- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1297-9686
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
The value of genomic relationship matrices to estimate levels of inbreeding ; volume:53 ; number:1 ; day:1 ; month:5 ; year:2021 ; pages:1-17 ; date:12.2021
Genetics, selection, evolution ; 53, Heft 1 (1.5.2021), 1-17, 12.2021
- Creator
-
Villanueva, Beatriz
Fernández, Almudena
Saura, María
Caballero, Armando
Fernández, Jesús
Morales-González, Elisabeth
Toro, Miguel A.
Pong-Wong, Ricardo
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s12711-021-00635-0
- URN
-
urn:nbn:de:101:1-2021102222460579155533
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:36 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Villanueva, Beatriz
- Fernández, Almudena
- Saura, María
- Caballero, Armando
- Fernández, Jesús
- Morales-González, Elisabeth
- Toro, Miguel A.
- Pong-Wong, Ricardo
- SpringerLink (Online service)
Other Objects (12)
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Assessment of inbreeding coefficients and inbreeding depression on complex traits from genomic and pedigree data in Nelore cattle
On the expected relationship between inbreeding, fitness, and extinction
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Population structure and genomic inbreeding in nine Swiss dairy cattle populations
Genomic patterns of homozygosity and inbreeding depression in Murciano-Granadina goats
Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
ICGRM: integrative construction of genomic relationship matrix combining multiple genomic regions for big dataset
A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction
Genomic selection requires genomic control of inbreeding
The use of relationship matrices to avoid inbreeding in small horse populations
Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle
Evaluating genomic inbreeding of two Chinese yak (Bos grunniens) populations
Assessment of inbreeding coefficients and inbreeding depression on complex traits from genomic and pedigree data in Nelore cattle
On the expected relationship between inbreeding, fitness, and extinction
Response and inbreeding from a genomic selection experiment in layer chickens
Population structure and genomic inbreeding in nine Swiss dairy cattle populations
Genomic patterns of homozygosity and inbreeding depression in Murciano-Granadina goats
Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
ICGRM: integrative construction of genomic relationship matrix combining multiple genomic regions for big dataset
A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction
Genomic selection requires genomic control of inbreeding
The use of relationship matrices to avoid inbreeding in small horse populations
Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle
Evaluating genomic inbreeding of two Chinese yak (Bos grunniens) populations
Assessment of inbreeding coefficients and inbreeding depression on complex traits from genomic and pedigree data in Nelore cattle
On the expected relationship between inbreeding, fitness, and extinction
Response and inbreeding from a genomic selection experiment in layer chickens
Population structure and genomic inbreeding in nine Swiss dairy cattle populations
Genomic patterns of homozygosity and inbreeding depression in Murciano-Granadina goats
Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information
ICGRM: integrative construction of genomic relationship matrix combining multiple genomic regions for big dataset