G
Gustavo de los Campos
Researcher at Michigan State University
Publications - 119
Citations - 11101
Gustavo de los Campos is an academic researcher from Michigan State University. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 41, co-authored 105 publications receiving 8862 citations. Previous affiliations of Gustavo de los Campos include International Maize and Wheat Improvement Center & University of Alabama.
Papers
More filters
Journal ArticleDOI
Genome-Wide Regression and Prediction with the BGLR Statistical Package
TL;DR: The BGLR R-package implements a large collection of Bayesian regression models, including parametric variable selection and shrinkage methods and semiparametric procedures, which allows integrating various parametric and nonparametric shrinkage and variable selection procedures in a unified and consistent manner.
Journal ArticleDOI
Genomic Selection in Plant Breeding: Methods, Models, and Perspectives
José Crossa,Paulino Pérez-Rodríguez,Jaime Cuevas,Osval A. Montesinos-López,Diego Jarquin,Gustavo de los Campos,Juan Burgueño,Juan Manuel González-Camacho,Sergio Pérez-Elizalde,Yoseph Beyene,Susanne Dreisigacker,Ravi P. Singh,Xuecai Zhang,Manje Gowda,Manish Roorkiwal,Jessica Rutkoski,Rajeev K. Varshney +16 more
TL;DR: Based on GP results, it is speculated how GS in germplasm enhancement programs could accelerate the flow of genes from gene bank accessions to elite lines and recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding.
Journal ArticleDOI
Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding
TL;DR: An overview of available methods for implementing parametric WGR models is provided, selected topics that emerge in applications are discussed, and a general discussion of lessons learned from simulation and empirical data analysis in the last decade are presented.
Journal ArticleDOI
Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.
José Crossa,Gustavo de los Campos,Gustavo de los Campos,Paulino Pérez,Daniel Gianola,Juan Burgueño,José Luis Araus,Dan Makumbi,Ravi P. Singh,Susanne Dreisigacker,Jianbing Yan,Vivi N. Arief,Marianne Bänziger,Hans J. Braun +13 more
TL;DR: Evaluated parametric and semiparametric models for GS using wheat and maize data in which different traits were measured in several environmental conditions indicate that models including marker information had higher predictive ability than pedigree-based models.
Journal ArticleDOI
Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree
Gustavo de los Campos,Hugo Naya,Daniel Gianola,José Crossa,Andres Legarra,Eduardo Manfredi,Kent A. Weigel,José Miguel Cotes +7 more
TL;DR: This article adapts the Bayesian least absolute shrinkage and selection operator (LASSO) to arrive at a regression model where markers, pedigrees, and covariates other than markers are considered jointly, and results indicate that inclusion of markers in the regression further improved the predictive ability of models.