Meineng Wang
Orcid: 0000-0001-8882-3156
According to our database1,
Meineng Wang
authored at least 11 papers
between 2020 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
2020
2021
2022
2023
2024
0
1
2
3
4
5
2
1
2
2
1
1
2
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Graph-Regularized Non-Negative Matrix Factorization for Single-Cell Clustering in scRNA-Seq Data.
IEEE J. Biomed. Health Informatics, August, 2024
Attention-Based Learning for Predicting Drug-Drug Interactions in Knowledge Graph Embedding Based on Multisource Fusion Information.
Int. J. Intell. Syst., 2024
A Single-Cell Clustering Algorithm Based on Structure Perturbation Non-Negative Matrix Factorization.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024
2023
Combining K Nearest Neighbor With Nonnegative Matrix Factorization for Predicting Circrna-Disease Associations.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023
2021
LDGRNMF: LncRNA-disease associations prediction based on graph regularized non-negative matrix factorization.
Neurocomputing, 2021
A learning-based method to predict LncRNA-disease associations by combining CNN and ELM.
BMC Bioinform., 2021
Weighted Nonnegative Matrix Factorization Based on Multi-source Fusion Information for Predicting CircRNA-Disease Associations.
Proceedings of the Intelligent Computing Theories and Application, 2021
2020
RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information.
BMC Bioinform., 2020
GNMFLMI: Graph Regularized Nonnegative Matrix Factorization for Predicting LncRNA-MiRNA Interactions.
IEEE Access, 2020
DTIFS: A Novel Computational Approach for Predicting Drug-Target Interactions from Drug Structure and Protein Sequence.
Proceedings of the Intelligent Computing Theories and Application, 2020
WGMFDDA: A Novel Weighted-Based Graph Regularized Matrix Factorization for Predicting Drug-Disease Associations.
Proceedings of the Intelligent Computing Methodologies - 16th International Conference, 2020