R. Fernando

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Sampling genotypes in large pedigrees with loops

S. Fernandez, R. Fernando, B. Guldbrandtsen, 2001, Genetics Selection Evolution.

Mixed-model analysis of a censored normal distribution with reference to animal breeding.

R. Fernando, A. Carriquiry, D. Gianola, 1987, Biometrics.

Genomic-Assisted Prediction of Genetic Value With Semiparametric Procedures

R. Fernando, D. Gianola, A. Stella, 2006, Genetics.

A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models

S. Fernandez, R. Fernando, B. Guldbrandtsen, 2003, Genetics Selection Evolution.

Prediction of Breeding Value Under Henderson's Selection Model: A Revisitation

R. Fernando, D. Gianola, S. Im, 1988 .

The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values

R. Fernando, J. Dekkers, D. Habier, 2007, Genetics.

Deregressing estimated breeding values and weighting information for genomic regression analyses

R. Fernando, Jeremy F Taylor, D. Garrick, 2009, Genetics Selection Evolution.

Genomic BLUP Decoded: A Look into the Black Box of Genomic Prediction

R. Fernando, D. Garrick, D. Habier, 2013, Genetics.

Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction

R. Fernando, D. Garrick, Hao Cheng, 2017, Journal of Animal Science and Biotechnology.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

R. Fernando, J. Dekkers, Jeremy F Taylor, 2011, Genetics Selection Evolution.

Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor

R. Fernando, G. de los Campos, A. Vazquez, 2013, PLoS genetics.

Controlling the Proportion of False Positives in Multiple Dependent Tests

R. Fernando, J. Dekkers, D. Nettleton, 2004, Genetics.

Factors Affecting Accuracy From Genomic Selection in Populations Derived From Multiple Inbred Lines: A Barley Case Study

Jean-Luc Jannink, Jack C M Dekkers, Rohan L Fernando, 2009, Genetics.

Additive Genetic Variability and the Bayesian Alphabet

Daniel Gianola, Gustavo de los Campos, Eduardo Manfredi, 2009, Genetics.

Heritability and Bayesian genome-wide association study of first service conception and pregnancy in Brangus heifers.

R. Fernando, J. Reecy, S. Peters, 2013, Journal of animal science.

Genome-wide mapping of quantitative trait loci in admixed populations using mixed linear model and Bayesian multiple regression analysis

R. Fernando, J. Dekkers, A. Toosi, 2018, Genetics Selection Evolution.

Bayesian Methods in Animal Breeding Theory

Daniel Gianola, R. Fernando, D. Gianola, 1986 .

A Two-Stage Approximation for Analysis of Mixture Genetic Models in Large Pedigrees

R. Fernando, L. Totir, D. Habier, 2010, Genetics.

Inferring trait-specific similarity among individuals from molecular markers and phenotypes with Bayesian regression.

R. Fernando, D. Gianola, C. Schön, 2019, Theoretical population biology.

On the Metropolis-Hastings Acceptance Probability to Add or Drop a Quantitative Trait Locus in Markov Chain Monte Carlo-Based Bayesian Analyses

Jean-Luc Jannink, Rohan L Fernando, R. Fernando, 2004, Genetics.

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle.

E. J. Pollak, R. Fernando, S. Peters, 2014, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Application of multivariate heavy-tailed distributions to residuals in the estimation of genetic parameters of growth traits in beef cattle.

E. J. Pollak, R. Fernando, S. Peters, 2013, Journal of animal science.

Genome-wide association study of infectious bovine keratoconjunctivitis in Angus cattle

R. Fernando, J. Reecy, K. Kızılkaya, 2013, BMC Genetics.

Genome-wide Association Study of First Service Conception Rate in Brangus Heifers using Probit, Robit and Logit models

R. Fernando, J. Reecy, S. Peters, 2014 .

Approaches investigated to correct for preferential treatment

R. Fernando, A. Freeman, A. E. Freeman, 1999 .

Detection and utilization of single genes without DNA assays.

R. Fernando, C. Stricker, T. Wang, 1998, Journal of dairy science.

Bayesian genome-wide association analysis of growth and yearling ultrasound measures of carcass traits in Brangus heifers

Dorian J. Garrick, Milt Thomas, James M. Reecy, 2012 .

