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Guilherme J. M. Rosa

D-Index & Metrics

Biology and Biochemistry

D-Index
64
Citations
13092
World Ranking
9786
National Ranking
4294

Guilherme J. M. Rosa publication distribution in Biology and Biochemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Biology and Biochemistry in 2026. The highlighted bar marks where Guilherme J. M. Rosa sits on this spectrum.

47–56 publications: 8 scientists 57–66 publications: 35 scientists 67–76 publications: 106 scientists 77–86 publications: 231 scientists 87–96 publications: 414 scientists 97–106 publications: 546 scientists 107–116 publications: 704 scientists 117–126 publications: 849 scientists 127–136 publications: 980 scientists 137–146 publications: 942 scientists 147–156 publications: 969 scientists 157–166 publications: 950 scientists 167–176 publications: 951 scientists 177–186 publications: 915 scientists 187–196 publications: 787 scientists 197–206 publications: 841 scientists 207–216 publications: 735 scientists 217–226 publications: 709 scientists 227–236 publications: 651 scientists 237–246 publications: 605 scientists 247–256 publications: 510 scientists 257–266 publications: 524 scientists 267–276 publications: 434 scientists 277–286 publications: 418 scientists 287–296 publications: 350 scientists 297–306 publications: 363 scientists 307–316 publications: 315 scientists 317–326 publications: 296 scientists 327–336 publications: 261 scientists 337–346 publications: 240 scientists 347–356 publications: 219 scientists 357–366 publications: 197 scientists 367–376 publications: 154 scientists 377–386 publications: 161 scientists 387–396 publications: 155 scientists 397–406 publications: 145 scientists 407–416 publications: 124 scientists 417–426 publications: 112 scientists 427–436 publications: 132 scientists 437–446 publications: 116 scientists 447–456 publications: 99 scientists 457–466 publications: 81 scientists 467–476 publications: 91 scientists 477–486 publications: 80 scientists 487–496 publications: 80 scientists 497–506 publications: 60 scientists 507–516 publications: 36 scientists 517–526 publications: 46 scientists 527–536 publications: 54 scientists 537–546 publications: 44 scientists 547–556 publications: 43 scientists 557–566 publications: 43 scientists 567–576 publications: 42 scientists 577–586 publications: 25 scientists 587–596 publications: 34 scientists 597–606 publications: 23 scientists 607–616 publications: 33 scientists 617–626 publications: 31 scientists 627–636 publications: 27 scientists 637–646 publications: 25 scientists 647–656 publications: 28 scientists 657–666 publications: 34 scientists 667–676 publications: 18 scientists 677–686 publications: 16 scientists 687–696 publications: 10 scientists 697–706 publications: 12 scientists 707–716 publications: 21 scientists 717–726 publications: 12 scientists 727–736 publications: 12 scientists 737–746 publications: 10 scientists 747–756 publications: 7 scientists 757–766 publications: 13 scientists 767–776 publications: 15 scientists 777–786 publications: 13 scientists 787–796 publications: 9 scientists 797–806 publications: 9 scientists 807–816 publications: 7 scientists 817–826 publications: 4 scientists 827–836 publications: 9 scientists 837–846 publications: 7 scientists 847–856 publications: 3 scientists 857–866 publications: 5 scientists 867–876 publications: 5 scientists 877–886 publications: 11 scientists 887–896 publications: 3 scientists 897–906 publications: 4 scientists 907–916 publications: 7 scientists 917–926 publications: 5 scientists 927–936 publications: 6 scientists 937–946 publications: 6 scientists 947–956 publications: 3 scientists 957–966 publications: 7 scientists 967–976 publications: 2 scientists 977–986 publications: 2 scientists 987–996 publications: 1 scientists 997–1,006 publications: 5 scientists 1,007–1,016 publications: 2 scientists 1,017–1,026 publications: 2 scientists 1,027 publications: 1 scientists 1,028+ publications: 100 scientists
47 publications 1,028+

This scientist: 327 publications — 82nd percentile

82% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,028 publications or more.

Guilherme J. M. Rosa D-index placement in Biology and Biochemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Biology and Biochemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Guilherme J. M. Rosa sits on this spectrum.

