Cell Decoder: decoding cell identity with multi-scale explainable deep learning
Applied to human bone and mouse embryonic data, Cell Decoder reveals the multi-scale heterogeneity of cell identities, providing a powerful framework for advancing our understanding of cellular diversity.
Authors
- Linhai Xie (ORCID: https://orcid.org/0000-0001-8593-2277)
- Yujia Xiang (ORCID: https://orcid.org/0000-0002-5070-6816)
- Li Yang (ORCID: https://orcid.org/0000-0001-8771-7044)
- Xinwen Dong (ORCID: https://orcid.org/0009-0006-3703-0694)
- Beini Xie (ORCID: https://orcid.org/0000-0003-2180-6321)
- Cheng Chang (ORCID: https://orcid.org/0000-0002-0361-2438)
- Xiaowen Wang (ORCID: https://orcid.org/0009-0004-0801-8982)
- Jun Zhu (ORCID: https://orcid.org/0000-0003-0834-8178)
- Peijie Zhou (ORCID: https://orcid.org/0000-0002-4585-2923)
- Zeyang Zhang (ORCID: https://orcid.org/0000-0003-1329-1313)
- Wenwu Zhu (ORCID: https://orcid.org/0000-0003-2236-9290)
- Ziwei Zhang (ORCID: https://orcid.org/0000-0003-2451-843X)
- Fuchu He (ORCID: https://orcid.org/0000-0002-1094-4019)
- Rongyan Yao (ORCID: https://orcid.org/0009-0001-5871-866X)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking University (CN)
- Guangzhou Experimental Station (CN)
- Tsinghua–Berkeley Shenzhen Institute (CN)
- Beijing Proteome Research Center (CN)
- Center for Life Sciences (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Genome biology
- Published
- 2025-10-20
- DOI
- https://doi.org/10.1186/s13059-025-03832-y
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Tsinghua University
- National Key Research and Development Program of China