CoxFormer enables spatial omics inference with multimodal generative modeling

Yiyang Yang, Xu Liao, Haoyu Zhang, Yida Wu, Yuling Jiao, Xiaobo Sun, Yao Wang, Tianshu Yu, Jin Liu

Open source

DOI
10.1038/s41467-026-76404-8
Published
2026-08-20
Container
Nature Communications
Publisher
Springer Science and Business Media LLC
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1038/s41467-026-76404-8,
  title = {CoxFormer enables spatial omics inference with multimodal generative modeling},
  author = {Yiyang Yang and Xu Liao and Haoyu Zhang and Yida Wu and Yuling Jiao and Xiaobo Sun and Yao Wang and Tianshu Yu and Jin Liu},
  year = {2026},
  journal = {Nature Communications},
  doi = {10.1038/s41467-026-76404-8},
  url = {https://doi.org/10.1038/s41467-026-76404-8}
}

RIS

TY  - JOUR
TI  - CoxFormer enables spatial omics inference with multimodal generative modeling
AU  - Yiyang Yang
AU  - Xu Liao
AU  - Haoyu Zhang
AU  - Yida Wu
AU  - Yuling Jiao
AU  - Xiaobo Sun
AU  - Yao Wang
AU  - Tianshu Yu
AU  - Jin Liu
PY  - 2026
JO  - Nature Communications
DO  - 10.1038/s41467-026-76404-8
UR  - https://doi.org/10.1038/s41467-026-76404-8
ER  - 

APA

Yang, Y., Liao, X., Zhang, H., Wu, Y., Jiao, Y., Sun, X., Wang, Y., Yu, T., & Liu, J. (2026). CoxFormer enables spatial omics inference with multimodal generative modeling. Nature Communications. https://doi.org/10.1038/s41467-026-76404-8

Source records