A multiple-trait Bayesian Lasso for genome-enabled analysis and prediction of complex traits

R. Fernando, D. Gianola, 2019, bioRxiv.

A Multiple-Trait Bayesian Lasso for Genome-Enabled Analysis and Prediction of Complex Traits

Daniel Gianola, Rohan L. Fernando, R. Fernando, 2019, Genetics.

Improved techniques for sampling complex pedigrees with the Gibbs sampler

K. J. Abraham, R. Fernando, L. Totir, 2007, Genetics Selection Evolution.

Irreducibility and efficiency of ESIP to sample marker genotypes in large pedigrees with loops

S. Fernandez, R. Fernando, B. Guldbrandtsen, 2002, Genetics Selection Evolution.

Covariance between relatives in multibreed populations: additive model

R. Fernando, L. Lo, M. Grossman, 1993, Theoretical and Applied Genetics.

The accuracy and bias of single-step genomic prediction for populations under selection

Dorian J. Garrick, Rohan L. Fernando, R. Fernando, 2016, bioRxiv.

Linear models for joint association and linkage QTL mapping

R. Fernando, A. Legarra, 2009, Genetics Selection Evolution.

Evaluation of High Oil Corn and Corn Silage for Lactating Cows

R. Fernando, K. Moore, E. H. Jaster, 1988 .

Accuracy of genomic prediction of shell quality in a White Leghorn line

R. Fernando, J. Dekkers, D. Garrick, 2020, Poultry science.

Estimation of heterogeneous variances using empirical Bayes methods: theoretical considerations.

D Gianola, K A Weigel, C. R. Henderson, 1992, Journal of dairy science.

Technical note: determining peeling order using sparse matrix algorithms.

S. Fernandez, R. Fernando, 2002, Journal of dairy science.

Quantitative trait locus analysis in crosses between outbred lines with dominance and inbreeding.

R. Fernando, M. Pérez-Enciso, P. Le Roy, 2001, Genetics.

The effect of linkage on the additive by additive covariance between relatives1

R. Fernando, L. Totir, 1998, Genetics Selection Evolution.

Reduction in accuracy of genomic prediction for ordered categorical data compared to continuous observations

R. Fernando, K. Kızılkaya, D. Garrick, 2014, Genetics Selection Evolution.

XSim: Simulation of Descendants from Ancestors with Sequence Data

R. Fernando, D. Garrick, Hao Cheng, 2015, G3: Genes, Genomes, Genetics.

Prospecting for pig single nucleotide polymorphisms in the human genome: have we struck gold?

R. Fernando, M. Rothschild, L. Grapes, 2006, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Epistatic interactions associated with fatty acid concentrations of beef from angus sired beef cattle

R. Fernando, N. Weeks, J. Reecy, 2016, BMC Genomics.

The effect of heritability estimates on high-density single nucleotide polymorphism analyses with related animals.

W. G. Hill, R. Fernando, W. Hill, 2009, Journal of animal science.

A comparison of identity‐by‐descent and identity‐by‐state matrices that are used for genetic evaluation and estimation of variance components

R. Fernando, D. Garrick, H. Cheng, 2017, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

The finite polygenic mixed model: An alternative formulation for the mixed model of inheritance

R. Elston, R. Fernando, C. Stricker, 1994, Theoretical and Applied Genetics.

Identification of recombination hotspots and quantitative trait loci for recombination rate in layer chickens

Z. Weng, R. Fernando, J. Dekkers, 2019, Journal of Animal Science and Biotechnology.

Effects of Nutrient Additives and Sodium Hydroxide on Ensiling Characteristics and In Vitro Fiber Digestion Kinetics of Dairy Cattle Waste-Energy Feedstuff Mixtures

L. L. Berger, R. Fernando, G. Fahey, 1985 .

QTL detection and marker-assisted composite line development

R. Fernando, J. Dekkers, N. Piyasatian, 2012 .

A nested mixture model for genomic prediction using whole-genome SNP genotypes

R. Fernando, J. Dekkers, J. Zeng, 2018, PloS one.

Associations between genetic markers and growth and carcass traits in a paternal half-sib family of Angus cattle.

R. Fernando, H. Lewin, J. Beever, 1990, Journal of animal science.

Computational strategies for alternative single-step Bayesian regression models with large numbers of genotyped and non-genotyped animals

R. Fernando, D. Garrick, Hao Cheng, 2016, Genetics Selection Evolution.

Implementing a QTL detection study (GWAS) using genomic prediction methodology.

