Publications in VIVO

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PEREZ RODRIGUEZ, Paulino Consultant, CIMMYT

Mexico

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selected publications

article
- Approximate Genome-Based Kernel Models for Large Data Sets Including Main Effects and Interactions.. FRONTIERS IN GENETICS. 11:567757-567757. 2020
- Genomic Prediction with Genotype by Environment Interaction Analysis for Kernel Zinc Concentration in Tropical Maize Germplasm. G3-GENES GENOMES GENETICS. 10:2629-2639. 2020
- Genome-based prediction of Bayesian linear and non-linear regression models for ordinal data.. PLANT GENOME. 13. 2020
- Genomic prediction across years in a maize doubled haploid breeding program to accelerate early-stage testcross testing. Theoretical and Applied Genetics. 133:2869-2879. 2020
- Bayesian regularized quantile regression: A robust alternative for genome-based prediction of skewed data. Crop Journal. 8:713-722. 2020
- META-R: A software to analyze data from multi-environment plant breeding trials. Crop Journal. 8:745-756. 2020
- Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia.. Frontiers in Plant Science. 11:353. 2020
- Genomic Prediction with Genotype by Environment Interaction Analysis for Kernel Zinc Concentration in Tropical Maize Germplasm. bioRxiv. 2020
- Modeling Genotype × Environment Interaction Using a Factor Analytic Model of On‐Farm Wheat Trials in the Yaqui Valley of Mexico. Agronomy Journal. 111:2647-2657. 2019
- Multivariate Bayesian Analysis of On‐Farm Trials with Multiple‐Trait and Multiple‐Environment Data. Agronomy Journal. 111:2658-2669. 2019
- Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics.. Nature Genetics. 51:1530-+. 2019
- Joint Use of Genome, Pedigree, and Their Interaction with Environment for Predicting the Performance of Wheat Lines in New Environments. G3: Genes, Genomes, Genetics. 9:2925-2934. 2019
- Deep Kernel for Genomic and Near Infrared Predictions in Multi-environment Breeding Trials.. G3: Genes, Genomes, Genetics. 9:2913-2924. 2019
- isqg: A Binary Framework for in Silico Quantitative Genetics. G3-GENES GENOMES GENETICS. 9:2425-2428. 2019
- Maize responsiveness to Azospirillum brasilense: Insights into genetic control, heterosis and genomic prediction.. PLOS ONE. 14:1-22. 2019
- An R Package for Bayesian Analysis of Multi-environment and Multi-trait Multi-environment Data for Genome-Based Prediction. G3-GENES GENOMES GENETICS. 9:1355-1369. 2019
- Hybrid Wheat Prediction Using Genomic, Pedigree, and Environmental Covariables Interaction Models.. PLANT GENOME. 12:180051. 2019
- Hybrid Wheat Prediction Using Genomic, Pedigree, and Environmental Covariables Interaction Models.. PLANT GENOME. 12:180051. 2019
- Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat.. G3-GENES GENOMES GENETICS. 9:1231-1247. 2019
- Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat.. G3-GENES GENOMES GENETICS. 9:1231-1247. 2019
- Deep Kernel and Deep Learning for Genome-Based Prediction of Single Traits in Multienvironment Breeding Trials.. FRONTIERS IN GENETICS. 10:1168. 2019
- Empirical Comparison of Tropical Maize Hybrids Selected Through Genomic and Phenotypic Selections.. Frontiers in Plant Science. 10:1502. 2019
- Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat. Theoretical and Applied Genetics. 132:177-194. 2019
- A Bayesian Decision Theory Approach for Genomic Selection. G3: Genes, Genomes, Genetics. 8:3019-3037. 2018
- Use of Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat. bioRxiv. 389825. 2018
- Applications of Machine Learning Methods to Genomic Selection in Breeding Wheat for Rust Resistance.. The Plant Genome. 11:170104. 2018
- Genomic prediction of the general combining ability of maize lines (Zea mays L.) and the performance of their single crosses. Plant Breeding. 137:379-387. 2018
- When less can be better: How can we make genomic selection more cost-effective and accurate in barley?. Theoretical and Applied Genetics. 131:1873-1890. 2018
