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Journal of Data Mining in Genomics & Proteomics
|
July 8, 2024
Large-Sample Genomic Data Mining for Quantitative Traits in U.S. Holstein Cows
Yang Da, Dzianis Prakapenka, Zuoxiang Liang
Frontiers in Genetics
|
October 31, 2022
Multifactorial methods integrating haplotype and epistasis effects for genomic estimation and prediction of quantitative traits
Yang Da, Zuoxiang Liang, Dzianis Prakapenka
International Journal of Molecular Sciences
|
April 28, 2023
Genome-Wide Association Study of Age at First Calving in U.S. Holstein Cows
Dzianis Prakapenka, Zuoxiang Liang, Yang Da
Biomolecules
|
October 28, 2023
Comparison of the Accuracy of Epistasis and Haplotype Models for Genomic Prediction of Seven Human Phenotypes
Zuoxiang Liang, Dzianis Prakapenka, Yang Da
International Journal of Molecular Sciences
|
June 26, 2025
Genomic Prediction and Heritability Estimation for Daughter Pregnancy Rate in U.S. Holstein Cows Using SNP, Epistasis and Haplotype Effects
Ruifei Yang, Dzianis Prakapenka, Zuoxiang Liang, et al.
Plos One
|
August 6, 2016
Genomic Inbreeding and Relatedness in Wild Panda Populations
John R Garbe, Dzianis Prakapenka, Cheng Tan, et al.
Genes
|
August 6, 2021
A Large-Scale Genome-Wide Association Study of Epistasis Effects of Production Traits and Daughter Pregnancy Rate in U.S. Holstein Cattle
Dzianis Prakapenka, Zuoxiang Liang, Jicai Jiang, et al.
International Journal of Molecular Sciences
|
November 27, 2025
Genome-Wide Association Study of Daughter Pregnancy Rate in Crossbred Dairy Cows
Ruifei Yang, Zuoxiang Liang, Dzianis Prakapenka, et al.
Frontiers in Genetics
|
December 16, 2020
Haplotype Analysis of Genomic Prediction Using Structural and Functional Genomic Information for Seven Human Phenotypes
Zuoxiang Liang, Cheng Tan, Dzianis Prakapenka, et al.
Frontiers in Genetics
|
April 23, 2020
GVCHAP: A Computing Pipeline for Genomic Prediction and Variance Component Estimation Using Haplotypes and SNP Markers
Dzianis Prakapenka, Chunkao Wang, Zuoxiang Liang, et al.
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Search research articles
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Showing results (1-10 of 21) with videos related to
Sort By:
Page
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Journal of Data Mining in Genomics & Proteomics
|
July 8, 2024
Large-Sample Genomic Data Mining for Quantitative Traits in U.S. Holstein Cows
Yang Da, Dzianis Prakapenka, Zuoxiang Liang
Frontiers in Genetics
|
October 31, 2022
Multifactorial methods integrating haplotype and epistasis effects for genomic estimation and prediction of quantitative traits
Yang Da, Zuoxiang Liang, Dzianis Prakapenka
International Journal of Molecular Sciences
|
April 28, 2023
Genome-Wide Association Study of Age at First Calving in U.S. Holstein Cows
Dzianis Prakapenka, Zuoxiang Liang, Yang Da
Biomolecules
|
October 28, 2023
Comparison of the Accuracy of Epistasis and Haplotype Models for Genomic Prediction of Seven Human Phenotypes
Zuoxiang Liang, Dzianis Prakapenka, Yang Da
International Journal of Molecular Sciences
|
June 26, 2025
Genomic Prediction and Heritability Estimation for Daughter Pregnancy Rate in U.S. Holstein Cows Using SNP, Epistasis and Haplotype Effects
Ruifei Yang, Dzianis Prakapenka, Zuoxiang Liang, et al.
Plos One
|
August 6, 2016
Genomic Inbreeding and Relatedness in Wild Panda Populations
John R Garbe, Dzianis Prakapenka, Cheng Tan, et al.
Genes
|
August 6, 2021
A Large-Scale Genome-Wide Association Study of Epistasis Effects of Production Traits and Daughter Pregnancy Rate in U.S. Holstein Cattle
Dzianis Prakapenka, Zuoxiang Liang, Jicai Jiang, et al.
International Journal of Molecular Sciences
|
November 27, 2025
Genome-Wide Association Study of Daughter Pregnancy Rate in Crossbred Dairy Cows
Ruifei Yang, Zuoxiang Liang, Dzianis Prakapenka, et al.
Frontiers in Genetics
|
December 16, 2020
Haplotype Analysis of Genomic Prediction Using Structural and Functional Genomic Information for Seven Human Phenotypes
Zuoxiang Liang, Cheng Tan, Dzianis Prakapenka, et al.
Frontiers in Genetics
|
April 23, 2020
GVCHAP: A Computing Pipeline for Genomic Prediction and Variance Component Estimation Using Haplotypes and SNP Markers
Dzianis Prakapenka, Chunkao Wang, Zuoxiang Liang, et al.
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of 3