数据链接：
官方服务：
资源简介：
SNPs, pedigree, phenotypes and breeding values simulated with AlphaSim
应用场景：
创建时间：
2017-06-24
相关数据集
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
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 RhoTermPredict: an algorithm for predicting Rho-dependent transcription terminators based on Escherichia coli, Bacillus subtilis and Salmonella enterica databases
Informations about whole genome predictions by RhoTermPredict from E. coli K-12. (TXT 20868 kb)
DataCite Commons2020-08-27 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
