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Peer-reviewedLicence not statedNature Genetics

Leveraging genomic deep learning models for the prediction of noncoding variant effects

  • Pooja Kathail1
  • Ayesha Bajwa2
  • Nilah M. Ioannidis3,4,5,6
6 affiliations
  1. 1Center for Computational Biology, University of California Berkeley, Berkeley, CA, USA
  2. 2Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA, USA
  3. 3Biohub, San Francisco, CA, USA. [email protected]
  4. 4Center for Computational Biology, University of California Berkeley, Berkeley, CA, USA. [email protected]
  5. 5Department of Applied Mathematics, University of California Santa Cruz, Santa Cruz, CA, USA. [email protected]
  6. 6Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, CA, USA. [email protected]
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Cite

BibTeXRIS
BibTeX
@article{kathail2026leveraging,
  title = {{Leveraging genomic deep learning models for the prediction of noncoding variant effects}},
  author = {Pooja Kathail and Ayesha Bajwa and Nilah M. Ioannidis},
  journal = {Nature Genetics},
  year = {2026},
  month = oct,
  doi = {10.1038/s41588-026-02769-7},
  url = {https://arxiv.org/abs/2411.11158},
}
RIS
TY  - JOUR
TI  - Leveraging genomic deep learning models for the prediction of noncoding variant effects
AU  - Pooja Kathail
AU  - Ayesha Bajwa
AU  - Nilah M. Ioannidis
PY  - 2026
DA  - 2026/10/21
JO  - Nature Genetics
DO  - 10.1038/s41588-026-02769-7
UR  - https://arxiv.org/abs/2411.11158
SN  - 1061-4036
SN  - 1546-1718
ER  -