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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:

Tensor decomposition with relational constraints for predicting multiple types of microRNA-disease associations
Feng Huang, Xiang Yue, Zhankun Xiong, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Open Access | Times Cited: 67

Showing 1-25 of 67 citing articles:

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: 90
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: 77
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: 75
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: 18
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
ACP-DA: Improving the Prediction of Anticancer Peptides Using Data Augmentation
Chen Xiangan, Wen Zhang, Xiaofei Yang, et al.
Frontiers in Genetics (2021) Vol. 12
Open Access | Times Cited: 50
Predicting miRNA-Disease Associations via Node-Level Attention Graph Auto-Encoder
Huizhe Zhang, Juntao Fang, Yuping Sun, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2022) Vol. 20, Iss. 2, pp. 1308-1318
Closed Access | Times Cited: 31
PrMFTP: Multi-functional therapeutic peptides prediction based on multi-head self-attention mechanism and class weight optimization
Wenhui Yan, Wending Tang, Lihua Wang, et al.
PLoS Computational Biology (2022) Vol. 18, Iss. 9, pp. e1010511-e1010511
Open Access | Times Cited: 30
Predicting miRNA-disease associations based on graph attention network with multi-source information
Guanghui Li, Tao Fang, Yuejin Zhang, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 29
NMCMDA: neural multicategory MiRNA–disease association prediction
Jingru Wang, Jin Li, Kun Yue, et al.
Briefings in Bioinformatics (2021) Vol. 22, Iss. 5
Closed Access | Times Cited: 36
Subgraph-Aware Graph Kernel Neural Network for Link Prediction in Biological Networks
Menglu Li, Zhiwei Wang, L. Liu, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 7, pp. 4373-4381
Closed Access | Times Cited: 5
LMI-DForest: A deep forest model towards the prediction of lncRNA-miRNA interactions
Wei Wang, Xiao‐Qing Guan, Muhammad Tahir Khan, et al.
Computational Biology and Chemistry (2020) Vol. 89, pp. 107406-107406
Closed Access | Times Cited: 37
Deep-Representation-Learning-Based Classification Strategy for Anticancer Peptides
Shujaat Khan
Mathematics (2024) Vol. 12, Iss. 9, pp. 1330-1330
Open Access | Times Cited: 4
MDA-CF: Predicting MiRNA-Disease associations based on a cascade forest model by fusing multi-source information
Qiuying Dai, Yanyi Chu, Zhiqi Li, et al.
Computers in Biology and Medicine (2021) Vol. 136, pp. 104706-104706
Closed Access | Times Cited: 26
The structure is the message: Preserving experimental context through tensor decomposition
Zhixin Cyrillus Tan, Aaron S. Meyer
Cell Systems (2024) Vol. 15, Iss. 8, pp. 679-693
Open Access | Times Cited: 3
RNMFMDA: A Microbe-Disease Association Identification Method Based on Reliable Negative Sample Selection and Logistic Matrix Factorization With Neighborhood Regularization
Lihong Peng, Ling Shen, Longjie Liao, et al.
Frontiers in Microbiology (2020) Vol. 11
Open Access | Times Cited: 25
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations
Guangzhan Zhang, Menglu Li, Huan Deng, et al.
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 22
CSGNN: Contrastive Self-Supervised Graph Neural Network for Molecular Interaction Prediction
Chengshuai Zhao, Shuai Liu, Feng Huang, et al.
(2021), pp. 3756-3763
Open Access | Times Cited: 21
Predicting Drug–Gene–Disease Associations by Tensor Decomposition for Network-Based Computational Drug Repositioning
Yoonbee Kim, Young‐Rae Cho
Biomedicines (2023) Vol. 11, Iss. 7, pp. 1998-1998
Open Access | Times Cited: 9
Machine learning in the development of targeting microRNAs in human disease
Yuxun Luo, Peng Li, Wenyu Shan, et al.
Frontiers in Genetics (2023) Vol. 13
Open Access | Times Cited: 8
A game theory based many-objective hybrid tensor decomposition for skin cancer prediction
Jianghui Cai, Jinqian Yang, Jie Wen, et al.
Expert Systems with Applications (2023) Vol. 239, pp. 122425-122425
Closed Access | Times Cited: 8
DF-MDA: An effective diffusion-based computational model for predicting miRNA-disease association
Haoyuan Li, Zhu‐Hong You, Lei Wang, et al.
Molecular Therapy (2021) Vol. 29, Iss. 4, pp. 1501-1511
Open Access | Times Cited: 18
Predicting Coding Potential of RNA Sequences by Solving Local Data Imbalance
Chen Xiangan, Shuai Liu, Wen Zhang
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2020) Vol. 19, Iss. 2, pp. 1075-1083
Closed Access | Times Cited: 19
A novel miRNA-disease association prediction model using dual random walk with restart and space projection federated method
Ang Li, Yingwei Deng, Tan Yan, et al.
PLoS ONE (2021) Vol. 16, Iss. 6, pp. e0252971-e0252971
Open Access | Times Cited: 17
Predicting multiple types of MicroRNA-disease associations based on tensor factorization and label propagation
Na Yu, Zhi–Ping Liu, Rui Gao
Computers in Biology and Medicine (2022) Vol. 146, pp. 105558-105558
Closed Access | Times Cited: 12
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