R. Fernando, D. Garrick, 2013, Methods in molecular biology.

Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions

R. Fernando, J. Dekkers, D. Garrick, 2016, Journal of Animal Science and Biotechnology.

Linkage analysis with an alternative formulation for the mixed model of inheritance: the finite polygenic mixed model.

R. Elston, R. Fernando, C. Stricker, 1995, Genetics.

Inverse of an Additive × Additive Relationship Matrix Due to Sires and Maternal Grandsires

R. Fernando, D. Gianola, H. L. Chang, 1989 .

Persistence of accuracy of genomic estimated breeding values over generations in layer chickens

R. Fernando, J. Dekkers, D. Garrick, 2011, Genetics Selection Evolution.

Breeding value prediction for production traits in layer chickens using pedigree or genomic relationships in a reduced animal model

R. Fernando, J. Dekkers, S. Lamont, 2011, Genetics Selection Evolution.

Accuracy of Genomic Predictions Across Breeding Lines of Chickens

R. Fernando, J. Dekkers, A. Kranis, 2010 .

Dominance models with method R for stature of Holsteins.

R. Fernando, T. Lawlor, I. Misztal, 1997, Journal of dairy science.

Genomic breeding value prediction and QTL mapping of QTLMAS2011 data using Bayesian and GBLUP methods

R. Fernando, J. Dekkers, J. Zeng, 2012, BMC Proceedings.

Analysis of egg production in layer chickens using a random regression model with genomic relationships.

R. Fernando, J. Dekkers, D. Garrick, 2013, Poultry science.

Development of persistent lymphocytosis in cattle is closely associated with DRB2

R. Fernando, H. Lewin, J. Beever, 1992, Immunogenetics.

Tests of candidate genes in breed cross populations for QTL mapping in livestock

R. Fernando, J. Dekkers, M. Rothschild, 2003, Mammalian Genome.

Genome-Wide Association Study for Marek's Disease Mortality in Layer Chickens

R. Fernando, J. Dekkers, D. Garrick, 2013, Avian diseases.

Power and Precision of Alternate Methods for Linkage Disequilibrium Mapping of QTL in Livestock

R. Fernando, H. H. Zhao, J. Dekkers, 2006 .

Validation of the linear regression method to evaluate population accuracy and bias of predictions for non-linear models

R. Fernando, J. Dekkers, Haipeng Yu, 2022, bioRxiv.

Inference about quantitative traits under selection: a Bayesian revisitation for the post-genomic era

R. Fernando, D. Gianola, C. Schön, 2022, Genetics Selection Evolution.

Cross-validation of best linear unbiased predictions of breeding values using an efficient leave-one-out strategy.

R. Fernando, J. Dekkers, Jian Cheng, 2021, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Parallel Computing to Speed up Whole-Genome Bayesian Regression Analyses Using Orthogonal Data Augmentation

R. Fernando, Cheng Hao, G. Dorian, 2017, bioRxiv.

Haplotype inference in crossbred populations without pedigree information

R. Fernando, J. Dekkers, A. Coster, 2009, Genetics Selection Evolution.

The effect of linkage on the additive by additive covariance between relatives1

R. Fernando, L. Totir, 1998, Genetics Selection Evolution.

Genetic evaluation with autosomal and X-chromosomal inheritance

R. Fernando, M. Grossman, 1990, Theoretical and Applied Genetics.

Genome-wide association study of disease resilience traits from a natural polymicrobial disease challenge model in pigs identifies the importance of the major histocompatibility complex region

R. Fernando, G. Plastow, S. Kachman, 2021, G3.

Detection of linkage between genetic markers and genes that affect growth and carcass traits in pigs.

R. Fernando, L. Schook, J. Beever, 1992, Journal of animal science.

An embryo transfer study of reciprocal cross differences in growth and carcass traits of Duroc and Landrace pigs.

R. Fernando, D. McLaren, P. Dziuk, 1992, Journal of animal science.

Genetic analyses of growth, real-time ultrasound, carcass, and pork quality traits in Duroc and Landrace pigs: I. Breed effects.

