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Prediction of Complex Traits Using Genomic Data

Gustavo De Los Campos, Daniel Gianola (Autoren)

Buch | Hardcover

350 Seiten

2026
Chapman & Hall/CRC (Verlag)
978-1-4822-5374-0 (ISBN)

Noch nicht erschienen (ca. Januar 2026)
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This book explains and demonstrates with real and simulated examples how whole-genome information can be used for predicting complex traits, with applications in animal, human, and plant genetics. After giving a brief introduction, the book covers linear models and dimensionality, plus regularized regressions. It then progresses to the genomic best linear unbiased predictor, the Bayesian alphabet, reproducing Kernel Hiblert spaces regressions, penalized neural networks, and re-sampling methods. Lastly, it covers whole genome regression and population stratification.

Introduction. A Brief History of Quantitative Genetics. Complex Traits, Interactions, and Challenges to Prediction. Linear Models and the Curse of Dimensionality. Regularized Regressions. The Genomic Best Linear Unbiased Predictor. The Bayesian Alphabet. Reproducing Kernel Hiblert Spaces Regressions. Penalized Neural Networks. Re-sampling Methods. Whole Genome Regression and Population Stratification. Appendices.

Erscheinungsdatum	01.01.2020
Reihe/Serie	Chapman & Hall/CRC Biostatistics Series
Zusatzinfo	20 Illustrations, black and white
Sprache	englisch
Maße	156 x 234 mm
Themenwelt	Mathematik / Informatik ► Mathematik
	Medizin / Pharmazie ► Allgemeines / Lexika
	Studium ► 2. Studienabschnitt (Klinik) ► Humangenetik
	Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
ISBN-10	1-4822-5374-7 / 1482253747
ISBN-13	978-1-4822-5374-0 / 9781482253740
Zustand	Neuware