Search Results - "Pocrnić, Ivan"

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  1. 1

    Genomic Characterization of Local Croatian Sheep Breeds-Effective Population Size, Inbreeding & Signatures of Selection by Ramljak, Jelena, Špehar, Marija, Ceranac, Dora, Držaić, Valentino, Pocrnić, Ivan, Barać, Dolores, Mioč, Boro, Širić, Ivan, Barać, Zdravko, Ivanković, Ante, Kasap, Ante

    Published in Animals (Basel) (29-06-2024)
    “…The Istrian (IS) and the Pag sheep (PS) are local Croatian breeds which provide significant income for the regional economy and have a cultural and traditional…”
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    Journal Article
  2. 2

    Novel combination of CRISPR-based gene drives eliminates resistance and localises spread by Faber, Nicky R., McFarlane, Gus R., Gaynor, R. Chris, Pocrnic, Ivan, Whitelaw, C. Bruce A., Gorjanc, Gregor

    Published in Scientific reports (04-03-2021)
    “…Invasive species are among the major driving forces behind biodiversity loss. Gene drive technology may offer a humane, efficient and cost-effective method of…”
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  3. 3

    Optimisation of the core subset for the APY approximation of genomic relationships by Pocrnic, Ivan, Lindgren, Finn, Tolhurst, Daniel, Herring, William O, Gorjanc, Gregor

    Published in Genetics selection evolution (Paris) (22-11-2022)
    “…By entering the era of mega-scale genomics, we are facing many computational issues with standard genomic evaluation models due to their dense data structure…”
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  4. 4

    Assessment of long-term trends in genetic mean and variance after the introduction of genomic selection in layers: a simulation study by Pocrnic, Ivan, Obšteter, Jana, Gaynor, R Chris, Wolc, Anna, Gorjanc, Gregor

    Published in Frontiers in genetics (10-05-2023)
    “…Nucleus-based breeding programs are characterized by intense selection that results in high genetic gain, which inevitably means reduction of genetic variation…”
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  5. 5

    Inheritance of the birth weights in crosses between Istrian, Awassi, East-Friesian and Travnik Pramenka sheep in Croatia: a case study by Pocrnic, Ivan, Dzidic, Alen

    Published in Journal of Central European agriculture (01-01-2021)
    “…The purpose of the study was to estimate the influence of the additive and non-additive genetic effects on the birth weight, using two different crossbreed…”
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  6. 6

    Temporal and genomic analysis of additive genetic variance in breeding programmes by Lara, Letícia A de C, Pocrnic, Ivan, Oliveira, Thiago de P, Gaynor, R Chris, Gorjanc, Gregor

    Published in Heredity (01-01-2022)
    “…Genetic variance is a central parameter in quantitative genetics and breeding. Assessing changes in genetic variance over time as well as the genome is…”
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  7. 7

    A method for partitioning trends in genetic mean and variance to understand breeding practices by Oliveira, Thiago P, Obšteter, Jana, Pocrnic, Ivan, Heslot, Nicolas, Gorjanc, Gregor

    Published in Genetics selection evolution (Paris) (02-06-2023)
    “…In breeding programmes, the observed genetic change is a sum of the contributions of different selection paths represented by groups of individuals…”
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  8. 8

    Accuracy of genomic BLUP when considering a genomic relationship matrix based on the number of the largest eigenvalues: a simulation study by Pocrnic, Ivan, Lourenco, Daniela A L, Masuda, Yutaka, Misztal, Ignacy

    Published in Genetics selection evolution (Paris) (12-12-2019)
    “…The dimensionality of genomic information is limited by the number of independent chromosome segments (M ), which is a function of the effective population…”
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  9. 9

    Single nucleotide polymorphism profile for quantitative trait nucleotide in populations with small effective size and its impact on mapping and genomic predictions by Pocrnic, Ivan, Lourenco, Daniela, Misztal, Ignacy

    Published in Genetics (Austin) (07-08-2024)
    “…Abstract Increasing SNP density by incorporating sequence information only marginally increases prediction accuracies of breeding values in livestock. To find…”
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  10. 10

    40 Factors Influencing Accuracy of Genomic Selection with Sequence Information by Misztal, Ignacy, Pocrnic, Ivan, Lourenco, Daniela

