Zixuan Wang

According to our database, Zixuan Wang authored at least 22 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Contrastive learning in both structure and function spaces improve drug-target interaction prediction.

Yongqing Zhang, Le Chen, Hong Luo, Tianhao Li, Shuwen Xiong, Zixuan Wang, Quan Zou, Wenqian Zhang

BMC Bioinform., December, 2026

SAD: Sparse-Aware Diffusion Model for Single-Cell Gene Expression Completion.

Tianhao Li, Yixin Xiang, Zixuan Wang, Mengwen Liu, Quan Zou, Yongqing Zhang

IEEE Trans. Comput. Biol. Bioinform., 2026

Deep generative framework for modeling single-cell drug perturbation response.

Yongqing Zhang, Chenpeng Wu, Tianhao Li, Zhigan Zhou, Zhengxiao Huang, Aochen Zhang, Zixuan Wang

Neural Networks, 2026

Distribution and expression aware retrospective learning for single-cell long-tailed class-incremental annotation.

Tianhao Li, Zixuan Wang, Chenpeng Wu, Zhengxiao Huang, Yixin Xiang, Yuhang Liu, Quan Zou, Naifeng Wen, Yongqing Zhang

Appl. Soft Comput., 2026

2025

An overview of computational methods in single-cell transcriptomic cell type annotation.

Tianhao Li, Zixuan Wang, Yuhang Liu, Sihan He, Quan Zou, Yongqing Zhang

Briefings Bioinform., May, 2025

A Multi-Omics Data Integration Framework for Gene Regulatory Network Inference Based on Contrastive Learning.

Yongqing Zhang, Zhigan Zhou, Maocheng Wang, Xinyu Mao, Zixuan Wang, Quan Zou

IEEE Trans. Comput. Biol. Bioinform., 2025

Supervised pre-training for feature extraction in cell type annotation of single-cell multi-omics data.

Yongqing Zhang, Tianhao Li, Yuhang Liu, Hong Luo, Yugui Xu, Zixuan Wang, Quan Zou

Appl. Soft Comput., 2025

Distribution and Knowledge Alignment-based Single-cell Multi-omics Cell Type Annotation.

Sihan He, Yongqing Zhang, Zhengxiao Huang, Zixuan Wang, Yuhang Liu, Tianhao Li

Proceedings of the International Joint Conference on Neural Networks, 2025

2024

scAuto as a comprehensive framework for single-cell chromatin accessibility data analysis.

Meiqin Gong, Yun Yu, Zixuan Wang, Junming Zhang, Xiongyi Wang, Cheng Fu, Yongqing Zhang, Xiaodong Wang

Comput. Biol. Medicine, 2024

Cell-Specific Highly Correlated Network for Self-Supervised Distillation in Cell Type Annotation.

Tianhao Li, Yugui Xu, Sihan He, Yuhang Liu, Zixuan Wang, Zhigan Zhou, Yongqing Zhang, Quan Zou

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

2023

Multiple sequence alignment based on deep reinforcement learning with self-attention and positional encoding.

Yuhang Liu, Hao Yuan, Qiang Zhang, Zixuan Wang, Shuwen Xiong, Naifeng Wen, Yongqing Zhang

Bioinform., October, 2023

HEAP: a task adaptive-based explainable deep learning framework for enhancer activity prediction.

Yuhang Liu, Zixuan Wang, Hao Yuan, Guiquan Zhu, Yongqing Zhang

Briefings Bioinform., September, 2023

HAMPLE: deciphering TF-DNA binding mechanism in different cellular environments by characterizing higher-order nucleotide dependency.

Zixuan Wang, Shuwen Xiong, Yun Yu, Jiliu Zhou, Yongqing Zhang

Bioinform., May, 2023

HGTDG: An Interpretable Heterogeneous Graph Transformer Framework for Cancer Driver Gene Prediction.

Shuwen Xiong, Zixuan Wang, Junming Zhang, Guiquan Zhu, Yongqing Zhang, Quan Zou

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

KDProg: A Knowledge distillation graph neural network for cancer prognosis prediction and analysis.

Shuwen Xiong, Zixuan Wang, Junming Zhang, Hong Luo, Yongqing Zhang, Quan Zou

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.

Yuhang Liu, Tianhao Li, Zixuan Wang, Guiquan Zhu, Yongqing Zhang, Quan Zou

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Towards a better understanding of TF-DNA binding prediction from genomic features.

Zixuan Wang, Meiqin Gong, Yuhang Liu, Shuwen Xiong, Maocheng Wang, Jiliu Zhou, Yongqing Zhang

Comput. Biol. Medicine, 2022

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

Yongqing Zhang, Zixuan Wang, Yuanqi Zeng, Yuhang Liu, Shuwen Xiong, Maocheng Wang, Jiliu Zhou, Quan Zou

Briefings Bioinform., 2022

Predicting cell type-specific effects of variants on TF-DNA binding by meta-learning.

Yongqing Zhang, Yuhang Liu, Zixuan Wang, Maocheng Wang, Shuwen Xiong, Quan Zou

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Single-cell TF-DNA binding prediction and analysis based on transfer learning framework.

Zixuan Wang, Yongqing Zhang, Yun Yu, Maocheng Wang, Yuhang Liu, Quan Zou

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.

Yongqing Zhang, Zixuan Wang, Yuanqi Zeng, Jiliu Zhou, Quan Zou

Briefings Bioinform., 2021

By hybrid neural networks for prediction and interpretation of transcription factor binding sites based on multi-omics.

Yongqing Zhang, Zixuan Wang, Yuhang Liu, Libo Lu, Xiaoyao Tan, Quan Zou

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021