Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
about
Construction of a High-Density American Cranberry (Vaccinium macrocarpon Ait.) Composite Map Using Genotyping-by-Sequencing for Multi-pedigree Linkage Mapping.Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.Social and spatial effects on genetic variation between foraging flocks in a wild bird population.Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel.Prediction of genomic breeding values using new computing strategies for the implementation of MixP.Improving the baking quality of bread wheat by genomic selection in early generations.Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.Genome-wide regression models considering general and specific combining ability predict hybrid performance in oilseed rape with similar accuracy regardless of trait architecture.Genome-Wide Association Analyses Identify QTL Hotspots for Yield and Component Traits in Durum Wheat Grown under Yield Potential, Drought, and Heat Stress Environments.Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato.Image-based phenotyping for identification of QTL determining fruit shape and size in American cranberry ( L.)Impact of residual covariance structures on genomic prediction ability in multi-environment trialsA fully automated pipeline for quantitative genotype calling from next generation sequencing data in autopolyploidsMultivariate GBLUP Improves Accuracy of Genomic Selection for Yield and Fruit Weight in Biparental Populations of Ait
P2860
Q37746451-4B8404AE-592F-4D30-AB5C-846F9510C737Q38841284-03D6BCC8-241D-4DA9-9559-92201683074DQ46323529-C68638CF-BD8D-45B4-BF52-FC83120BB6C6Q46910878-F9D178E8-6555-4D7F-97BC-F7095E0D7E89Q47151766-932F5FB5-B2C5-431B-B9B9-61BD9F1959DEQ47612348-0B4C1CF5-B4BC-4213-BD53-9D90E3246D69Q47682420-9D6D774E-8353-421C-80DD-61D9B891FA36Q49832477-6ED466C0-DF5A-4134-B103-37D097A0F0ABQ50101657-D16DE49B-3D8C-4D23-8E6B-2261C9922A08Q50328154-7ADA5BA4-E7FA-4783-83E5-D17FD3B8286CQ52347062-812D91E1-24BA-4988-A44A-18EE92F9F29AQ57169321-AB10641E-6D80-405D-96C9-57A6D0EB5D33Q57922568-086E828E-7584-4B3E-8050-779DD0622779Q58078773-0A600C8F-7D17-455D-B91E-8FB9D7D60C50Q58746257-4FB527AB-0622-4EE0-84F7-DA7B41990A22
P2860
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@ast
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@en
type
label
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@ast
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@en
prefLabel
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@ast
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@en
P2860
P1433
P1476
Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.
@en
P2860
P304
P356
10.1371/JOURNAL.PONE.0156744
P407
P577
2016-06-06T00:00:00Z