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:
HPODNets: deep graph convolutional networks for predicting human protein–phenotype associations
Lizhi Liu, Hiroshi Mamitsuka, Shanfeng Zhu
Bioinformatics (2021) Vol. 38, Iss. 3, pp. 799-808
Closed Access | Times Cited: 6
Lizhi Liu, Hiroshi Mamitsuka, Shanfeng Zhu
Bioinformatics (2021) Vol. 38, Iss. 3, pp. 799-808
Closed Access | Times Cited: 6
Showing 6 citing articles:
HPOseq: a deep ensemble model for predicting the protein-phenotype relationships based on protein sequences
Kai Zhao, Zhongzhong Ji, Linlin Zhang, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
Kai Zhao, Zhongzhong Ji, Linlin Zhang, et al.
BMC Bioinformatics (2025) Vol. 26, Iss. 1
Open Access
Long-distance dependency combined multi-hop graph neural networks for protein–protein interactions prediction
Wen Zhong, Changxiang He, Xiao Chen, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 8
Wen Zhong, Changxiang He, Xiao Chen, et al.
BMC Bioinformatics (2022) Vol. 23, Iss. 1
Open Access | Times Cited: 8
GMAT: A Graph Modeling Method for Group Preference Prediction
Xiangyu Li, Xunhua Guo, Guoqing Chen
Journal of Systems Science and Systems Engineering (2024) Vol. 33, Iss. 4, pp. 475-493
Closed Access | Times Cited: 1
Xiangyu Li, Xunhua Guo, Guoqing Chen
Journal of Systems Science and Systems Engineering (2024) Vol. 33, Iss. 4, pp. 475-493
Closed Access | Times Cited: 1
DeepMoIC: multi-omics data integration via deep graph convolutional networks for cancer subtype classification
Junnan Wu, Zhaoliang Chen, Shunxin Xiao, et al.
BMC Genomics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Junnan Wu, Zhaoliang Chen, Shunxin Xiao, et al.
BMC Genomics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Integration of Human Protein Sequence and Protein-Protein Interaction Data by Graph Autoencoder to Identify Novel Protein-Abnormal Phenotype Associations
Yuan Liu, Ruirui He, Yingjie Qu, et al.
Cells (2022) Vol. 11, Iss. 16, pp. 2485-2485
Open Access | Times Cited: 5
Yuan Liu, Ruirui He, Yingjie Qu, et al.
Cells (2022) Vol. 11, Iss. 16, pp. 2485-2485
Open Access | Times Cited: 5
SSLpheno: a self-supervised learning approach for gene–phenotype association prediction using protein–protein interactions and gene ontology data
Xuehua Bi, Weiyang Liang, Qichang Zhao, et al.
Bioinformatics (2023) Vol. 39, Iss. 11
Open Access | Times Cited: 2
Xuehua Bi, Weiyang Liang, Qichang Zhao, et al.
Bioinformatics (2023) Vol. 39, Iss. 11
Open Access | Times Cited: 2
Phenolinker: Phenotype-Gene Link Prediction and Explanation Using Heterogeneous Graph Neural Networks
Jose Luis Mellina Andreu, Luis Bernal Escobedo, Antonio Skármeta, et al.
(2024)
Open Access
Jose Luis Mellina Andreu, Luis Bernal Escobedo, Antonio Skármeta, et al.
(2024)
Open Access
