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J. H. J. van der Werf

J. H. J. van der Werf

University of New England
Australia

D-Index & Metrics

Animal Science and Veterinary

D-Index
59
Citations
11398
World Ranking
353
National Ranking
26

J. H. J. van der Werf publication distribution in Animal Science and Veterinary in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Animal Science and Veterinary in 2026. The highlighted bar marks where J. H. J. van der Werf sits on this spectrum.

29–33 publications: 1 scientists 34–38 publications: 6 scientists 39–43 publications: 17 scientists 44–48 publications: 23 scientists 49–53 publications: 28 scientists 54–58 publications: 44 scientists 59–63 publications: 66 scientists 64–68 publications: 75 scientists 69–73 publications: 71 scientists 74–78 publications: 85 scientists 79–83 publications: 108 scientists 84–88 publications: 105 scientists 89–93 publications: 84 scientists 94–98 publications: 103 scientists 99–103 publications: 97 scientists 104–108 publications: 95 scientists 109–113 publications: 89 scientists 114–118 publications: 88 scientists 119–123 publications: 109 scientists 124–128 publications: 93 scientists 129–133 publications: 89 scientists 134–138 publications: 95 scientists 139–143 publications: 92 scientists 144–148 publications: 80 scientists 149–153 publications: 75 scientists 154–158 publications: 74 scientists 159–163 publications: 67 scientists 164–168 publications: 53 scientists 169–173 publications: 62 scientists 174–178 publications: 63 scientists 179–183 publications: 50 scientists 184–188 publications: 55 scientists 189–193 publications: 50 scientists 194–198 publications: 27 scientists 199–203 publications: 44 scientists 204–208 publications: 31 scientists 209–213 publications: 28 scientists 214–218 publications: 38 scientists 219–223 publications: 33 scientists 224–228 publications: 36 scientists 229–233 publications: 29 scientists 234–238 publications: 35 scientists 239–243 publications: 23 scientists 244–248 publications: 24 scientists 249–253 publications: 29 scientists 254–258 publications: 28 scientists 259–263 publications: 21 scientists 264–268 publications: 25 scientists 269–273 publications: 11 scientists 274–278 publications: 18 scientists 279–283 publications: 13 scientists 284–288 publications: 18 scientists 289–293 publications: 10 scientists 294–298 publications: 12 scientists 299–303 publications: 11 scientists 304–308 publications: 15 scientists 309–313 publications: 14 scientists 314–318 publications: 14 scientists 319–323 publications: 8 scientists 324–328 publications: 8 scientists 329–333 publications: 13 scientists 334–338 publications: 14 scientists 339–343 publications: 13 scientists 344–348 publications: 10 scientists 349–353 publications: 11 scientists 354–358 publications: 5 scientists 359–363 publications: 8 scientists 364–368 publications: 8 scientists 369–373 publications: 6 scientists 374–378 publications: 7 scientists 379–383 publications: 8 scientists 384–388 publications: 3 scientists 389–393 publications: 4 scientists 394–398 publications: 5 scientists 399–403 publications: 8 scientists 404–408 publications: 5 scientists 409–413 publications: 4 scientists 414–418 publications: 3 scientists 419–423 publications: 8 scientists 424–428 publications: 5 scientists 429–433 publications: 3 scientists 434–438 publications: 5 scientists 439–441 publications: 5 scientists 442+ publications: 99 scientists
29 publications 442+

This scientist: 522 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 442 publications or more.

J. H. J. van der Werf D-index placement in Animal Science and Veterinary in 2026

The chart shows the D-index (discipline H-index) distribution of Animal Science and Veterinary scientists ranked by Research.com in 2026. The highlighted bar marks where J. H. J. van der Werf sits on this spectrum.

