Titlebook: Genomic Prediction of Complex Traits; Methods and Protocol Nourollah Ahmadi,Jérôme Bartholomé Book 2022 The Editor(s) (if applicable) and T

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Development of the Social Value Stock,er, we focused on and reviewed the genomic prediction methods that incorporate external biological information into genomic prediction, such as sequence ontology, linkage disequilibrium (LD) of SNPs, quantitative trait loci (QTL), and multi-layer omics data (e.g., transcriptome, epigenome, and microbiome).

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Genome-Enabled Prediction Methods Based on Machine Learning,ctive qualities. It was found that some kernel, Bayesian, and ensemble methods displayed greater robustness and predictive ability. However, the type of study and data distribution must be considered in order to choose the most appropriate model for a given problem.

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1064-3745 ation advice from the experts.This volume explores the conceptual framework and the practical issues related to genomic prediction of complex traits in human medicine and in animal and plant breeding. The book is organized into five parts. Part One reminds molecular genetics approaches intending to

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Medical and Surgical Treatment of BPPV computer packages has exploded in recent years given the interest in this technology. In this chapter, we explore the main computer packages available to fit these models; we also review the special features, strengths, and weaknesses of the methods behind the most popular computer packages.

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