| P50 | author | Jill E Cairns | Q58435989 |
| | José Crossa | Q42395398 |
| P2093 | author name string | P Pérez | |
| | R Babu | |
| | G de Los Campos | |
| | D Gianola | |
| | J M González-Camacho | |
| | G Mahuku | |
| P2860 | cites work | Efficient methods to compute genomic predictions | Q46643131 |
| | Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods. | Q51648130 |
| | Reproducing kernel Hilbert spaces regression: a general framework for genetic evaluation. | Q51940648 |
| | Orthogonal least squares learning algorithm for radial basis function networks. | Q52238148 |
| | The Bayesian Lasso | Q55922132 |
| | Spline Models for Observational Data | Q56287267 |
| | Universal Approximation Using Radial-Basis-Function Networks | Q57311896 |
| | Genomic Selection and Prediction in Plant Breeding | Q58896055 |
| | Data and theory point to mainly additive genetic variance for complex traits | Q21145056 |
| | Prediction of total genetic value using genome-wide dense marker maps | Q29619613 |
| | Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat | Q34043789 |
| | Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. | Q34196431 |
| | Genomic-assisted prediction of genetic value with semiparametric procedures | Q34897878 |
| | Invited review: Genomic selection in dairy cattle: progress and challenges | Q34928306 |
| | Genomic-Enabled Prediction Based on Molecular Markers and Pedigree Using the Bayesian Linear Regression Package in R. | Q34967584 |
| | Reproducing kernel hilbert spaces regression methods for genomic assisted prediction of quantitative traits | Q36571838 |
| | Nonparametric methods for incorporating genomic information into genetic evaluations: an application to mortality in broilers. | Q36571844 |
| | Predicting quantitative traits with regression models for dense molecular markers and pedigree | Q37173407 |
| | Genome-enabled prediction using the BLR (Bayesian Linear Regression) R-package | Q38113715 |
| | Marker-assisted prediction of non-additive genetic values | Q39739283 |
| | Radial basis function regression methods for predicting quantitative traits using SNP markers. | Q43560142 |
| | A penalized maximum likelihood method for estimating epistatic effects of QTL. | Q46640090 |
| P433 | issue | 4 | |
| P407 | language of work or name | English | Q1860 |
| P304 | page(s) | 759-771 | |
| P577 | publication date | 2012-05-08 | |
| P1433 | published in | Theoretical and Applied Genetics | Q2694323 |
| P1476 | title | Genome-enabled prediction of genetic values using radial basis function neural networks | |
| P478 | volume | 125 | |