Bost, B., Dillmann, C. & De Vienne, D. (1999). Fluxes and metabolic pools as model traits for quantitative genetics. Genetics 153, 2001–2012.
Bulmer, M. G. (1980). The Mathematical Theory of Quantitative Genetics. Oxford: Clarendon Press.
Chang, H. L. A. (1988). Studies on estimation of genetic variances under nonadditive gene action. Ph.D. Thesis, University of Illinois at Urbana-Champaign.
Cheverud, J. M. & Routman, E. J. (1995). Epistasis and its contribution to genetic variance components. Genetics 139, 1455–1461.
Cockerham, C. C. (1954). An extension of the concept of partitioning hereditary variance for analysis of covariances among relatives when epistasis is present. Genetics 39, 859–882.
Cockerham, C. C. (1956). Effect of linkage on the covariances between relatives. Genetics 41, 138–141.
Craven, P. & Wahba, G. (1979). Smoothing noisy data with spline functions. Numerische Mathematik 31, 377–403.
de los Campos, G., Gianola, D. & Rosa, G. J. M. (2008). Reproducing kernel Hilbert spaces regression: a general framework for genetic evaluation. Journal of Animal Science (accepted).
Dempster, E. R. & Lerner, I. M. (1950). Heritability of threshold characters. Genetics 35, 212–236.
Falconer, D. S. & Mackay, T. F. C. (1996). Introduction to Quantitative Genetics, 4th edn. New York: Longman.
Feldman, M. W. & Lewontin, R. C. (1975). The heritability hang-up. Science 190, 1163–1168.
Gallais, A. (1974). Covariances between arbitrary relatives with linkage and epistasis in the case of linkage disequilibrium. Biometrics 30, 429–446.
Gianola, D. (1982). Theory and analysis of threshold characters. Journal of Animal Science 54, 1079–1096.
Gianola, D., Fernando, R. L. & Stella, A. (2006). Genomic assisted prediction of genetic value with semi-parametric procedures. Genetics 173, 1761–1776.
Gianola, D. & van Kaam, J. B. C. H. M. (2008). Reproducing kernel Hilbert spaces methods for genomic assisted prediction of quantitative traits. Genetics 178, 2289–2303.
González-Recio, O., Gianola, D., Long, N., Weigel, K. A., Rosa, G. J. M. & Avendaño, S. (2008 a). Nonparametric methods for incorporating genomic information into genetic evaluations: an application to mortality in broilers. Genetics 178, 2305–2313.
Gonzalez-Recio, O., Gianola, D., Rosa, G. J. M., Weigel, K. A. & Avendaño, S. (2008 b). Genome-assisted prediction of a quantitative trait in parents and progeny: application to food conversion rate in chickens. Genetics Selection Evolution, submitted.
Henderson, C. R. (1973). Sire evaluation and genetic trends. In Proceedings of the Animal Breeding Genetics Symposium in Honour of J. L. Lush, pp. 10–41. Champaign, IL: American Society of Animal Science and American Dairy Science Association.
Henderson, C. R. (1984). Applications of Linear Models in Animal Breeding. Guelph, ON: University of Guelph.
Henderson, C. R. (1985). Best linear unbiased prediction of nonadditive genetic merits in noninbred populations. Journal of Animal Science 60, 111–117.
Hill, W. G., Goddard, M. E. & Visscher, P. M. (2008). Data and theory point to mainly additive genetic variance for complex traits. PLOS Genetics 4, el000008.
Karlin, S., Cameron, E. C. & Chakraborty, R. (1983). Path analysis in genetic epidemiology: a critique. American Journal of Human Genetics 35, 695–732.
Kempthorne, O. (1954). The correlation between relatives in a random mating population. Proceedings of the Royal Society of London, Series B 143, 103–113.
Kempthorne, O. (1978). Logical, epistemological and statistical aspects of nature-nurture data interpretation. Biometrics 34, 1–23.
Kimeldorf, G. & Wahba, G. (1971). Some results on Tchebycheffian spline functions. Journal of Mathematical Analysis and Applications 35, 82–95.
Kojima, K. I. (1959). Role of epistasis and overdominance in stability of equilibria with selection. Proceedings of the National Academy of Sciences of the USA 45, 984–989.
Lee, H. K. H. (2004). Bayesian Nonparametrics Via Neural Networks. Philadelphia, PA: ASA-SIAM.
Long, N., Gianola, D., Rosa, G. J. M., Weigel, K. & Avendaño, S. (2007). Machine learning classification procedure for selecting SNPs in genomic selection: application to early mortality in broilers. Journal of Animal Breeding and Genetics 124, 377–389.
Long, N., Gianola, D., Rosa, G. J. M., Weigel, K. A. & Avendaño, S. (2008). Marker-assisted assessment of genotype by environment interaction: a case study of SNP–mortality association in broilers in two hygiene environments. Journal of Animal Science (in press).
Lynch, M. & Walsh, B. (1998). Genetics and Analysis of Quantitative Traits. Sunderland, MA: Sinauer.
Motsinger-Reif, A. A., Dudek, S. M., Hahn, L. W. & Ritchie, M. D. (2008). Comparison of approaches for machine learning optimization of neural networks for detecting gene–gene interactions in genetic epidemiology. Genetic Epidemiology 32, 325–340.
Schnell, F. W. (1963). The covariance between relatives in the presence of linkage. In Statistical Genetics and Plant Breeding. (ed. Hanson, W. D. & Robinson, H. F.), pp. 463–483. Washington, DC: National Academy of Sciences – National Research Council.
Sorensen, D. & Gianola, D. (2002). Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics. New York: Springer.
Rasmussen, C. E. & Williams, C. K. I. (2006). Gaussian Processes for Machine Learning. Cambridge, MA: MIT Press.
Ruppert, D., Wand, M. P. & Carroll, R. J. (2003). Semiparametric Regression. Cambridge, UK: Cambridge University Press.
Templeton, A. R. (2000). Epistasis and complex traits. In Epistasis and the Evolutionary Process (ed. Wolf, J. B., Brodie, E. D.III and Wade, M. J.), pp. 41–57. New York: Oxford University Press.
Vapnik, V. (1998). Statistical Learning Theory. New York: Wiley.
Wahba, G. (1990). Spline Models for Observational Data. Philadelphia, PA: Society for Industrial and Applied Mathematics.
Wang, C. S., Rutledge, J. J. & Gianola, D. (1993). Marginal inferences about variance components in a mixed linear model using Gibbs sampling. Genetics Selection Evolution 25, 41–62.
Wang, C. S., Rutledge, J. J. & Gianola, D. (1994). Bayesian analysis of mixed linear models via Gibbs sampling with an application to litter size in Iberian pigs. Genetics Selection Evolution 26, 91–115.
Wang, T. & Zeng, Z.-B. (2006). Models and partition of variance for quantitative trait loci with epistasis and linkage disequilibrium. BMC Genetics 7, 9.
Weir, B. S. & Cockerham, C. C. (1977). Two-locus theory in quantitative genetics. In Proceedings of the International Conference on Quantitative Genetics, pp. 247–269. Ames, IA: Iowa State University Press.