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EDUCATION:

BSc, Animal Sciences, San Paulo State University, 1990
MSc, Animal Breeding, San Paulo State University, 1994
PhD, Biostatistics, University of San Paulo , 1999
Post doctoral, Statistical Genetics, University of Wisconsin - Madison, 2000

TEACHING:

AnSci/DySci 361 Intro to Animal & Veterinary Genetics
AnSci/DySci 362 Veterinary Genetics
AnSci/DySci 363 Principles of Animal Breeding

RECENT PUBLICATIONS:

Fernandes, A. F. A., Dorea, J. R. R., Fitzgerald, R., Herring, W. and Rosa, G. J. M. A novel automated system to acquire biometric and morphological measurements, and predict body weight of pigs via 3D computer vision. Journal of Animal Science 97: 496-508, 2019.

Passafaro, T.L., Van de Stroet, D., Bello, N. M., Williams, N. H. and Rosa, G. J. M. Generalized additive mixed model on the analysis of total transport losses of market-weight pigs. Journal of Animal Science 97: 2025-2034, 2019.

Aiken, V, C. F., Dórea, J. R. R., Acedo, J. S., Sousa, F. G., Dias, F. G. and Rosa, G. J. M. Record linkage for farm-level data analytics: Comparison of deterministic, stochastic and machine learning methods. Computers and Electronics in Agriculture 163: 104857, 2019.

Chitakasempornkul, K., Meneget, M. B., Rosa, G. J. M., Lopes, F. B., Jager, A., Gonçalves, M. A. D., Dritz, S. S., Tokach, M. D., Goodband, R. D. and Bello, N. M. Investigating causal biological relationships between reproductive performance traits in high-performing gilts and sows. Journal of Animal Science 97: 2385-2401, 2019.

Goto, T., Fernandes, A. F. A., Tsudzuki, M. and Rosa, G. J. M. Causal phenotypic networks for egg traits in an F2 chicken population. Molecular Genetics and Genomics, 2019 (in press - https://doi.org/10.1007/s00438-019-01588-2)

Abdalla, E. A., Lopes, F. B., Byrem, T. M., Weigel, K. A. and Rosa, G. J. M. Genomic prediction of bovine leukosis incidence in a US Holstein population. Livestock Science 225: 73–77, 2019.

Bresolin, T., Rosa, G. J. M., Valente, B. D., Espigolan, R., Gordo, D. G. M., Braz, C. U., Fernandes, G. A., Magalhães, A. F. B., Garcia, D. A., Frezarim, G. B., Leão, G. F. C., Carvalheiro, R., Baldi, F., Oliveira H. N. and Albuquerque, L. G. Effect of quality control, density and allele frequency of markers on the accuracy of genomic prediction for complex traits in Nellore cattle. Animal Production Science 59(1): 48-54, 2019.

Bello, N. M., Ferreira, V. C., Gianola, D. and Rosa, G. J. M. Conceptual framework for investigating causal effects from observational data in livestock. Journal of Animal Science 96(10): 4045-4062, 2018.

Momen M, Mehrgardi AA, Sheikhi A, Kranis A, Tusell L, Morota G, Rosa GJM, Gianola D. Predictive ability of genome-assisted statistical models under various forms of gene action.Scientific Reports 8:12309, 2018

Huang, X., Elston, R. C., Rosa, G. J. M., Mayer, J., Ye, Z., Kitchner, T., Brilliant, M. H., Page, D. and Hebbring, S. J. Applying family analyses to electronic health records to facilitate genetic research. Bioinformatics 34(4): 635-642, 2018.

Baker, L. A., Rosa, G. J. M., Hao, Z., Piazza, A., Hoffman, C., Binversie, E. E., Sample, S. J. and Muir, P. Multivariate genome-wide association analysis identifies novel and relevant variants associated with anterior cruciate ligament rupture risk in the dog model. BMC Genetics 19:39, 2018.

Dórea, J. R. R., Rosa, G. J. M., Weld, K. A. and Armentano, L. E. Mining data from milk infrared spectroscopy to improve feed intake predictions in lactating dairy cows. Journal of Dairy Science 101(7): 5878-5889, 2018.

Wang, Y., Mi, X., Rosa, G. J. M., Chen, Z., Lin, P., Wang, S. and Bao, Z. Technical note: an R package for fitting sparse neural networks with application in animal breeding. Journal of Animal Science 96: 2016-2026, 2018.

Momen, M., Mehrgardi, A. A., Amiri Roudbar, M., Kranis, A., Pinto, R. M., Valente, B. D., Morota, G., Rosa, G. J. M. and Gianola, D. Including phenotypic causal networks in genome-wide association studies using mixed effects structural equation models. Frontiers in Genetics, 9:455, 2018.

Lopes, F. B., Wu, X.-L., Li, H., Xu, J., Perkins, T., Genho, J., Ferretti, R., Tait Jr. R. G., Bauck, S. and Rosa, G. J. M. Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes. Journal of Animal Breeding and Genetics 135: 14-27, 2018.

PATENTS & APPLICATIONS

Association of the progesterone receptor with fertility
Publication date: 2014-02-11 Patent application number: US 12/946,865

Identification of genes or polypeptides the expression of which correlates to fertility, ovarian function and/or fetal/newborn viability Publication date: 2007-10-11 Patent application number: US20070238111 A1

For the identification of "pregnancy competent" oocytes; identifying female subjects, preferably human females having impaired fertility function; evaluating the efficacy of a putative fertility treatment
Publication date: 2006-02-02 Patent application number: US20060024693 A1