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:

Prediction of Potential Disease-Associated MicroRNAs by Using Neural Networks
Xiangxiang Zeng, Wen Wang, Gaoshan Deng, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 16, pp. 566-575
Open Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Sezen Vatansever, Avner Schlessinger, Daniel Wacker, et al.
Medicinal Research Reviews (2020) Vol. 41, Iss. 3, pp. 1427-1473
Open Access | Times Cited: 260
Machine intelligence in peptide therapeutics: A next‐generation tool for rapid disease screening
Shaherin Basith, Balachandran Manavalan, Tae Hwan Shin, et al.
Medicinal Research Reviews (2020) Vol. 40, Iss. 4, pp. 1276-1314
Closed Access | Times Cited: 255
Graph-Based Semi-Supervised Learning: A Comprehensive Review
Zixing Song, Xiangli Yang, Zenglin Xu, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 34, Iss. 11, pp. 8174-8194
Open Access | Times Cited: 166
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
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
Event-triggered distributed control for synchronization of multiple memristive neural networks under cyber-physical attacks
Shengbo Wang, Yuting Cao, Tingwen Huang, et al.
Information Sciences (2020) Vol. 518, pp. 361-375
Closed Access | Times Cited: 94
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
DRESIS: the first comprehensive landscape of drug resistance information
Xiuna Sun, Yintao Zhang, Hanyang Li, et al.
Nucleic Acids Research (2022) Vol. 51, Iss. D1, pp. D1263-D1275
Open Access | Times Cited: 56
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
Event-based sliding-mode synchronization of delayed memristive neural networks via continuous/periodic sampling algorithm
Yuxiao Wang, Yuting Cao, Zhenyuan Guo, et al.
Applied Mathematics and Computation (2020) Vol. 383, pp. 125379-125379
Closed Access | Times Cited: 53
Complex systems and network science: a survey
Kewei Yang, Jichao Li, Maidi Liu, et al.
Journal of Systems Engineering and Electronics (2023) Vol. 34, Iss. 3, pp. 543-573
Open Access | Times Cited: 19
Inspector: a lysine succinylation predictor based on edited nearest-neighbor undersampling and adaptive synthetic oversampling
Yan Zhu, Cangzhi Jia, Fuyi Li, et al.
Analytical Biochemistry (2020) Vol. 593, pp. 113592-113592
Closed Access | Times Cited: 49
iPiDi-PUL: identifying Piwi-interacting RNA-disease associations based on positive unlabeled learning
Hang Wei, Yong Xu, Bin Liu
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 39
Prediction of Anticancer Peptides Using a Low-Dimensional Feature Model
Qingwen Li, Wenyang Zhou, Donghua Wang, et al.
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 39
Predicting miRNA-disease associations based on lncRNA–miRNA interactions and graph convolution networks
Wengang Wang, Hailin Chen
Briefings in Bioinformatics (2022) Vol. 24, Iss. 1
Closed Access | Times Cited: 23
DAPNEML: Disease-Diet Associations Prediction in a NEtwork using a Machine Learning based approach
Rashmeet Toor, Inderveer Chana
Journal of Network and Computer Applications (2025), pp. 104140-104140
Closed Access
FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou’s Five-Step Rule
Yi Zou, Yijie Ding, Jijun Tang, et al.
International Journal of Molecular Sciences (2019) Vol. 20, Iss. 17, pp. 4175-4175
Open Access | Times Cited: 35
iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier
Lijun Dou, Xiaoling Li, Lichao Zhang, et al.
Journal of Proteome Research (2020) Vol. 20, Iss. 1, pp. 191-201
Closed Access | Times Cited: 31
ACP-GCN: The Identification of Anticancer Peptides Based on Graph Convolution Networks
B. Dharma Rao, Lichao Zhang, Guoying Zhang
IEEE Access (2020) Vol. 8, pp. 176005-176011
Open Access | Times Cited: 29
Missing Value Estimation Methods Research for Arrhythmia Classification Using the Modified Kernel Difference-Weighted KNN Algorithms
Fei Yang, Jiazhi Du, Jiying Lang, et al.
BioMed Research International (2020) Vol. 2020, Iss. 1
Open Access | Times Cited: 28
Adaptive multi-source multi-view latent feature learning for inferring potential disease-associated miRNAs
Qiu Xiao, Ning Zhang, Jiawei Luo, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 2, pp. 2043-2057
Closed Access | Times Cited: 27
Combined embedding model for MiRNA-disease association prediction
Bailong Liu, Xiaoyan Zhu, Lei Zhang, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 22
CFNCM: Collaborative filtering neighborhood-based model for predicting miRNA-disease associations
Biffon Manyura Momanyi, Hasan Zulfiqar, Bakanina Kissanga Grace-Mercure, et al.
Computers in Biology and Medicine (2023) Vol. 163, pp. 107165-107165
Closed Access | Times Cited: 8
The Classification of Enzymes by Deep Learning
Zhiyu Tao, Benzhi Dong, Zhixia Teng, et al.
IEEE Access (2020) Vol. 8, pp. 89802-89811
Open Access | Times Cited: 23
Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model
Lei Zhang, Bailong Liu, Zhengwei Li, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 23
Page 1 - Next Page

Scroll to top