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Animal Breeding & Genetics Short Courses
Summer 2012
at Iowa State University
Ames, IA USA
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Statistical Methods for Genome-Enabled Selection
(Co-sponsored by the Department of Statistics)
May 6-10, 2012
Course Instructors:
Daniel Gianola
Gustavo de los Campos
Topics Covered:
- Paradigms of quantitative genetic prediction models
- Opportunities and challenges posed by high-dimensional data for prediction Parametric whole genome prediction models
- - Linear Bayesian regression
- Semi-parametric whole genome prediction models
- - Reproducing Kernel Hilbert Spaces Neural Networks
- - Others
Requirements
This course isdesigned for advanced PhD students and postdoctoral fellows with background in regression methods, statistical distributions, Bayesian Inference and quantitative genetics, although some review will be provided.
Labs will be based on R (http://www.r-project.org/ ).
Basic exposure to the R environment is required.
Course Syllabus
Registration Has Closed
Link to area hotels
Link to information on airport transportation
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