- 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”, Jukarainen et al 2022
- “Validation of Genomic Predictions for a Lifetime Merit Selection Index for the US Dairy Industry”, Fessenden et al 2020
- “Multi-Trait Genomic Selection Methods for Crop Improvement”, Moeinizade 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”, Batista et al 2018
- “Possibilities in an Age of Genomics: The Future of Selection Indices”, Cole & VanRaden 2018
- “Improving Genetic Prediction by Leveraging Genetic Correlations among Human Diseases and Traits”, Maier et al 2018
- “Fifty Years of Pig Breeding in France: Outcomes and Perspectives”, Bidanel et al 2018
- “Embryo Biopsies for Genomic Selection”, Mullaart & Wells 2018
- “Economic Selection Index Development for Beefmaster Cattle I: Terminal Breeding Objective”, Ochsner et al 2017
- “Genomic Selection in Plant Breeding: Methods, Models, and Perspectives”, Crossa et al 2017
- “A 100-Year Review: Methods and Impact of Genetic Selection in Dairy Cattle—From Daughter-Dam Comparisons to Deep Learning Algorithms”, Weigel et al 2017
- “Genomic Selection in Dairy Cattle: The USDA Experience”, Wiggans 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”, Ruff et al 2015
- “Growth, Efficiency, and Yield of Commercial Broilers from 1957, 1978, and 2005”, Zuidhof et al 2014
- “On the Genetic Architecture of Intelligence and Other Quantitative Traits”, Hsu 2014
- “Genetic Influences on the Behavior of Chickens Associated With Welfare and Productivity § Selection Involving Production Traits”, Muir 2014 (page 21)
- “25 Years of Selection for Improved Leg Health in Purebred Broiler Lines and Underlying Genetic Parameters”, Kapell 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”, Madrigal 2012
- “Use of Haplotypes to Estimate Mendelian Sampling Effects and Selection Limits”, Cole & VanRaden 2011
- “Economic Evaluation of Genomic Breeding Programs”, König et al 2009
- “Prediction of Response to Marker-Assisted and Genomic Selection Using Selection Index Theory”, Dekkers 2007
- “Artificial Selection and Maintenance of Genetic Variance in the Global Dairy Cow Population”, Brotherstone & Goddard 2005
- “Long-Term Selection With Known Quantitative Trait Loci”, Dekkers & Settar 2004
- “Selection on Net Merit to Improve Lifetime Profit”, VanRaden 2004
- “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”, Trut 1999
- “Strategies to Use Marker-Quantitative Trait Loci Associations”, Haley & Visscher 1998
- “Theory of Index Selection”, Walsh & Lynch 1997
- “Applications of Index Selection”, Walsh & Lynch 1997
- “Selection Indices and Prediction of Genetic Merit in Animal Breeding”, Cameron 1997
- “Economic Aspects of Animal Breeding”, Weller 1994
- “Economic Weights and Index Selection of Milk Production Traits When Multiple Production Quotas Apply”, Gibson 1989
- “Selection Indices for Non-Linear Profit Functions”, Goddard 1983
- “Index Selection for Genetic Improvement of Quantitative Characters”, Lin 1978
- “Multi-Stage Index Selection”, Cunningham 1975
- “Restricted Selection Indices”, Kempthorne & Nordskog 1959
- “The Optimum Emphasis on Dams’ Records When Proving Dairy Sires”, Lush 1944
- “The Genetic Basis For Constructing Selection Indexes”, Hazel 1943b
- “The Efficiency of 3 Methods of Selection”
- “A Discriminant Function For Plant Selection”, Smith 1936
- “Animal Breeding Plans, Lush 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”
- Sort By Magic
- Wikipedia
- Miscellaneous
- Bibliography
See Also
Gwern
“Origins of Innovation: Bakewell & Breeding”, Gwern 2018
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”, Jukarainen et al 2022
Genetic risk factors have a substantial impact on healthy life years
“Validation of Genomic Predictions for a Lifetime Merit Selection Index for the US Dairy Industry”, Fessenden et al 2020
Validation of genomic predictions for a lifetime merit selection index for the US dairy industry
“Multi-Trait Genomic Selection Methods for Crop Improvement”, Moeinizade 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”, Batista et al 2018
“Possibilities in an Age of Genomics: The Future of Selection Indices”, Cole & VanRaden 2018
Possibilities in an age of genomics: The future of selection indices
“Improving Genetic Prediction by Leveraging Genetic Correlations among Human Diseases and Traits”, Maier et al 2018
Improving genetic prediction by leveraging genetic correlations among human diseases and traits
“Fifty Years of Pig Breeding in France: Outcomes and Perspectives”, Bidanel et al 2018
