TY - JOUR AU - Pérez-Enciso, M. AU - Rincón, J. C. AU - Legarra, A. PY - 2015 DA - 2015// TI - Sequence- vs. chip-assisted genomic selection: accurate biological information is advised JO - Genet Sel Evol. VL - 47 UR - https://doi.org/10.1186/s12711-015-0117-5 DO - 10.1186/s12711-015-0117-5 ID - Pérez-Enciso2015 ER - TY - JOUR AU - Binsbergen, R. AU - Calus, M. P. L. AU - Bink, M. C. A. M. AU - Eeuwijk, F. A. AU - Schrooten, C. AU - Veerkamp, R. F. PY - 2015 DA - 2015// TI - Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle JO - Genet Sel Evol. VL - 47 UR - https://doi.org/10.1186/s12711-015-0149-x DO - 10.1186/s12711-015-0149-x ID - Binsbergen2015 ER - TY - JOUR AU - Houle, D. AU - Govindaraju, D. R. AU - Omholt, S. PY - 2010 DA - 2010// TI - Phenomics: the next challenge JO - Nat Rev Genet VL - 11 UR - https://doi.org/10.1038/nrg2897 DO - 10.1038/nrg2897 ID - Houle2010 ER - TY - JOUR AU - Mahner, M. AU - Kary, M. PY - 1997 DA - 1997// TI - What exactly are genomes, genotypes and phenotypes? And what about phenomes? JO - J Theor Biol VL - 186 UR - https://doi.org/10.1006/jtbi.1996.0335 DO - 10.1006/jtbi.1996.0335 ID - Mahner1997 ER - TY - JOUR AU - Brito, L. F. AU - Oliveira, H. R. AU - McConn, B. R. AU - Schinckel, A. P. AU - Arrazola, A. AU - Marchant-Forde, J. N. PY - 2020 DA - 2020// TI - Large-scale phenotyping of livestock welfare in commercial production systems: a new frontier in animal breeding JO - Front Genet. VL - 11 UR - https://doi.org/10.3389/fgene.2020.00793 DO - 10.3389/fgene.2020.00793 ID - Brito2020 ER - TY - JOUR AU - Rosenfeld, A. PY - 1993 DA - 1993// TI - Image analysis and computer vision: 1992 JO - CVGIP Image Underst. VL - 58 UR - https://doi.org/10.1006/ciun.1993.1033 DO - 10.1006/ciun.1993.1033 ID - Rosenfeld1993 ER - TY - JOUR AU - Berghof, T. V. L. AU - Poppe, M. AU - Mulder, H. A. PY - 2019 DA - 2019// TI - Opportunities to improve resilience in animal breeding programs JO - Front Genet. VL - 9 UR - https://doi.org/10.3389/fgene.2018.00692 DO - 10.3389/fgene.2018.00692 ID - Berghof2019 ER - TY - JOUR AU - Pooley, C. M. AU - Marion, G. AU - Bishop, S. C. AU - Bailey, R. I. AU - Doeschl-Wilson, A. B. PY - 2020 DA - 2020// TI - Estimating individuals’ genetic and non-genetic effects underlying infectious disease transmission from temporal epidemic data JO - PLoS Comput Biol VL - 16 UR - https://doi.org/10.1371/journal.pcbi.1008447 DO - 10.1371/journal.pcbi.1008447 ID - Pooley2020 ER - TY - JOUR AU - Koltes, J. E. AU - Cole, J. B. AU - Clemmens, R. AU - Dilger, R. N. AU - Kramer, L. M. AU - Lunney, J. K. PY - 2019 DA - 2019// TI - A vision for development and utilization of high-throughput phenotyping and big data analytics in livestock JO - Front Genet. VL - 10 UR - https://doi.org/10.3389/fgene.2019.01197 DO - 10.3389/fgene.2019.01197 ID - Koltes2019 ER - TY - JOUR AU - Baes, C. AU - Schenkel, F. PY - 2020 DA - 2020// TI - The future of phenomics JO - Anim Front. VL - 10 UR - https://doi.org/10.1093/af/vfaa013 DO - 10.1093/af/vfaa013 ID - Baes2020 ER - TY - JOUR AU - Rexroad, C. AU - Vallet, J. AU - Matukumalli, L. K. AU - Reecy, J. AU - Bickhart, D. AU - Blackburn, H. PY - 2019 DA - 2019// TI - Genome to phenome: improving animal health, production, and well-being—a new USDA blueprint for animal genome research 2018–2027 JO - Front Genet. VL - 10 UR - https://doi.org/10.3389/fgene.2019.00327 DO - 10.3389/fgene.2019.00327 ID - Rexroad2019 ER - TY - JOUR AU - Cole, J. B. AU - Eaglen, S. A. E. AU - Maltecca, C. AU - Mulder, H. A. AU - Pryce, J. E. PY - 2020 DA - 2020// TI - The future of phenomics in dairy cattle breeding JO - Anim Front. VL - 10 UR - https://doi.org/10.1093/af/vfaa007 DO - 10.1093/af/vfaa007 ID - Cole2020 ER - TY - JOUR AU - Bijma, P. PY - 2014 DA - 2014// TI - The quantitative genetics of indirect genetic effects: a selective review of modelling issues JO - Heredity VL - 122 UR - https://doi.org/10.1038/hdy.2013.15 DO - 10.1038/hdy.2013.15 ID - Bijma2014 ER - TY - JOUR AU - Turner, S. P. AU - D’Eath, R. B. AU - Roehe, R. AU - Lawrence, A. B. PY - 2010 DA - 2010// TI - Selection against aggressiveness in pigs at re-grouping: practical application and implications for long-term behavioural patterns JO - Anim Welf VL - 19 UR - https://doi.org/10.1017/S0962728600002323 DO - 10.1017/S0962728600002323 ID - Turner2010 ER - TY - JOUR AU - Chen, C. AU - Zhu, W. AU - Steibel, J. AU - Siegford, J. AU - Wurtz, K. AU - Han, J. PY - 2020 DA - 2020// TI - Recognition of aggressive episodes of pigs based on convolutional neural network and long short-term memory JO - Comput Electron Agric. VL - 169 UR - https://doi.org/10.1016/j.compag.2019.105166 DO - 10.1016/j.compag.2019.105166 ID - Chen2020 ER - TY - JOUR AU - Brown-Brandl, T. M. AU - Rohrer, G. A. AU - Eigenberg, R. A. PY - 2013 DA - 2013// TI - Analysis of feeding behavior of group housed growing-finishing pigs JO - Comput Electron Agric. VL - 96 UR - https://doi.org/10.1016/j.compag.2013.06.002 DO - 10.1016/j.compag.2013.06.002 ID - Brown-Brandl2013 ER - TY - JOUR AU - Fernandes, A. F. A. AU - Dórea, J. R. R. AU - Rosa, G. J. PY - 2020 DA - 2020// TI - Image analysis and computer vision applications in animal sciences: an overview JO - Front Vet Sci. VL - 7 UR - https://doi.org/10.3389/fvets.2020.551269 DO - 10.3389/fvets.2020.551269 ID - Fernandes2020 ER - TY - JOUR AU - Turner, S. P. PY - 2011 DA - 2011// TI - Breeding against harmful social behaviours in pigs and chickens: state of the art and the way forward JO - Appl Anim Behav Sci VL - 134 UR - https://doi.org/10.1016/j.applanim.2011.06.001 DO - 10.1016/j.applanim.2011.06.001 ID - Turner2011 ER - TY - JOUR AU - Angarita, B. K. AU - Cantet, R. J. C. AU - Wurtz, K. E. AU - O’Malley, C. I. AU - Siegford, J. M. AU - Ernst, C. W. PY - 2019 DA - 2019// TI - Estimation of indirect social genetic effects for skin lesion count in group-housed pigs by quantifying behavioral interactions JO - J Anim Sci VL - 97 UR - https://doi.org/10.1093/jas/skz244 DO - 10.1093/jas/skz244 ID - Angarita2019 ER - TY - JOUR AU - Foister, S. AU - Doeschl-Wilson, A. AU - Roehe, R. AU - Arnott, G. AU - Boyle, L. AU - Turner, S. PY - 2018 DA - 2018// TI - Social network properties predict chronic aggression in