MutFormer: a multimodal deep learning framework for predicting somatic mutation hotspots from sequence and chromatin features
- DOI
- 10.1186/s12864-026-13246-0
- Published
- 2026-08-11
- Container
- BMC Genomics
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12864-026-13246-0,
title = {MutFormer: a multimodal deep learning framework for predicting somatic mutation hotspots from sequence and chromatin features},
author = {Tianbao Li and Yan Jiang and Junjie Wu and Junru Lin and Reisa Widjaja and Ailan Wang and Qi Liu and Hongbo Zhou},
year = {2026},
journal = {BMC Genomics},
doi = {10.1186/s12864-026-13246-0},
url = {https://doi.org/10.1186/s12864-026-13246-0}
}RIS
TY - JOUR TI - MutFormer: a multimodal deep learning framework for predicting somatic mutation hotspots from sequence and chromatin features AU - Tianbao Li AU - Yan Jiang AU - Junjie Wu AU - Junru Lin AU - Reisa Widjaja AU - Ailan Wang AU - Qi Liu AU - Hongbo Zhou PY - 2026 JO - BMC Genomics DO - 10.1186/s12864-026-13246-0 UR - https://doi.org/10.1186/s12864-026-13246-0 ER -
APA
Li, T., Jiang, Y., Wu, J., Lin, J., Widjaja, R., Wang, A., Liu, Q., & Zhou, H. (2026). MutFormer: a multimodal deep learning framework for predicting somatic mutation hotspots from sequence and chromatin features. BMC Genomics. https://doi.org/10.1186/s12864-026-13246-0
Source records
- crossref · retrieved 2026-11-07T04:20:24.750Z