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:

NCMCMDA: miRNA–disease association prediction through neighborhood constraint matrix completion
Xing Chen, Lian-Gang Sun, Yan Zhao
Briefings in Bioinformatics (2019) Vol. 22, Iss. 1, pp. 485-496
Closed Access | Times Cited: 179

Showing 1-25 of 179 citing articles:

MicroRNAs and complex diseases: from experimental results to computational models
Xing Chen, Di Xie, Qi Zhao, et al.
Briefings in Bioinformatics (2017) Vol. 20, Iss. 2, pp. 515-539
Closed Access | Times Cited: 587
A deep learning method for predicting metabolite–disease associations via graph neural network
Feiyue Sun, Jianqiang Sun, Qi Zhao
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Closed Access | Times Cited: 199
Predicting the potential human lncRNA–miRNA interactions based on graph convolution network with conditional random field
Wenya Wang, Li Zhang, Jianqiang Sun, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 189
Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism
Tianyi Wang, Jianqiang Sun, Qi Zhao
Computers in Biology and Medicine (2022) Vol. 153, pp. 106464-106464
Closed Access | Times Cited: 165
Circular RNAs and complex diseases: from experimental results to computational models
Chun-Chun Wang, Chendi Han, Qi Zhao, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Open Access | Times Cited: 139
Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models
Huang Li, Li Zhang, Xing Chen
Briefings in Bioinformatics (2022) Vol. 23, Iss. 5
Closed Access | Times Cited: 91
Identification of miRNA–disease associations via deep forest ensemble learning based on autoencoder
Wei Liu, Hui Lin, Huang Li, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 88
Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models
Huang Li, Li Zhang, Xing Chen
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 77
Designing antimicrobial peptides using deep learning and molecular dynamic simulations
Qiushi Cao, Cheng Ge, Xuejie Wang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 54
Identification of human microRNA-disease association via low-rank approximation-based link propagation and multiple kernel learning
Yizheng Wang, Xin Zhang, Ying Ju, et al.
Frontiers of Computer Science (2024) Vol. 18, Iss. 2
Closed Access | Times Cited: 19
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: 2
Optical sorting: past, present and future
Meng Yang, Yuzhi Shi, Qinghua Song, et al.
Light Science & Applications (2025) Vol. 14, Iss. 1
Open Access | Times Cited: 2
An Improved Anticancer Drug-Response Prediction Based on an Ensemble Method Integrating Matrix Completion and Ridge Regression
Chuanying Liu, Wei Dong, Ju Xiang, et al.
Molecular Therapy — Nucleic Acids (2020) Vol. 21, pp. 676-686
Open Access | Times Cited: 80
MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph
Yanyi Chu, Xuhong Wang, Qiuying Dai, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 62
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: 60
Predicting miRNA-Disease Associations Based On Multi-View Variational Graph Auto-Encoder With Matrix Factorization
Yulian Ding, Xiujuan Lei, Bo Liao, et al.
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 26, Iss. 1, pp. 446-457
Closed Access | Times Cited: 57
Identification of lncRNA/circRNA-miRNA-mRNA ceRNA Network as Biomarkers for Hepatocellular Carcinoma
Shanshan Chen, Yongchao Zhang, Xiaoyan Ding, et al.
Frontiers in Genetics (2022) Vol. 13
Open Access | Times Cited: 57
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
Predicting potential interactions between lncRNAs and proteins via combined graph auto-encoder methods
Jingxuan Zhao, Jianqiang Sun, Stella C. Shuai, et al.
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 44
NCMD: Node2vec-Based Neural Collaborative Filtering for Predicting MiRNA-Disease Association
Jihwan Ha, Sanghyun Park
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1257-1268
Open Access | Times Cited: 43
Predicting CircRNA-Disease Associations via Feature Convolution Learning With Heterogeneous Graph Attention Network
Peng Li, Yang Cheng, Yi‐Fan Chen, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 6, pp. 3072-3082
Closed Access | Times Cited: 42
Predicting miRNA-Disease Association Based on Neural Inductive Matrix Completion with Graph Autoencoders and Self-Attention Mechanism
Chen Jin, Zhuangwei Shi, Ken Lin, et al.
Biomolecules (2022) Vol. 12, Iss. 1, pp. 64-64
Open Access | Times Cited: 39
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
MPCLCDA: predicting circRNA–disease associations by using automatically selected meta-path and contrastive learning
Wei Liu, Ting Tang, Xu Lu, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 38
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
Page 1 - Next Page

Scroll to top