Machine learning-guided multi-omics suggests iron-dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress.
- DOI
- 10.1111/nph.71336
- Published
- 2026 Aug
- Container
- The New phytologist
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1111/nph.71336,
title = {Machine learning-guided multi-omics suggests iron-dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress.},
author = {Shen W and Ren Q and Chen X and Dai Y and Zhang Y and Xiong F},
year = {2026},
journal = {The New phytologist},
doi = {10.1111/nph.71336},
url = {https://doi.org/10.1111/nph.71336}
}RIS
TY - JOUR TI - Machine learning-guided multi-omics suggests iron-dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress. AU - Shen W AU - Ren Q AU - Chen X AU - Dai Y AU - Zhang Y AU - Xiong F PY - 2026 JO - The New phytologist DO - 10.1111/nph.71336 UR - https://doi.org/10.1111/nph.71336 ER -
APA
W, S., Q, R., X, C., Y, D., Y, Z., & F, X. (2026). Machine learning-guided multi-omics suggests iron-dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress.. The New phytologist. https://doi.org/10.1111/nph.71336
Source records
- pubmed · retrieved 2026-09-25T07:13:52.085Z