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 | Acesso ao texto completo restrito à biblioteca da Embrapa Suínos e Aves. Para informações adicionais entre em contato com cnpsa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
10/06/2016 |
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Data da última atualização: |
10/06/2016 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VENTURA, H. T.; SILVA, F. F e; VARONA, L.; FIGUEIREDO, E. A. P. de; COSTA, E. V.; SILVA, L. P. da; VENTURA. R.; LOPES, P. S. |
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Afiliação: |
HENRIQUE TORRES VENTURA, UFV/ABCZ; FABYANO FONSECA E SILVA, UFV; LUIZ VARONA, Universidad de Zaragoza; ELSIO ANTONIO PEREIRA DE FIGUEIREDO, CNPSA; EDSON VINÍCIUS COSTA, UFV; LUCIANO PINHEIRO DA SILVA, UFC; RICARDO VENTURA, University of Guelph; PAULO SÁVIO LOPES, UFV. |
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Título: |
Comparing multi-trait Poisson and Gaussian Bayesian models for genetic evaluation of litter traits in pigs. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
Livestock Science, v. 176, p. 47-53, 2015. |
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DOI: |
10.1016/j.livsci.2015.03.030 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Reproductive traits as number of piglets born (NPB) and weaned (NWP) are directly related to the economic efficiency of swine production systems. Pig breeding programs seek to increase the number of weaned piglets per sow per year, and the NPB is among the factors that directly and indirectly influence the NWP. Thus, multi-trait evaluations are essential to estimate heritabilities and mainly genetic correlations between these traits over different farrowing orders. In general, Gaussian linear mixed models have been used to genetic evaluation of litter traits; however since these traits are characterized as count variables, Poisson models are also indicated. Some studies were carried out using Poisson mixed models in the area of Animal Breeding and Genetics, but they do not point out for a multi-trait scenario, as it should be for litter size at birth and weaning. Toward this orientation, we aimed to apply a multi-trait Poisson mixed model (MPM) for the genetic evaluation of the number of born and weaned piglets under a Bayesian framework. It was aimed also to compare the proposed model with the traditional multi-trait Gaussian model (MGM) by using posterior based goodness-of-fit measures. Two-trait analyses for NPB and NWP were performed separately by each considered farrowing order (first, second and third) using MPM and MGM fitted to data from a commercial Landrace population. Based on DIC (Deviance Information Criterion) and PMP (Posterior Model Probability) values, the MGM outperformed the MPM, but the genetic parameter and breeding values provided by both models were consistent and similar over the three first farrowing orders. Bayesian generalized a multi-trait mixed model approach is feasible for genetic evaluations in the animal breeding context and can be an alternative method for genetic evaluations assuming non-Normal phenotypes. MenosAbstract: Reproductive traits as number of piglets born (NPB) and weaned (NWP) are directly related to the economic efficiency of swine production systems. Pig breeding programs seek to increase the number of weaned piglets per sow per year, and the NPB is among the factors that directly and indirectly influence the NWP. Thus, multi-trait evaluations are essential to estimate heritabilities and mainly genetic correlations between these traits over different farrowing orders. In general, Gaussian linear mixed models have been used to genetic evaluation of litter traits; however since these traits are characterized as count variables, Poisson models are also indicated. Some studies were carried out using Poisson mixed models in the area of Animal Breeding and Genetics, but they do not point out for a multi-trait scenario, as it should be for litter size at birth and weaning. Toward this orientation, we aimed to apply a multi-trait Poisson mixed model (MPM) for the genetic evaluation of the number of born and weaned piglets under a Bayesian framework. It was aimed also to compare the proposed model with the traditional multi-trait Gaussian model (MGM) by using posterior based goodness-of-fit measures. Two-trait analyses for NPB and NWP were performed separately by each considered farrowing order (first, second and third) using MPM and MGM fitted to data from a commercial Landrace population. Based on DIC (Deviance Information Criterion) and PMP (Posterior Model Probability) val... Mostrar Tudo |
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Thesagro: |
Genética animal; Melhoramento genético animal; Produção animal; Suíno. |
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Thesaurus Nal: |
Animal breeding; Animal genetics; Animal reproduction; Molecular genetics; Swine. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02837naa a2200325 a 4500
001 2046791
005 2016-06-10
008 2015 bl uuuu u00u1 u #d
024 7 $a10.1016/j.livsci.2015.03.030$2DOI
100 1 $aVENTURA, H. T.
