GS-Impute: A neural network framework for accurate imputation of low-density markers in across-population genomic selection.
- DOI
- 10.1016/j.xplc.2026.101821
- Published
- 2026 May 11
- Container
- Plant communications
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.xplc.2026.101821,
title = {GS-Impute: A neural network framework for accurate imputation of low-density markers in across-population genomic selection.},
author = {Wang X and Jiang Z and Ding T and Cao Y and Zhou K and Yu G and Li P and Yang Z and Zhang X and Xu S and Xu Y and Xu C},
year = {2026},
journal = {Plant communications},
doi = {10.1016/j.xplc.2026.101821},
url = {https://doi.org/10.1016/j.xplc.2026.101821}
}RIS
TY - JOUR TI - GS-Impute: A neural network framework for accurate imputation of low-density markers in across-population genomic selection. AU - Wang X AU - Jiang Z AU - Ding T AU - Cao Y AU - Zhou K AU - Yu G AU - Li P AU - Yang Z AU - Zhang X AU - Xu S AU - Xu Y AU - Xu C PY - 2026 JO - Plant communications DO - 10.1016/j.xplc.2026.101821 UR - https://doi.org/10.1016/j.xplc.2026.101821 ER -
APA
X, W., Z, J., T, D., Y, C., K, Z., G, Y., P, L., Z, Y., X, Z., S, X., Y, X., & C, X. (2026). GS-Impute: A neural network framework for accurate imputation of low-density markers in across-population genomic selection.. Plant communications. https://doi.org/10.1016/j.xplc.2026.101821
Source records
- pubmed · retrieved 2026-09-26T03:24:30.943Z