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Abstract

Background: Genomic prediction for novel traits, which can be costly and labor-intensive to measure, is often hampered by low accuracy due to the limited size of the reference population. As an option to improve prediction accuracy, we introduced a semi-supervised learning strategy known as the...

Author(s)
Yao Chen; Zhu XiaoJin; Weigel, K. A.
Publisher
BioMed Central Ltd, London, UK
Citation
Genetics, Selection, Evolution, 2016, 48, 84, pp (7 November 2016)
Abstract

Feed efficiency in dairy cattle has gained much attention recently. Due to the cost-prohibitive measurement of individual feed intakes, combining data from multiple countries is often necessary to ensure an adequate reference population. It may then be essential to model genetic heterogeneity when...

Author(s)
Yao, C.; Campos, G. de los; VandeHaar, M. J.; Spurlock, D. M.; Armentano, L. E.; Coffey, M.; Haas, Y. de; Veerkamp, R. F.; Staples, C. R.; Connor, E. E.; Wang, Z.; Hanigan, M. D.; Tempelman, R. J.; Weigel, K. A.
Publisher
Elsevier Inc., Philadelphia, USA
Citation
Journal of Dairy Science, 2017, 100, 3, pp 2007-2016
Abstract

Since the introduction of genome-enabled prediction for dairy cattle in 2009, genomic selection has markedly changed many aspects of the dairy genetics industry and enhanced the rate of response to selection for most economically important traits. Young dairy bulls are genotyped to obtain their...

Author(s)
Mikshowsky, A. A.; Gianola, D.; Weigel, K. A.
Publisher
Elsevier Inc., Philadelphia, USA
Citation
Journal of Dairy Science, 2017, 100, 1, pp 453-464
Abstract

Genomic selection has revolutionized the dairy genetics industry and enhanced the rate of response to selection for most economically important traits. All young bulls are now genotyped using commercially available single nucleotide polymorphism arrays to compute genomic predicted transmitting...

Author(s)
Mikshowsky, A. A.; Gianola, D.; Weigel, K. A.
Publisher
Elsevier Inc., Philadelphia, USA
Citation
Journal of Dairy Science, 2016, 99, 5, pp 3632-3645
Abstract

The common practice on most commercial dairy farms is to inseminate all cows that are eligible for breeding, while ignoring (or absorbing) the costs associated with semen and labor directed toward low-fertility cows that are unlikely to conceive. Modern analytical methods, such as machine learning...

Author(s)
Shahinfar, S.; Guenther, J. N.; Page, C. D.; Kalantari, A. S.; Cabrera, V. E.; Fricke, P. M.; Weigel, K. A.
Publisher
Elsevier Inc., Philadelphia, USA
Citation
Journal of Dairy Science, 2015, 98, 6, pp 3717-3728
Abstract

The L2-Boosting algorithm is one of the most promising machine-learning techniques that has appeared in recent decades. It may be applied to high-dimensional problems such as whole-genome studies, and it is relatively simple from a computational point of view. In this study, we used this algorithm...

Author(s)
González-Recio, O.; Weigel, K. A.; Gianola, D.; Naya, H.; Rosa, G. J. M.
Publisher
Cambridge University Press, Cambridge, UK
Citation
Genetics Research, 2010, 92, 3, pp 227-237
Abstract

Genome-assisted prediction of genetic merit of individuals for a quantitative trait requires building statistical models that can handle data sets consisting of a massive number of markers and many fewer observations. Numerous regression models have been proposed in which marker effects are treated ...

Author(s)
Long, N.; Gianola, D.; Rosa, G. J. M.; Weigel, K. A.
Publisher
Wiley-Blackwell, Berlin, Germany
Citation
Journal of Animal Breeding and Genetics, 2011, 128, 4, pp 247-257
Abstract

Clinical mastitis is typically coded as presence/absence during some period of exposure, and records are analyzed with linear or binary data models. Because presence includes cows with multiple episodes, there is loss of information when a count is treated as a binary response. The Poisson model is ...

Author(s)
Vazquez, A. I.; Gianola, D.; Bates, D.; Weigel, K. A.; Heringstad, B.
Publisher
American Dairy Science Association, Savoy, USA
Citation
Journal of Dairy Science, 2009, 92, 2, pp 739-748
Abstract

Breeding values of Holstein sires for daughter longevity in each of 9 geographical regions of the United States were predicted using a Weibull proportional hazards model. Longevity (also commonly referred to as herd life or length of productive life) was defined as the number of days from first...

Author(s)
Caraviello, D. Z.; Weigel, K. A.; Gianola, D.
Publisher
American Dairy Science Association, Savoy, USA
Citation
Journal of Dairy Science, 2004, 87, 10, pp 3518-3525

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