245 $aComparing multi-trait Poisson and Gaussian Bayesian models for genetic evaluation of litter traits in pigs.$h[electronic resource]
260 $c2015
520 $aAbstract: Reproductive traits as number of piglets born (NPB) and weaned (NWP) are directly related to the economic efficiency of swine production systems. Pig breeding programs seek to increase the number of weaned piglets per sow per year, and the NPB is among the factors that directly and indirectly influence the NWP. Thus, multi-trait evaluations are essential to estimate heritabilities and mainly genetic correlations between these traits over different farrowing orders. In general, Gaussian linear mixed models have been used to genetic evaluation of litter traits; however since these traits are characterized as count variables, Poisson models are also indicated. Some studies were carried out using Poisson mixed models in the area of Animal Breeding and Genetics, but they do not point out for a multi-trait scenario, as it should be for litter size at birth and weaning. Toward this orientation, we aimed to apply a multi-trait Poisson mixed model (MPM) for the genetic evaluation of the number of born and weaned piglets under a Bayesian framework. It was aimed also to compare the proposed model with the traditional multi-trait Gaussian model (MGM) by using posterior based goodness-of-fit measures. Two-trait analyses for NPB and NWP were performed separately by each considered farrowing order (first, second and third) using MPM and MGM fitted to data from a commercial Landrace population. Based on DIC (Deviance Information Criterion) and PMP (Posterior Model Probability) values, the MGM outperformed the MPM, but the genetic parameter and breeding values provided by both models were consistent and similar over the three first farrowing orders. Bayesian generalized a multi-trait mixed model approach is feasible for genetic evaluations in the animal breeding context and can be an alternative method for genetic evaluations assuming non-Normal phenotypes.
650 $aAnimal breeding
650 $aAnimal genetics
650 $aAnimal reproduction
650 $aMolecular genetics
650 $aSwine
650 $aGenética animal
650 $aMelhoramento genético animal
650 $aProdução animal
650 $aSuíno
700 1 $aSILVA, F. F e
700 1 $aVARONA, L.
700 1 $aFIGUEIREDO, E. A. P. de
700 1 $aCOSTA, E. V.
700 1 $aSILVA, L. P. da
700 1 $aVENTURA. R.
700 1 $aLOPES, P. S.
773 $tLivestock Science$gv. 176, p. 47-53, 2015.
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Embrapa Suínos e Aves (CNPSA) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
08/01/2010 |
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Data da última atualização: |
15/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
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Autoria: |
CASTRO, A. de; FRONZA, C. F.; HERAI, R. H.; ALVES, D. |
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Afiliação: |
ALEXANDRE DE CASTRO, CNPTIA; CARLOS F. FRONZA, Unifesp; ROBERTO HIROCHI HERAI, IB/Unicamp; DOMINGOS ALVES, USP. |
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Título: |
Evidence of deterministic evolution in the immunological memory process. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: INTERNATIONAL SYMPOSIUM ON MATHEMATICAL AND COMPUTATIONAL BIOLOGY, 9., 2009, Brasília, DF. Proceedings... Brasília, DF: BIOMAT Institute for Advanced Studies of Biosystems, 2009. |
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Páginas: |
p. 1-14. |
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DOI: |
10.1142/9789814304900_0004 |
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Idioma: |
Inglês |
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Conteúdo: |
In this paper, we study the behavior of immune memory against antigenic mutation. Using a dynamic model proposed by one of the authors in a previous study, we have performed simulations of several inoculations, where in each virtual sample the viral population undergo mutations. Our results suggest that the sustainability of the immunizations is dependent on viral variability and that the memory lifetimes are not random, what condradicts what was suggested by Tarlinton et al.. We show that what may cause an apparent random behavior of the immune memory is the antigenic variability. |
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Palavras-Chave: |
Evolução determinística; Memória imunológica; Mutação antigênica. |
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Thesagro: |
Mutação. |
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Thesaurus NAL: |
Memory; Mutation. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 01420nam a2200241 a 4500
001 1580026
005 2020-01-15
008 2009 bl uuuu u00u1 u #d
024 7 $a10.1142/9789814304900_0004$2DOI
100 1 $aCASTRO, A. de
245 $aEvidence of deterministic evolution in the immunological memory process.$h[electronic resource]
260 $aIn: INTERNATIONAL SYMPOSIUM ON MATHEMATICAL AND COMPUTATIONAL BIOLOGY, 9., 2009, Brasília, DF. Proceedings... Brasília, DF: BIOMAT Institute for Advanced Studies of Biosystems$c2009
300 $ap. 1-14.
520 $aIn this paper, we study the behavior of immune memory against antigenic mutation. Using a dynamic model proposed by one of the authors in a previous study, we have performed simulations of several inoculations, where in each virtual sample the viral population undergo mutations. Our results suggest that the sustainability of the immunizations is dependent on viral variability and that the memory lifetimes are not random, what condradicts what was suggested by Tarlinton et al.. We show that what may cause an apparent random behavior of the immune memory is the antigenic variability.
650 $aMemory
650 $aMutation
650 $aMutação
653 $aEvolução determinística
653 $aMemória imunológica
653 $aMutação antigênica
700 1 $aFRONZA, C. F.
700 1 $aHERAI, R. H.
700 1 $aALVES, D.
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