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 association based on inductive matrix completion
Xing Chen, Lei Wang, Jia Qu, et al.
Bioinformatics (2018) Vol. 34, Iss. 24, pp. 4256-4265
Open Access | Times Cited: 451

Showing 1-25 of 451 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
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
Deep-belief network for predicting potential miRNA-disease associations
Xing Chen, Tianhao Li, Yan Zhao, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 137
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
Predicting human microbe–drug associations via graph convolutional network with conditional random field
Yahui Long, Min Wu, Chee Keong Kwoh, et al.
Bioinformatics (2020) Vol. 36, Iss. 19, pp. 4918-4927
Open Access | Times Cited: 119
Novel Human miRNA-Disease Association Inference Based on Random Forest
Xing Chen, Chun-Chun Wang, Jun Yin, et al.
Molecular Therapy — Nucleic Acids (2018) Vol. 13, pp. 568-579
Open Access | Times Cited: 118
Identifying a miRNA signature for predicting the stage of breast cancer
Srinivasulu Yerukala Sathipati, Shinn‐Ying Ho
Scientific Reports (2018) Vol. 8, Iss. 1
Open Access | Times Cited: 114
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
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
Progresses and challenges in link prediction
Tao Zhou
iScience (2021) Vol. 24, Iss. 11, pp. 103217-103217
Open Access | Times Cited: 90
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
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
Page 1 - Next Page

Scroll to top