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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:

Computational models for lncRNA function prediction and functional similarity calculation
Xing Chen, Yazhou Sun, Na‐Na Guan, et al.
Briefings in Functional Genomics (2018) Vol. 18, Iss. 1, pp. 58-82
Closed Access | Times Cited: 159

Showing 1-25 of 159 citing articles:

Application of Machine Learning in Microbiology
Kaiyang Qu, Fei Guo, Xiangrong Liu, et al.
Frontiers in Microbiology (2019) Vol. 10
Open Access | Times Cited: 174
Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions
Jiayang Chen, Zhihang Hu, Siqi Sun, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 87
Telomerase RNA component lncRNA as potential diagnostic biomarker promotes CRC cellular migration and apoptosis evasion via modulation of β-catenin protein level
Mohamed Bakr Zaki, Mai A. Abd‐Elmawla, Hanan Elimam, et al.
Non-coding RNA Research (2023) Vol. 8, Iss. 3, pp. 302-314
Open Access | Times Cited: 52
Computational Methods for Identifying Similar Diseases
Liang Cheng, Hengqiang Zhao, Pingping Wang, et al.
Molecular Therapy — Nucleic Acids (2019) Vol. 18, pp. 590-604
Open Access | Times Cited: 113
LncRNAs Regulatory Networks in Cellular Senescence
Pavan Kumar P
International Journal of Molecular Sciences (2019) Vol. 20, Iss. 11, pp. 2615-2615
Open Access | Times Cited: 93
A random forest based computational model for predicting novel lncRNA-disease associations
Dengju Yao, Xiaojuan Zhan, Xiaorong Zhan, et al.
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 71
GANLDA: Graph attention network for lncRNA-disease associations prediction
Wei Lan, WU Xi-min, Qingfeng Chen, et al.
Neurocomputing (2021) Vol. 469, pp. 384-393
Closed Access | Times Cited: 71
LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine
Lihong Peng, Liangliang Huang, Qiongli Su, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 25
Data resources and computational methods for lncRNA-disease association prediction
Nan Sheng, Lan Huang, Yuting Lu, et al.
Computers in Biology and Medicine (2023) Vol. 153, pp. 106527-106527
Open Access | Times Cited: 24
RPITER: A Hierarchical Deep Learning Framework for ncRNA–Protein Interaction Prediction
Cheng Peng, Siyu Han, Hui Zhang, et al.
International Journal of Molecular Sciences (2019) Vol. 20, Iss. 5, pp. 1070-1070
Open Access | Times Cited: 72
Functions and Regulatory Mechanisms of lncRNAs in Skeletal Myogenesis, Muscle Disease and Meat Production
Shanshan Wang, Jianjun Jin, Zaiyan Xu, et al.
Cells (2019) Vol. 8, Iss. 9, pp. 1107-1107
Open Access | Times Cited: 72
GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest
Qing-Wen Wu, Junfeng Xia, Jiancheng Ni, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 5
Closed Access | Times Cited: 65
A novel collaborative filtering model for LncRNA-disease association prediction based on the Naïve Bayesian classifier
Jingwen Yu, Zhanwei Xuan, Xiang Feng, et al.
BMC Bioinformatics (2019) Vol. 20, Iss. 1
Open Access | Times Cited: 61
Inferring LncRNA-disease associations based on graph autoencoder matrix completion
WU Xi-min, Wei Lan, Qingfeng Chen, et al.
Computational Biology and Chemistry (2020) Vol. 87, pp. 107282-107282
Closed Access | Times Cited: 53
Attentional multi-level representation encoding based on convolutional and variance autoencoders for lncRNA–disease association prediction
Nan Sheng, Hui Cui, Tiangang Zhang, et al.
Briefings in Bioinformatics (2020) Vol. 22, Iss. 3
Closed Access | Times Cited: 53
GCRFLDA: scoring lncRNA-disease associations using graph convolution matrix completion with conditional random field
Yongxian Fan, Meijun Chen, Xiaoyong Pan
Briefings in Bioinformatics (2021) Vol. 23, Iss. 1
Closed Access | Times Cited: 45
EnANNDeep: An Ensemble-based lncRNA–protein Interaction Prediction Framework with Adaptive k-Nearest Neighbor Classifier and Deep Models
Lihong Peng, Jingwei Tan, Xiongfei Tian, et al.
Interdisciplinary Sciences Computational Life Sciences (2022) Vol. 14, Iss. 1, pp. 209-232
Closed Access | Times Cited: 37
gGATLDA: lncRNA-disease association prediction based on graph-level graph attention network
Li Wang, Cheng Zhong
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 31
Predicting lncRNA–disease associations based on combining selective similarity matrix fusion and bidirectional linear neighborhood label propagation
Guobo Xie, Rui-Bin Chen, Zhiyi Lin, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 1
Closed Access | Times Cited: 18
GEnDDn: An lncRNA–Disease Association Identification Framework Based on Dual-Net Neural Architecture and Deep Neural Network
Lihong Peng, Mengnan Ren, Liangliang Huang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 2, pp. 418-438
Closed Access | Times Cited: 7
A Probabilistic Matrix Factorization Method for Identifying lncRNA-Disease Associations
Zhanwei Xuan, Jiechen Li, Jingwen Yu, et al.
Genes (2019) Vol. 10, Iss. 2, pp. 126-126
Open Access | Times Cited: 53
RFSMMA: A New Computational Model to Identify and Prioritize Potential Small Molecule–MiRNA Associations
Chun-Chun Wang, Xing Chen, Jia Qu, et al.
Journal of Chemical Information and Modeling (2019) Vol. 59, Iss. 4, pp. 1668-1679
Closed Access | Times Cited: 47
Finding lncRNA-Protein Interactions Based on Deep Learning With Dual-Net Neural Architecture
Lihong Peng, Chang Wang, Xiongfei Tian, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2021) Vol. 19, Iss. 6, pp. 3456-3468
Closed Access | Times Cited: 41
LPI-deepGBDT: a multiple-layer deep framework based on gradient boosting decision trees for lncRNA–protein interaction identification
Liqian Zhou, Zhao Wang, Xiongfei Tian, et al.
BMC Bioinformatics (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 40
Multi-channel graph attention autoencoders for disease-related lncRNAs prediction
Nan Sheng, Lan Huang, Yan Wang, et al.
Briefings in Bioinformatics (2022) Vol. 23, Iss. 2
Closed Access | Times Cited: 25
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