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| Registros recuperados : 224 | |
| 81. |  | NEGRI, R.; AGUILAR, I.; FELTES, G. L.; COBUCI, J. A. Selection for test-day milk yield and thermotolerance in brazilian holstein cattle. Animals, January 2021, Volume 11, Issue 1, Article number 128, Pages 1-13. OPEN ACCESS. Doi: https://doi.org/10.3390/ani11010128 Article history: Received 16 November 2020; Accepted 29 December 2020; Published 8 January 2021.
Corresponding author: Negri, R.; Department of Animal Science, Federal University of Rio Grande do Sul, Porto Alegre, Brazil;...| Biblioteca(s): INIA Las Brujas. |
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| 83. | | MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. Technical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements. Journal of Animal Science, 2015, v. 93, p. 4670 - 4674. Published October 9, 2015 Article history: Received June 8, 2015.; Accepted August 7, 2015.
1. We acknowledge the work by François Guillaume in programming a hash function. We greatly appreciate the work of the two anonymous reviewers.
2. The AIREMLF90 program...| Biblioteca(s): INIA Las Brujas. |
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| 87. | | ZHANG, X.; LOURENCO, D.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A. Weighted single-step genomic BLUP: an iterative approach for accurate calculation of GEBV and GWAS. Volume Methods and Tools: Statistical and genomic tools for mapping QTL and genes (Posters), 681. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.681.| Biblioteca(s): INIA Las Brujas. |
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| 88. | | ZHANG, X.; LOURENCO, D.; AGUILAR, I.; LEGARRA, A.; MISZTAL, I. Weighting strategies for single-step genomic BLUP: An iterative approach for accurate calculation of GEBV and GWAS. Frontiers in Genetics, 19 August 2016, Volume 7, Issue AUG, Article number 151. OPEN ACCESS Article history: Received 15 May 2016 // Accepted 04 August 2016 // Published 19 August 2016.
Specialty section:
This article was submitted to Statistical Genetics and Methodology, a section of the journal Frontiers in Genetics.| Biblioteca(s): INIA Las Brujas. |
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| 92. | | LOURENCO, D; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LAWLOR, T. J.; WELLER, J. I. Are evaluations on young genotyped dairy bulls benefiting from the past generations? [conference paper]. Volume Species Breeding: Dairy cattle, 297. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.297.| Biblioteca(s): INIA Las Brujas. |
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| 95. | | LEMA, O.M.; BRITO, G.; CLARIGET, J.; PEREZ, E.; RAVAGNOLO, O.; AGUILAR, I.; MONTOSSI, F. Dos años de evaluación de ganancia diaria invernal de terneros con paternidad conocida y su efecto sobre la recría
y terminación. In: CONGRESO ARGENTINO DE PRODUCCIÓN ANIMAL, 38., 2015. Resúmenes. Santa Rosa, La Pampa, AR: ASAS/AAPA, 2015 Revista Argentina de Producción Animal, 2015, v.35, Supl.1, p.62| Biblioteca(s): INIA La Estanzuela; INIA Treinta y Tres. |
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| 98. | | NAVAJAS, E.; MACEDO, F.; LEMA, O.M.; LUZARDO, S.; AGUILAR, I. Accuracy of genomic predictions for carcass and meat quality traits in the Uruguayan Hereford breed. Volume Species - Bovine (beef) 1, p. 636. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018. 6 p. Acknowledgements: This work was supported by the Agencia Nacional de Investigación e Innovación (ANII) (grants RTS_1_2012_1_3489 and FMV_1_2011_1_6671), Instituto Nacional de Investigación Agropecuaria (INIA), Sociedad de Criadores de...| Biblioteca(s): INIA Las Brujas. |
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| 99. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Accuracy of indirect predictions for large datasets based on prediction error covariance of SNP effects from single-step GBLUP. [abstract 22]. Issue Section: Animal Breeding and Genetics. Journal of Animal Science, 2020, Volume 98, Issue Supplement 4, Pages 6-7. doi: https://doi.org/10.1093/jas/skaa278.012 Article history: 30 November 2020.
