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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:

MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction
Xing Chen, Jun Yin, Jia Qu, et al.
PLoS Computational Biology (2018) Vol. 14, Iss. 8, pp. e1006418-e1006418
Open Access | Times Cited: 334

Showing 1-25 of 334 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: 581
Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction
Jin Li, Sai Zhang, Tao Liu, et al.
Bioinformatics (2019) Vol. 36, Iss. 8, pp. 2538-2546
Closed Access | Times Cited: 268
Ensemble of decision tree reveals potential miRNA-disease associations
Xing Chen, Chi-Chi Zhu, Jun Yin
PLoS Computational Biology (2019) Vol. 15, Iss. 7, pp. e1007209-e1007209
Open Access | Times Cited: 186
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
Application of Machine Learning in Microbiology
Kaiyang Qu, Fei Guo, Xiangrong Liu, et al.
Frontiers in Microbiology (2019) Vol. 10
Open Access | Times Cited: 169
MicroRNA-small molecule association identification: from experimental results to computational models
Xing Chen, Na‐Na Guan, Yazhou Sun, et al.
Briefings in Bioinformatics (2018)
Closed Access | Times Cited: 162
Identifying Gut Microbiota Associated With Colorectal Cancer Using a Zero-Inflated Lognormal Model
Dongmei Ai, Hongfei Pan, Xiaoxin Li, et al.
Frontiers in Microbiology (2019) Vol. 10
Open Access | Times Cited: 150
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: 136
Multi-view Multichannel Attention Graph Convolutional Network for miRNA–disease association prediction
Xinru Tang, Jiawei Luo, Cong Shen, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 6
Closed Access | Times Cited: 114
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: 89
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: 87
Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion
Huang Li, Li Zhang, Xing Chen
Briefings in Bioinformatics (2022) Vol. 23, Iss. 6
Closed Access | Times Cited: 76
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: 73
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
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: 15
iCircDA-MF: identification of circRNA-disease associations based on matrix factorization
Hang Wei, Bin Liu
Briefings in Bioinformatics (2019) Vol. 21, Iss. 4, pp. 1356-1367
Closed Access | Times Cited: 141
Predicting lncRNA–miRNA interactions based on logistic matrix factorization with neighborhood regularized
Hongsheng Liu, Guofei Ren, Haoyu Chen, et al.
Knowledge-Based Systems (2019) Vol. 191, pp. 105261-105261
Closed Access | Times Cited: 123
MNDR v3.0: mammal ncRNA–disease repository with increased coverage and annotation
Lin Ning, Tianyu Cui, Boyang Zheng, et al.
Nucleic Acids Research (2020) Vol. 49, Iss. D1, pp. D160-D164
Open Access | Times Cited: 118
Computational Methods for Identifying Similar Diseases
Liang Cheng, Hengqiang Zhao, Pingping Wang, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 18, pp. 590-604
Open Access | Times Cited: 113
MLMDA: a machine learning approach to predict and validate MicroRNA–disease associations by integrating of heterogenous information sources
Kai Zheng, Zhu‐Hong You, Lei Wang, et al.
Journal of Translational Medicine (2019) Vol. 17, Iss. 1
Open Access | Times Cited: 112
Convolutional neural network-based annotation of bacterial type IV secretion system effectors with enhanced accuracy and reduced false discovery
Jiajun Hong, Yongchao Luo, Minjie Mou, et al.
Briefings in Bioinformatics (2019) Vol. 21, Iss. 5, pp. 1825-1836
Closed Access | Times Cited: 107
Integrating Bipartite Network Projection and KATZ Measure to Identify Novel CircRNA-Disease Associations
Qi Zhao, Yingjuan Yang, Guofei Ren, et al.
IEEE Transactions on NanoBioscience (2019) Vol. 18, Iss. 4, pp. 578-584
Closed Access | Times Cited: 98
Anticancer Drug Response Prediction in Cell Lines Using Weighted Graph Regularized Matrix Factorization
Na‐Na Guan, Yan Zhao, Chun-Chun Wang, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 17, pp. 164-174
Open Access | Times Cited: 86
Variational graph auto-encoders for miRNA-disease association prediction
Yulian Ding, Li‐Ping Tian, Xiujuan Lei, et al.
Methods (2020) Vol. 192, pp. 25-34
Closed Access | Times Cited: 83
Adaptive multi-view multi-label learning for identifying disease-associated candidate miRNAs
Cheng Liang, Shengpeng Yu, Jiawei Luo
PLoS Computational Biology (2019) Vol. 15, Iss. 4, pp. e1006931-e1006931
Open Access | Times Cited: 79
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