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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:

Multi-way relation-enhanced hypergraph representation learning for anti-cancer drug synergy prediction
Xuan Liu, Congzhi Song, Shichao Liu, et al.
Bioinformatics (2022) Vol. 38, Iss. 20, pp. 4782-4789
Closed Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

CancerGPT for few shot drug pair synergy prediction using large pretrained language models
Tianhao Li, Sandesh Shetty, Advaith Kamath, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 42
Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs
Tarek Abd El‐Hafeez, Mahmoud Y. Shams, Yaseen A. M. M. Elshaier, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 42
MPCLCDA: predicting circRNA–disease associations by using automatically selected meta-path and contrastive learning
Wei Liu, Ting Tang, Xu Lu, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 4
Closed Access | Times Cited: 38
MGAE-DC: Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders
Peng Zhang, Shikui Tu
PLoS Computational Biology (2023) Vol. 19, Iss. 3, pp. e1010951-e1010951
Open Access | Times Cited: 23
A granularity-level information fusion strategy on hypergraph transformer for predicting synergistic effects of anticancer drugs
Wei Wang, Gaolin Yuan, Shitong Wan, et al.
Briefings in Bioinformatics (2023) Vol. 25, Iss. 1
Open Access | Times Cited: 23
A review on graph neural networks for predicting synergistic drug combinations
Milad Besharatifard, Fatemeh Vafaee
Artificial Intelligence Review (2024) Vol. 57, Iss. 3
Open Access | Times Cited: 4
Deep learning for predicting synergistic drug combinations: State‐of‐the‐arts and future directions
Yu Wang, Junjie Wang, Yun Liu
Clinical and Translational Discovery (2024) Vol. 4, Iss. 3
Open Access | Times Cited: 4
Artificial intelligence in tumor drug resistance: Mechanisms and treatment prospects
Jianyou Gu, Junfeng Zhang, Silüe Zeng, et al.
(2025)
Closed Access
MMGCSyn : Explainable synergistic drug combination prediction based on multimodal fusion
Yongqing Zhang, Hao Yuan, Yuhang Liu, et al.
Future Generation Computer Systems (2025) Vol. 168, pp. 107784-107784
Closed Access
Predicting Synergistic Drug Combinations Based on Fusion of Cell and Drug Molecular Structures
Shiyu Yan, Gang Yu, Juan Yang, et al.
Interdisciplinary Sciences Computational Life Sciences (2025)
Closed Access
MGTNSyn: Molecular structure-aware graph transformer network with relational attention for drug synergy prediction
Yunjiong Liu, Peiliang Zhang, Dongyang Li, et al.
Expert Systems with Applications (2025), pp. 127699-127699
Closed Access
Integrating edge features and complementary attention mechanism for drug response prediction
Chuang Li, Minhui Wang, Chang Tang, et al.
Knowledge-Based Systems (2025), pp. 113508-113508
Closed Access
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder
Dayu Tan, Cheng Yang, Jing Wang, et al.
Briefings in Bioinformatics (2024) Vol. 25, Iss. 2
Open Access | Times Cited: 3
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction
Xinwei Zhao, Junqing Xu, Youyuan Shui, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 3
New methods for drug synergy prediction: A mini-review
Fatemeh Abbasi, Juho Rousu
Current Opinion in Structural Biology (2024) Vol. 86, pp. 102827-102827
Open Access | Times Cited: 3
Identification of drug-side effect association via correntropy-loss based matrix factorization with neural tangent kernel
Yijie Ding, Hongmei Zhou, Quan Zou, et al.
Methods (2023) Vol. 219, pp. 73-81
Closed Access | Times Cited: 8
A general hypergraph learning algorithm for drug multi-task predictions in micro-to-macro biomedical networks
Shuting Jin, Hong Yue, Zeng Li, et al.
PLoS Computational Biology (2023) Vol. 19, Iss. 11, pp. e1011597-e1011597
Open Access | Times Cited: 7
RedCDR: Dual Relation Distillation for Cancer Drug Response Prediction
Muhao Xu, Zhenfeng Zhu, Yawei Zhao, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024) Vol. 21, Iss. 5, pp. 1468-1479
Closed Access | Times Cited: 2
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide
Sun-Woo Kim, Soo Y. Lee, Yue Gao, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6534-6544
Open Access | Times Cited: 2
MPFFPSDC: A multi-pooling feature fusion model for predicting synergistic drug combinations
Xin Bao, Jianqiang Sun, Ming Yi, et al.
Methods (2023) Vol. 217, pp. 1-9
Closed Access | Times Cited: 6
Multi-view Contrastive Learning Hypergraph Neural Network for Drug-Microbe-Disease Association Prediction
L. Liu, Feng Huang, Xuan Liu, et al.
(2023), pp. 4829-4837
Open Access | Times Cited: 5
SDDSynergy: Learning Important Molecular Substructures for Explainable Anticancer Drug Synergy Prediction
Yunjiong Liu, Peiliang Zhang, Chao Che, et al.
Journal of Chemical Information and Modeling (2024)
Closed Access | Times Cited: 1
DualSyn: A dual-level feature interaction method to predict synergistic drug combinations
Zehui Chen, Zimeng Li, Xiangzhen Shen, et al.
Expert Systems with Applications (2024) Vol. 257, pp. 125065-125065
Closed Access | Times Cited: 1
MMCL-CDR: enhancing cancer drug response prediction with multi-omics and morphology images contrastive representation learning
Yang Li, Zihou Guo, Xin Gao, et al.
Bioinformatics (2023) Vol. 39, Iss. 12
Open Access | Times Cited: 3
Natural product based anticancer drug combination discovery assisted by deep learning and network analysis
Elton L. Cao
Frontiers in Natural Products (2024) Vol. 2
Open Access
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