Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

iGRLCDA: identifying circRNA–disease association based on graph representation learning
Han-Yuan Zhang, Lei Wang, Zhu‐Hong You, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

AMDECDA: Attention Mechanism Combined With Data Ensemble Strategy for Predicting CircRNA-Disease Association
Lei Wang, Leon Wong, Zhu‐Hong You, et al.
IEEE Transactions on Big Data (2023) Vol. 10, Iss. 4, pp. 320-329
Closed 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
iCircDA-NEAE: Accelerated attribute network embedding and dynamic convolutional autoencoder for circRNA-disease associations prediction
Lin Yuan, Jiawang Zhao, Zhen Shen, et al.
PLoS Computational Biology (2023) Vol. 19, Iss. 8, pp. e1011344-e1011344
Open Access | Times Cited: 18
RPI-CapsuleGAN: Predicting RNA-protein interactions through an interpretable generative adversarial capsule network
Yifei Wang, Xue Wang, Cheng Chen, et al.
Pattern Recognition (2023) Vol. 141, pp. 109626-109626
Closed Access | Times Cited: 13
DeepCMI: a graph-based model for accurate prediction of circRNA–miRNA interactions with multiple information
Yue-Chao Li, Zhu‐Hong You, Chang-Qing Yu, et al.
Briefings in Functional Genomics (2023) Vol. 23, Iss. 3, pp. 276-285
Closed Access | Times Cited: 13
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
GE-Impute: graph embedding-based imputation for single-cell RNA-seq data
Xiaobin Wu, Yuan Zhou
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 21
Explainable and programmable hypergraph convolutional network for imaging genetics data fusion
Xia-an Bi, Sheng Luo, Siyu Jiang, et al.
Information Fusion (2023) Vol. 100, pp. 101950-101950
Closed Access | Times Cited: 11
A Brief Survey of Deep Learning-based Models for CircRNA-Protein Binding Sites Prediction
Zhen Shen, Lin Yuan, Wenzheng Bao, et al.
Neurocomputing (2025), pp. 129637-129637
Open Access
MVGNCDA: Identifying Potential circRNA-Disease Associations Based on Multi-view Graph Convolutional Networks and Network Embeddings
Guicong Sun, Mengxin Zheng, Yongxian Fan, et al.
Interdisciplinary Sciences Computational Life Sciences (2025)
Closed Access
MethPriorGCN: a deep learning tool for inferring DNA methylation prior knowledge and guiding personalized medicine
Jie Ni, Bin Li, Shumei Miao, et al.
Briefings in Bioinformatics (2025) Vol. 26, Iss. 2
Open Access
Benchmarking of computational methods for predicting circRNA-disease associations
Wei Lan, Yi Dong, Hongyu Zhang, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 17
Predicting circRNA-Disease Associations by Using Multi-Biomolecular Networks Based on Variational Graph Auto-Encoder with Attention Mechanism
Jing Yang, Xiujuan Lei, Yi Pan
Chinese Journal of Electronics (2024) Vol. 33, Iss. 6, pp. 1526-1537
Closed Access | Times Cited: 3
RLFDDA: a meta-path based graph representation learning model for drug–disease association prediction
Meng-Long Zhang, Bo-Wei Zhao, Xiaorui Su, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 15
GSLCDA: An Unsupervised Deep Graph Structure Learning Method for Predicting CircRNA-Disease Association
Lei Wang, Zhengwei Li, Zhu‐Hong You, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 3, pp. 1742-1751
Closed Access | Times Cited: 8
Identify potential circRNA-disease associations through a multi-objective evolutionary algorithm
Yuchen Zhang, Xiujuan Lei, Cai Dai, et al.
Information Sciences (2023) Vol. 647, pp. 119437-119437
Closed Access | Times Cited: 7
Identification of gene biomarkers for brain diseases via multi-network topological semantics extraction and graph convolutional network
Ping Zhang, Weihan Zhang, Weicheng Sun, et al.
BMC Genomics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 2
PMDAGS: Predicting miRNA-Disease Associations With Graph Nonlinear Diffusion Convolution Network and Similarities
Cheng Yan, Guihua Duan
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 3, pp. 394-404
Closed Access | Times Cited: 2
RDGAN: Prediction of circRNA-Disease Associations Via Resistance Distance and Graph Attention Network
Pengli Lu, Yuehao Wang
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 5, pp. 1445-1457
Closed Access | Times Cited: 2
Community Graph Convolution Neural Network for Alzheimer’s Disease Classification and Pathogenetic Factors Identification
Xia-an Bi, Ke Chen, Siyu Jiang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 36, Iss. 2, pp. 1959-1973
Closed Access | Times Cited: 6
HGECDA: A Heterogeneous Graph Embedding Model for CircRNA-Disease Association Prediction
Yao Fu, Runtao Yang, Lina Zhang, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 10, pp. 5177-5186
Closed Access | Times Cited: 4
AMPCDA: Prediction of circRNA–disease associations by utilizing attention mechanisms on metapaths
Pengli Lu, W. Zhang, Jinkai Wu
Computational Biology and Chemistry (2023) Vol. 108, pp. 107989-107989
Closed Access | Times Cited: 4
Exploring potential circRNA biomarkers for cancers based on double-line heterogeneous graph representation learning
Yi Zhang, ZhenMei Wang, Hanyan Wei, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
CircRNA-based therapeutics: Current opinions and clinical potential
Hanyuan Liu, Xuelin Yao, Ying Zhou, et al.
The Innovation Medicine (2024) Vol. 2, Iss. 3, pp. 100081-100081
Closed Access | Times Cited: 1
Association prediction of CircRNAs and diseases using multi-homogeneous graphs and variational graph auto-encoder
Yao Fu, Runtao Yang, Lina Zhang
Computers in Biology and Medicine (2022) Vol. 151, pp. 106289-106289
Closed Access | Times Cited: 7
Page 1 - Next Page

Scroll to top