D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Biology and Biochemistry D-index 45 Citations 6,401 180 World Ranking 12887 National Ranking 5510

Research.com Recognitions

Awards & Achievements

2016 - Rockefeller Prentice Award in Animal Breeding and Genetics, American Society of Animal Science

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Gene
  • Genetics

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:

  • Gene
  • Statistics
  • Genetics

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

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.

J.L.M. Vasconcelos;J.L.M. Vasconcelos;R.W. Silcox;G.J.M. Rosa;J.R. Pursley.
Theriogenology (1999)

779 Citations

Comparison of Ovarian Function and Circulating Steroids in Estrous Cycles of Holstein Heifers and Lactating Cows

R. Sartori;J.M. Haughian;R.D. Shaver;G.J.M. Rosa.
Journal of Dairy Science (2004)

465 Citations

Glucosamine and chondroitin sulfate regulate gene expression and synthesis of nitric oxide and prostaglandin E2 in articular cartilage explants

P. S. Chan;J. P. Caron;G. J M Rosa;Michael W. Orth.
Osteoarthritis and Cartilage (2005)

269 Citations

Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods

Gustavo De Los Campos;Daniel Gianola;Guilherme J. M. Rosa;Kent A. Weigel.
Genetics Research (2010)

257 Citations

Ovarian Structures and Circulating Steroids in Heifers and Lactating Cows in Summer and Lactating and Dry Cows in Winter

R. Sartori;G.J.M. Rosa;M.C. Wiltbank.
Journal of Dairy Science (2002)

231 Citations

The transcriptome of human oocytes

Arif Murat Kocabas;Javier Crosby;Pablo J. Ross;Hasan H. Otu;Hasan H. Otu.
Proceedings of the National Academy of Sciences of the United States of America (2006)

207 Citations

A powerful and flexible linear mixed model framework for the analysis of relative quantification RT-PCR data

Juan Pedro Steibel;Rosangela Poletto;Paul M. Coussens;Guilherme J.M. Rosa.
Genomics (2009)

203 Citations

Mutations in the STAT5A gene are associated with embryonic survival and milk composition in cattle.

H. Khatib;R.L. Monson;V. Schutzkus;D.M. Kohl.
Journal of Dairy Science (2008)

179 Citations

Predicting complex quantitative traits with Bayesian neural networks: a case study with Jersey cows and wheat

Daniel Gianola;Hayrettin Okut;Kent A Weigel;Guilherme Jm Rosa.
BMC Genetics (2011)

176 Citations

Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation

G.J.M. Rosa;C.R. Padovani;D. Gianola.
Biometrical Journal (2003)

156 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Guilherme J. M. Rosa

Milo C. Wiltbank

Milo C. Wiltbank

University of Wisconsin–Madison

Publications: 79

Daniel Gianola

Daniel Gianola

University of California, Santa Barbara

Publications: 64

José Crossa

José Crossa

International Maize and Wheat Improvement Center

Publications: 63

Lucia Galvão de Albuquerque

Lucia Galvão de Albuquerque

Sao Paulo State University

Publications: 50

José E. P. Santos

José E. P. Santos

University of Florida

Publications: 50

Paul M. Fricke

Paul M. Fricke

University of Wisconsin–Madison

Publications: 46

Jean-Luc Jannink

Jean-Luc Jannink

Agricultural Research Service

Publications: 42

Ricardo C. Chebel

Ricardo C. Chebel

University of Florida

Publications: 36

Christian Maltecca

Christian Maltecca

North Carolina State University

Publications: 35

Fernando Baldi

Fernando Baldi

Sao Paulo State University

Publications: 34

Paulo Sávio Lopes

Paulo Sávio Lopes

Universidade Federal de Viçosa

Publications: 33

José Luiz Moraes Vasconcelos

José Luiz Moraes Vasconcelos

Sao Paulo State University

Publications: 32

Flavio S Schenkel

Flavio S Schenkel

University of Guelph

Publications: 26

Dorian J. Garrick

Dorian J. Garrick

Massey University

Publications: 25

Ronaldo L.A. Cerri

Ronaldo L.A. Cerri

University of British Columbia

Publications: 24

Jeffrey S. Stevenson

Jeffrey S. Stevenson

Kansas State University

Publications: 24

Trending Scientists

André Seznec

André Seznec

French Institute for Research in Computer Science and Automation - INRIA

Kamin Whitehouse

Kamin Whitehouse

University of Virginia

Kenneth Zeger

Kenneth Zeger

University of California, San Diego

Armand Joseph Beaudoin

Armand Joseph Beaudoin

Cornell University

John A. Katzenellenbogen

John A. Katzenellenbogen

University of Illinois at Urbana-Champaign

Maria Vamvakaki

Maria Vamvakaki

University of Crete

Vitor Sencadas

Vitor Sencadas

University of Wollongong

Hui Zhang

Hui Zhang

Zhejiang University

Tobias B. Haack

Tobias B. Haack

University of Tübingen

Andrew J. Marshall

Andrew J. Marshall

University of Michigan–Ann Arbor

Rod J. Snowdon

Rod J. Snowdon

University of Giessen

Michael R. Barnes

Michael R. Barnes

Queen Mary University of London

Eero Castrén

Eero Castrén

University of Helsinki

Martien L. Kapsenberg

Martien L. Kapsenberg

University of Amsterdam

Ellen T. Chang

Ellen T. Chang

Stanford University

Kate Crawford

Kate Crawford

Microsoft (United States)

Something went wrong. Please try again later.