R. Fernando, J. Novakofski, D. McLaren, 1992, Journal of animal science.

Relationships Between Predicted Difference for Milk Production Traits and Buck Designation in Dairy Goats

R. Fernando, T. Gipson, M. Grossman, 1986 .

Effects of data imbalance on estimation of heritability

R. Fernando, M. Grossman, R. F. Caro, 1985, Theoretical and Applied Genetics.

The evolution of methodologies for genomic prediction

R. Fernando, J. Dekkers, D. Garrick, 2014 .

Effects of Intake of a Mixed Diet by Dairy Steers on Digestion Events

L. L. Berger, R. Fernando, G. Fahey, 1984 .

Identifying All Connected Subsets in a Two-Way Classification Without Interaction

R. Fernando, D. Gianola, M. Grossman, 1983 .

A MONTE-CARLO COMPARISON OF ESTIMATORS OF AVERAGE DAILY GAIN IN BODY WEIGHT

R. Fernando, R. Shanks, M. Grossman, 2022 .

Comparison of linkage disequilibrium estimated from genotypes versus haplotypes for crossbred populations

M. Calus, R. Fernando, J. Dekkers, 2022, Genetics, selection, evolution : GSE.

Comparison of alternative approaches to single-trait genomic prediction using genotyped and non-genotyped Hanwoo beef cattle

R. Fernando, J. Dekkers, D. Garrick, 2017, Genetics Selection Evolution.

Genetic analyses of growth, real-time ultrasound, carcass, and pork quality traits in Duroc and Landrace pigs: II. Heritabilities and correlations.

R. Fernando, J. Novakofski, D. McLaren, 1992, Journal of animal science.

Accuracy of Genomic Selection Methods in a Standard Data Set of Loblolly Pine (Pinus taeda L.)

T. A. Martin, R. Fernando, T. Martin, 2012, Genetics.

Genome-wide association analysis and genetic architecture of egg weight and egg uniformity in layer chickens.

Rex D. Fernando, W. G. Hill, R. Fernando, 2012, Animal genetics.

Exact Distribution of Linkage Disequilibrium in the Presence of Mutation, Selection, or Minor Allele Frequency Filtering

R. Fernando, S. Kachman, D. Garrick, 2019, bioRxiv.

Genomic breeding value prediction and QTL mapping of QTLMAS2010 data using Bayesian Methods

R. Fernando, J. Dekkers, D. Garrick, 2011, BMC proceedings.

Genomic selection in admixed and crossbred populations.

R. Fernando, J. Dekkers, A. Toosi, 2010, Journal of animal science.

Extent and consistency of linkage disequilibrium and identification of DNA markers for production and egg quality traits in commercial layer chicken populations

R. Fernando, J. Dekkers, S. Lamont, 2009, BMC Genomics.

Genomic Selection Using Low-Density Marker Panels

R. Fernando, J. Dekkers, D. Habier, 2009, Genetics.

Genomic selection in admixed and crossbred populations 1

R. Fernando, J. Dekkers, A. Toosi, 2009 .

Power and Precision of Alternate Methods for Linkage Disequilibrium Mapping of Quantitative Trait Loci

R. Fernando, J. Dekkers, H. Zhao, 2007, Genetics.

Genome-wide association study for egg production and quality in layer chickens.

R. Fernando, J. Dekkers, A. Wolc, 2014, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Empirical Comparisons of Different Statistical Models To Identify and Validate Kernel Row Number-Associated Variants from Structured Multi-parent Mapping Populations of Maize

R. Fernando, J. Dekkers, Cheng-Ting Yeh, 2018, G3: Genes, Genomes, Genetics.

Tests of association based on genomic windows can lead to spurious associations when using genotype panels with heterogeneous SNP densities

R. Fernando, Hao Cheng, Jinghui Li, 2021, Genetics, selection, evolution : GSE.

Interpretable artificial neural networks incorporating Bayesian alphabet models for genome-wide prediction and association studies

R. Fernando, Hao Cheng, T. Zhao, 2021, bioRxiv.

Evaluation of variant identification methods for whole genome sequencing data in dairy cattle

James M Reecy, Christine Flury, Eric Fritz-Waters, 2014, BMC Genomics.

