Benchmarking deep learning methods for biologically conserved single-cell integration.

Yi C, Cheng J, Chen J, Liu W, Liu J, Li Y

Open source

DOI: 10.1186/s13059-025-03869-z
Published: 2025 Nov 20
Container: Genome biology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s13059-025-03869-z,
  title = {Benchmarking deep learning methods for biologically conserved single-cell integration.},
  author = {Yi C and Cheng J and Chen J and Liu W and Liu J and Li Y},
  year = {2025},
  journal = {Genome biology},
  doi = {10.1186/s13059-025-03869-z},
  url = {https://doi.org/10.1186/s13059-025-03869-z}
}

RIS

TY  - JOUR
TI  - Benchmarking deep learning methods for biologically conserved single-cell integration.
AU  - Yi C
AU  - Cheng J
AU  - Chen J
AU  - Liu W
AU  - Liu J
AU  - Li Y
PY  - 2025
JO  - Genome biology
DO  - 10.1186/s13059-025-03869-z
UR  - https://doi.org/10.1186/s13059-025-03869-z
ER  -

APA

C, Y., J, C., J, C., W, L., J, L., & Y, L. (2025). Benchmarking deep learning methods for biologically conserved single-cell integration.. Genome biology. https://doi.org/10.1186/s13059-025-03869-z

Source records

pubmed · retrieved 2026-09-26T11:30:22.305Z
europe-pmc · retrieved 2026-09-26T11:30:22.302Z
doaj · retrieved 2026-09-26T11:30:22.282Z