40–41 D-Index: 80 scientists 42–43 D-Index: 183 scientists 44–45 D-Index: 317 scientists 46–47 D-Index: 504 scientists 48–49 D-Index: 718 scientists 50–51 D-Index: 900 scientists 52–53 D-Index: 1,026 scientists 54–55 D-Index: 1,150 scientists 56–57 D-Index: 1,236 scientists 58–59 D-Index: 1,253 scientists 60–61 D-Index: 1,163 scientists 62–63 D-Index: 1,131 scientists 64–65 D-Index: 1,032 scientists 66–67 D-Index: 897 scientists 68–69 D-Index: 814 scientists 70–71 D-Index: 715 scientists 72–73 D-Index: 709 scientists 74–75 D-Index: 596 scientists 76–77 D-Index: 512 scientists 78–79 D-Index: 473 scientists 80–81 D-Index: 412 scientists 82–83 D-Index: 373 scientists 84–85 D-Index: 358 scientists 86–87 D-Index: 285 scientists 88–89 D-Index: 273 scientists 90–91 D-Index: 227 scientists 92–93 D-Index: 208 scientists 94–95 D-Index: 193 scientists 96–97 D-Index: 153 scientists 98–99 D-Index: 157 scientists 100–101 D-Index: 148 scientists 102–103 D-Index: 120 scientists 104–105 D-Index: 113 scientists 106–107 D-Index: 100 scientists 108–109 D-Index: 86 scientists 110–111 D-Index: 67 scientists 112–113 D-Index: 72 scientists 114–115 D-Index: 73 scientists 116–117 D-Index: 64 scientists 118–119 D-Index: 53 scientists 120–121 D-Index: 60 scientists 122–123 D-Index: 54 scientists 124–125 D-Index: 43 scientists 126–127 D-Index: 38 scientists 128–129 D-Index: 49 scientists 130–131 D-Index: 26 scientists 132–133 D-Index: 18 scientists 134–135 D-Index: 23 scientists 136–137 D-Index: 32 scientists 138–139 D-Index: 32 scientists 140–141 D-Index: 27 scientists 142–143 D-Index: 19 scientists 144–145 D-Index: 22 scientists 146–147 D-Index: 12 scientists 148–149 D-Index: 16 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 10 scientists 154–155 D-Index: 13 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 9 scientists 162–163 D-Index: 13 scientists 164–165 D-Index: 4 scientists 166 D-Index: 4 scientists 167+ D-Index: 98 scientists
40 D-Index 167+

This scientist: 64 D-Index — 52nd percentile

52% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 167 D-Index or more.

Research.com Recognitions

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

Overview

Guilherme J. M. Rosa is affiliated with the University of Wisconsin-Madison in the United States. Their research encompasses multiple disciplines within agricultural and biological sciences as well as biochemistry, genetics, and molecular biology.

The primary fields of study for Guilherme J. M. Rosa include:

  • Agricultural and Biological Sciences
  • Biochemistry, Genetics and Molecular Biology

Their work extends into several subfields, notably:

  • Genetics
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • Small Animals
  • Plant Science

The principal topics covered in their research involve:

  • Genetic and phenotypic traits in livestock
  • Genetic Mapping and Diversity in Plants and Animals
  • Effects of Environmental Stressors on Livestock
  • Animal Behavior and Welfare Studies
  • Reproductive Physiology in Livestock
  • Animal Nutrition and Physiology
  • Meat and Animal Product Quality

Frequent coauthors collaborating with Guilherme J. M. Rosa include:

  • J.R.R. Dórea
  • Fernando Brito Lopes
  • Arthur Fernandes
  • Anderson Antônio Carvalho Alves
  • Tiago Luciano Passafaro

The scientist has published extensively in several outlets, with multiple publications in the following venues:

  • Journal of Animal Science
  • Journal of Dairy Science
  • Frontiers in Genetics
  • Scientific Reports
  • Journal of Animal Breeding and Genetics

Representative recent papers authored or coauthored by Guilherme J. M. Rosa include:

  • Enviromics in breeding: applications and perspectives on envirotypic-assisted selection, 2020, Theoretical and Applied Genetics
  • Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia, 2020, Computers and Electronics in Agriculture
  • Image Analysis and Computer Vision Applications in Animal Sciences: An Overview, 2020, Frontiers in Veterinary Science
  • Genome-wide scan highlights the role of candidate genes on phenotypic plasticity for age at first calving in Nellore heifers, 2020, Scientific Reports
  • The economic cost of metritis in dairy herds, 2021, Journal of Dairy Science

Guilherme J. M. Rosa received the Rockefeller Prentice Award in Animal Breeding and Genetics from the American Society of Animal Science in 2016.

