| Big data analytics and precision animal agriculture symposium: Machine learning and data mining advance predictive big data analysis in precision animal agriculture G Morota, RV Ventura, FF Silva, M Koyama, SC Fernando Journal of animal science 96 (4), 1540-1550, 2018 | 179 | 2018 |
| Kernel-based whole-genome prediction of complex traits: a review G Morota, D Gianola Frontiers in genetics 5, 113004, 2014 | 176 | 2014 |
| Predicting bull fertility using genomic data and biological information R Abdollahi-Arpanahi, G Morota, F Peñagaricano Journal of Dairy Science 100 (12), 9656-9666, 2017 | 71 | 2017 |
| Prediction of Plant Height in Arabidopsis thaliana Using DNA Methylation Data Y Hu, G Morota, GJM Rosa, D Gianola Genetics 201 (2), 779-793, 2015 | 70 | 2015 |
| Estimates of genomic heritability and genome-wide association study for fatty acids profile in Santa Inês sheep GA Rovadoscki, SFN Pertile, AB Alvarenga, ASM Cesar, F Pértille, ... BMC genomics 19, 1-14, 2018 | 63 | 2018 |
| Genome-enabled prediction of quantitative traits in chickens using genomic annotation G Morota, R Abdollahi-Arpanahi, A Kranis, D Gianola BMC genomics 15, 1-10, 2014 | 54 | 2014 |
| Predictive ability of genome-assisted statistical models under various forms of gene action M Momen, AA Mehrgardi, A Sheikhi, A Kranis, L Tusell, G Morota, ... Scientific reports 8 (1), 12309, 2018 | 53 | 2018 |
| Machine learning and data mining advance predictive big data analysis in precision animal agriculture G Morota, RV Ventura, FF Silva, M Koyama, SC Fernando Journal of Animal Science 96 (4), 1540-1550, 2018 | 51 | 2018 |
| Utilizing random regression models for genomic prediction of a longitudinal trait derived from high‐throughput phenotyping M Campbell, H Walia, G Morota Plant Direct 2 (9), e00080, 2018 | 49 | 2018 |
| Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data G Morota, M Koyama, GJ M Rosa, KA Weigel, D Gianola Genetics Selection Evolution 45, 1-15, 2013 | 48 | 2013 |
| MeSH ORA framework: R/Bioconductor packages to support MeSH over-representation analysis K Tsuyuzaki, G Morota, M Ishii, T Nakazato, S Miyazaki, I Nikaido BMC bioinformatics 16, 1-17, 2015 | 45 | 2015 |
| Leveraging breeding values obtained from random regression models for genetic inference of longitudinal traits M Campbell, M Momen, H Walia, G Morota The Plant Genome 12 (2), 180075, 2019 | 39 | 2019 |
| Dissection of additive genetic variability for quantitative traits in chickens using SNP markers R Abdollahi‐Arpanahi, A Pakdel, A Nejati‐Javaremi, ... Journal of Animal Breeding and Genetics 131 (3), 183-193, 2014 | 37 | 2014 |
| Predicting longitudinal traits derived from high-throughput phenomics in contrasting environments using genomic Legendre polynomials and B-splines M Momen, MT Campbell, H Walia, G Morota G3: Genes, Genomes, Genetics 9 (10), 3369-3380, 2019 | 34 | 2019 |
| SeedExtractor: An Open-Source GUI for Seed Image Analysis F Zhu, P Paul, W Hussain, K Wallman, BK Dhatt, J Sandhu, L Irvin, ... Frontiers in plant science 11, 581546, 2021 | 33 | 2021 |
| Including phenotypic causal networks in genome-wide association studies using mixed effects structural equation models M Momen, A Ayatollahi Mehrgardi, M Amiri Roudbar, A Kranis, ... Frontiers in genetics 9, 409431, 2018 | 33 | 2018 |
| Kernel-based variance component estimation and whole-genome prediction of pre-corrected phenotypes and progeny tests for dairy cow health traits G Morota, P Boddhireddy, N Vukasinovic, D Gianola, S DeNise Frontiers in Genetics 5, 75304, 2014 | 33 | 2014 |
| Allelic variation in rice Fertilization Independent Endosperm 1 contributes to grain width under high night temperature stress BK Dhatt, P Paul, J Sandhu, W Hussain, L Irvin, F Zhu, ... New Phytologist 229 (1), 335-350, 2021 | 31 | 2021 |
| Divergent phenotypic response of rice accessions to transient heat stress during early seed development P Paul, BK Dhatt, J Sandhu, W Hussain, L Irvin, G Morota, P Staswick, ... Plant Direct 4 (1), e00196, 2020 | 31 | 2020 |
| Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens R Abdollahi-Arpanahi, G Morota, BD Valente, A Kranis, GJM Rosa, ... Genetics Selection Evolution 48, 1-13, 2016 | 29 | 2016 |
Daniel GianolaSewall Wright Emeritus Professor University of Wisconsin-Madison在 ansci.wisc.edu 的电子邮件经过验证
