Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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im Januar 2018 veröffentlichter wissenschaftlicher Artikel

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wetenschappelijk artikel

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наукова стаття, опублікована у 2018

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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P1476

Genomic Prediction of Complex Phenotypes Using Genic Similarity Based Relatedness Matrix

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P2093

Hao Zhang

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Jiaqi Li

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Jinyan Teng

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Ning Gao

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Shaopan Ye

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Shuwen Huang

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Xiaolong Yuan

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Xiquan Zhang

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Zhe Zhang

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P2860

Prediction of total genetic value using genome-wide dense marker maps

BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis.

Developmental progress and current status of the Animal QTLdb.

Extension of the bayesian alphabet for genomic selection.

Best linear unbiased estimation and prediction under a selection model.

Best linear unbiased prediction of genomic breeding values using a trait-specific marker-derived relationship matrix

Using whole-genome sequence data to predict quantitative trait phenotypes in Drosophila melanogaster.

Association mapping of local climate-sensitive quantitative trait loci in Arabidopsis thaliana.

On the distance of genetic relationships and the accuracy of genomic prediction in pig breeding.

Genomic evaluations using similarity between haplotypes.

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364

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P31

scholarly article

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10.3389/FGENE.2018.00364

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English

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P577

2018-01-01T00:00:00Z

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P698

30233646

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P921

molecular medicine

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6127733

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