“‘Index Selection (breeding)’ Tag”,2019-11-18 (backlinks):
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Bibliography for tag
genetics/selection/artificial/index-selection, most recent first: 42 annotations & 6 links (parent).
- See Also
- Gwern
- Links
- “Microbiome-Driven Breeding Strategy Potentially Improves Beef Fatty Acid Profile Benefiting Human Health and Reduces Methane Emissions”, Martínez-Álvaro et al 2022
- “Genetic Risk Factors Have a Substantial Impact on Healthy Life Years”, et al 2022
- “Validation of Genomic Predictions for a Lifetime Merit Selection Index for the US Dairy Industry”, et al 2020
- “Multi-Trait Genomic Selection Methods for Crop Improvement”, et al 2020
- “Plant Breeders Should Be Determining Economic Weights for a Selection Index instead of Using Independent Culling for Choosing Parents in Breeding Programs With Genomic Selection”, et al 2018
- “Possibilities in an Age of Genomics: The Future of Selection Indices”, Cole & Van2018
- “Improving Genetic Prediction by Leveraging Genetic Correlations among Human Diseases and Traits”, et al 2018
- “Fifty Years of Pig Breeding in France: Outcomes and Perspectives”, et al 2018
- “Embryo Biopsies for Genomic Selection”, 2018
- “Economic Selection Index Development for Beefmaster Cattle I: Terminal Breeding Objective”, et al 2017
- “Genomic Selection in Plant Breeding: Methods, Models, and Perspectives”, et al 2017
- “A 100-Year Review: Methods and Impact of Genetic Selection in Dairy Cattle—From Daughter-Dam Comparisons to Deep Learning Algorithms”, et al 2017
- “Genomic Selection in Dairy Cattle: The USDA Experience”, et al 2017
- “Low-Dose Paroxetine Exposure Causes Lifetime Declines in Male Mouse Body Weight, Reproduction and Competitive Ability As Measured by the Novel Organismal Performance Assay”, et al 2015
- “Growth, Efficiency, and Yield of Commercial Broilers from 1957, 1978, and 2005”, et al 2014
- “On the Genetic Architecture of Intelligence and Other Quantitative Traits”, 2014
- “Genetic Influences on the Behavior of Chickens Associated With Welfare and Productivity § Selection Involving Production Traits”, 2014 (page 21)
- “25 Years of Selection for Improved Leg Health in Purebred Broiler Lines and Underlying Genetic Parameters”, et al 2012
- “The Perfect Milk Machine: How Big Data Transformed the Dairy Industry: Dairy Scientists Are the Gregor Mendels of the Genomics Age, Developing New Methods for Understanding the Link between Genes and Living Things, All While Quadrupling the Average Cow’s Milk Production Since Your Parents Were Born”, 2012
- “Use of Haplotypes to Estimate Mendelian Sampling Effects and Selection Limits”, Cole & Van2011
- “Economic Evaluation of Genomic Breeding Programs”, et al 2009
- “Prediction of Response to Marker-Assisted and Genomic Selection Using Selection Index Theory”, 2007
- “Artificial Selection and Maintenance of Genetic Variance in the Global Dairy Cow Population”, 2005
- “Long-Term Selection With Known Quantitative Trait Loci”, 2004
- “Selection on Net Merit to Improve Lifetime Profit”, Van2004
- “Early Canid Domestication: The Farm-Fox Experiment: Foxes Bred for Tamability in a 40-Year Experiment Exhibit Remarkable Transformations That Suggest an Interplay between Behavioral Genetics and Development”, 1999
- “Strategies to Use Marker-Quantitative Trait Loci Associations”, 1998
- “Theory of Index Selection”, 1997
- “Applications of Index Selection”, 1997
- “Selection Indices and Prediction of Genetic Merit in Animal Breeding”, 1997
- “Economic Aspects of Animal Breeding”, 1994
- “Economic Weights and Index Selection of Milk Production Traits When Multiple Production Quotas Apply”, 1989
- “Selection Indices for Non-Linear Profit Functions”, 1983
- “Index Selection for Genetic Improvement of Quantitative Characters”, 1978
- “Multi-Stage Index Selection”, 1975
- “Restricted Selection Indices”, 1959
- “The Optimum Emphasis on Dams’ Records When Proving Dairy Sires”, 1944
- “The Genetic Basis For Constructing Selection Indexes”, 1943b
- “The Efficiency of 3 Methods of Selection”
- “A Discriminant Function For Plant Selection”, 1936
- “Animal Breeding Plans, 1943: How Selection Changes A Population’, ’Selection For Many Characteristics At Once”
- “Why a Pro/con List Is 75% As Good As Your Fancy Machine Learning Algorithm”
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