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:

Predicting miRNA–disease associations via learning multimodal networks and fusing mixed neighborhood information
Zhengzheng Lou, Zhaoxu Cheng, Hui Li, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

AMHMDA: attention aware multi-view similarity networks and hypergraph learning for miRNA–disease associations identification
Ning Qiao, Yaomiao Zhao, Jun Gao, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 47
Motif-Aware miRNA-Disease Association Prediction via Hierarchical Attention Network
Bo-Wei Zhao, Yi-Zhou He, Xiaorui Su, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 7, pp. 4281-4294
Closed Access | Times Cited: 17
A Survey of Deep Learning for Detecting miRNA- Disease Associations: Databases, Computational Methods, Challenges, and Future Directions
Nan Sheng, Xuping Xie, Yan Wang, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 3, pp. 328-347
Closed Access | Times Cited: 9
Supervised contrastive knowledge graph learning for ncRNA–disease association prediction
Yan Wang, Xuping Xie, Ye Wang, et al.
Expert Systems with Applications (2025) Vol. 269, pp. 126257-126257
Closed Access | Times Cited: 1
Predicting miRNA-disease associations based on graph attention network with multi-source information
Guanghui Li, Tao Fang, Yuejin Zhang, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 29
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy
Zhen Tian, Yue Yu, Haichuan Fang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 21
AMDGT: Attention aware multi-modal fusion using a dual graph transformer for drug–disease associations prediction
Junkai Liu, Shixuan Guan, Quan Zou, et al.
Knowledge-Based Systems (2023) Vol. 284, pp. 111329-111329
Open Access | Times Cited: 18
Improving the identification of miRNA–disease associations with multi-task learning on gene–disease networks
Qiang He, Wei Qiao, Hui Fang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 16
Multi-view graph neural network with cascaded attention for lncRNA-miRNA interaction prediction
Hui Li, Bin Wu, Miaomiao Sun, et al.
Knowledge-Based Systems (2023) Vol. 268, pp. 110492-110492
Closed Access | Times Cited: 15
Predicting miRNA-disease association via graph attention learning and multiplex adaptive modality fusion
Z M Jin, Minhui Wang, Chang Tang, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107904-107904
Closed Access | Times Cited: 13
MGCNSS: miRNA–disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy
Zhen Tian, Chenguang Han, Lewen Xu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 5
Cross-domain contrastive graph neural network for lncRNA–protein interaction prediction
Hui Li, Bin Wu, Miaomiao Sun, et al.
Knowledge-Based Systems (2024) Vol. 296, pp. 111901-111901
Closed Access | Times Cited: 5
CLMT: graph contrastive learning model for microbe-drug associations prediction with transformer
Xiaolu Li, Junlong Wu, Fan Liu, et al.
Frontiers in Genetics (2025) Vol. 16
Open Access
MFF-nDA: A Computational Model for ncRNA–Disease Association Prediction Based on Multimodule Fusion
Zhihao Guan, Xiu Jin, Xiaodan Zhang
Journal of Chemical Information and Modeling (2025)
Closed Access
GONNMDA: A Ordered Message Passing GNN Approach for miRNA–Disease Association Prediction
Sihao Zeng, Shanwen Zhang, Zhen Wang, et al.
Genes (2025) Vol. 16, Iss. 4, pp. 425-425
Open Access
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: 22
HGSMDA: miRNA–Disease Association Prediction Based on HyperGCN and Sørensen-Dice Loss
Zhenghua Chang, Rong Zhu, Jin‐Xing Liu, et al.
Non-Coding RNA (2024) Vol. 10, Iss. 1, pp. 9-9
Open Access | Times Cited: 4
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction
Boya Ji, Haitao Zou, Li‐Wen Xu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 4
DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks
Guang Yang, Yinbo Liu, SiJian Wen, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
Predicting miRNA-disease associations based on PPMI and attention network
Xuping Xie, Yan Wang, Kai He, et al.
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 10
ReHoGCNES-MDA: prediction of miRNA-disease associations using homogenous graph convolutional networks based on regular graph with random edge sampler
Yufang Zhang, Yanyi Chu, Shenggeng Lin, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 3
PGCNMDA: Learning node representations along paths with graph convolutional network for predicting miRNA-disease associations
S. Chu, Guihua Duan, Cheng Yan
Methods (2024) Vol. 229, pp. 71-81
Closed Access | Times Cited: 3
HGTMDA: A Hypergraph Learning Approach with Improved GCN-Transformer for miRNA–Disease Association Prediction
Daying Lu, Jian Li, Chun-Hou Zheng, et al.
Bioengineering (2024) Vol. 11, Iss. 7, pp. 680-680
Open Access | Times Cited: 3
DAmiRLocGNet: miRNA subcellular localization prediction by combining miRNA–disease associations and graph convolutional networks
Tao Bai, Ke Yan, Bin Liu
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 8
MVNMDA: A Multi-View Network Combing Semantic and Global Features for Predicting miRNA–Disease Association
Chen Yang, Zhen Wang, Shanwen Zhang, et al.
Molecules (2023) Vol. 29, Iss. 1, pp. 230-230
Open Access | Times Cited: 8
Page 1 - Next Page

Scroll to top