PepOSX-AI: CPP - an interpretable transformer-based deep learning model for prediction of cell-penetrating peptides.
- DOI
- 10.1016/j.aca.2026.345991
- Published
- 2026 Oct 8
- Container
- Analytica chimica acta
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.aca.2026.345991,
title = {PepOSX-AI: CPP - an interpretable transformer-based deep learning model for prediction of cell-penetrating peptides.},
author = {Chen H and He W and Feng K and Xu R and Yin S and Zheng L and Chen J and Zhao M and Xu J and You L},
year = {2026},
journal = {Analytica chimica acta},
doi = {10.1016/j.aca.2026.345991},
url = {https://doi.org/10.1016/j.aca.2026.345991}
}RIS
TY - JOUR TI - PepOSX-AI: CPP - an interpretable transformer-based deep learning model for prediction of cell-penetrating peptides. AU - Chen H AU - He W AU - Feng K AU - Xu R AU - Yin S AU - Zheng L AU - Chen J AU - Zhao M AU - Xu J AU - You L PY - 2026 JO - Analytica chimica acta DO - 10.1016/j.aca.2026.345991 UR - https://doi.org/10.1016/j.aca.2026.345991 ER -
APA
H, C., W, H., K, F., R, X., S, Y., L, Z., J, C., M, Z., J, X., & L, Y. (2026). PepOSX-AI: CPP - an interpretable transformer-based deep learning model for prediction of cell-penetrating peptides.. Analytica chimica acta. https://doi.org/10.1016/j.aca.2026.345991
Source records
- pubmed · retrieved 2026-09-27T12:46:38.879Z