Xiao-Rui Su
This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.
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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
Fusing Higher and Lower-Order Biological Information for Drug Repositioning via Graph Representation Learning.
IEEE Trans. Emerg. Top. Comput., 2024
Dual-Channel Learning Framework for Drug-Drug Interaction Prediction via Relation-Aware Heterogeneous Graph Transformer.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
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
IEEE J. Biomed. Health Informatics, 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
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
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
2021
In silico drug repositioning using deep learning and comprehensive similarity measures.
BMC Bioinform., 2021
SANE: A sequence combined attentive network embedding model for COVID-19 drug repositioning.
Appl. Soft Comput., 2021
Detection of Drug-Drug Interactions Through Knowledge Graph Integrating Multi-attention with Capsule Network.
Proceedings of the Intelligent Computing Theories and Application, 2021
Protein-Protein Interaction Prediction by Integrating Sequence Information and Heterogeneous Network Representation.
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
A Unified Deep Biological Sequence Representation Learning with Pretrained Encoder-Decoder Model.
Proceedings of the Intelligent Computing Theories and Application, 2020
A Novel Computational Approach for Predicting Drug-Target Interactions via Network Representation Learning.
Proceedings of the Intelligent Computing Theories and Application, 2020
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
A Facile Electrochemical Sensor Labeled by Ferrocenoyl Cysteine Conjugate for the Detection of Nitrite in Pickle Juice.
Sensors, 2019