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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:

CRPGCN: predicting circRNA-disease associations using graph convolutional network based on heterogeneous network
Zhihao Ma, Zhufang Kuang, Lei Deng
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 20

Showing 20 citing articles:

RNMFLP: Predicting circRNA–disease associations based on robust nonnegative matrix factorization and label propagation
Peng Li, Yang Cheng, Huang Li, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 56
Deep learning models for disease-associated circRNA prediction: a review
Yaojia Chen, Jiacheng Wang, Chuyu Wang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 37
Collaborative deep learning improves disease-related circRNA prediction based on multi-source functional information
Yongtian Wang, Xinmeng Liu, Yewei Shen, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 19
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: 8
MAMLCDA: A Meta-Learning Model for Predicting circRNA-Disease Association Based on MAML Combined With CNN
Yuanyi Tian, Quan Zou, Chunyu Wang, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 7, pp. 4325-4335
Closed Access | Times Cited: 7
Predicting circRNA-drug sensitivity associations by learning multimodal networks using graph auto-encoders and attention mechanism
Bo Yang, Hailin Chen
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 23
GraphCDA: a hybrid graph representation learning framework based on GCN and GAT for predicting disease-associated circRNAs
Qiguo Dai, Ziqiang Liu, Zhaowei Wang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 20
Metapath Aggregated Graph Neural Network and Tripartite Heterogeneous Networks for Microbe-Disease Prediction
Yali Chen, Xiujuan Lei
Frontiers in Microbiology (2022) Vol. 13
Open Access | Times Cited: 17
NGCICM: A Novel Deep Learning-Based Method for Predicting circRNA-MiRNA Interactions
Zhihao Ma, Zhufang Kuang, Lei Deng
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 20, Iss. 5, pp. 3080-3092
Closed Access | Times Cited: 7
SEBGLMA: Semantic Embedded Bipartite Graph Network for Predicting lncRNA-miRNA Associations
Zhengyang Zhao, Jie Lin, Zhen Wang, et al.
International Journal of Intelligent Systems (2023) Vol. 2023, pp. 1-15
Open Access | Times Cited: 6
GCNPCA: miRNA-Disease Associations Prediction Algorithm Based on Graph Convolutional Neural Networks
Jiwen Liu, Zhufang Kuang, Lei Deng
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1041-1052
Closed Access | Times Cited: 9
MNCLCDA: predicting circRNA-drug sensitivity associations by using mixed neighbourhood information and contrastive learning
Guanghui Li, Feifan Zeng, Jiawei Luo, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open 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
CDA-SKAG: Predicting circRNA-disease associations using similarity kernel fusion and an attention-enhancing graph autoencoder
Huiqing Wang, Jiale Han, Haolin Li, et al.
Mathematical Biosciences & Engineering (2023) Vol. 20, Iss. 5, pp. 7957-7980
Open Access | Times Cited: 3
RMDGCN: Prediction of RNA methylation and disease associations based on graph convolutional network with attention mechanism
Lian Liu, Yumeng Zhou, Xiujuan Lei
PLoS Computational Biology (2023) Vol. 19, Iss. 12, pp. e1011677-e1011677
Open Access | Times Cited: 3
DETHACDA: A Dual-View Edge and Topology Hybrid Attention Model for CircRNA-Disease Associations Prediction
Wenjing Yin, Shudong Wang, Sibo Qiao, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 8, pp. 4421-4431
Closed Access | Times Cited: 2
CircRNA-Disease Association Prediction based on Heterogeneous Graph Representation
Xinmeng Liu, Yuhe Zhang, Yewei Shen, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022), pp. 2411-2417
Closed Access | Times Cited: 4
Prediction of circRNA-drug sensitivity using random auto-encoders and multi-layer heterogeneous graph transformers
Yinbo Liu, Xinxin Ren, Jun Li, et al.
Applied Intelligence (2024) Vol. 55, Iss. 4
Closed Access
Tensor product graph diffusion based on nonlinear fusion of multi-source information to predict circRNA-disease associations
Hao Liu, Chen Chen, Ying Su, et al.
Applied Soft Computing (2023) Vol. 152, pp. 111215-111215
Closed Access
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