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ORCIDGuilherme J. M. Rosa
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- affiliation: University of Wisconsin-Madison, Department of Animal Sciences, WI, USA
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2020 – today
- 2022
[j8]Rafael E. P. Ferreira
, Tiago Bresolin, Guilherme J. M. Rosa, João Ricardo Rebouças Dórea:
Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms. Comput. Electron. Agric. 201: 107272 (2022)- 2020
- [j7]Arthur F. A. Fernandes, Eduardo M. Turra, Érika R. de Alvarenga, Tiago L. Passafaro, Fernando B. Lopes, Gabriel F. O. Alves, Vikas Singh, Guilherme J. M. Rosa:
Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia. Comput. Electron. Agric. 170: 105274 (2020)
2010 – 2019
- 2019
- [j6]Vera Cardoso Ferreira Aiken, João Ricardo Rebouças Dórea, Juliano Sabella Acedo, Fernando Gonçalves de Sousa, Fábio Guerra Dias, Guilherme Jordão de Magalhães Rosa:
Record linkage for farm-level data analytics: Comparison of deterministic, stochastic and machine learning methods. Comput. Electron. Agric. 163 (2019) - 2018
- [j5]Xiayuan Huang, Robert C. Elston, Guilherme J. M. Rosa, John Mayer, Zhan Ye, Terrie E. Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring:
Applying family analyses to electronic health records to facilitate genetic research. Bioinform. 34(4): 635-642 (2018) - 2015
- [j4]Francisco Peñagaricano, Bruno Valente, Juan P. Steibel, Ronald O. Bates, Catherine W. Ernst, Hasan Khatib, Guilherme J. M. Rosa:
Exploring causal networks underlying fat deposition and muscularity in pigs through the integration of phenotypic, genotypic and transcriptomic data. BMC Syst. Biol. 9: 58 (2015)
2000 – 2009
- 2009
- [j3]David B. Allison, Peter M. Visscher, Guilherme J. M. Rosa, Christopher I. Amos:
Statistical genetics & statistical genomics: Where biology, epistemology, statistics, and computation collide. Comput. Stat. Data Anal. 53(5): 1531-1534 (2009) - [j2]William M. Muir, Guilherme J. M. Rosa, Barry R. Pittendrigh, Z. Xu, S. D. Rider, Matthew Fountain, Joe Ogas:
A mixture model approach for the analysis of small exploratory microarray experiments. Comput. Stat. Data Anal. 53(5): 1566-1576 (2009) - [j1]Juan P. Steibel, Guilherme J. M. Rosa, Robert J. Tempelman:
Optimizing design of two-stage experiments for transcriptional profiling. Comput. Stat. Data Anal. 53(5): 1639-1649 (2009)
Coauthor Index
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