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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • The transcriptome of human oocytes

    Arif Murat Kocabas;Javier Crosby;Pablo J. Ross;Hasan H. Otu;Hasan H. Otu

  • 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

  • Reproducing kernel Hilbert spaces regression: a general framework for genetic evaluation.

    G. de los Campos;D. Gianola;G. J. M. Rosa

  • Machine Learning Classification Procedure for Selecting SNPs in Genomic Selection : Application to Early Mortality in Broilers

    N. Long;D. Gianola;G.J.M. Rosa;K.A. Weigel

  • Machine learning methods and predictive ability metrics for genome-wide prediction of complex traits $

    Oscar González-Recio;Oscar González-Recio;Guilherme J.M. Rosa;Daniel Gianola

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

    G.J.M. Rosa;C.R. Padovani;D. Gianola

  • Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers.

    K.A. Weigel;G. de los Campos;O. González-Recio;H. Naya

  • Technical note: an R package for fitting generalized linear mixed models in animal breeding.

    A. I. Vazquez;D. M. Bates;G. J. M. Rosa;D. Gianola

  • The association of bovine PPARGC1A and OPN genes with milk composition in two independent Holstein cattle populations.

    H. Khatib;I. Zaitoun;J. Wiebelhaus-Finger;Y.M. Chang

  • Inferring causal phenotype networks using structural equation models.

    Guilherme J M Rosa;Bruno D. Valente;Bruno D. Valente;Gustavo De Los Campos;Xiao Lin Wu

  • Nonparametric Methods for Incorporating Genomic Information Into Genetic Evaluations: An Application to Mortality in Broilers

    Oscar González-Recio;Daniel Gianola;Nanye Long;Kent A. Weigel

  • Antioxidant defense in rat brain regions after developmental lead exposure

    Estefania Gastaldello Moreira;Guilherme Jordao de Magalhaes Rosa;Silvia Berlanga Moraes Barros;Vera Silvia Vassilieff

  • Accuracy of direct genomic values derived from imputed single nucleotide polymorphism genotypes in Jersey cattle

    K.A. Weigel;G. de los Campos;A.I. Vazquez;G.J.M. Rosa

Frequent Co-Authors

Daniel Gianola
Daniel Gianola University of Wisconsin–Madison
Kent A. Weigel
Kent A. Weigel University of Wisconsin–Madison
Lucia Galvão de Albuquerque
Lucia Galvão de Albuquerque Sao Paulo State University
José E. P. Santos
José E. P. Santos University of Florida
Rodrigo C. Bicalho
Rodrigo C. Bicalho Cornell University
William W. Thatcher
William W. Thatcher University of Florida
Ricardo C. Chebel
Ricardo C. Chebel University of Florida
Klibs N. Galvão
Klibs N. Galvão University of Florida
Hasan Khatib
Hasan Khatib University of Wisconsin–Madison
Robert J. Tempelman
Robert J. Tempelman Michigan State University

External Links

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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 Wisconsin–Madison

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

Juan P. Steibel

Juan P. Steibel

Michigan State University

Publications: 44

Jean-Luc Jannink

Jean-Luc Jannink

Agricultural Research Service

Publications: 42

Gustavo de los Campos

Gustavo de los Campos

Michigan State University

Publications: 39

William W. Thatcher

William W. Thatcher

University of Florida

Publications: 39

Ricardo C. Chebel

Ricardo C. Chebel

University of Florida

Publications: 36

Francisco Peñagaricano

Francisco Peñagaricano

University of Wisconsin–Madison

Publications: 36

Christian Maltecca

Christian Maltecca

North Carolina State University

Publications: 35

Fabyano Fonseca e Silva

Fabyano Fonseca e Silva

Universidade Federal de Viçosa

Publications: 35

Fernando Baldi

Fernando Baldi

Sao Paulo State University

Publications: 34

Paulo Sávio Lopes

Paulo Sávio Lopes

Universidade Federal de Viçosa

Publications: 33

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