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008			220422s2022 xxua o |||| 0|eng d
020			_a9781071622056
024	7		_a10.1007/978-1-0716-2205-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQH447 _b2022 EB
245	0	0	_aGenomic Prediction of Complex Traits : _bMethods and Protocols _cedited by Nourollah Ahmadi, Jérôme Bartholomé
250			_a1st edition 2022
264		1	_aNew York, NY _bSpringer International Publising _c2022
300			_a1 recurso en línea (XI, 648 páginas) _b73 ilustraciones, 63 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v2467
505	0		_aGenetic Bases of Complex Traits: From Quantitative Trait Loci to Predictions -- Genomic Prediction of Complex Traits, Principles, Overview of Factors Affecting the Reliability of Genomic Prediction, and Algebra of the Reliability -- Building a Calibration Set for Genomic Prediction, Characteristics to be Considered and Optimization Approaches -- Genotyping, the Usefulness of Imputation to Increase SNP Density, Imputation Methods and Tools -- Overview of Genomic Prediction Methods and the Associated Assumptions on the Variance of Marker Effect, and on the Architecture of the Target Trait -- Overview of Major Computer Packages for Genomic Prediction of Complex Traits -- Genome-Enabled Prediction Methods Based on Machine Learning -- Genomic Prediction Methods Accounting for Non-Additive Genetic Effects -- Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction -- Accounting for Correlation between Traits in Genomic Prediction -- Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models -- Incorporating Omics Data in Genomic Prediction -- Integration of Crop Growth Models and Genomic Prediction -- Phenomic Selection: A New and Efficient Alternative to Genomic Selection -- From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits -- Genomic Prediction of Complex Traits in Animal Breeding with Long Breeding History, The Dairy Cattle Case -- Genomic Selection in Aquaculture Species -- Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees -- Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case -- Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids -- Genomic Prediction: Progress and Perspective for Rice Improvement -- Analyzing the Economic Effectiveness of Genomic Selection Relative to Conventional Breeding Approaches.
520			_aThis 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 predict phenotypic variations. Part Two presents the principles of genomic prediction of complex traits, and reviews factors that affect its reliability. Part Three describes genomic prediction methods, including machine-learning approaches, accounting for different degree of biological complexity, and reviews the associated computer-packages. Part Four reports on emerging trends such as phenomic prediction and incorporation into genomic prediction models of "omics" data and crop growth models. Part Five is dedicated to lessons learned from cases studies in the fields of human health and animal and plant breeding, and to methods for analysis of the economic effectiveness of genomic prediction. Written in the highly successful Methods in Molecular Biology series format, the book provides theoretical bases and practical guidelines for an informed decision making of practitioners and identifies pertinent routes for further methodological researches. Cutting-edge and thorough, Complex Trait Predictions: Methods and Protocols is a valuable resource for scientists and researchers who are interested in learning more about this important and developing field. Chapters 3, 9, 13, 14, and 21 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. .
988			_aSpringer_Protocols_2022
650		7	_2embne _9162605 _aGenomas
776	0	8	_iPrinted edition: _z9781071622049
776	0	8	_iPrinted edition: _z9781071622063
776	0	8	_iPrinted edition: _z9781071622070
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-2205-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2023 _dz _eb _zSI