Phenotype values for genotypes estimated by genomic prediction.
收藏NIAID Data Ecosystem2026-03-13 收录
数据链接：
官方服务：
资源简介：
(XLSX)
应用场景：
创建时间：
2021-11-05
相关数据集
Additional file 4 of Genomic prediction models for traits differing in heritability for soybean, rice, and maize
Additional file 4. Zip file containing R scripts used in this study.
DataCite Commons2022-02-27 更新90
Supplemental Material for Baker et al., 2020
These files are the genotyping datasets that were used to perform the analyses in Baker et al. 2020. The filesets represent individuals that were recruited from University of Wisconsin-Madison and fro
NIAID Data Ecosystem30
Table_1_Integrating Gene Expression Data Into Genomic Prediction.pdf
Gene expression profiles potentially hold valuable information for the prediction of breeding values and phenotypes. In this study, the utility of transcriptome data for phenotype prediction was teste
NIAID Data Ecosystem10
Additional file 2 of Genomic prediction using machine learning: a comparison of the performance of regularized regression, ensemble, instance-based and deep learning methods on synthetic and empirical data
Additional file 2. R codes used to fit the ML algorithms to the simulated (animal breeding) dataset. Includes six R files: one for the simple regularized methods, one for the adaptive regularized meth
DataCite Commons2024-08-18 更新60
Table_4_Detecting the QTL-Allele System of Seed Oil Traits Using Multi-Locus Genome-Wide Association Analysis for Population Characterization and Optimal Cross Prediction in Soybean.XLSX
Soybean is one of the world's major vegetative oil sources, while oleic acid and linolenic acid content are the major quality traits of soybean oil. The restricted two-stage multi-locus genome-wide as
NIAID Data Ecosystem30