ASAS Annual 2020 Meeting Abstracts.| Biblioteca(s): INIA Las Brujas. |
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| 100. | | LEGARRA, A.; CHRISTENSEN, O. F.; VITEZICA, Z. G.; AGUILAR, I.; MISZTAL, I. Across-breeds ancestral relationships and metafounders for genomic evaluation. Volume Genetic Improvement Programs: Selection using molecular information, 075. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.075. Acknowledgements: This project has been financed by X-Gen and GenSSeq actions from SelGen metaprogram (INRA). We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees for providing computing resources.| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 224 | |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
26/11/2015 |
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Actualizado : |
25/11/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. |
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Afiliación : |
Y. MASUDA, Universidad de Georgia (UG); Obihiro University of Agriculture and Veterinary Medicine (Japón); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SHOGO TSURUTA, Universidad de Georgia (UG); IGNACY MISZTAL, Universidad de Georgia (UG). |
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Título : |
Technical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Journal of Animal Science, 2015, v. 93, p. 4670 - 4674. Published October 9, 2015 |
|
DOI : |
10.2527/jas.2015-9395 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received June 8, 2015.; Accepted August 7, 2015.
1. We acknowledge the work by François Guillaume in programming a hash function. We greatly appreciate the work of the two anonymous reviewers.
2. The AIREMLF90 program with a sparse package YAMS, along with a manual, is available at http://nce.ads.uga.edu. The YAMS package is available on request for academic or noncommercial purposes by contacting the corresponding author. |
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Contenido : |
ABSTRACT.
The objective of this study was to remove bottlenecks generally found in a computer program for average-information REML. The refinements included improvements to setting-up mixed-model equations on a hash table with a faster hash function as sparse matrix storage, changing sparse structures in calculation of traces, and replacing a sparse matrix
package using traditional methods (FSPAK) with a new package using supernodal methods (YAMS); the latter package quickly processed sparse matrices containing large, dense blocks. Comparisons included 23 models with data sets from broiler, swine, beef, and dairy cattle. Models included single-trait, multiple-trait, maternal, and random regression models with phenotypic data; selected models used genomic information in a singlestep approach. Setting-up mixed model equations was completed without abnormal termination in all analyses. Calculations in traces were accelerated with a hash format, especially for models with a genomic relationship matrix, and the maximum speed was 67 times faster. Computations with YAMS were, on average, more than 10 times faster than with FSPAK and had greater advantages for large data and more complicated models including multiple traits, random regressions, and genomic effects. These refinements can be applied to general average-information REML programs.
© 2015 American Society of Animal Science. All rights reserved. |
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Palabras claves : |
AVERAGE-INFORMATION REML; HASH FORMAT; SPARSE MATRIX; SPARSE PACKAGES. |
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Thesagro : |
MODELOS DE SIMULACIÓN. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02649naa a2200241 a 4500
001 1054007
005 2019-11-25
008 2015 bl uuuu u00u1 u #d
024 7 $a10.2527/jas.2015-9395$2DOI
100 1 $aMASUDA, Y.
245 $aTechnical note$bAcceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements.$h[electronic resource]
260 $c2015
500 $aArticle history: Received June 8, 2015.; Accepted August 7, 2015. 1. We acknowledge the work by François Guillaume in programming a hash function. We greatly appreciate the work of the two anonymous reviewers. 2. The AIREMLF90 program with a sparse package YAMS, along with a manual, is available at http://nce.ads.uga.edu. The YAMS package is available on request for academic or noncommercial purposes by contacting the corresponding author.
520 $aABSTRACT. The objective of this study was to remove bottlenecks generally found in a computer program for average-information REML. The refinements included improvements to setting-up mixed-model equations on a hash table with a faster hash function as sparse matrix storage, changing sparse structures in calculation of traces, and replacing a sparse matrix package using traditional methods (FSPAK) with a new package using supernodal methods (YAMS); the latter package quickly processed sparse matrices containing large, dense blocks. Comparisons included 23 models with data sets from broiler, swine, beef, and dairy cattle. Models included single-trait, multiple-trait, maternal, and random regression models with phenotypic data; selected models used genomic information in a singlestep approach. Setting-up mixed model equations was completed without abnormal termination in all analyses. Calculations in traces were accelerated with a hash format, especially for models with a genomic relationship matrix, and the maximum speed was 67 times faster. Computations with YAMS were, on average, more than 10 times faster than with FSPAK and had greater advantages for large data and more complicated models including multiple traits, random regressions, and genomic effects. These refinements can be applied to general average-information REML programs. © 2015 American Society of Animal Science. All rights reserved.
650 $aMODELOS DE SIMULACIÓN
653 $aAVERAGE-INFORMATION REML
653 $aHASH FORMAT
653 $aSPARSE MATRIX
653 $aSPARSE PACKAGES
700 1 $aAGUILAR, I.
700 1 $aTSURUTA, S.
700 1 $aMISZTAL, I.
773 $tJournal of Animal Science, 2015$gv. 93, p. 4670 - 4674. Published October 9, 2015
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