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7,171 to 7,180 of 13,456 Results
Replication Data for: Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints
Nov 14, 2020 - CIMMYT Research Data
Sansaloni, Carolina; Franco, Jorge; Santos, Bruno; Percival-Alwyn, Lawrence; Singh, Sukhwinder; Petroli, Cesar; Campos, Jaime; Dreher, Kate; Payne, Thomas; Marshall, David; Kilian, Benjamin; Milne, Iain; Raubach, Sebastian; Shaw, Paul; Stephen, Gordon; Carling, Jason; Saint Pierre, Carolina; Burgueño, Juan; Crossa, Jose; Li, Huihui; Guzman, Carlos; Kilian, Andrzej; Wenzl, Peter; Amri, Ahmed; Uauy, Cristobal; Banziger, Marianne; Caccamo, Mario; Pixley, Kevin, 2020, "Replication Data for: Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints", https://hdl.handle.net/11529/10548030, CIMMYT Research Data & Software Repository Network, V2
A diverse panel of domesticated hexaploid and tetraploid wheat lines and their tetraploid and diploid wild relatives were genotyped using the DArtSeq technology and characterized in a global wheat diversity analysis.
wheat_request_fastq_file_access_agreement.txt
Nov 14, 2020 - Replication Data for: Diversity analysis of 80,000 wheat accessions reveals consequences and opportunities of selection footprints
Plain Text - 700 B - MD5: 5288308dd1ddf20fc990d3aa0466bd56
To request access to fastq data files linked to this dataset, please download this file and follow the instructions it includes
CIMMYT Maize Genetic Resource Lines
CIMMYT Maize Genetic Resource Lines
Nov 13, 2020 - CIMMYT Research Data
Molnar, Terence; Carvalho Andrade, Marcela; Chanona, Enrique Rodriguez; Chepetla Calderon, Daniel; Burgueño, Juan; Crossa, Jose, 2020, "CIMMYT Maize Genetic Resource Lines", https://hdl.handle.net/11529/10548528, CIMMYT Research Data & Software Repository Network, V2
CIMMYT makes available to the public a set of maize inbred lines called CIMMYT Maize Genetic Resource Lines (CMGRL). The CMGRLs are derived from crosses between elite CIMMYT lines and landrace accessions, populations or synthetics from the CIMMYT Germplasm Bank. CMGRLs are intend...
CMGRL Release-1 2.Data for TSC Lines.pdf
CMGRL Release-1 2.Data for TSC Lines.pdf
Nov 13, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 442.3 KB - MD5: b211f5dd29d9fde52173490d996cd653
CMGRL Release-1 1.Line Information.pdf
CMGRL Release-1 1.Line Information.pdf
Oct 27, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 409.8 KB - MD5: f1f3d821a23690cdcc7f6a8a8f79e0f7
CMGRL Release-1 3.Data for Drought Lines.pdf
CMGRL Release-1 3.Data for Drought Lines.pdf
Oct 27, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 439.6 KB - MD5: 86f24b95892517d1f8776b5a2e1da723
CMGRL Release-1 4.Collaborator Acknowledgements.pdf
CMGRL Release-1 4.Collaborator Acknowledgements.pdf
Oct 27, 2020 - CIMMYT Maize Genetic Resource Lines
Adobe PDF - 48.7 KB - MD5: 32964fa6f7603408a220f9f09f4dff33
Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction
Oct 24, 2020 - CIMMYT Research Data
Montesinos-López, Abelardo; Montesinos-López, Osval A.; Montesinos-López, José Cricelio; Flores-Cortes, Carlos Alberto; de la Rosa, Roberto; Crossa, Jose, 2020, "Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction", https://hdl.handle.net/11529/10548532, CIMMYT Research Data & Software Repository Network, V1
The data contained in these datasets can be used to implement Bayesian generalized kernel regression methods for genome-enabled prediction in the statistical software R, The accompanying paper describes the building process of 7 kernel methods (linear, polynomial, sigmoid, Gaussi...
Data_Toy_EYT.RData.gz
Oct 24, 2020 - Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction
Gzip Archive - 10.0 KB - MD5: 3976d1f35394e734911a7a8ad9c4ea5e
Data_Wheat_2019.RData.gz
Oct 24, 2020 - Replication Data for: A guide for generalized kernel regression methods for genomic-enabled prediction
Gzip Archive - 305.5 KB - MD5: 43c83cc75a677aec136d1aa79b1b5f17
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