Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics
Type:
Title:
Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics
Creator:
Togninalli, M.;
Xu Wang;
Kucera, T.;
Shrestha, S.;
Juliana, P.;
Mondal, S.;
Pinto Espinosa, F.;
Velu, G.;
Crespo-Herrera, L.A.;
Huerta-Espino, J.;
https://orcid.org/0000-0001-8334-9862
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Researcher ID
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Singh, R.P.;
Borgwardt, K.;
Poland, J.A.
Xu Wang;
Kucera, T.;
Shrestha, S.;
Juliana, P.;
Mondal, S.;
Pinto Espinosa, F.;
Velu, G.;
Crespo-Herrera, L.A.;
Huerta-Espino, J.;
Huerta-Espino, J.
https://orcid.org/0000-0001-8334-9862
Scopus ID
Researcher ID
Items in this Repository
View
Singh, R.P.;
Borgwardt, K.;
Poland, J.A.
Year:
2023
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:
Bioinformatics
Journal volume:
39
Journal issue:
6
Article number:
btad336
Place of Publication:
Oxford (United Kingdom)
Publisher:
Oxford University Press
