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| Registros recuperados : 4 | |
| 3. |  | HERD, R.M.; ARTHUR, P.F.; HEGARTY, R.S.; BIRD-GARDINER, T.; DONOGHUE, K.A.; VELAZCO, J.I. Predicting metabolisable energy intake by free-ranging cattle using multiple short-term breath samples and applied to a pasture case-study. (Article in Press) Animal Production Science, 4 Nov. 2020, 61(4), p. 381-389 Doi: https://doi.org/10.1071/AN20162 Article history: Received 3 April 2020, accepted 11 October 2020, published online 4 November 2020.| Biblioteca(s): INIA Treinta y Tres. |
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| 4. | | HERD, R. M.; VELAZCO, J.I.; SMITH, H.; ARTHUR, P. F.; HINE, B.; ODDY, H.; DOBOS, R. C.; HEGARTY, R. S. Genetic variation in residual feed intake is associated with body composition, behavior, rumen, heat production, hematology, and immune competence traits in Angus cattle. Journal of Animal Science: 2019, skz077, Corrected Proof, Available online 20 february 2019. In Press. Article history: Received: 05 November 2018//Revision Received: 04 February 2019// Accepted: 20 February 2019.| Biblioteca(s): INIA Treinta y Tres. |
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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 : |
04/10/2014 |
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Actualizado : |
10/02/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 2 |
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Autor : |
AGUILAR, I.; MISZTAL, I.; LEGARRA, A.; TSURUTA, S. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation. |
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Fecha de publicación : |
2011 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2011, v.128, no.6, p.422-428. |
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ISSN : |
0931-2668 |
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DOI : |
10.1111/j.1439-0388.2010.00912.x |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
Genomic evaluations can be calculated using a unified procedure that combines phenotypic, pedigree and genomic information. Implementation of such a procedure requires the inverse of the relationship matrix based on pedigree and genomic relationships. The objective of this study was to investigate efficient computing options to create relationship matrices based on genomic markers and pedigree information as well as their inverses. SNP maker information was simulated for a panel of 40K SNPs, with the number of genotyped animals up to 30000. Matrix multiplication in the computation of the genomic relationship was by a simple 'do' loop, by two optimized versions of the loop, and by a specific matrix multiplication subroutine. Inversion was by a generalized inverse algorithm and by a LAPACK subroutine. With the most efficient choices and parallel processing, creation of matrices for 30000 animals would take a few hours. Matrices required to implement a unified approach can be computed efficiently. Optimizations can be either by modifications of existing code or by the use of efficient automatic optimizations provided by open source or third-party libraries.
© 2011 Blackwell Verlag GmbH. |
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Thesagro : |
MEJORAMIENTO GENÉTICO ANIMAL; MODELOS MATEMÁTICOS; SELECCIÓN GENÓMICA. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
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024 7 $a10.1111/j.1439-0388.2010.00912.x$2DOI
100 1 $aAGUILAR, I.
245 $aEfficient computation of the genomic relationship matrix and other matrices used in single-step evaluation.$h[electronic resource]
260 $c2011
520 $aABSTRACT. Genomic evaluations can be calculated using a unified procedure that combines phenotypic, pedigree and genomic information. Implementation of such a procedure requires the inverse of the relationship matrix based on pedigree and genomic relationships. The objective of this study was to investigate efficient computing options to create relationship matrices based on genomic markers and pedigree information as well as their inverses. SNP maker information was simulated for a panel of 40K SNPs, with the number of genotyped animals up to 30000. Matrix multiplication in the computation of the genomic relationship was by a simple 'do' loop, by two optimized versions of the loop, and by a specific matrix multiplication subroutine. Inversion was by a generalized inverse algorithm and by a LAPACK subroutine. With the most efficient choices and parallel processing, creation of matrices for 30000 animals would take a few hours. Matrices required to implement a unified approach can be computed efficiently. Optimizations can be either by modifications of existing code or by the use of efficient automatic optimizations provided by open source or third-party libraries. © 2011 Blackwell Verlag GmbH.
650 $aMEJORAMIENTO GENÉTICO ANIMAL
650 $aMODELOS MATEMÁTICOS
650 $aSELECCIÓN GENÓMICA
700 1 $aMISZTAL, I.
700 1 $aLEGARRA, A.
700 1 $aTSURUTA, S.
773 $tJournal of Animal Breeding and Genetics, 2011$gv.128, no.6, p.422-428.
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