Fifty years of pig breeding in France: outcomes and perspectives
“Embryo Biopsies for Genomic Selection”, Mullaart & Wells 2018
“Economic Selection Index Development for Beefmaster Cattle I: Terminal Breeding Objective”, Ochsner et al 2017
Economic selection index development for Beefmaster cattle I: Terminal breeding objective
“Genomic Selection in Plant Breeding: Methods, Models, and Perspectives”, Crossa et al 2017
Genomic Selection in Plant Breeding: Methods, Models, and Perspectives:
“A 100-Year Review: Methods and Impact of Genetic Selection in Dairy Cattle—From Daughter-Dam Comparisons to Deep Learning Algorithms”, Weigel et al 2017
“Genomic Selection in Dairy Cattle: The USDA Experience”, Wiggans 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”, Ruff et al 2015
“Growth, Efficiency, and Yield of Commercial Broilers from 1957, 1978, and 2005”, Zuidhof et al 2014
Growth, efficiency, and yield of commercial broilers from 1957, 1978, and 2005
“On the Genetic Architecture of Intelligence and Other Quantitative Traits”, Hsu 2014
On the genetic architecture of intelligence and other quantitative traits
“Genetic Influences on the Behavior of Chickens Associated With Welfare and Productivity § Selection Involving Production Traits”, Muir 2014 (page 21)
“25 Years of Selection for Improved Leg Health in Purebred Broiler Lines and Underlying Genetic Parameters”, Kapell 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”, Madrigal 2012
“Use of Haplotypes to Estimate Mendelian Sampling Effects and Selection Limits”, Cole & VanRaden 2011
Use of haplotypes to estimate Mendelian sampling effects and selection limits
“Economic Evaluation of Genomic Breeding Programs”, König et al 2009
“Prediction of Response to Marker-Assisted and Genomic Selection Using Selection Index Theory”, Dekkers 2007
Prediction of response to marker-assisted and genomic selection using selection index theory
“Artificial Selection and Maintenance of Genetic Variance in the Global Dairy Cow Population”, Brotherstone & Goddard 2005
Artificial selection and maintenance of genetic variance in the global dairy cow population
“Long-Term Selection With Known Quantitative Trait Loci”, Dekkers & Settar 2004
“Selection on Net Merit to Improve Lifetime Profit”, VanRaden 2004
“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”, Trut 1999
“Strategies to Use Marker-Quantitative Trait Loci Associations”, Haley & Visscher 1998
Strategies to use Marker-Quantitative Trait Loci Associations
“Theory of Index Selection”, Walsh & Lynch 1997
“Applications of Index Selection”, Walsh & Lynch 1997
“Selection Indices and Prediction of Genetic Merit in Animal Breeding”, Cameron 1997
Selection Indices and Prediction of Genetic Merit in Animal Breeding:
“Economic Aspects of Animal Breeding”, Weller 1994
“Economic Weights and Index Selection of Milk Production Traits When Multiple Production Quotas Apply”, Gibson 1989
Economic weights and index selection of milk production traits when multiple production quotas apply
“Selection Indices for Non-Linear Profit Functions”, Goddard 1983
“Index Selection for Genetic Improvement of Quantitative Characters”, Lin 1978
Index selection for genetic improvement of quantitative characters
“Multi-Stage Index Selection”, Cunningham 1975
“Restricted Selection Indices”, Kempthorne & Nordskog 1959
“The Optimum Emphasis on Dams’ Records When Proving Dairy Sires”, Lush 1944
The Optimum Emphasis on Dams’ Records When Proving Dairy Sires
“The Genetic Basis For Constructing Selection Indexes”, Hazel 1943b
“The Efficiency of 3 Methods of Selection”
“A Discriminant Function For Plant Selection”, Smith 1936
“Animal Breeding Plans, Lush 1943: How Selection Changes A Population', 'Selection For Many Characteristics At Once”
View External Link:
https://archive.org/details/animalbreedingpl032391mbp/page/n167/mode/2up
“Why a Pro/con List Is 75% As Good As Your Fancy Machine Learning Algorithm”
Why a pro/con list is 75% as good as your fancy machine learning algorithm:
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animal-breeding
breeding-economics
genomic-selection
Wikipedia
Miscellaneous
Bibliography
-
https://www.sciencedirect.com/science/article/pii/S0032579119394003: “25 Years of Selection for Improved Leg Health in Purebred Broiler Lines and Underlying Genetic Parameters”, -
https://www.theatlantic.com/technology/archive/2012/05/the-perfect-milk-machine-how-big-data-transformed-the-dairy-industry/256423/: “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”,