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:

MHDMF: Prediction of miRNA–disease associations based on Deep Matrix Factorization with Multi-source Graph Convolutional Network
Ning Ai, Yong Liang, Hao-Laing Yuan, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 106069-106069
Closed Access | Times Cited: 17

Showing 17 citing articles:

Graph Convolutional Network with Neural Collaborative Filtering for Predicting miRNA-Disease Association
Jihwan Ha
Biomedicines (2025) Vol. 13, Iss. 1, pp. 136-136
Open Access | Times Cited: 1
Predicting miRNA–Disease Associations by Combining Graph and Hypergraph Convolutional Network
Xujun Liang, Ming Guo, Longying Jiang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 2, pp. 289-303
Closed Access | Times Cited: 8
A novel interactive deep cascade spectral graph convolutional network with multi-relational graphs for disease prediction
Sihui Li, Rui Zhang
Neural Networks (2024) Vol. 175, pp. 106285-106285
Closed Access | Times Cited: 5
Gene-related multi-network collaborative deep feature learning for predicting miRNA-disease associations
Pengli Lu, Xu Cao
Computers & Electrical Engineering (2025) Vol. 123, pp. 110242-110242
Closed Access
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
SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning
Yanhao Fan, Che Zhang, Xiaowen Hu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 3
Open Access | Times Cited: 4
MGHSTCKW: Predicting miRNA-drug sensitivity association using hypergraph sparse transformer and hypergraph-induced contrastive learning based on meta-path
Dong Ouyang, Bo Jin, Jing Tian, et al.
Expert Systems with Applications (2025), pp. 126879-126879
Closed Access
Adaptive deep propagation graph neural network for predicting miRNA–disease associations
Hua Hu, Huan Zhao, Tangbo Zhong, et al.
Briefings in Functional Genomics (2023) Vol. 22, Iss. 5, pp. 453-462
Closed Access | Times Cited: 9
Prediction of miRNA–Disease Associations by Cascade Forest Model Based on Stacked Autoencoder
Xiang Hu, Zhixiang Yin, Zhiliang Zeng, et al.
Molecules (2023) Vol. 28, Iss. 13, pp. 5013-5013
Open Access | Times Cited: 9
GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization
Ning Ai, Yong Liang, Haoliang Yuan, et al.
BMC Genomics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 6
Identification of disease related biomarkers in time varying ‘Omic data: A non-negative matrix factorization aided multi level self organizing map based approach
Anirban Dey, Kaushik Das Sharma, Pritha Bhattacharjee, et al.
Biomedical Signal Processing and Control (2023) Vol. 90, pp. 105860-105860
Closed Access | Times Cited: 4
DGAMDA: Predicting miRNA‐disease association based on dynamic graph attention network
Changxin Jia, Fuyu Wang, Baoxiang Xing, et al.
International Journal for Numerical Methods in Biomedical Engineering (2024) Vol. 40, Iss. 5
Closed Access | Times Cited: 1
HGCN_MDA: Hierarchical Heterogeneous GraphConvolutional Neural Network for PredictingmiRNA-Disease Associations
Ying Wai Li, Xiao Yang, Ruihan Sun, et al.
Research Square (Research Square) (2024)
Open Access
Multi-View Multiattention Graph Learning With Stack Deep Matrix Factorization for circRNA-Drug Sensitivity Association Identification
Ning Ai, Haoliang Yuan, Yong Liang, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 12, pp. 7670-7682
Closed Access
Advanced Graph Convolutional Networks for Semantic Relationship Mining in Large-Scale Ontologies
R. Anuradha, B Swathi, Rakesh Kumar, et al.
(2024) Vol. 2189, pp. 1-6
Closed Access
Prediction of miRNA-disease association based on heterogeneous hypergraph convolution and heterogeneous graph multi-scale convolution
Wei Dai, S.K. Pang, Zhichen He, et al.
Health Information Science and Systems (2024) Vol. 13, Iss. 1
Closed Access
MDformer: A transformer-based method for predicting miRNA-Disease associations using multi-source feature fusion and maximal meta-path instances encoding
Benzhi Dong, Weidong Sun, Dali Xu, et al.
Computers in Biology and Medicine (2023) Vol. 167, pp. 107585-107585
Closed Access | Times Cited: 1
Page 1

Scroll to top