A new deep learning calibration method enhances genome-based prediction of continuous crop traits
Type:
Title:
A new deep learning calibration method enhances genome-based prediction of continuous crop traits
Creator:
Montesinos-Lopez, O.A.;
https://orcid.org/0000-0002-3973-6547
Scopus ID
Items in this Repository
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Montesinos-Lopez, A.;
Mosqueda-Gonzalez, B.A.;
Bentley, A.R.;
Lillemo, M.;
Varshney, R.K.;
Crossa, J.
Montesinos-Lopez, O.A.
https://orcid.org/0000-0002-3973-6547
Scopus ID
Items in this Repository
View
Montesinos-Lopez, A.;
Mosqueda-Gonzalez, B.A.;
Bentley, A.R.;
Lillemo, M.;
Varshney, R.K.;
Crossa, J.
Year:
2021
Copyright:
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Journal:
Frontiers in Genetics
Journal volume:
12
Article number:
798840
Place of Publication:
Switzerland
Publisher:
Frontiers
