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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:

MCA-Net: Multi-Feature Coding and Attention Convolutional Neural Network for Predicting lncRNA-Disease Association
Yuan Zhang, Fei Ye, Xieping Gao
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 5, pp. 2907-2919
Closed Access | Times Cited: 15

Showing 15 citing articles:

Transformer Architecture and Attention Mechanisms in Genome Data Analysis: A Comprehensive Review
Sanghyuk Roy Choi, Minhyeok Lee
Biology (2023) Vol. 12, Iss. 7, pp. 1033-1033
Open Access | Times Cited: 63
Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction
Guanghui Li, Peihao Bai, Liang Cheng, et al.
BMC Genomics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 16
Heterogeneous graph attention network based on meta-paths for lncRNA–disease association prediction
Xiaosa Zhao, Xiaowei Zhao, Minghao Yin
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 53
MAGCNSE: predicting lncRNA-disease associations using multi-view attention graph convolutional network and stacking ensemble model
Ying Liang, Zequn Zhang, Nian-Nian Liu, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 32
Multitask Learning Model for Predicting Non-coding RNA-Disease Associations: Incorporating Local and Global Context
Xiaohan Li, Guohua Wang, Dan Li, et al.
Methods (2025)
Closed Access
Deep Learning Approaches for lncRNA-Mediated Mechanisms: A Comprehensive Review of Recent Developments
Yoojoong Kim, Minhyeok Lee
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 12, pp. 10299-10299
Open Access | Times Cited: 12
Transformer-based multi-attention hybrid networks for skin lesion segmentation
Z.-W. Dong, Jinjiang Li, Zhen Hua
Expert Systems with Applications (2023) Vol. 244, pp. 123016-123016
Closed Access | Times Cited: 11
MFF-nDA: A Computational Model for ncRNA–Disease Association Prediction Based on Multimodule Fusion
Zhihao Guan, Xiu Jin, Xiaodan Zhang
Journal of Chemical Information and Modeling (2025)
Closed Access
Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation
Silvia Rinaldi, Elisabetta Moroni, Riccardo Rozza, et al.
Journal of Chemical Theory and Computation (2024) Vol. 20, Iss. 3, pp. 993-1018
Closed Access | Times Cited: 3
GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization
Ning Ai, Yong Liang, Haoliang Yuan, et al.
BMC Genomics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 6
Recent advances in predicting lncRNA–disease associations based on computational methods
Jing Yan, Ruobing Wang, Jianjun Tan
Drug Discovery Today (2022) Vol. 28, Iss. 2, pp. 103432-103432
Closed Access | Times Cited: 10
A comprehensive survey on deep learning-based identification and predicting the interaction mechanism of long non-coding RNAs
Biyu Diao, Jin Luo, Yu Guo
Briefings in Functional Genomics (2024) Vol. 23, Iss. 4, pp. 314-324
Closed Access | Times Cited: 1
A lncRNA-disease association prediction model based on the two-step PU learning and fully connected neural networks
Hou Biyu, Tan Guangwen, Ming Zeng, et al.
Heliyon (2023) Vol. 9, Iss. 7, pp. e17726-e17726
Open Access | Times Cited: 1
Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction
Guanghui Li, Peihao Bai, Liang Cheng, et al.
Research Square (Research Square) (2023)
Open Access
SRF-LDA: A Stacking-Based Ensemble Learning Model for LncRNA-Disease Association Prediction
捷 孙
Hans Journal of Computational Biology (2023) Vol. 13, Iss. 04, pp. 35-44
Closed Access
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