Comparison of variant calling methods for whole genome sequencing data in dairy cattle

R. Fernando, F. Schmitz-Hsu, C. Baes, 2014 .

Genomics of response to porcine reproductive and respiratory syndrome virus in purebred and crossbred sows: antibody response and performance following natural infection vs. vaccination

R. Fernando, J. Dekkers, D. Linhares, 2021, Journal of animal science.

Genomics of response to PRRSV in purebred and crossbred sows: antibody response and performance following natural infection versus vaccination 1

R. Fernando, J. Dekkers, D. Linhares, 2021 .

Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes.

R. Fernando, K. Kızılkaya, D. Garrick, 2010, Journal of animal science.

Introgressing multiple QTL in breeding programmes of limited size.

R. Fernando, J. Dekkers, N. Piyasatian, 2008, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Influence of slaughter weight on growth and carcass characteristics, commercial cutting and curing yields, and meat quality of barrows and gilts from two genotypes.

R. Fernando, M. Ellis, F. Mckeith, 1996, Journal of animal science.

A nonsense mutation in cGMP-dependent type II protein kinase (PRKG2) causes dwarfism in American Angus cattle

R. Fernando, L. Totir, M. Georges, 2009, Proceedings of the National Academy of Sciences.

Genetic associations of sow longevity with age at first farrowing, number of piglets weaned, and wean to insemination interval in the Finnish Landrace swine population.

R. Fernando, K. Stalder, T. Serenius, 2008, Journal of animal science.

Further host-genomic characterization of total antibody response to PRRSV vaccination and its relationship with reproductive performance in commercial sows: genome-wide haplotype and zygosity analyses

R. Fernando, N. Serão, D. Linhares, 2021, Genetics, selection, evolution : GSE.

Genetic Analysis of Antibody Response to Porcine Reproductive and Respiratory Syndrome Vaccination as an Indicator Trait for Reproductive Performance in Commercial Sows

R. Fernando, J. Dekkers, D. Linhares, 2020, Frontiers in Genetics.

JWAS: Julia implementation of Whole-genome Analyses Software

Dorian J. Garrick, Rohan L. Fernando, Hao Cheng, 2018 .

Extension of the bayesian alphabet for genomic selection

Rohan L. Fernando, Dorian Garrick, David Habier, 2011, BMC Bioinformatics.

Genomic selection of purebreds for crossbred performance

R. Fernando, J. Dekkers, N. Ibáñez-Escriche, 2009, Genetics Selection Evolution.

Genetic evaluation by BLUP in two-breed terminal crossbreeding systems under dominance.

R. Fernando, L. Lo, M. Grossman, 1997, Journal of animal science.

Pregnancy rate and first-service conception rate in Angus heifers.

R. Fernando, L. Totir, S. Kachman, 2006, Journal of animal science.

Genetic relationship between purebred and crossbred sow longevity

R. Fernando, M. Rothschild, K. Stalder, 2016, Journal of Animal Science and Biotechnology.

Performance of hair breeds and prolific wool breeds of sheep in southern Illinois: effect of breed of service sire on lamb production of Suffolk and Targhee ewes.

R. Fernando, D. Thomas, T. G. Nash, 1993, Journal of animal science.

Evaluations for Frame Size at Weaning in Angus Cattle Effects of Method of Scaling on Heritability Estimates and Sire

R. Fernando, D. Gianola, R. Billingsley, 2011 .

Genetic evaluation with uncertain parentage: a comparison of methods

R. Fernando, M. Pérez-Enciso, 1992, Theoretical and Applied Genetics.

Effects of Method of Scaling on Heritability Estimates and Sire Evaluations for Frame Size at Weaning in Angus Cattle

R. Fernando, D. Gianola, R. Billingsley, 1983 .

Prediction Accuracy of Pedigree and Genomic Estimated Breeding Values over Generations in Layer Chickens

Z. Weng, R. Fernando, J. Dekkers, 2014 .

Comparing Linkage Disequilibrium-Based Methods for Fine Mapping Quantitative Trait Loci

R. Fernando, J. Dekkers, M. Rothschild, 2004, Genetics.

Fast parallelized sampling of Bayesian regression models for whole-genome prediction

R. Fernando, D. Garrick, Hao Cheng, 2020, Genetics Selection Evolution.

The effect of using genealogy-based haplotypes for genomic prediction

R. Fernando, B. Guldbrandtsen, M. Lund, 2013, Genetics Selection Evolution.

Mixed Model Methodology and the Box-Cox Theory of Transformations: A Bayesian Approach

Daniel Gianola, Rohan L. Fernando, Jean-Louis Foulley, 1990 .

