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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:

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

Showing 24 citing articles:

The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review
Zahra Mohtasham‐Amiri, Arash Heidari, Nima Jafari Navimipour, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 11, pp. 5757-5797
Open Access | Times Cited: 61
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: 17
Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases
Nan Sheng, Yan Wang, Lan Huang, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 5
Closed Access | Times Cited: 24
Supervised contrastive knowledge graph learning for ncRNA–disease association prediction
Yan Wang, Xuping Xie, Ye Wang, et al.
Expert Systems with Applications (2025) Vol. 269, pp. 126257-126257
Closed Access | Times Cited: 1
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
Finding potential lncRNA–disease associations using a boosting-based ensemble learning model
Liqian Zhou, Xinhuai Peng, Lijun Zeng, et al.
Frontiers in Genetics (2024) Vol. 15
Open Access | Times Cited: 6
Competing endogenous RNAs (ceRNAs) and drug resistance to cancer therapy
Kenneth K.W. To, Hang Zhang, William C. Cho
Cancer Drug Resistance (2024)
Open Access | Times Cited: 5
A survey of computational methods and databases for lncRNA-miRNA interaction prediction
Nan Sheng, Lan Huang, Ling Gao, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 20, Iss. 5, pp. 2810-2826
Open Access | Times Cited: 10
LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks
Bing Zhang, H. Wang, Chao Ma, et al.
BMC Bioinformatics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 2
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers
Xinfei Wang, Lan Huang, Yan Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 2
GP-HTNLoc: A graph prototype head-tail network-based model for multi-label subcellular localization prediction of ncRNAs
Shuangkai Han, Lin Liu
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 2034-2048
Open Access | Times Cited: 1
Identification and immune landscape of sarcopenia-related molecular clusters in inflammatory bowel disease by machine learning and integrated bioinformatics
Chongkang Yue, Huiping Xue
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Graph pooling in graph neural networks: methods and their applications in omics studies
Yan Wang, Wenju Hou, Nan Sheng, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 11
Open Access | Times Cited: 1
COMPARISON OF PERFORMANCE OF DIFFERENT K VALUES WITH K-FOLD CROSS VALIDATION IN A GRAPH-BASED LEARNING MODEL FOR IncRNA-DISEASE PREDICTION
Zeynep BARUT, Volkan Altuntaş
Kırklareli Üniversitesi Mühendislik ve Fen Bilimleri Dergisi (2023) Vol. 9, Iss. 1, pp. 63-82
Open Access | Times Cited: 3
HRGCNLDA: Forecasting of lncRNA-disease association based on hierarchical refinement graph convolutional neural network
Peng Li, Yujie Yang, Yang Cheng, et al.
Mathematical Biosciences & Engineering (2024) Vol. 21, Iss. 4, pp. 4814-4834
Open Access
GP-HTNLoc: A Graph Prototype Head-Tail Network-based Model for Multi-label Subcellular Localization Prediction of ncRNAs
Shuangkai Han, Lin Liu
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
REVOLUTIONIZING HEALTHCARE: AN IN-DEPTH ANALYSIS OF DEEP LEARNING MODELS
Ankita Roy
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES (2024) Vol. spl11, Iss. 1
Open Access
Multi-view learning framework for predicting unknown types of cancer markers via directed graph neural networks fitting regulatory networks
Xinfei Wang, Lan Huang, Yan Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access
GMF-MGCN-LDA: Prediction of IncRNA-disease association based on novel generalized matrix factorization and graph neural networks
Qi Gao, Guosheng Han, Jialin Li, et al.
(2024), pp. 1-10
Closed Access
Computational Resources for lncRNA Functions and Targetome
Anamika Thakur, Manoj Kumar
Methods in molecular biology (2024), pp. 299-323
Closed Access
Computational Prediction of Gene Regulation by lncRNAs
Tanvi Sinha, Susovan Sadhukhan, Amaresh C. Panda
Methods in molecular biology (2024), pp. 343-362
Closed Access
Heterogeneous graph framework for predicting the association between lncRNA and disease and case on uterine fibroid
Qingjing Sheng, Yuan Tan, Liyuan Zhang, et al.
Computers in Biology and Medicine (2023) Vol. 165, pp. 107331-107331
Closed Access
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
Contrastive self-supervised graph convolutional network for detecting the relationship among lncRNAs, miRNAs, and diseases
Nan Sheng, Lan Huang, Yan Wang, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023), pp. 622-629
Closed Access
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