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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:

SMAP: Similarity-based matrix factorization framework for inferring miRNA-disease association
Jihwan Ha
Knowledge-Based Systems (2023) Vol. 263, pp. 110295-110295
Closed Access | Times Cited: 38

Showing 1-25 of 38 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: 3
Hybrid Techniques for the Diagnosis of Acute Lymphoblastic Leukemia Based on Fusion of CNN Features
Ibrahim Abdulrab Ahmed, Ebrahim Mohammed Senan, Hamzeh Salameh Ahmad Shatnawi, et al.
Diagnostics (2023) Vol. 13, Iss. 6, pp. 1026-1026
Open Access | Times Cited: 26
Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases
Nan Sheng, Yan Wang, Lan Huang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 5
Closed Access | Times Cited: 25
lncRNA-disease association prediction based on optimizing measures of multi-graph regularized matrix factorization
Bin Yao, Yunzhong Song
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-16
Closed Access | Times Cited: 1
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: 5
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
Establishing a GRU-GCN coordination-based prediction model for miRNA-disease associations
Kai-Cheng Chuang, Ping-Sung Cheng, Yu-Hung Tsai, et al.
BMC Genomic Data (2025) Vol. 26, Iss. 1
Open Access
MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction
Dhekra Saeed, Huanlai Xing, Barakat AlBadani, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
DeepWalk-Based Graph Embeddings for miRNA–Disease Association Prediction Using Deep Neural Network
Jihwan Ha
Biomedicines (2025) Vol. 13, Iss. 3, pp. 536-536
Open Access
Identification of UBE2N as a biomarker of Alzheimer’s disease by combining WGCNA with machine learning algorithms
Gangyi Feng, Manli Zhong, Hudie Huang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
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
DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations
Yuyao Yan, Xinyi Chai, Jiajun Liu, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
Association prediction of lncRNAs and diseases using multiview graph convolution neural network
Wei Zhang, Yifu Zeng, Xiaowen Xiang, et al.
Frontiers in Genetics (2025) Vol. 16
Open Access
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
Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis
Saleem Ahmad, Imran Zafar, Shaista Shafiq, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Lysosome-related biomarkers in preeclampsia and cancers: Machine learning and bioinformatics analysis
Hai Tang, Xin Luo, Xiuyin Shen, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108201-108201
Closed Access | Times Cited: 3
Classification of Alzheimer's disease using robust TabNet neural networks on genetic data
Yu Jin, Zhe Ren, Wenjie Wang, et al.
Mathematical Biosciences & Engineering (2023) Vol. 20, Iss. 5, pp. 8358-8374
Open Access | Times Cited: 8
SLGCN: Structure-enhanced line graph convolutional network for predicting drug–disease associations
Bao-Min Liu, Ying-Lian Gao, Feng Li, et al.
Knowledge-Based Systems (2023) Vol. 283, pp. 111187-111187
Closed Access | Times Cited: 8
Identifying Hub Genes for Glaucoma Based on Bulk RNA Sequencing Data and Multi-machine Learning Models
Yangyang Xie, Kai Yu
Current Medicinal Chemistry (2024) Vol. 31, Iss. 42, pp. 7059-7071
Closed Access | Times Cited: 2
Similarity-guided Graph Contrastive Learning for LncRNA-disease Association Prediction
Qingfeng Chen, Junlai Qiu, Wei Lan, et al.
Journal of Molecular Biology (2024), pp. 168609-168609
Closed Access | Times Cited: 2
Multi-Kernel Graph Attention Deep Autoencoder for MiRNA-Disease Association Prediction
Cui-Na Jiao, Feng Zhou, Bao-Min Liu, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 2, pp. 1110-1121
Closed Access | Times Cited: 4
Investigation of the Potential Mechanism of Compound Dragon's Blood Capsule against Myocardial Ischemia Based on Network Pharmacology
Xin Su, Hong‐Wei Xue, Yang Lou, et al.
Combinatorial Chemistry & High Throughput Screening (2024) Vol. 27, Iss. 19, pp. 2940-2950
Closed Access | Times Cited: 1
A Five-gene Signature based on MicroRNA for Predicting Prognosis and Immunotherapy in Stomach Adenocarcinoma
Tianwei Wang, Piji Chen, Tingting Li, et al.
Current Medicinal Chemistry (2024) Vol. 31, Iss. 17, pp. 2378-2399
Closed Access | Times Cited: 1
DAE-CFR: detecting microRNA-disease associations using deep autoencoder and combined feature representation
Yanling Liu, Ruiyan Zhang, Xiaojing Dong, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1
MNESEDA: A prior-guided subgraph representation learning framework for predicting disease-related enhancers
Jinsheng Xu, Weicheng Sun, Kai Li, et al.
Knowledge-Based Systems (2024) Vol. 294, pp. 111734-111734
Closed Access | Times Cited: 1
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