- A bayesian genomic regression model with skew normal random errors. G3-GENES GENOMES GENETICS. 8:1771-1785. 2018
- Prospects and Challenges of Applied Genomic Selection-A New Paradigm in Breeding for Grain Yield in Bread Wheat. PLANT GENOME. 11. 2018
- Rapid Cycling Genomic Selection in a Multiparental Tropical Maize Population.. G3-GENES GENOMES GENETICS. 7:2315-2326. 2017
- Single‐Step Genomic and Pedigree Genotype × Environment Interaction Models for Predicting Wheat Lines in International Environments. PLANT GENOME. 10:1-15. 2017
- Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.. G3-GENES GENOMES GENETICS. 7:1995-2014. 2017
- Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids. Theoretical and Applied Genetics. 130:1431-1440. 2017
- Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models. G3-GENES GENOMES GENETICS. 7:41-53. 2017
- Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models. PLANT GENOME. 9:1-20. 2016
- Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models. PLANT GENOME. 9:1-20. 2016
- Extending the Marker × Environment Interaction Model for Genomic‐Enabled Prediction and Genome‐Wide Association Analysis in Durum Wheat. CROP SCIENCE. 56:2193-2209. 2016
- Genomic Prediction of Gene Bank Wheat Landraces. G3-GENES GENOMES GENETICS. 6:1819-1834. 2016
- Genomic prediction for grain zinc and iron concentrations in spring wheat. Theoretical and Applied Genetics. 129:1595-1605. 2016
- Genome-enabled prediction using probabilistic neural network classifiers.. BMC Genomics. 17:208-208. 2016
- Genomic prediction for grain zinc and iron concentrations in spring wheat. Theoretical and Applied Genetics. 129:1595-1605. 2016
- Genomic Prediction Models for Count Data. Journal of Agricultural Biological and Environmental Statistics. 20:533-554. 2015
- Selection of the Bandwidth Parameter in a Bayesian Kernel Regression Model for Genomic-Enabled Prediction. Journal of Agricultural Biological and Environmental Statistics. 20:512-532. 2015
- A Pedigree‐Based Reaction Norm Model for Prediction of Cotton Yield in Multienvironment Trials. CROP SCIENCE. 55:1143-1151. 2015
- Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs. Heredity. 114:291-299. 2015
- Threshold models for genome-enabled prediction of ordinal categorical traits in plant breeding.. G3-GENES GENOMES GENETICS. 5:291-300. 2015
- Bayesian Genomic-Enabled Prediction as an Inverse Problem. G3-GENES GENOMES GENETICS. 4:1991-2001. 2014
- Genomic-enabled prediction with classification algorithms.. Heredity. 112:616-626. 2014
- A reaction norm model for genomic selection using high-dimensional genomic and environmental data. Theoretical and Applied Genetics. 127:595-607. 2014
- Genomic prediction in CIMMYT maize and wheat breeding programs. Heredity. 112:48-60. 2014
- Genomic Prediction in Maize Breeding Populations with Genotyping-by-Sequencing. G3-GENES GENOMES GENETICS. 3:1903-1926. 2013
- Technical Note: An R package for fitting Bayesian regularized neural networks with applications in animal breeding. Journal of Animal Science. 91:3522-3531. 2013
- Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat. G3: Genes, Genomes, Genetics. 2:1595-1605. 2012
- Genomic prediction of genetic values for resistance to wheat rusts. PLANT GENOME. 5:136-148. 2012
- Genome-enabled prediction of genetic values using radial basis function neural networks. Theoretical and Applied Genetics. 125:759-771. 2012
- Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers. Genetics. 186:713-724. 2010
dataset
document
- Planning the use of fish for food security in Solomon Islands 2012
- Characterization of the proteins fractions extracted from leaves of Amaranthus dubius (Amaranthus spp.) 2011
review
- Genomic Selection in Plant Breeding: Methods, Models, and Perspectives. Trends in Plant Science. 961-975. 2017
- Genomic Selection in Plant Breeding: Methods, Models, and Perspectives. Trends in Plant Science. 961-975. 2017