Sequence-based chromatin activity modeling and regulatory impact prediction of genetic variants in farmed animals using deep learning.
- DOI
- 10.1093/nargab/lqaf139
- Published
- 2025 Dec
- Container
- NAR genomics and bioinformatics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1093/nargab/lqaf139,
title = {Sequence-based chromatin activity modeling and regulatory impact prediction of genetic variants in farmed animals using deep learning.},
author = {Nguyen DT and Knutsen TM and Sandve SR and Lien S and Grønvold L},
year = {2025},
journal = {NAR genomics and bioinformatics},
doi = {10.1093/nargab/lqaf139},
url = {https://doi.org/10.1093/nargab/lqaf139}
}RIS
TY - JOUR TI - Sequence-based chromatin activity modeling and regulatory impact prediction of genetic variants in farmed animals using deep learning. AU - Nguyen DT AU - Knutsen TM AU - Sandve SR AU - Lien S AU - Grønvold L PY - 2025 JO - NAR genomics and bioinformatics DO - 10.1093/nargab/lqaf139 UR - https://doi.org/10.1093/nargab/lqaf139 ER -
APA
DT, N., TM, K., SR, S., S, L., & L, G. (2025). Sequence-based chromatin activity modeling and regulatory impact prediction of genetic variants in farmed animals using deep learning.. NAR genomics and bioinformatics. https://doi.org/10.1093/nargab/lqaf139
Source records
- pubmed · retrieved 2026-09-26T12:52:21.574Z