Implementation of genomic selection in the poultry industry

R. Fernando, J. Dekkers, J. Hickey, 2016 .

Dissecting the genetic architecture of frost tolerance in Central European winter wheat

R. Fernando, Yusheng Zhao, J. Reif, 2013, Journal of experimental botany.

Dietary Fat in Milk or Milk Replacers for Dairy Calves Raised in Hutches During the Winter

R. Fernando, G. Mccoy, E. H. Jaster, 1990 .

Identification of recombination hotspots and quantitative trait loci for recombination rate in layer chickens

Z. Weng, R. Fernando, J. Dekkers, 2019, Journal of Animal Science and Biotechnology.

Accuracy of genomic prediction using an evenly spaced, low-density single nucleotide polymorphism panel in broiler chickens.

R. Fernando, J. Dekkers, S. Avendaño, 2013, Poultry science.

Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

R. Fernando, J. Dekkers, J. Zeng, 2013, Genetics Selection Evolution.

Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens

R. Fernando, W. Muir, A. Legarra, 2014, Front. Genet..

Power and precision of regression-based linkage disequilibrium mapping of QTL.

R. Fernando, J. Dekkers, Honghua H. Zhao, 2006 .

Estimation of segregation variance for birth weight in beef cattle

R. Fernando, R. Cantet, A. N. Birchmeier, 2002 .

Genetic evaluation by best linear unbiased prediction using marker and trait information in a multibreed population.

R. Fernando, T. Wang, M. Grossman, 1998, Genetics.

On the principle underlying the tabular method to compute coancestry

R. Fernando, M. Grossman, H. L. Chang, 1991, Theoretical and Applied Genetics.

Genomic Prediction of Hybrid Wheat Performance

R. Fernando, J. Zeng, Yusheng Zhao, 2013 .

Models for marker-assisted genetic evaluation with multiple QTL in a crossbred population

R. Fernando, J. Dekkers, N. Piyasatian, 2009 .

A class of Bayesian methods to combine large numbers of genotyped and non-genotyped animals for whole-genome analyses

Rohan L Fernando, R. Fernando, J. Dekkers, 2014, Genetics Selection Evolution.

Application of Whole-Genome Prediction Methods for Genome-Wide Association Studies: A Bayesian Approach

Jack Dekkers, Rohan Fernando, Ali Toosi, 2014 .

A class of Bayesian methods to combine large numbers of genotyped and non-genotyped animals for whole-genome analyses

R. Fernando, J. Dekkers, D. Garrick, 2014, Genetics Selection Evolution.

Bayesian methods applied to GWAS.

Dorian Garrick, Rohan L Fernando, R. Fernando, 2013, Methods in molecular biology.

Genome-wide mapping of quantitative trait loci in admixed populations using mixed linear model and Bayesian multiple regression analysis

R. Fernando, J. Dekkers, A. Toosi, 2018, Genetics Selection Evolution.

XSim version 2: simulation of modern breeding programs

Chunpeng James Chen, R. Fernando, D. Garrick, 2022, G3.

A certain invariance property of BLUE in a whole‐genome regression context

R. Fernando, D. Gianola, D. Garrick, 2019, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Analysis of generalized linear mixed models with Matvec.

R. Fernando, S. Kachman, 2002 .

Digestion criteria in nursing beef calves supplemented with limited levels of protein and energy.

R. Fernando, G. Fahey, D. Faulkner, 1991, Journal of animal science.

Correlations between parities for lactation traits in United States dairy goats.

W. A. Mohammad, R. Fernando, R. Shanks, 1986, Journal of dairy science.

Response and inbreeding from a genomic selection experiment in layer chickens

R. Fernando, S. Lamont, D. Garrick, 2015, Genetics Selection Evolution.

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

R. Fernando, K. Kızılkaya, D. Garrick, 2010, Genetics Selection Evolution.

Estimates of dispersion parameters and of genetic and environmental trends for weaning weight in Angus cattle using a maternal animal model with genetic grouping

R. Fernando, D. Gianola, R. Cantet, 1993 .

Estimation of Individual and Maternal Heterosis, Repeatability and Heritability for Ewe Productivity and its Components in Suffolk and Targhee Sheep

R. Fernando, D. Thomas, T. Long, 1989 .

Relationship between growth of Suffolk rams on central performance test and growth of their progeny.

