Peer-reviewedCC BY-NC-ND 4.0BMC Genomics
scDAEC: deep clustering of single-cell data based on dual autoencoder
Related
- Attention-based hierarchical graph autoencoder for dose-specific single-cell resistance dynamics
- Resolving Heterogeneous Mechanical Domains via Physics-Aware Deep Clustering of Single-Molecule Force Spectroscopy Data
- scLTF: A self-training clustering framework for large-scale single-cell RNA-Seq data
- Patient classification using single-cell RNA-sequencing data with deep learning convolutional neural networks
- Deep learning-based analysis reveals patient-level cancer therapy trajectories using single-cell PBMC chromatin images
BibTeX
@article{zhu2026scdaec,
title = {{scDAEC: deep clustering of single-cell data based on dual autoencoder}},
author = {Yue Zhu and Chen Chen and Yue Liu and Yanlei Kang and Hancan Zhu and Zhong Li},
journal = {BMC Genomics},
year = {2026},
month = oct,
doi = {10.1186/s12864-026-13261-1},
url = {https://link.springer.com/article/10.1186/s12864-026-13261-1},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - scDAEC: deep clustering of single-cell data based on dual autoencoder
AU - Yue Zhu
AU - Chen Chen
AU - Yue Liu
AU - Yanlei Kang
AU - Hancan Zhu
AU - Zhong Li
PY - 2026
DA - 2026/10/17
JO - BMC Genomics
DO - 10.1186/s12864-026-13261-1
UR - https://link.springer.com/article/10.1186/s12864-026-13261-1
SN - 1471-2164
ER -