20 D-Index: 5 scientists 21 D-Index: 22 scientists 22 D-Index: 31 scientists 23 D-Index: 44 scientists 24 D-Index: 53 scientists 25 D-Index: 66 scientists 26 D-Index: 80 scientists 27 D-Index: 101 scientists 28 D-Index: 106 scientists 29 D-Index: 116 scientists 30 D-Index: 154 scientists 31 D-Index: 158 scientists 32 D-Index: 143 scientists 33 D-Index: 137 scientists 34 D-Index: 126 scientists 35 D-Index: 134 scientists 36 D-Index: 112 scientists 37 D-Index: 115 scientists 38 D-Index: 105 scientists 39 D-Index: 111 scientists 40 D-Index: 107 scientists 41 D-Index: 87 scientists 42 D-Index: 74 scientists 43 D-Index: 62 scientists 44 D-Index: 61 scientists 45 D-Index: 41 scientists 46 D-Index: 51 scientists 47 D-Index: 43 scientists 48 D-Index: 28 scientists 49 D-Index: 47 scientists 50 D-Index: 40 scientists 51 D-Index: 34 scientists 52 D-Index: 33 scientists 53 D-Index: 43 scientists 54 D-Index: 16 scientists 55 D-Index: 32 scientists 56 D-Index: 21 scientists 57 D-Index: 18 scientists 58 D-Index: 28 scientists 59 D-Index: 33 scientists 60 D-Index: 17 scientists 61 D-Index: 21 scientists 62 D-Index: 18 scientists 63 D-Index: 21 scientists 64 D-Index: 9 scientists 65 D-Index: 20 scientists 66 D-Index: 11 scientists 67 D-Index: 16 scientists 68 D-Index: 12 scientists 69 D-Index: 17 scientists 70 D-Index: 13 scientists 71 D-Index: 15 scientists 72 D-Index: 11 scientists 73 D-Index: 11 scientists 74 D-Index: 14 scientists 75 D-Index: 5 scientists 76 D-Index: 6 scientists 77+ D-Index: 100 scientists
20 D-Index 77+

This scientist: 59 D-Index — 89th percentile

89% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 77 D-Index or more.

Overview

J. H. J. van der Werf is affiliated with the University of New England in Australia and has contributed extensively to the fields of Biochemistry, Genetics and Molecular Biology as well as Agricultural and Biological Sciences. Their research predominantly focuses on genetics, with a significant emphasis on genetics applied to livestock.

Their main fields of study include:

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

Subfields of study that characterize their work cover:

  • Genetics
  • Animal Science and Zoology
  • Agronomy and Crop Science
  • Small Animals
  • Cancer Research

The primary research topics J. H. J. van der Werf has worked on are:

  • 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
  • Cancer-related molecular mechanisms research
  • Animal Nutrition and Physiology
  • Livestock Management and Performance Improvement

They have published in several recurring academic venues, with multiple publications in the following journals:

  • Genetics Selection Evolution
  • Animal Production Science
  • Journal of Animal Breeding and Genetics
  • animal
  • Frontiers in Genetics

Selected recent papers authored or co-authored by van der Werf include:

  • Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle (2020, Genetics Selection Evolution)
  • A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits (2021, Genetics Selection Evolution)
  • Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives (2020, Nature Communications)
  • Analysis of culling reasons and age at culling in Australian dairy cattle (2021, Animal Production Science)
  • Breeding objectives for dairy cattle under low, medium and high production systems in the tropics (2022, animal)

Van der Werf has collaborated frequently with several researchers, including:

  • Sam Clark
  • Sara de las Heras-Saldana
  • Nasir Moghaddar
  • Dajeong Lim
  • Susanne Hermesch

Best Publications

  • Genetic and statistical properties of residual feed intake

    B.W. Kennedy;J.H.J. van der Werf;T.H.E. Meuwissen

  • The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes.

    Samuel A Clark;John M Hickey;Hans D Daetwyler;Julius H J van der Werf

  • Genetic correlation between days until start of luteal activity and milk yield, energy balance, and live weights.

    R.F. Veerkamp;J.K. Oldenbroek;H.J. Van Der Gaast;J.H.J. Van Der Werf

  • MTG2: an efficient algorithm for multivariate linear mixed model analysis based on genomic information.

    S. H. Lee;S. H. Lee;J. H. J. van der Werf

  • Different models of genetic variation and their effect on genomic evaluation

    Samuel A Clark;Samuel A Clark;John M Hickey;Julius H J van der Werf;Julius H J van der Werf

  • The Use of Covariance Functions and Random Regressions for Genetic Evaluation of Milk Production Based on Test Day Records

    J.H.J. Van Der Werf;M.E. Goddard;K. Meyer

  • Predicting Unobserved Phenotypes for Complex Traits from Whole-Genome SNP Data

    Sang Hong Lee;Sang Hong Lee;Julius H. J. van der Werf;Ben J. Hayes;Michael E. Goddard