R. Fernando, J. Stookey, David L. Thomas, 1986 .

Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction

R. Fernando, D. Garrick, Hao Cheng, 2017, Journal of Animal Science and Biotechnology.

Polydactyl inheritance in the pig.

R. Fernando, L. Totir, M. Rothschild, 2010, The Journal of heredity.

Effects of increasing crude protein level on nitrogen retention and intestinal supply of amino acids in lambs fed diets based on alkaline hydrogen peroxide-treated wheat straw.

L. L. Berger, R. Fernando, G. Fahey, 1991, Journal of animal science.

INTEGRATED STRATEGIES AND METHODOLOGIES FOR THE GENETIC IMPROVEMENT OF ANIMALS

R. Fernando, H. Lewin, L. Schook, 1990 .

Genetic parameters for energy balance, feed efficiency, and related traits in Holstein cattle.

Rex D. Fernando, R. Fernando, J. Dekkers, 2012, Journal of dairy science.

Optimal Haplotype Structure for Linkage Disequilibrium-Based Fine Mapping of Quantitative Trait Loci Using Identity by Descent

R. Fernando, J. Dekkers, M. Rothschild, 2006, Genetics.

Efficient genetic value prediction using incomplete omics data

R. Fernando, A. Melchinger, G. Thaller, 2019, Theoretical and Applied Genetics.

An approximation to the likelihood for a pedigree with loops

R. C. Elston, R. Elston, R. Fernando, 1996, Theoretical and Applied Genetics.

An efficient algorithm to compute the posterior genotypic distribution for every member of a pedigree without loops

R. C. Elston, C. Stricker, R. Elston, 1993, Theoretical and Applied Genetics.

Computing algorythms in a general purpose BLUP package for multivariate prediction and estimation

R. Fernando, E. Groeneveld, M. Kovac, 1992 .

An Upper Bound for Accuracy of Prediction Using GBLUP

Dorian J. Garrick, Rohan L. Fernando, Emre Karaman, 2016, PloS one.

Bayesian genome-wide association analysis of growth and yearling ultrasound measures of carcass traits in Brangus heifers.

R. Fernando, J. Reecy, S. Peters, 2012, Journal of animal science.

Pedigree and genomic analyses of feed consumption and residual feed intake in laying hens.

R. Fernando, J. Dekkers, D. Garrick, 2013, Poultry science.

Computational strategies for alternative single-step Bayesian regression models with large numbers of genotyped and non-genotyped animals

R. Fernando, D. Garrick, Hao Cheng, 2016, Genetics Selection Evolution.

363. JWAS version 2: leveraging biological information and highthroughput phenotypes into genomic prediction and association

R. Fernando, D. Garrick, J. Qu, 2022, Proceeding of 12th World Congress on Genetics Applied to Livestock Production (WCGALP).

A fast and efficient Gibbs sampler for BayesB in whole-genome analyses

R. Fernando, D. Garrick, Hao Cheng, 2015, Genetics Selection Evolution.

Contributions of linkage disequilibrium and co-segregation information to the accuracy of genomic prediction

R. Fernando, J. Dekkers, Xiaochen Sun, 2016, Genetics Selection Evolution.

Response and inbreeding from a genomic selection experiment in layer chickens

R. Fernando, J. Dekkers, S. Lamont, 2015, Genetics Selection Evolution.

The Accuracy and Bias of Single-Step Genomic Prediction for Populations Under Selection

Rohan L Fernando, R. Fernando, D. Garrick, 2016, G3: Genes, Genomes, Genetics.

Genomic selection for marker-assisted improvement in line crosses

R. Fernando, J. Dekkers, N. Piyasatian, 2007, Theoretical and Applied Genetics.

Whole genome analysis of infectious bovine keratoconjunctivitis in Angus cattle using Bayesian threshold models

James M Reecy, Rohan L Fernando, Kadir Kizilkaya, 2011, BMC proceedings.

