, pp. 213-233
Closed Access | Times Cited: 2
LPIH2V: LncRNA-protein interactions prediction using HIN2Vec based on heterogeneous networks model
Meng-Meng Wei, Chang-Qing Yu, Liping Li, et al.
Frontiers in Genetics (2023) Vol. 14
Open Access | Times Cited: 5
A Hierarchical GNN Across Semantic and Topological Domains for Predicting circRNA-microRNA Interactions
Ji-Ren Zhou, Boya Ji, Rui Niu, et al.
Knowledge-Based Systems (2024), pp. 112549-112549
Closed Access | Times Cited: 1
GSASVM-RBPs: Predicting miRNA-binding protein sites with aggregated multigraph neural networks and an SVM
T. J. Zhang, Zihao Qi, Shikai Qiao, et al.
Network Modeling Analysis in Health Informatics and Bioinformatics (2024) Vol. 13, Iss. 1
Closed Access | Times Cited: 1
Hither-CMI: Prediction of circRNA-miRNA Interactions Based on a Hybrid Multimodal Network and Higher-Order Neighborhood Information via a Graph Convolutional Network
Jiang Chen, Lei Wang, Chang-Qing Yu, et al.
Journal of Chemical Information and Modeling (2024) Vol. 65, Iss. 1, pp. 446-459
Closed Access | Times Cited: 1
Multirelational Hypergraph Representation Learning for Predicting circRNA-miRNA Associations
Wenjing Yin, Shudong Wang, Yuanyuan Zhang, et al.
Journal of Chemical Information and Modeling (2024)
Closed Access
CMAGN: circRNA–miRNA association prediction based on graph attention auto-encoder and network consistency projection
Alexandre Yin, Lei Chen, Bo Zhou, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access
Multi-view learning framework for predicting unknown types of cancer markers via directed graph neural networks fitting regulatory networks
Xinfei Wang, Lan Huang, Yan Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access
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