Predicting complex quantitative traits with Bayesian neural networks: A case study with Jersey cows and wheat

BMC Genetics

Volumn 12, Issue , 2011, Pages

  Gianola, Daniel ^a,b   Okut, Hayrettin ^a,c   Weigel, Kent A ^a   Rosa, Guilherme J M ^a,b  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^c YUZUNCU YIL UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

MOLECULAR MARKER;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; COW; GENOMICS; GENOTYPE; INHERITANCE; MILK PRODUCTION; NONHUMAN; PEDIGREE; PHENOTYPE; PREDICTION; QUANTITATIVE TRAIT; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL MODEL; UNITED STATES; WHEAT; ANIMAL; BIOLOGICAL MODEL; CATTLE; GENETIC MARKER; GENETICS; MILK; REGRESSION ANALYSIS;

TRITICUM AESTIVUM;

ANIMALS; BAYES THEOREM; CATTLE; GENETIC MARKERS; GENOTYPE; MILK; MODELS, GENETIC; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT, HERITABLE; REGRESSION ANALYSIS; TRITICUM;

EID: 80053594474     PISSN: None     EISSN: 14712156     Source Type: Journal    
DOI: 10.1186/1471-2156-12-87     Document Type: Article

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