commercial pig systems JO - PLoS ONE VL - 13 UR - https://doi.org/10.1371/journal.pone.0205122 DO - 10.1371/journal.pone.0205122 ID - Foister2018 ER - TY - JOUR AU - Lassen, J. AU - Løvendahl, P. PY - 2016 DA - 2016// TI - Heritability estimates for enteric methane emissions from Holstein cattle measured using noninvasive methods JO - J Dairy Sci VL - 99 UR - https://doi.org/10.3168/jds.2015-10012 DO - 10.3168/jds.2015-10012 ID - Lassen2016 ER - TY - JOUR AU - Negussie, E. AU - Lehtinen, J. AU - Mäntysaari, P. AU - Bayat, A. R. AU - Liinamo, A. E. AU - Mäntysaari, E. A. PY - 2017 DA - 2017// TI - Non-invasive individual methane measurement in dairy cows JO - Animal. VL - 11 UR - https://doi.org/10.1017/S1751731116002718 DO - 10.1017/S1751731116002718 ID - Negussie2017 ER - TY - JOUR AU - Lu, D. AU - Jiao, S. AU - Tiezzi, F. AU - Knauer, M. AU - Huang, Y. AU - Gray, K. A. PY - 2017 DA - 2017// TI - The relationship between different measures of feed efficiency and feeding behavior traits in Duroc pigs JO - J Anim Sci VL - 95 ID - Lu2017 ER - TY - JOUR AU - Casey, D. S. AU - Stern, H. S. AU - Dekkers, J. C. M. PY - 2005 DA - 2005// TI - Identification of errors and factors associated with errors in data from electronic swine feeders JO - J Anim Sci VL - 83 UR - https://doi.org/10.2527/2005.835969x DO - 10.2527/2005.835969x ID - Casey2005 ER - TY - JOUR AU - Ragab, M. AU - Piles, M. AU - Quintanilla, R. AU - Sánchez, J. P. PY - 2019 DA - 2019// TI - Indirect genetic effect model using feeding behaviour traits to define the degree of interaction between mates: an implementation in pigs growth rate JO - Animal. VL - 13 UR - https://doi.org/10.1017/S1751731118001192 DO - 10.1017/S1751731118001192 ID - Ragab2019 ER - TY - JOUR AU - Nye, J. AU - Zingaretti, L. M. AU - Pérez-Enciso, M. PY - 2020 DA - 2020// TI - Estimating conformational traits in dairy cattle with DeepAPS: a two-step deep learning automated phenotyping and segmentation approach JO - Front Genet. VL - 11 UR - https://doi.org/10.3389/fgene.2020.00513 DO - 10.3389/fgene.2020.00513 ID - Nye2020 ER - TY - JOUR AU - Psota, E. T. AU - Mittek, M. AU - Pérez, L. C. AU - Schmidt, T. AU - Mote, B. PY - 2019 DA - 2019// TI - Multi-pig part detection and association with a fully-convolutional network JO - Sensors. VL - 19 UR - https://doi.org/10.3390/s19040852 DO - 10.3390/s19040852 ID - Psota2019 ER - TY - JOUR AU - Chen, C. AU - Zhu, W. AU - Steibel, J. AU - Siegford, J. AU - Han, J. AU - Norton, T. PY - 2020 DA - 2020// TI - Recognition of feeding behaviour of pigs and determination of feeding time of each pig by a video-based deep learning method JO - Comput Electron Agric. VL - 176 UR - https://doi.org/10.1016/j.compag.2020.105642 DO - 10.1016/j.compag.2020.105642 ID - Chen2020 ER - TY - STD TI - Thomasen JR, Lassen J, Nielsen GGB, Borggard C, Stentebjerg PRB, Hansen RH, et al. Individual cow identification in a commercial herd using 3D camera technology. In: Proceedings of the 11th World Congress on Genetics Applied to Livestock Production: 7–11 February 2018; Auckland. 