Zixuan Wang

Orcid: 0000-0003-4829-1073

According to our database1, Zixuan Wang authored at least 11 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
An overview of computational methods in single-cell transcriptomic cell type annotation.
Briefings Bioinform., 2025

Supervised pre-training for feature extraction in cell type annotation of single-cell multi-omics data.
Appl. Soft Comput., 2025

2024
Cell-Specific Highly Correlated Network for Self-Supervised Distillation in Cell Type Annotation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023
HGTDG: An Interpretable Heterogeneous Graph Transformer Framework for Cancer Driver Gene Prediction.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

KDProg: A Knowledge distillation graph neural network for cancer prognosis prediction and analysis.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Exploring Parameter-Efficient Fine-Tuning of a Large-Scale Pre-Trained Model for scRNA-seq Cell Type Annotation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
A novel convolution attention model for predicting transcription factor binding sites by combination of sequence and shape.
Briefings Bioinform., 2022

Predicting cell type-specific effects of variants on TF-DNA binding by meta-learning.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Single-cell TF-DNA binding prediction and analysis based on transfer learning framework.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021
High-resolution transcription factor binding sites prediction improved performance and interpretability by deep learning method.
Briefings Bioinform., 2021

By hybrid neural networks for prediction and interpretation of transcription factor binding sites based on multi-omics.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021


  Loading...