  • Design and role of an information nucleus in sheep breeding programs

    J. H. J. van der Werf;J. H. J. van der Werf;B. P. Kinghorn;B. P. Kinghorn;R. G. Banks;R. G. Banks

  • Genetic and phenotypic parameters for milk production and fertility traits in upgraded dairy cattle

    J Hoekstra;A.W van der Lugt;J.H.J van der Werf;W Ouweltjes

  • Components of the accuracy of genomic prediction in a multi-breed sheep population

    H. D. Daetwyler;K. E. Kemper;J. H. J. van der Werf;J. H. J. van der Werf;B. J. Hayes;B. J. Hayes

  • Genetic parameters for meat quality traits of Australian lamb meat

    S.I. Mortimer;J.H.J. van der Werf;R.H. Jacob;D.L. Hopkins

  • A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

    John M Hickey;Brian P Kinghorn;Bruce Tier;Julius H J van der Werf;Julius H J van der Werf

  • Accuracy of estimated genomic breeding values for wool and meat traits in a multi-breed sheep population

    H. D. Daetwyler;J. M. Hickey;J. M. Henshall;S. Dominik

  • Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation

    Hans D Daetwyler;Andrew A Swan;Andrew A Swan;Julius H J van der Werf;Julius H J van der Werf;Ben J Hayes;Ben J Hayes

  • Selection Bias and Multiple Trait Evaluation

    E.J. Pollak;J.H.J. van der Werf;R.L. Quaas

  • A combined long-range phasing and long haplotype imputation method to impute phase for SNP genotypes.

    John M Hickey;Brian P Kinghorn;Bruce Tier;James F Wilson

  • Genomic Best Linear Unbiased Prediction (gBLUP) for the Estimation of Genomic Breeding Values

    Samuel A. Clark;Julius van der Werf

  • Estimation of additive genetic variance when base populations are selected.

    J.H.J. van der Werf;I.J.M. de Boer

  • Accuracy of genotype imputation in sheep breeds.

    B. J. Hayes;P. J. Bowman;H. D. Daetwyler;J. W. Kijas

  • Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML.

    Troy M Fischer;Arthur R Gilmour;Julius H.J. van der Werf

  • Genetic correlations among and between wool, growth and reproduction traits in Merino sheep

    E Safari;N M Fogarty;A R Gilmour;K D Atkins

  • Estimation of Genetic Parameters in a Crossbred Population of Black and White Dairy Cattle

    J.H.J. Van Der Werf;W. De Boer

  • Description of lamb growth using random regression on field data

    T.M. Fischer;J.H.J. Van der Werf;R.G. Banks;A.J. Ball

  • Across population genetic parameters for wool, growth, and reproduction traits in Australian Merino sheep. 2. Estimates of heritability and variance components

    E. Safari;N. M. Fogarty;A. R. Gilmour;K. D. Atkins

  • Preliminary estimates of genetic parameters for carcass and meat quality traits in Australian sheep

    S. I. Mortimer;J. H. J. van der Werf;J. H. J. van der Werf;R. H. Jacob;R. H. Jacob;D. W. Pethick;D. W. Pethick

  • Genetic parameters for carcass and meat quality traits and their relationships to liveweight and wool production in hogget Merino rams

    J.C. Greeff;E. Safari;E. Safari;N.M. Fogarty;N.M. Fogarty;D.L. Hopkins

  • Response to selection in beef cattle using IGF-1 as a selection criterion for residual feed intake under different Australian breeding objectives

    B.J. Wood;J.A. Archer;J.H.J. van der Werf

  • Genetic relationships between fertility traits for dairy cows in different parities

    J. Jansen;J.H.J. van der Werf;W. de Boer

  • Reproductive performance in the Sheep CRC Information Nucleus using artificial insemination across different sheep-production environments in southern Australia

    K. G. Geenty;F. D. Brien;G. N. Hinch;R. C. Dobos

  • Genetic variation within and between subpopulations of the Australian Merino breed

    Andrew A. Swan;Daniel J. Brown;Julius H. J. van der Werf

  • Across population genetic parameters for wool, growth, and reproduction traits in Australian Merino sheep. 1. Data structure and non-genetic effects

    E. Safari;N. M. Fogarty;A. R. Gilmour;K. D. Atkins

  • Across flock (co)variance components for faecal worm egg count, live weight, and fleece traits for Australian merinos

