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Kategorie szczegółowe BISAC

Genes, Environments and Interactions: Evolutionary and Quantitative Genetics Brought Up-To-Date

ISBN-13: 9783031411588 / Angielski

José M. Álvarez-Castro
Genes, Environments and Interactions: Evolutionary and Quantitative Genetics Brought Up-To-Date Jos? M. ?lvarez-Castro 9783031411588 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Genes, Environments and Interactions: Evolutionary and Quantitative Genetics Brought Up-To-Date

ISBN-13: 9783031411588 / Angielski

José M. Álvarez-Castro
cena 651,63
(netto: 620,60 VAT:  5%)

Najniższa cena z 30 dni: 578,30
Termin realizacji zamówienia:
ok. 16-18 dni roboczych.

Darmowa dostawa!
Kategorie:
Nauka, Biologia i przyroda
Kategorie BISAC:
Science > Life Sciences - Evolution
Science > Life Sciences - Genetics & Genomics
Mathematics > Matematyka stosowana
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9783031411588

See Attachments 

José M Álvarez-Castro is a mathematician and biologist by training. He studied the maintenance of variability under selection during his PhD at the University of Santiago de Compostela (Spain). He then moved to the Ludwig Maximilian University (Munich, Germany) where he inspected the interplay between selection and genetic architecture of quantitative traits, a project led by Prof. Thomas Hansen at the Florida State University (USA). During his second postdoc, he worked at Prof. Örjan Carlborg's group at the Uppsala University (Sweden), where he set up the NOIA model of genetic effects, integrating previous models under a unifying mathematical framework. He then became an assistant professor (at the Swedish University of Agricultural Sciences). Eventually, he returned to the University of Santiago de Compostela, where he kept on implementing and applying models of genetic effects and variance decomposition as PI. He spent visiting periods at several renowned international institutions, like the Gulbenkian Institute of Science (Oeiras, Portugal) and the Roslin Institute (University of Edinbourgh, Scotland). Currently, he has held various assignments at the Department of Education, University, and Professional Training of the autonomous administration Xunta de Galicia (Spain), while remaining connected to the University of Santiago de Compostela as an external collaborator at the Department of Statistics, Mathematical Analysis and Optimization.


Genetic effects are the core concepts from which quantitative genetics and the evolutionary synthesis emerged. The groundbreaking theory of genetic effects was first proposed over a century ago. This book revises that theory, both conceptually and mathematically, and brings it up-to-date.

  • The theory here compiled is supplemented with non-previously-published developments covering the broadest spectrum of simultaneously multiallelic and multilocus architectures with autosomal and sex-linked loci
  • Arbitrary interactions (dominance, gene-gene, gene-environment, gene-sex, and parent-of-origin interactions) are accounted for
  • Both effects of allele substitutions from the reference of individual genotypes and in the context of populations are worked out
  • Populations are considered regardless of any departures from equilibrium frequencies (including both departures from Hardy-Weinberg, departures from linkage equilibrium, and non-random associations between/among genes and environments)
  • All developments are derived under the same mathematical framework, so that transformations of genetic effects between different contexts are easily allowed

In brief, this book enables novel applications to current empirical paradigms (like gene-mapping and genomic prediction) while adhering to the classical conceptualization of genetic effects and variance decomposition that let quantitative genetics and the evolutionary synthesis flourish.

All relevant concepts are carefully clarified and discussed from a historical perspective. The theoretical developments presented in the book are illustrated by built-in cases and applications with real data. Reassuringly, the adequacy of the theory here presented is corroborated based on the fundamentals of model development.




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