What is he best known for?
The fields of study he is best known for:
Guilherme J. M. Rosa mostly deals with Genetics, Statistics, Linear model, Single-nucleotide polymorphism and SNP.
His Genetics study integrates concerns from other disciplines, such as Bayesian linear regression and Bayesian probability, Bayes' theorem.
As a part of the same scientific family, Guilherme J. M. Rosa mostly works in the field of Bayesian linear regression, focusing on Regression analysis and, on occasion, Artificial intelligence.
Guilherme J. M. Rosa focuses mostly in the field of Statistics, narrowing it down to topics relating to Selection and, in certain cases, Genetic model.
His study focuses on the intersection of Linear model and fields such as Mixed model with connections in the field of Generalized linear mixed model, Bioinformatics, Goodness of fit and Recursion.
The study incorporates disciplines such as Allele, Embryo and Human fertilization in addition to Single-nucleotide polymorphism.
His most cited work include:
- Synchronization rate, size of the ovulatory follicle, and pregnancy rate after synchronization of ovulation beginning on different days of the estrous cycle in lactating dairy cows. (512 citations)
- Comparison of Ovarian Function and Circulating Steroids in Estrous Cycles of Holstein Heifers and Lactating Cows (327 citations)
- Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods (204 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Statistics, Genetics, Animal science, Heritability and Selection.
Statistics and Residual are frequently intertwined in his study.
His Single-nucleotide polymorphism, Quantitative trait locus, Genotype, Genome-wide association study and Gene study are his primary interests in Genetics.
His Animal science study incorporates themes from Ice calving and Lactation.
His work on Genetic correlation expands to the thematically related Heritability.
His research on Linear model frequently links to adjacent areas such as Mixed model.
He most often published in these fields:
- Statistics (23.81%)
- Genetics (20.95%)
- Animal science (18.10%)
What were the highlights of his more recent work (between 2018-2021)?
- Animal science (18.10%)
- Statistics (23.81%)
- Artificial intelligence (8.57%)
In recent papers he was focusing on the following fields of study:
Guilherme J. M. Rosa spends much of his time researching Animal science, Statistics, Artificial intelligence, Beef cattle and Structural equation modeling.
Guilherme J. M. Rosa has researched Animal science in several fields, including Weight gain, Metritis, Birth weight and Selection.
His Statistics research is multidisciplinary, incorporating elements of Purebred, Tick infestation and Heritability.
His Artificial intelligence research includes themes of Mean squared error, Machine learning, Computer vision and Data analysis.
His research in Beef cattle intersects with topics in Feedlot and Linear regression.
Guilherme J. M. Rosa combines subjects such as Regression analysis and Regression with his study of Bayes' theorem.
Between 2018 and 2021, his most popular works were:
- A novel automated system to acquire biometric and morphological measurements and predict body weight of pigs via 3D computer vision (19 citations)
- A Vision for Development and Utilization of High-Throughput Phenotyping and Big Data Analytics in Livestock. (18 citations)
- Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia (15 citations)
In his most recent research, the most cited papers focused on:
Guilherme J. M. Rosa mainly investigates Artificial intelligence, Genome-wide association study, SNP, Genetics and Animal science.
The various areas that Guilherme J. M. Rosa examines in his Artificial intelligence study include Machine learning and Computer vision.
His study in Genome-wide association study is interdisciplinary in nature, drawing from both Dairy cattle, Brown Swiss, Udder, Structural equation modeling and Genetic architecture.
His research integrates issues of Regression, Computational biology, Bayesian probability and DNA methylation in his study of SNP.
Guilherme J. M. Rosa works in the field of Genetics, focusing on Candidate gene in particular.
His Animal science research integrates issues from Fertility, Metritis, Ice calving and Artificial insemination.
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