Blar i Publikasjoner fra Cristin - NMBU på forfatter "Gangsei, Lars Erik"
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Building an in vivo anatomical atlas to close the phenomic gap in animal breeding
Gangsei, Lars Erik; Kongsro, Jørgen; Olstad, Kristin; Grindflek, Eli; Sæbø, Solve (Journal article; Peer reviewed, 2016) -
Classification of breed combinations for slaughter pigs based on genotypes—modeling DNA samples of crossbreeds as fuzzy sets from purebred founders
Vinje, Hilde; Brustad, Hilde Kjelgaard; Heggli, Andrew Russell; Sevillano, Claudia Alejandra; van Son, Maren; Gangsei, Lars Erik (Peer reviewed; Journal article, 2023) -
Effects of dietary beef, pork, chicken and salmon on intestinal carcinogenesis in A/J Min/+ mice
Steppeler, Christina; Sødring, Marianne Sundt; Egelandsdal, Bjørg Tordis; Kirkhus, Bente; Oostindjer, Marije; Alvseike, Ole; Gangsei, Lars Erik; Hovland, Ellen Margrethe; Pierre, Fabrice; Paulsen, Jan Erik (Journal article; Peer reviewed, 2017) -
Prediction precision for lean meat percentage in Norwegian pig carcasses using ‘Hennessy grading probe 7’: Evaluation of methods emphasized at exploiting additional information from computed tomography
Gangsei, Lars Erik; Kongsro, Jørgen; Olsen, Eli Vibeke; Røe, Morten; Alvseike, Ole; Sæbø, Solve (Journal article; Peer reviewed, 2016) -
A QTL for number of teats shows breed specific effects on number of vertebrae in pigs: Bridging the gap between molecular and quantitative genetics
van Son, Maren; Lopes, Marcos S; Martell, Henry J; Derks, Martijn F.L.; Gangsei, Lars Erik; Kongsro, Jørgen; Wass, Mark N.; Grindflek, Eli; Harlizius, Barbara (Peer reviewed; Journal article, 2019)Modern breeding schemes for livestock species accumulate a large amount of genotype and phenotype data which can be used for genome-wide association studies (GWAS). Many chromosomal regions harboring effects on quantitative ... -
Theoretical evaluation of prediction error in linear regression with a bivariate response variable containing missing data
Gangsei, Lars Erik; Almøy, Trygve; Sæbø, Solve (Peer reviewed; Journal article, 2017)Methods for linear regression with multivariate response variables are well described in statistical literature. In this study we conduct a theoretical evaluation of the expected squared prediction error in bivariate linear ...