| Likelihood, Bayesian and MCMC Methods in Quantitative Genetics D Sorensen, D Gianola Springer, 2002 | 1370* | 2002 |
| Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers J Crossa, G Campos, P Pérez, D Gianola, J Burgueno, JL Araus, ... Genetics 186 (2), 713-724, 2010 | 952 | 2010 |
| Sire evaluation for ordered categorical data with a threshold model D Gianola, JL Foulley Genetique Selection Evolution 15 (2), 201-224, 1983 | 839 | 1983 |
| Predicting quantitative traits with regression models for dense molecular markers and pedigree G De Los Campos, H Naya, D Gianola, J Crossa, A Legarra, E Manfredi, ... Genetics 182 (1), 375-385, 2009 | 794 | 2009 |
| Theory and analysis of threshold characters D Gianola J. Anim. sci 54 (5), 1079-1096, 1982 | 624 | 1982 |
| Additive genetic variability and the Bayesian alphabet D Gianola, G de Los Campos, WG Hill, E Manfredi, R Fernando Genetics 183 (1), 347-363, 2009 | 613 | 2009 |
| Genomic-assisted prediction of genetic value with semiparametric procedures D Gianola, RL Fernando, A Stella Genetics 173 (3), 1761-1776, 2006 | 572 | 2006 |
| Priors in whole-genome regression: the Bayesian alphabet returns D Gianola Genetics 194 (3), 573-596, 2013 | 531 | 2013 |
| Reproducing kernel Hilbert spaces regression methods for genomic assisted prediction of quantitative traits D Gianola, JB Van Kaam Genetics 178 (4), 2289-2303, 2008 | 523 | 2008 |
| Bayesian methods in animal breeding theory D Gianola, RL Fernando Journal of Animal Science 63 (1), 217-244, 1986 | 515 | 1986 |
| Bayesian inference in threshold models using Gibbs sampling DA Sorensen, S Andersen, D Gianola, I Korsgaard Genetics Selection Evolution 27 (3), 229-249, 1995 | 493 | 1995 |
| Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods G de Los Campos, D Gianola, GJM Rosa, KA Weigel, J Crossa Genetics research 92 (4), 295-308, 2010 | 398 | 2010 |
| Genomic heritability: what is it? G de Los Campos, D Sorensen, D Gianola PLoS Genetics 11 (5), e1005048, 2015 | 348 | 2015 |
| Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat D Gianola, H Okut, KA Weigel, GJM Rosa BMC genetics 12 (1), 87, 2011 | 330 | 2011 |
| Bayesian analysis of mixed linear models via Gibbs sampling with an application to litter size in Iberian pigs CS Wang, JJ Rutledge, D Gianola Genetics Selection Evolution 26 (2), 91-115, 1994 | 301 | 1994 |
| Predicting genetic predisposition in humans: the promise of whole-genome markers G De Los Campos, D Gianola, DB Allison Nature Reviews Genetics 11 (12), 880-886, 2010 | 294 | 2010 |
| Genomic‐enabled prediction based on molecular markers and pedigree using the Bayesian linear regression package in R P Pérez, G de Los Campos, J Crossa, D Gianola The plant genome 3 (2), 2010 | 283 | 2010 |
| Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat P Pérez-Rodríguez, D Gianola, JM González-Camacho, J Crossa, ... G3: Genes| Genomes| Genetics 2 (12), 1595-1605, 2012 | 270 | 2012 |
| Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes D Gianola, D Sorensen Genetics 167 (3), 1407-1424, 2004 | 254 | 2004 |
| Marginal inferences about variance components in a mixed linear model using Gibbs sampling CS Wang, JJ Rutledge, D Gianola Genetics Selection Evolution 25 (1), 41-62, 1993 | 252 | 1993 |
Kent WeigelUniversity of WisconsinVerified email at wisc.edu
