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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:

MiRNA–disease association prediction based on meta-paths
Liang Yu, Yujia Zheng, Lin Gao
Briefings in Bioinformatics (2021) Vol. 23, Iss. 2
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Accurately identifying hemagglutinin using sequence information and machine learning methods
Xidan Zou, Liping Ren, Peiling Cai, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 68
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
miRNAs in Heart Development and Disease
Estefanía Lozano-Velasco, José M. Inácio, Inês Sousa, et al.
International Journal of Molecular Sciences (2024) Vol. 25, Iss. 3, pp. 1673-1673
Open Access | Times Cited: 9
HOPEXGB: A Consensual Model for Predicting miRNA/lncRNA-Disease Associations Using a Heterogeneous Disease-miRNA-lncRNA Information Network
Jian He, Menglong Li, Jiangguo Qiu, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 7, pp. 2863-2877
Closed Access | Times Cited: 9
A knowledge-driven network for fine-grained relationship detection between miRNA and disease
Shengpeng Yu, Hong Wang, Tianyu Liu, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 3
Closed Access | Times Cited: 13
Predicting Disease-Metabolite Associations Based on the Metapath Aggregation of Tripartite Heterogeneous Networks
W.D. Liu, Pengli Lu
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 4, pp. 829-843
Closed Access | Times Cited: 2
MSHGANMDA: Meta-Subgraphs Heterogeneous Graph Attention Network for miRNA-Disease Association Prediction
Shudong Wang, Fuyu Wang, Sibo Qiao, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 27, Iss. 10, pp. 4639-4648
Closed Access | Times Cited: 11
BertNDA: A Model Based on Graph-Bert and Multi-Scale Information Fusion for ncRNA-Disease Association Prediction
Zhiwei Ning, Jinyang Wu, Yidong Ding, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 11, pp. 5655-5664
Open Access | Times Cited: 5
Prediction of apoptosis protein subcellular location based on amphiphilic pseudo amino acid composition
Wenxia Su, Shuyi Deng, Zhi-Feng Gu, et al.
Frontiers in Genetics (2023) Vol. 14
Open Access | Times Cited: 4
Predicting enhancer-promoter interaction based on epigenomic signals
Leqiong Zheng, Li Liu, Wen Zhu, et al.
Frontiers in Genetics (2023) Vol. 14
Open Access | Times Cited: 4
KATZNCP: a miRNA–disease association prediction model integrating KATZ algorithm and network consistency projection
Min Chen, Yingwei Deng, Zejun Li, et al.
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 4
DGAMDA: Predicting miRNA‐disease association based on dynamic graph attention network
Changxin Jia, Fuyu Wang, Baoxiang Xing, et al.
International Journal for Numerical Methods in Biomedical Engineering (2024) Vol. 40, Iss. 5
Closed Access | Times Cited: 1
A miRNA-disease association prediction model based on tree-path global feature extraction and fully connected artificial neural network with multi-head self-attention mechanism
Hou Biyu, Mengshan Li, Yuxin Hou, et al.
BMC Cancer (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
RSANMDA: Resampling based subview attention network for miRNA-disease association prediction
Longfei Luo, Zhuokun Tan, Shunfang Wang
Methods (2024) Vol. 230, pp. 99-107
Closed Access | Times Cited: 1
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction
Zhengwei Li, Lipeng Wan, Lei Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 5
Open Access | Times Cited: 1
Prediction of YY1 loop anchor based on multi-omics features
Jun Ren, Zhiling Guo, Yangfan Qi, et al.
Methods (2024) Vol. 232, pp. 96-106
Closed Access | Times Cited: 1
Computational identification of promoters in Klebsiella aerogenes by using support vector machine
Yan Lin, Meili Sun, Junjie Zhang, et al.
Frontiers in Microbiology (2023) Vol. 14
Open Access | Times Cited: 3
A message passing framework with multiple data integration for miRNA-disease association prediction
Thi Ngan Dong, Johanna Schrader, Stefanie Mücke, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 5
Prediction of thermophilic protein using 2-D general series correlation pseudo amino acid features
Hao Wan, Yanan Zhang, Shibo Huang
Methods (2023) Vol. 218, pp. 141-148
Closed Access | Times Cited: 2
SVMMDR: Prediction of miRNAs-drug resistance using support vector machines based on heterogeneous network
Tao Duan, Zhufang Kuang, Lei Deng
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 4
A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective
Dongmin Bang, Jeonghyeon Gu, Joonhyeong Park, et al.
International Journal of Molecular Sciences (2022) Vol. 23, Iss. 19, pp. 11498-11498
Open Access | Times Cited: 3
De Novo Mutations Promote Inflammation in Children with Stat3 Gain-of-Functionsyndrome by Affecting Il-1β Expression
Jiyu Chen, Yanfang Li, Zhu Zhou, et al.
(2024)
Open Access
De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression
Jiyu Chen, Yanfang Li, Xue-Mei Jiang, et al.
Research Square (Research Square) (2024)
Open Access
Three-layer heterogeneous network based on the integration of CircRNA information for MiRNA-disease association prediction
Jia Qu, Shuting Liu, Han Li, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e2070-e2070
Open Access
De novo mutations promote inflammation in children with STAT3 gain-of-function syndrome by affecting IL-1β expression
Jiyu Chen, Yanfang Li, Zhu Zhou, et al.
International Immunopharmacology (2024) Vol. 140, pp. 112755-112755
Open Access
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