2018. ID - ref29 ER - TY - JOUR AU - Cardoso, F. F. AU - Tempelman, R. J. PY - 2003 DA - 2003// TI - Bayesian inference on genetic merit under uncertain paternity JO - Genet Sel Evol. VL - 33 UR - https://doi.org/10.1186/1297-9686-35-6-469 DO - 10.1186/1297-9686-35-6-469 ID - Cardoso2003 ER - TY - JOUR AU - Cardoso, F. F. AU - Tempelman, R. J. PY - 2004 DA - 2004// TI - Genetic evaluation of beef cattle accounting for uncertain paternity JO - Livest Prod Sci. VL - 89 UR - https://doi.org/10.1016/j.livprodsci.2004.02.006 DO - 10.1016/j.livprodsci.2004.02.006 ID - Cardoso2004 ER - TY - JOUR AU - Perez-Enciso, M. AU - Fernando, R. L. PY - 1992 DA - 1992// TI - Genetic evaluation with uncertain parentage: a comparison of methods JO - Theor Appl Genet VL - 84 UR - https://doi.org/10.1007/BF00223997 DO - 10.1007/BF00223997 ID - Perez-Enciso1992 ER - TY - JOUR AU - Hinton, G. AU - Salakhutdinov, R. PY - 2006 DA - 2006// TI - Reducing the dimensionality of data with neural networks JO - Science VL - 313 UR - https://doi.org/10.1126/science.1127647 DO - 10.1126/science.1127647 ID - Hinton2006 ER - TY - BOOK AU - Goodfellow, I. AU - Bengio, Y. AU - Courville, A. PY - 2016 DA - 2016// TI - Deep learning PB - The MIT Press CY - Cambridge ID - Goodfellow2016 ER - TY - JOUR AU - Maaten, L. AU - Hinton, G. E. PY - 2008 DA - 2008// TI - Visualizing data using t-SNE JO - J Mach Learn Res. VL - 9 ID - Maaten2008 ER - TY - STD TI - Donoho DL. High-dimensional data analysis: The curses and blessings of dimensionality. In: Proceedings of the AMS Conference on Mathematical Challenges of the 21st Century: 7–12 August 2000; Los Angeles. 2000;1–33. ID - ref36 ER - TY - BOOK AU - Hastie, T. AU - Tibshirani, R. AU - Friedman, J. PY - 2009 DA - 2009// TI - The elements of statistical learning: Data mining, inference, and prediction PB - Springer CY - New York UR - https://doi.org/10.1007/978-0-387-84858-7 DO - 10.1007/978-0-387-84858-7 ID - Hastie2009 ER - TY - JOUR AU - Gianola, D. PY - 2013 DA - 2013// TI - Priors in whole-genome regression: the Bayesian alphabet returns JO - Genetics VL - 194 UR - https://doi.org/10.1534/genetics.113.151753 DO - 10.1534/genetics.113.151753 ID - Gianola2013 ER - TY - STD TI - Gal Y, Ghahramani Z. Dropout as a Bayesian approximation: representing model uncertainty in deep learning. arXiv:1506.02142; 2016. UR - http://arxiv.org/abs/1506.02142 ID - ref39 ER - TY - JOUR AU - Breiman, L. PY - 2001 DA - 2001// TI - Statistical modeling: the two cultures JO - Statist Sci. VL - 16 UR - https://doi.org/10.1214/ss/1009213726 DO - 10.1214/ss/1009213726 ID - Breiman2001 ER - TY - JOUR AU - Browning, B. L. AU - Browning, S. R. PY - 2013 DA - 2013// TI - Improving the accuracy and efficiency of identity-by-descent detection in population data JO - Genetics VL - 194 UR - https://doi.org/10.1534/genetics.113.150029 DO - 10.1534/genetics.113.150029 ID - Browning2013 ER - TY - JOUR AU - Buuren, S. AU - Groothuis-Oudshoorn, K. PY - 2011 DA - 2011// TI - mice: multivariate imputation by chained equations in R JO - J Stat Softw VL - 45 UR - https://doi.org/10.18637/jss.v045.i03 DO - 10.18637/jss.v045.i03 ID - Buuren2011 ER - TY - STD TI - Karras T, Aila T, Laine S, Lehtinen J. Progressive growing of GANs for improved quality, stability, and variation. arXiv:1710.10196; 2017. UR - http://arxiv.org/abs/1710.10196 ID - ref43 ER - TY - JOUR AU - Alqahtani, H. AU - Kavakli-Thorne, M. AU - Kumar, G. PY - 2019 DA - 2019// TI - Applications of generative adversarial networks (GANs): an updated review JO - Arch Comput Methods Eng. VL - 28 UR - https://doi.org/10.1007/s11831-019-09388-y DO - 10.1007/s11831-019-09388-y ID - Alqahtani2019 ER - TY - BOOK AU - Biecek, P. AU - Burzykowski, T. PY - 2021 DA - 2021// TI - Explanatory model analysis: explore, explain, and examine predictive models PB - Hall/CRC Data Science Series CY - London UR - https://doi.org/10.1201/9780429027192 DO - 10.1201/9780429027192 ID - Biecek2021 ER - TY - JOUR AU - Castelvecchi, D. PY - 2016 DA - 2016// TI - Can we open the black box of AI? JO - Nature VL - 538 UR - https://doi.org/10.1038/538020a DO - 10.1038/538020a ID - Castelvecchi2016 ER - TY - JOUR AU - Pérez-Enciso, M. AU - Quevedo, J. R. AU - Bahamonde, A. PY - 2007 DA - 2007// TI - Genetical genomics: use all data JO - BMC Genom. VL - 8 UR - https://doi.org/10.1186/1471-2164-8-69 DO - 10.1186/1471-2164-8-69 ID - Pérez-Enciso2007 ER - TY - JOUR AU - Wu, X. L. AU - Heringstad, B. AU - Gianola, D. PY - 2010 DA - 2010// TI - Bayesian structural equation models for inferring relationships between phenotypes: a review of methodology, identifiability, and applications JO - J Anim Breed Genet VL - 127 UR - https://doi.org/10.1111/j.1439-0388.2009.00835.x DO - 10.1111/j.1439-0388.2009.00835.x ID - Wu2010 ER - TY - STD TI - Caesar H, Bankiti V, Lang AH, Vora S, Liong VE, Xu Q, et al. nuScenes: a multimodal dataset for autonomous driving. arXiv:1903.11027; 2019. UR - http://arxiv.org/abs/1903.11027 ID - ref49 ER - TY - JOUR AU - Cooper, M. AU - Technow, F. AU - Messina, C. AU - Gho, C. AU - Totir, L. R. PY - 2016 DA - 2016// TI - Use of crop growth models with hole-genome prediction: application to a maize multienvironment trial JO - Crop Sci VL - 56 UR - https://doi.org/10.2135/cropsci2015.08.0512 DO - 10.2135/cropsci2015.08.0512 ID - Cooper2016 ER - TY - JOUR AU - Technow, F. AU - Messina, C. D. AU - Totir, L. R. AU - Cooper, M. PY - 2015 DA - 2015// TI - Integrating crop growth models with whole genome prediction through approximate Bayesian computation JO - PLoS ONE VL - 10 UR - https://doi.org/10.1371/journal.pone.0130855 DO - 10.1371/journal.pone.0130855 ID - Technow2015 ER - TY - JOUR AU - Los Campos, G. AU - Pérez-Rodríguez, P. AU - Bogard, M. AU - Gouache, D. AU - Crossa, J. PY - 2020 DA - 2020// TI - A data-driven simulation platform to predict cultivars’ performances under uncertain weather conditions JO - Nat Commun. VL - 11 UR - https://doi.org/10.1038/s41467-020-18480-y DO - 10.1038/s41467-020-18480-y ID - Los Campos2020 ER - TY - JOUR AU - Pedregosa, F. AU - Varoquaux, G. AU - Gramfort, A. AU - Michel, V. AU - Thirion, B. AU - Grisel, O. PY - 2011 DA - 2011// TI - Scikit-learn: machine learning in Python JO - J Mach Learn Res. VL - 12 ID - Pedregosa2011 ER -