ComicGTN infers disease-associated rare cell states from single-cell multiomic data using DNA sequence-augmented graph transformer networks.
- DOI
- 10.1101/gr.281661.125
- Published
- 2026 Aug 3
- Container
- Genome research
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
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
Source records
- pubmed · retrieved 2026-09-25T10:46:03.404Z