PlantPTM: A deep-learning framework integrating protein language models with multi-view features for predicting diverse post-translational modification sites in plants
- DOI
- 10.1016/j.molp.2026.08.002
- Published
- 2026-08
- Container
- Molecular Plant
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.molp.2026.08.002,
title = {PlantPTM: A deep-learning framework integrating protein language models with multi-view features for predicting diverse post-translational modification sites in plants},
author = {Gensheng Dou and Kaiyuan Wang and Zhaohui Qin and Min Zhang and Wentian Zhang and Chunbo Miao and Junzhou Li and Zhen Chen},
year = {2026},
journal = {Molecular Plant},
doi = {10.1016/j.molp.2026.08.002},
url = {https://doi.org/10.1016/j.molp.2026.08.002}
}RIS
TY - JOUR TI - PlantPTM: A deep-learning framework integrating protein language models with multi-view features for predicting diverse post-translational modification sites in plants AU - Gensheng Dou AU - Kaiyuan Wang AU - Zhaohui Qin AU - Min Zhang AU - Wentian Zhang AU - Chunbo Miao AU - Junzhou Li AU - Zhen Chen PY - 2026 JO - Molecular Plant DO - 10.1016/j.molp.2026.08.002 UR - https://doi.org/10.1016/j.molp.2026.08.002 ER -
APA
Dou, G., Wang, K., Qin, Z., Zhang, M., Zhang, W., Miao, C., Li, J., & Chen, Z. (2026). PlantPTM: A deep-learning framework integrating protein language models with multi-view features for predicting diverse post-translational modification sites in plants. Molecular Plant. https://doi.org/10.1016/j.molp.2026.08.002
Source records
- crossref · retrieved 2026-09-25T15:36:15.914Z