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9,731 to 9,740 of 12,627 Results

New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Oct 22, 2018 - CIMMYT Research Data Montesinos-López, Osval A.; Martín-Vallejo, Javier; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Montesinos-López, Abelardo; Juliana, Philomin; Singh, Ravi, 2018, "New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes", https://hdl.handle.net/11529/10548140, CIMMYT Research Data & Software Repository Network, V1 The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.
Data_Set_1.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 4.3 MB - MD5: 231fdf85ad051b494deacd4886d55708
Data_Set_2.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 4.4 MB - MD5: 74cf012e823cf8ff5eff6a51f10d592c
Data_Set_3.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 6.8 MB - MD5: 4c158d81032c889c280f1918b5d1b16f
Data_Set_4.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 7.0 MB - MD5: bc2a4fce307e769e24b9f477e14592f6
Data_Set_5.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 6.8 MB - MD5: 0af143aab2914c4d065ef8ef9037632d
Data_Set_6.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 153.6 KB - MD5: d891bbd1db0577097ef9ce267581237f
Data_Set_7.RData.gz Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes Gzip Archive - 261.2 KB - MD5: f0396ede52b49e1a91090a95e299bc31
SUPPLEMENTARY MATERIAL.docx Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes MS Word - 358.9 KB - MD5: 6bfa2583115c2816b2945150fb882e77
Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices Oct 8, 2018 - CIMMYT Research Data Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", https://hdl.handle.net/11529/10548136, CIMMYT Research Data & Software Repository Network, V1 This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices.

New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Oct 22, 2018 - CIMMYT Research Data

Montesinos-López, Osval A.; Martín-Vallejo, Javier; Crossa, Jose; Gianola, Daniel; Hernández-Suarez, Carlos Moisés; Montesinos-López, Abelardo; Juliana, Philomin; Singh, Ravi, 2018, "New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes", https://hdl.handle.net/11529/10548140, CIMMYT Research Data & Software Repository Network, V1

The seven data sets are wheat data from CIMMYT Global Wheat Breeding program. They comprise different traits, like days to heading, days to maturity, grain yield, grain color, different type of leaf and stripe rust in wheat. Also the trials were run in different environments.

Data_Set_1.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 4.3 MB -

Data_Set_2.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 4.4 MB -

Data_Set_3.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 6.8 MB -

Data_Set_4.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 7.0 MB -

Data_Set_5.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 6.8 MB -

Data_Set_6.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 153.6 KB -

Data_Set_7.RData.gz

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

Gzip Archive - 261.2 KB -

SUPPLEMENTARY MATERIAL.docx

Oct 22, 2018 - New deep learning genomic prediction model for multi-traits with mixed binary, ordinal, and continuous phenotypes

MS Word - 358.9 KB -

Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices

Oct 8, 2018 - CIMMYT Research Data

Cerón-Rojas, J.Jesús; Toledo, Fernando; Crossa, Jose, 2018, "Supplemental Materials for The Relative Efficiency of Three Constrained Multistage Linear Phenotypic Selection Indices", https://hdl.handle.net/11529/10548136, CIMMYT Research Data & Software Repository Network, V1

This dataset provides supplemental information related to an investigation of constrained multistage linear phenotypic selection indices.

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