Bo-Wei Zhao
Orcid: 0000-0001-8200-6016
According to our database1,
Bo-Wei Zhao
authored at least 35 papers
between 2020 and 2024.
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Bibliography
2024
Discovering Consensus Regions for Interpretable Identification of RNA N6-Methyladenosine Modification Sites via Graph Contrastive Clustering.
IEEE J. Biomed. Health Informatics, April, 2024
Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations.
Briefings Bioinform., January, 2024
Fusing Higher and Lower-Order Biological Information for Drug Repositioning via Graph Representation Learning.
IEEE Trans. Emerg. Top. Comput., 2024
2023
PDA-PRGCN: identification of Piwi-interacting RNA-disease associations through subgraph projection and residual scaling-based feature augmentation.
BMC Bioinform., December, 2023
Biocaiv: an integrative webserver for motif-based clustering analysis and interactive visualization of biological networks.
BMC Bioinform., December, 2023
iGRLDTI: an improved graph representation learning method for predicting drug-target interactions over heterogeneous biological information network.
Bioinform., August, 2023
Biomedical Knowledge Graph Embedding With Capsule Network for Multi-Label Drug-Drug Interaction Prediction.
IEEE Trans. Knowl. Data Eng., June, 2023
Incorporating higher order network structures to improve miRNA-disease association prediction based on functional modularity.
Briefings Bioinform., January, 2023
Multi-level Subgraph Representation Learning for Drug-Disease Association Prediction Over Heterogeneous Biological Information Network.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
A Deep Learning Approach Incorporating Data Missing Mechanism in Predicting Acute Kidney Injury in ICU.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
A Novel Graph Representation Learning Model for Drug Repositioning Using Graph Transition Probability Matrix Over Heterogenous Information Networks.
Proceedings of the Advanced Intelligent Computing Technology and Applications, 2023
Drug Repositioning Method Based on Pre-trained Large Model and Network Embedding Representation.
Proceedings of the IEEE International Conference on Data Mining, 2023
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023
2022
IEEE J. Biomed. Health Informatics, 2022
RLFDDA: a meta-path based graph representation learning model for drug-disease association prediction.
BMC Bioinform., 2022
Multi-view heterogeneous molecular network representation learning for protein-protein interaction prediction.
BMC Bioinform., 2022
A geometric deep learning framework for drug repositioning over heterogeneous information networks.
Briefings Bioinform., 2022
HINGRL: predicting drug-disease associations with graph representation learning on heterogeneous information networks.
Briefings Bioinform., 2022
iGRLCDA: identifying circRNA-disease association based on graph representation learning.
Briefings Bioinform., 2022
A machine learning framework based on multi-source feature fusion for circRNA-disease association prediction.
Briefings Bioinform., 2022
Attention-based Knowledge Graph Representation Learning for Predicting Drug-drug Interactions.
Briefings Bioinform., 2022
A deep learning method for repurposing antiviral drugs against new viruses via multi-view nonnegative matrix factorization and its application to SARS-CoV-2.
Briefings Bioinform., 2022
A novel circRNA-miRNA association prediction model based on structural deep neural network embedding.
Briefings Bioinform., 2022
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022
MRLDTI: A Meta-path-Based Representation Learning Model for Drug-Target Interaction Prediction.
Proceedings of the Intelligent Computing Theories and Application, 2022
Predicting Drug-Disease Associations via Meta-path Representation Learning based on Heterogeneous Information Net works.
Proceedings of the Intelligent Computing Theories and Application, 2022
Cost and Care Insight: An Interactive and Scalable Hierarchical Learning System for Identifying Cost Saving Opportunities.
Proceedings of the Intelligent Computing Theories and Application, 2022
2021
SANE: A sequence combined attentive network embedding model for COVID-19 drug repositioning.
Appl. Soft Comput., 2021
Predicting Large-scale Protein-protein Interactions by Extracting Coevolutionary Patterns with MapReduce Paradigm.
Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021
Proceedings of the Intelligent Computing Theories and Application, 2021
Detection of Drug-Drug Interactions Through Knowledge Graph Integrating Multi-attention with Capsule Network.
Proceedings of the Intelligent Computing Theories and Application, 2021
Predicting miRNA-Disease Associations via a New MeSH Headings Representation of Diseases and eXtreme Gradient Boosting.
Proceedings of the Intelligent Computing Theories and Application, 2021
2020
Predicting LncRNA-miRNA Interactions via Network Embedding with Integrated Structure and Attribute Information.
Proceedings of the Intelligent Computing Theories and Application, 2020
A Novel Computational Method for Predicting LncRNA-Disease Associations from Heterogeneous Information Network with SDNE Embedding Model.
Proceedings of the Intelligent Computing Theories and Application, 2020