Abstracts
- 09/01/2012 - V. A. Huynh-Thu
- 09/01/2012 - R. Küffner
- 09/01/2012 - C. Ambroise
- 16/09/2011 - M. Bunster
- 27/04/2011 - P. Meyer
- 06/04/2011 - D. Débois
- 30/03/2011 - J. Wouters
- 28/01/2011 - J.-C. Lambert
- 13/12/2010 - J. Giard
- 17/11/2010 - B. Charloteaux
- 12/05/2010 - P. Soumillion
- 30/04/2010 - J.-P. Vert
- 14/04/2010 - X. Tordoir
- 24/03/2010 - J.C. Voegel
- 17/03/2010 - A. Turtoi
- 24/02/2010 - L. Palmeira
- 27/01/2010 - D. Devos
- 09/12/2009 - F. Heuze
- 25/11/2009 - L. Geris
- 19/11/2009 - V. Gabelica
- 14/10/2009 - G. Zocchi
- 30/09/2009 - K. Van Steen
- 12/06/2009 - D. Gianola
- 05/06/2009 - F. J. Theis
- 02/06/2009 - M. Babu
- 07/05/2009 - J. Eyzaguirre
- 22/04/2009 - E. Bullinger
- 08/04/2009 - F. Francis
- 04/03/2009 - Kick-off
Prediction of genetic values in animal breeding: history, methods and post-genomic challenges
Daniel Gianola
Date and place: Friday June, 12th 2:00 pm at S.33 (B37 - Institut de Mathématique)
The approximately two-hour presentation provides a brief history of landmark models in statistical methods for quantitative genetic analysis, from path analysis to Bayesian inference. Challenges to methodology presented by genomic and post-genomic data are discussed. One of the standing difficulties is that of accommodating high-dimensional interactions between loci; arguably, existing methods break down. An alternative, especially appealing for genomic-assisted selection of animals and plants (or for prediction of complex diseases),is provided by reproducing kernel Hilbert spaces regression, kernel regressions and use of ensemble methods, such as bagging and boosting. Application of non-parametric methods to genomic assisted selection are presented.