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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:

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

Showing 1-25 of 137 citing articles:

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: 193
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: 186
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: 161
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: 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
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: 51
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: 41
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
A representation learning model based on variational inference and graph autoencoder for predicting lncRNA-disease associations
Zhuangwei Shi, Han Zhang, Chen Jin, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 67
Cell–cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies
Lihong Peng, Feixiang Wang, Zhao Wang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 4
Closed Access | Times Cited: 67
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
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: 43
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: 40
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
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: 35
Deciphering ligand–receptor-mediated intercellular communication based on ensemble deep learning and the joint scoring strategy from single-cell transcriptomic data
Lihong Peng, Jingwei Tan, Wei Xiong, et al.
Computers in Biology and Medicine (2023) Vol. 163, pp. 107137-107137
Closed Access | Times Cited: 34
CellEnBoost: A Boosting-Based Ligand-Receptor Interaction Identification Model for Cell-to-Cell Communication Inference
Lihong Peng, Ruya Yuan, Chendi Han, et al.
IEEE Transactions on NanoBioscience (2023) Vol. 22, Iss. 4, pp. 705-715
Closed Access | Times Cited: 28
A Survey of Deep Learning for Detecting miRNA- Disease Associations: Databases, Computational Methods, Challenges, and Future Directions
Nan Sheng, Xuping Xie, Yan Wang, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 3, pp. 328-347
Closed Access | Times Cited: 9
Predicting miRNA–Disease Associations by Combining Graph and Hypergraph Convolutional Network
Xujun Liang, Ming Guo, Longying Jiang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 2, pp. 289-303
Closed Access | Times Cited: 8
iGRLCDA: identifying circRNA–disease association based on graph representation learning
Han-Yuan Zhang, Lei Wang, Zhu‐Hong You, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 36
A new modelling framework to assess changes in groundwater level
Ikechukwu Kalu, Christopher E. Ndehedehe, Onuwa Okwuashi, et al.
Journal of Hydrology Regional Studies (2022) Vol. 43, pp. 101185-101185
Open Access | Times Cited: 35
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
Identidication of novel biomarkers in non-small cell lung cancer using machine learning
Fangwei Wang, Qisheng Su, Chaoqian Li
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 28
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