| OpenCMISS: a multi-physics & multi-scale computational infrastructure for the VPH/Physiome project C Bradley, A Bowery, R Britten, V Budelmann, O Camara, R Christie, ... Progress in biophysics and molecular biology 107 (1), 32-47, 2011 | 157 | 2011 |
| Effects of heterozygosity on performance of purebred and crossbred pigs MW Iversen, Ø Nordbø, E Gjerlaug-Enger, E Grindflek, MS Lopes, ... Genetics Selection Evolution 51, 1-13, 2019 | 65 | 2019 |
| Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds I van Den Berg, R Xiang, J Jenko, H Pausch, M Boussaha, C Schrooten, ... Genetics Selection Evolution 52, 1-16, 2020 | 49 | 2020 |
| Using markers with large effect in genetic and genomic predictions MS Lopes, H Bovenhuis, M Van Son, Ø Nordbø, EH Grindflek, EF Knol, ... Journal of animal science 95 (1), 59-71, 2017 | 44 | 2017 |
| Methodology for CO2 chain analysis JP Jakobsen, G Tangen, Ø Nordbø, MJ Mølnvik International Journal of Greenhouse Gas Control 2 (4), 439-447, 2008 | 27 | 2008 |
| Scenario for large-scale implementation of CCS in Europe T Wildenborg, P Coussy, A Doukelis, C Ekström, G Georgiou, ... Energy Procedia 1 (1), 4265-4272, 2009 | 22 | 2009 |
| Neural network firing-rate models on integral form: effects of temporal coupling kernels on equilibrium-state stability Ø Nordbø, J Wyller, GT Einevoll Biological Cybernetics 97, 195-209, 2007 | 22 | 2007 |
| A computational pipeline for quantification of mouse myocardial stiffness parameters Ø Nordbø, P Lamata, S Land, S Niederer, JM Aronsen, WE Louch, ... Computers in biology and medicine 53, 65-75, 2014 | 17 | 2014 |
| Optimized deep-learning-based method for cattle udder traits classification H Afridi, M Ullah, Ø Nordbø, FA Cheikh, AG Larsgard Mathematics 10 (17), 3097, 2022 | 13 | 2022 |
| Level-biases in estimated breeding values due to the use of different SNP panels over time in ssGBLUP Ø Nordbø, AB Gjuvsland, LS Eikje, T Meuwissen Genetics Selection Evolution 51, 1-8, 2019 | 12 | 2019 |
| Including crossbred pigs in the genomic relationship matrix through utilization of both linkage disequilibrium and linkage analysis MW Iversen, Ø Nordbø, E Gjerlaug-Enger, E Grindflek, MS Lopes, ... Journal of animal science 95 (12), 5197-5207, 2017 | 10 | 2017 |
| Genomic selection in pig breeding for improved meat quality E Gjerlaug-Enger, Ø Nordbø, E Grindflek Proceedings of the 10th World Congress of Genetics Applied to Livestock …, 2014 | 10 | 2014 |
| The genetic correlation between scapula shape and shoulder lesions in sows Ø Nordbø, LE Gangsei, T Aasmundstad, E Grindflek, J Kongsro Journal of Animal Science 96 (4), 1237-1245, 2018 | 9 | 2018 |
| Correcting for base-population differences and unknown parent groups in single-step genomic predictions of Norwegian Red cattle TK Belay, LS Eikje, AB Gjuvsland, Ø Nordbø, T Tribout, T Meuwissen Journal of Animal Science 100 (9), skac227, 2022 | 8 | 2022 |
| Tracking-by-self detection: A self-supervised framework for multiple animal tracking CB Dev Narayan, F Rahman, M Ullah, FA Cheikh, AS Imran, C Coello, ... IFIP International Conference on Artificial Intelligence Applications and …, 2023 | 6 | 2023 |
| The effect of including genomic relationships in the estimation of genetic parameters of functional traits in pigs T Aasmundstad, I Andersen‐Ranberg, Ø Nordbø, T Meuwissen, ... Journal of Animal Breeding and Genetics 132 (5), 386-391, 2015 | 6 | 2015 |
| Deep learning–based automated measurements of the scrotal circumference of Norwegian Red bulls from 3D images J Bremer, M Maj, Ø Nordbø, E Kommisrud Smart Agricultural Technology 3, 100133, 2023 | 5 | 2023 |
| Multi-encoder convolution block attention model for binary segmentation K Mamadou, M Ullah, Ø Nordbø, FA Cheikh 2022 International Conference on Frontiers of Information Technology (FIT …, 2022 | 4 | 2022 |
| Predicting survival and longevity of sows using purebred and crossbred data MW Iversen, Ø Nordbø, E Gjerlaug-Enger, E Grindflek, THE Meuwissen Translational Animal Science 4 (2), 993-1005, 2020 | 4 | 2020 |
| Deep learning based udder classification for cattle traits analysis H Afridi, M Ullah, Ø Nordbø, FA Cheikh Image 390, 2, 2022 | 3 | 2022 |