    Published in Journal of animal science (01-11-2021)
    “…Abstract Incorporating the sequence information only marginally increases the accuracy of genomic selection. The purpose of this study was to find out why by…”
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  11. 11
  12. 12

    Core-dependent changes in genomic predictions using the Algorithm for Proven and Young in single-step genomic best linear unbiased prediction by Misztal, Ignacy, Tsuruta, Shogo, Pocrnic, Ivan, Lourenco, Daniela

    Published in Journal of animal science (01-12-2020)
    “…Abstract Single-step genomic best linear unbiased prediction with the Algorithm for Proven and Young (APY) is a popular method for large-scale genomic…”
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  13. 13

    Quantifying the effects of the mitochondrial genome on milk production traits in dairy cows: empirical results and modelling challenges by Brajkovic, Vladimir, Pocrnic, Ivan, Kaps, Miroslav, Špehar, Marija, Cubric-Curik, Vlatka, Ristov, Strahil, Novosel, Dinko, Gorjanc, Gregor, Curik, Ino

    Published in Journal of dairy science (14-10-2024)
    “…Significant advances in livestock traits have been achieved primarily through selection strategies targeting variation in the nuclear genome, with little…”
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  14. 14

    334 Investigating core-dependent changes in predictions using the algorithm for proven and young in ssGBLUP by Lourenco, Daniela, Tsuruta, Shogo, Pocrnic, Ivan, Misztal, Ignacy

    Published in Journal of animal science (05-12-2019)
    “…Abstract Large-scale single-step GBLUP (ssGBLUP) evaluations rely on techniques to approximate or avoid the inversion of the genomic relationship matrix (G)…”
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  15. 15

    Investigating core-dependent changes in predictions using the algorithm for proven and young in ssGBLUP by Lourenco, Daniela, Tsuruta, Shogo, Pocrnic, Ivan, Misztal, Ignacy

    Published in Journal of animal science (01-12-2019)
    “…Large-scale single-step GBLUP (ssGBLUP) evaluations rely on techniques to approximate or avoid the inversion of the genomic relationship matrix (G). The…”
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  16. 16

    The Dimensionality of Genomic Information and Its Effect on Genomic Prediction by Pocrnic, Ivan, Lourenco, Daniela A L, Masuda, Yutaka, Legarra, Andres, Misztal, Ignacy

    Published in Genetics (Austin) (01-05-2016)
    “…The genomic relationship matrix (GRM) can be inverted by the algorithm for proven and young (APY) based on recursion on a random subset of animals. While a…”
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  17. 17

    208 Crossbred evaluations using single-step genomic BLUP and algorithm for proven and young with different sources of data by Pocrnic, Ivan, Lourenco, Daniela, Chen, Ching-Yi, Herring, William O, Misztal, Ignacy

    Published in Journal of animal science (05-12-2019)
    “…Abstract Genomic selection is routinely applied to many purebred farm species but can be extended to predictions across purebreds as well as for crossbreds…”
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  18. 18

    Crossbred evaluations using single-step genomic BLUP and algorithm for proven and young with different sources of data by Pocrnic, Ivan, Lourenco, Daniela, Chen, Ching-Yi, Herring, William O, Misztal, Ignacy

    Published in Journal of animal science (01-12-2019)
    “…Genomic selection is routinely applied to many purebred farm species but can be extended to predictions across purebreds as well as for crossbreds. This is…”
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    Journal Article
  19. 19

    Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species by Pocrnic, Ivan, Lourenco, Daniela A L, Masuda, Yutaka, Misztal, Ignacy

    Published in Genetics selection evolution (Paris) (31-10-2016)
    “…A genomic relationship matrix (GRM) can be inverted efficiently with the Algorithm for Proven and Young (APY) through recursion on a small number of core…”
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  20. 20

    Crossbred evaluations using single-step genomic BLUP and algorithm for proven and young with different sources of data1 by Pocrnic, Ivan, Lourenco, Daniela A L, Chen, Ching-Yi, Herring, William O, Misztal, Ignacy

    Published in Journal of animal science (03-04-2019)
    “…Abstract Genomic selection (GS) is routinely applied to many purebreds and lines of farm species. However, this method can be extended to predictions across…”
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