ComicGTN infers disease-associated rare cell states from single-cell multiomic data using DNA sequence-augmented graph transformer networks.

Yang B, Hua J, Zhou G, Feng Y, Qi J, Guo Y, Sheng D, Jin S

Open source

DOI
10.1101/gr.281661.125
Published
2026 Aug 3
Container
Genome research
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1101/gr.281661.125,
  title = {ComicGTN infers disease-associated rare cell states from single-cell multiomic data using DNA sequence-augmented graph transformer networks.},
  author = {Yang B and Hua J and Zhou G and Feng Y and Qi J and Guo Y and Sheng D and Jin S},
  year = {2026},
  journal = {Genome research},
  doi = {10.1101/gr.281661.125},
  url = {https://doi.org/10.1101/gr.281661.125}
}

RIS

TY  - JOUR
TI  - ComicGTN infers disease-associated rare cell states from single-cell multiomic data using DNA sequence-augmented graph transformer networks.
AU  - Yang B
AU  - Hua J
AU  - Zhou G
AU  - Feng Y
AU  - Qi J
AU  - Guo Y
AU  - Sheng D
AU  - Jin S
PY  - 2026
JO  - Genome research
DO  - 10.1101/gr.281661.125
UR  - https://doi.org/10.1101/gr.281661.125
ER  - 

APA

B, Y., J, H., G, Z., Y, F., J, Q., Y, G., D, S., & S, J. (2026). ComicGTN infers disease-associated rare cell states from single-cell multiomic data using DNA sequence-augmented graph transformer networks.. Genome research. https://doi.org/10.1101/gr.281661.125

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