A study on the minimum number of loci required for genetic evaluation using a finite locus model

S. Fernandez, R. Fernando, L. Totir, 2004, Genetics Selection Evolution.

Theory for modelling means and covariances in a two-breed population with dominance inheritance

R. Fernando, R. Cantet, L. Lo, 2004, Theoretical and Applied Genetics.

A gene frequency model for QTL mapping using Bayesian inference

R. Fernando, J. Dekkers, H. Gilbert, 2010, Genetics Selection Evolution.

Genetics Selection Evolution BioMed Central

R. Fernando, D. Garrick, JEREMY F. Taylor, 2009 .

Genomic prediction in hybrid breeding: I. Optimizing the training set design

R. Fernando, C. Schön, Hans-Jürgen Auinger, 2023, Theoretical and Applied Genetics.

Genomic Prediction from Multiple-Trait Bayesian Regression Methods Using Mixture Priors

Dorian Garrick, Kadir Kizilkaya, Hao Cheng, 2018, Genetics.

307. A Bayesian hierarchical model to integrate a mechanistic growth model in genomic prediction

R. Fernando, E. Knol, J. van Milgen, 2022, Proceeding of 12th World Congress on Genetics Applied to Livestock Production (WCGALP).

Effects of dietary energy level and supplemental protein source on performance of growing steers and nutrient digestibility and nitrogen balance in lambs.

L. L. Berger, R. Fernando, G. Fahey, 1987, Journal of animal science.

Genomic selection using low-density SNPs

P. VanRaden, R. Fernando, N. Gengler, 2008 .

Multilocus analysis for gene-centromere mapping using first polar bodies and secondary oocytes.

R. Fernando, H. Lewin, Y. Da, 1995, Genetics.

Applications of Graphical Clustering Algorithms in Genome Wide Association Mapping

Rohan Fernando, K. J. Abraham, R. Fernando, 2012 .

Impact of fitting dominance and additive effects on accuracy of genomic prediction of breeding values in layers.

R. Fernando, J. Dekkers, J. Zeng, 2016, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes.

R. Fernando, K. Kızılkaya, D. Garrick, 2010, Journal of animal science.

observed 50k SNP genotypes Genomic prediction of simulated multi-breed and purebred performance using

R. Fernando, K. Kızılkaya, D. Garrick, 2011 .

Fast parallelized sampling of Bayesian regression models for whole-genome prediction

R. Fernando, D. Garrick, Hao Cheng, 2020, Genetics Selection Evolution.

Application of Whole-Genome Prediction Methods for Genome-Wide Association Studies: A Bayesian Approach

R. Fernando, D. Garrick, A. Wolc, 2017, Journal of Agricultural, Biological and Environmental Statistics.

Comparison of alternative approaches to single-trait genomic prediction using genotyped and non-genotyped Hanwoo beef cattle

Jack Dekkers, Kyungdo Park, Dorian Garrick, 2017, Genetics Selection Evolution.

Effects of number of training generations on genomic prediction for various traits in a layer chicken population

Z. Weng, R. Fernando, J. Dekkers, 2016, Genetics Selection Evolution.

Mixture models detect large effect QTL better than GBLUP and result in more accurate and persistent predictions

R. Fernando, J. Dekkers, D. Garrick, 2016, Journal of Animal Science and Biotechnology.

Accuracy of prediction of simulated polygenic phenotypes and their underlying quantitative trait loci genotypes using real or imputed whole-genome markers in cattle

R. Fernando, D. Garrick, M. Saatchi, 2015, Genetics Selection Evolution.

Efficient genetic value prediction using incomplete omics data

R. Fernando, A. Melchinger, G. Thaller, 2019, Theoretical and Applied Genetics.

Factors Affecting Accuracy From Genomic Selection in Populations Derived From Multiple Inbred Lines: A Barley Case Study

R. Fernando, J. Dekkers, J. Jannink, 2009, Genetics.

Bayesian methods applied to GWAS.

R. Fernando, D. Garrick, 2013, Methods in molecular biology.

Application of the false discovery rate to quantitative trait loci interval mapping with multiple traits.

R. Fernando, J. Dekkers, M. Rothschild, 2002, Genetics.

Additive Genetic Variability and the Bayesian Alphabet

W. G. Hill, R. Fernando, D. Gianola, 2009, Genetics.

Bayesian inference of genomic similarity among individuals from mark- ers and phenotypes

R. Fernando, D. Gianola, 2018 .