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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:

Joint deep autoencoder and subgraph augmentation for inferring microbial responses to drugs
Zhecheng Zhou, Linlin Zhuo, Xiangzheng Fu, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 24

Showing 24 citing articles:

Identifying potential ligand–receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis
Lihong Peng, Pengfei Gao, Wei Xiong, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108110-108110
Closed Access | Times Cited: 11
Regulation-aware graph learning for drug repositioning over heterogeneous biological network
Bo-Wei Zhao, Xiaorui Su, Yue Yang, et al.
Information Sciences (2024) Vol. 686, pp. 121360-121360
Closed Access | Times Cited: 11
LncRNA–miRNA interactions prediction based on meta‐path similarity and Gaussian kernel similarity
Jingxuan Xie, Peng Xu, Lin Ye, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 19
Open Access | Times Cited: 10
Predicting the potential associations between circRNA and drug sensitivity using a multisource feature‐based approach
Shuaidong Yin, Peng Xu, Yefeng Jiang, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 19
Open Access | Times Cited: 10
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: 5
GraphADT: empowering interpretable predictions of acute dermal toxicity with multi-view graph pooling and structure remapping
Xinqian Ma, Xiangzheng Fu, Tao Wang, et al.
Bioinformatics (2024) Vol. 40, Iss. 7
Open Access | Times Cited: 5
MPEMDA: A Multi-Similarity Integration Approach with Pre-completion and Error Correction for Predicting Microbe-Drug Associations
Yuxiang Li, Haochen Zhao, Jianxin Wang
Methods (2025)
Closed Access
Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines
Zhina Wang, Yishan Chen, Hongming Ma, et al.
Frontiers in Pharmacology (2025) Vol. 15
Open Access
Predicting cell–cell communication by combining heterogeneous ensemble deep learning and weighted geometric mean
Lihong Peng, L. C. Liu, Liangliang Huang, et al.
Applied Soft Computing (2025), pp. 112839-112839
Closed Access
scGIR: deciphering cellular heterogeneity via gene ranking in single-cell weighted gene correlation networks
Fei Xu, Huan Hu, Hai Lin, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 3
Developing explainable models for lncRNA-Targeted drug discovery using graph autoencoders
Huiying Liu, Xiangzheng Fu, Haiting Chen, et al.
Future Generation Computer Systems (2024) Vol. 160, pp. 29-39
Closed Access | Times Cited: 3
HPTRMF: Collaborative Matrix Factorization-Based Prediction Method for LncRNA-Disease Associations Using High-Order Perturbation and Flexible Trifactor Regularization
Guobo Xie, Dayin Li, Zhiyi Lin, et al.
Journal of Chemical Information and Modeling (2024)
Closed Access | Times Cited: 2
Predicting potential microbe–disease associations based on dual branch graph convolutional network
Jing Chen, Yongjun Zhu, Qun Yuan
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 15
Open Access | Times Cited: 2
Microbe–disease associations prediction by graph regularized non‐negative matrix factorization with L2,1$$ {L}_{2,1} $$ norm regularization terms
Ziwei Chen, Liangzhe Zhang, Jingyi Li, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 17
Open Access | Times Cited: 2
Advanced mathematical modeling of mitigating security threats in smart grids through deep ensemble model
Sanaa Sharaf, Mahmoud Ragab, Nasser Albogami, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
CVGAE: A Self-Supervised Generative Method for Gene Regulatory Network Inference Using Single-Cell RNA Sequencing Data
Wei Liu, Zhijie Teng, Zejun Li, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 4, pp. 990-1004
Closed Access | Times Cited: 1
Multi-source data integration for explainable miRNA-driven drug discovery
Zhen Li, Qingquan Liao, Wenbin Liu, et al.
Future Generation Computer Systems (2024) Vol. 160, pp. 109-119
Closed Access | Times Cited: 1
Adversarial regularized autoencoder graph neural network for microbe-disease associations prediction
Limuxuan He, Quan Zou, Qi Dai, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access | Times Cited: 1
Knowledge enhanced attention aggregation network for medicine recommendation
Jiedong Wei, Yijia Zhang, Xingwang Li, et al.
Computational Biology and Chemistry (2024) Vol. 111, pp. 108099-108099
Closed Access
HTFSMMA: Higher-Order Topological Guided Small Molecule–MicroRNA Associations Prediction
Xiaoyan Sun, Zhenjie Hou, Wenguang Zhang, et al.
Journal of Computational Biology (2024) Vol. 31, Iss. 9, pp. 886-906
Closed Access
CMFHMDA: a prediction framework for human disease-microbe associations based on cross-domain matrix factorization
Jing Chen, Ran Tao, Yi Qiu, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 6
Open Access
GRL-PUL: Predicting microbe-drug association based on graph representation learning and positive unlabeled learning
Junwu Liang, Yuping Sun, Jie Ling
Molecular Omics (2024) Vol. 21, Iss. 1, pp. 38-50
Closed Access
THGB: predicting ligand-receptor interactions by combining tree boosting and histogram-based gradient boosting
Liqian Zhou, Jiao Song, Zejun Li, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
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