Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.

Xia H, Chen H, Wu Y, Zhang T, Zhang G, Zou J, Zhang Y

DOI: 10.1002/tpg2.70301
Published: 2026 Sep
Container: The plant genome
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1002/tpg2.70301,
  title = {Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.},
  author = {Xia H and Chen H and Wu Y and Zhang T and Zhang G and Zou J and Zhang Y},
  year = {2026},
  journal = {The plant genome},
  doi = {10.1002/tpg2.70301},
  url = {https://doi.org/10.1002/tpg2.70301}
}

RIS

TY  - JOUR
TI  - Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.
AU  - Xia H
AU  - Chen H
AU  - Wu Y
AU  - Zhang T
AU  - Zhang G
AU  - Zou J
AU  - Zhang Y
PY  - 2026
JO  - The plant genome
DO  - 10.1002/tpg2.70301
UR  - https://doi.org/10.1002/tpg2.70301
ER  -

APA

H, X., H, C., Y, W., T, Z., G, Z., J, Z., & Y, Z. (2026). Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.. The plant genome. https://doi.org/10.1002/tpg2.70301

Source records

pubmed · retrieved 2026-09-25T05:35:24.787Z