scDEBGCL: a deep embedding approach based on bipartite graph contrastive learning for single-cell RNA-seq data.

Wang J, Ke D, Xia J, Liu A, Su Y, Zheng CH

DOI: 10.1186/s12915-026-02598-4
Published: 2026 Apr 14
Container: BMC biology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s12915-026-02598-4,
  title = {scDEBGCL: a deep embedding approach based on bipartite graph contrastive learning for single-cell RNA-seq data.},
  author = {Wang J and Ke D and Xia J and Liu A and Su Y and Zheng CH},
  year = {2026},
  journal = {BMC biology},
  doi = {10.1186/s12915-026-02598-4},
  url = {https://doi.org/10.1186/s12915-026-02598-4}
}

RIS

TY  - JOUR
TI  - scDEBGCL: a deep embedding approach based on bipartite graph contrastive learning for single-cell RNA-seq data.
AU  - Wang J
AU  - Ke D
AU  - Xia J
AU  - Liu A
AU  - Su Y
AU  - Zheng CH
PY  - 2026
JO  - BMC biology
DO  - 10.1186/s12915-026-02598-4
UR  - https://doi.org/10.1186/s12915-026-02598-4
ER  -

APA

J, W., D, K., J, X., A, L., Y, S., & CH, Z. (2026). scDEBGCL: a deep embedding approach based on bipartite graph contrastive learning for single-cell RNA-seq data.. BMC biology. https://doi.org/10.1186/s12915-026-02598-4

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pubmed · retrieved 2026-09-26T12:09:10.791Z