    M. Khusro;J.H.J. Van der Werf;D.J. Brown;A. Ball

  • Genetic correlations between meat quality traits and growth and carcass traits in Merino sheep

    Suzanne I Mortimer;Suzanne I Mortimer;Neal M Fogarty;Neal M Fogarty;Julius H J van der Werf;Daniel J Brown

  • QTL and gene expression analyses identify genes affecting carcass weight and marbling on BTA14 in Hanwoo (Korean Cattle)

    Seung Hwan Lee;Seung Hwan Lee;J. H. J. van der Werf;Nam Kuk Kim;Sang Hong Lee

  • Design and phenotyping procedures for recording wool, skin, parasite resistance, growth, carcass yield and quality traits of the SheepGENOMICS mapping flock

    Jason D. White;Peter G. Allingham;Chris M. Gorman;David L. Emery

  • Breeding for veal and beef production in Dutch Red and White cattle.

    J. Dijkstra;J.K. Oldenbroek;S. Korver;J.H.J. van der Werf

  • Genomic Evaluations in the Australian Sheep Industry

    A. A Swan;D. J. Brown;H. D. Daetwyler;B. J. Hayes

Frequent Co-Authors

Andrew Swan
Andrew Swan University of New England
J.A.M. van Arendonk
J.A.M. van Arendonk Wageningen University & Research
Alex J. Ball
Alex J. Ball University of New England
Andrew Thompson
Andrew Thompson Murdoch University
Norah M. E. Fogarty
Norah M. E. Fogarty King's College London
Ben J. Hayes
Ben J. Hayes University of Queensland
S. W. Walkden-Brown
S. W. Walkden-Brown University of New England
Sang Hong Lee
Sang Hong Lee University of South Australia
Hans D. Daetwyler
Hans D. Daetwyler Bayer Pharmaceuticals
David L. Hopkins
David L. Hopkins Charles Sturt University

External Links

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Related Online Degrees & Career Pathways

For those interested in Animal Science and Veterinary fields, expanding knowledge in related health and counseling areas can open diverse career pathways. For example, professionals seeking advanced clinical expertise might explore the online apa-accredited psyd programs that offer specialized training without GRE requirements. These programs complement veterinary care by focusing on psychological support roles, particularly in animal-assisted therapy.

Additionally, addressing animal welfare involves understanding human behavioral health, making degrees such as the online substance abuse counseling degree appealing for those interested in counseling clients regarding addiction, which may impact responsible pet ownership.

For students aiming to work with families and communities, an online masters in marriage and family therapy provides vital skills in managing complex interpersonal dynamics that indirectly affect animal care environments.

For career advancement, pursuing an online doctorate in counseling offers deep specialization for those wanting leadership or research roles in counseling related to veterinary behavioral health or animal-assisted interventions.

Best Scientists Citing J. H. J. van der Werf

Roel F. Veerkamp

Roel F. Veerkamp

Wageningen University & Research

Publications: 67

Ben J. Hayes

Ben J. Hayes

University of Queensland

Publications: 53

Donagh P. Berry

Donagh P. Berry

Teagasc - The Irish Agriculture and Food Development Authority

Publications: 50

David W. Pethick

David W. Pethick

Murdoch University

Publications: 49

Graham E. Gardner

Graham E. Gardner

Murdoch University

Publications: 42

Hans D. Daetwyler

Hans D. Daetwyler

Bayer Pharmaceuticals

Publications: 35

Jennie E. Pryce

Jennie E. Pryce

La Trobe University

Publications: 34

Mike Coffey

Mike Coffey

Scotland's Rural College

Publications: 33

Michael E. Goddard

Michael E. Goddard

University of Melbourne

Publications: 30

Andrew Swan

Andrew Swan

University of New England

Publications: 26

David L. Hopkins

David L. Hopkins

Charles Sturt University

Publications: 26

J.A.M. van Arendonk

J.A.M. van Arendonk

Wageningen University & Research

Publications: 26

Andrew Thompson

Andrew Thompson

Murdoch University

Publications: 25

Robin H. Jacob

Robin H. Jacob

Government of Western Australia

Publications: 24

Jack C. M. Dekkers

Jack C. M. Dekkers

Iowa State University

Publications: 23

Georgios Banos

Georgios Banos

Scotland's Rural College

Publications: 23

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