Hai-Cheng Yi
Orcid: 0000-0001-8339-396X
According to our database1,
Hai-Cheng Yi
authored at least 22 papers
between 2019 and 2023.
Collaborative distances:
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Bibliography
2023
IEEE J. Biomed. Health Informatics, 2023
2022
DeepWalk based method to predict lncRNA-miRNA associations via lncRNA-miRNA-disease-protein-drug graph.
BMC Bioinform., 2022
Briefings Bioinform., 2022
2021
Learning Representation of Molecules in Association Network for Predicting Intermolecular Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021
In silico drug repositioning using deep learning and comprehensive similarity measures.
BMC Bioinform., 2021
A learning-based method to predict LncRNA-disease associations by combining CNN and ELM.
BMC Bioinform., 2021
MeSHHeading2vec: a new method for representing MeSH headings as vectors based on graph embedding algorithm.
Briefings Bioinform., 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
2020
A deep learning-based method for drug-target interaction prediction based on long short-term memory neural network.
BMC Medical Informatics Decis. Mak., March, 2020
Using Weighted Extreme Learning Machine Combined With Scale-Invariant Feature Transform to Predict Protein-Protein Interactions From Protein Evolutionary Information.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020
RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information.
BMC Bioinform., 2020
NEMPD: a network embedding-based method for predicting miRNA-disease associations by preserving behavior and attribute information.
BMC Bioinform., 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
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
Inferring Drug-miRNA Associations by Integrating Drug SMILES and MiRNA Sequence Information.
Proceedings of the Intelligent Computing Theories and Application, 2020
Predicting Drug-Target Interactions by Node2vec Node Embedding in Molecular Associations Network.
Proceedings of the Intelligent Computing Theories and Application, 2020
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
2019
In Silico Identification of Anticancer Peptides with Stacking Heterogeneous Ensemble Learning Model and Sequence Information.
Proceedings of the Intelligent Computing Theories and Application, 2019
A Gated Recurrent Unit Model for Drug Repositioning by Combining Comprehensive Similarity Measures and Gaussian Interaction Profile Kernel.
Proceedings of the Intelligent Computing Theories and Application, 2019
Combining Evolutionary Information and Sparse Bayesian Probability Model to Accurately Predict Self-interacting Proteins.
Proceedings of the Intelligent Computing Theories and Application, 2019