World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
95
Citations
33083
World Ranking
898
National Ranking
448

Medicine

D-Index
94
Citations
33238
World Ranking
10470
National Ranking
5387

Peter N. Robinson publication distribution in Genetics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Genetics in 2026. The highlighted bar marks where Peter N. Robinson sits on this spectrum.

45–54 publications: 6 scientists 55–64 publications: 10 scientists 65–74 publications: 35 scientists 75–84 publications: 84 scientists 85–94 publications: 102 scientists 95–104 publications: 151 scientists 105–114 publications: 175 scientists 115–124 publications: 203 scientists 125–134 publications: 217 scientists 135–144 publications: 205 scientists 145–154 publications: 193 scientists 155–164 publications: 188 scientists 165–174 publications: 170 scientists 175–184 publications: 178 scientists 185–194 publications: 164 scientists 195–204 publications: 173 scientists 205–214 publications: 159 scientists 215–224 publications: 134 scientists 225–234 publications: 143 scientists 235–244 publications: 105 scientists 245–254 publications: 114 scientists 255–264 publications: 92 scientists 265–274 publications: 88 scientists 275–284 publications: 87 scientists 285–294 publications: 80 scientists 295–304 publications: 62 scientists 305–314 publications: 75 scientists 315–324 publications: 67 scientists 325–334 publications: 60 scientists 335–344 publications: 52 scientists 345–354 publications: 40 scientists 355–364 publications: 48 scientists 365–374 publications: 47 scientists 375–384 publications: 46 scientists 385–394 publications: 31 scientists 395–404 publications: 27 scientists 405–414 publications: 40 scientists 415–424 publications: 30 scientists 425–434 publications: 43 scientists 435–444 publications: 29 scientists 445–454 publications: 14 scientists 455–464 publications: 28 scientists 465–474 publications: 21 scientists 475–484 publications: 21 scientists 485–494 publications: 22 scientists 495–504 publications: 17 scientists 505–514 publications: 12 scientists 515–524 publications: 11 scientists 525–534 publications: 8 scientists 535–544 publications: 8 scientists 545–554 publications: 14 scientists 555–564 publications: 4 scientists 565–574 publications: 11 scientists 575–584 publications: 5 scientists 585–594 publications: 11 scientists 595–604 publications: 12 scientists 605–614 publications: 7 scientists 615–624 publications: 6 scientists 625–634 publications: 10 scientists 635–644 publications: 9 scientists 645–654 publications: 10 scientists 655–664 publications: 6 scientists 665–674 publications: 6 scientists 675–684 publications: 6 scientists 685–694 publications: 4 scientists 695–702 publications: 6 scientists 703+ publications: 100 scientists
45 publications 703+

This scientist: 358 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 703 publications or more.

Peter N. Robinson D-index placement in Genetics in 2026

The chart shows the D-index (discipline H-index) distribution of Genetics scientists ranked by Research.com in 2026. The highlighted bar marks where Peter N. Robinson sits on this spectrum.

40–41 D-Index: 24 scientists 42–43 D-Index: 52 scientists 44–45 D-Index: 84 scientists 46–47 D-Index: 112 scientists 48–49 D-Index: 118 scientists 50–51 D-Index: 141 scientists 52–53 D-Index: 143 scientists 54–55 D-Index: 145 scientists 56–57 D-Index: 179 scientists 58–59 D-Index: 162 scientists 60–61 D-Index: 175 scientists 62–63 D-Index: 191 scientists 64–65 D-Index: 172 scientists 66–67 D-Index: 184 scientists 68–69 D-Index: 164 scientists 70–71 D-Index: 158 scientists 72–73 D-Index: 150 scientists 74–75 D-Index: 136 scientists 76–77 D-Index: 127 scientists 78–79 D-Index: 127 scientists 80–81 D-Index: 111 scientists 82–83 D-Index: 110 scientists 84–85 D-Index: 110 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 102 scientists 90–91 D-Index: 66 scientists 92–93 D-Index: 72 scientists 94–95 D-Index: 70 scientists 96–97 D-Index: 54 scientists 98–99 D-Index: 60 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 55 scientists 104–105 D-Index: 45 scientists 106–107 D-Index: 42 scientists 108–109 D-Index: 28 scientists 110–111 D-Index: 39 scientists 112–113 D-Index: 25 scientists 114–115 D-Index: 31 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 34 scientists 120–121 D-Index: 29 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 18 scientists 126–127 D-Index: 27 scientists 128–129 D-Index: 22 scientists 130–131 D-Index: 16 scientists 132–133 D-Index: 11 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 12 scientists 138–139 D-Index: 21 scientists 140–141 D-Index: 4 scientists 142–143 D-Index: 9 scientists 144–145 D-Index: 14 scientists 146–147 D-Index: 6 scientists 148–149 D-Index: 10 scientists 150–151 D-Index: 7 scientists 152–153 D-Index: 9 scientists 154–155 D-Index: 8 scientists 156–157 D-Index: 8 scientists 158–159 D-Index: 9 scientists 160+ D-Index: 96 scientists
40 D-Index 160+

This scientist: 95 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 160 D-Index or more.

Overview

Peter N. Robinson is affiliated with The Jackson Laboratory in the United States. Their research spans multiple disciplines within the biological and medical sciences, with a notable focus on biochemistry, genetics, and molecular biology, alongside significant contributions in the field of medicine.

The primary subfields in which they have published include molecular biology, genetics, artificial intelligence, infectious diseases, and cancer research. Their work often intersects with various specialized topics such as genomics and rare diseases, biomedical text mining and ontologies, bioinformatics and genomic networks, genomic variations and chromosomal abnormalities, cancer genomics and diagnostics, semantic web and ontologies, and RNA research and splicing.

Peter N. Robinson has been involved in numerous academic publications, with frequent contributions appearing in notable venues. The most common publication venues include bioRxiv (Cold Spring Harbor Laboratory), Zenodo (CERN European Organization for Nuclear Research), UNC Libraries, Bioinformatics, and arXiv (Cornell University).

Among their recent papers, the following are highlighted along with year of publication and venues:

  • The Human Phenotype Ontology in 2021, 2020, Nucleic Acids Research
  • The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment, 2020, Journal of the American Medical Informatics Association
  • Characterizing Long COVID: Deep Phenotype of a Complex Condition, 2021, EBioMedicine
  • Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes, 2022, EBioMedicine
  • Challenges in defining Long COVID: Striking differences across literature, Electronic Health Records, and patient-reported information, 2021, bioRxiv (Cold Spring Harbor Laboratory)

The scientist collaborates frequently with a number of co-authors, including Melissa Haendel, Justin Reese, Chris Mungall, Elena Casiraghi, and Giorgio Valentini.

Best Publications

  • Walking the Interactome for Prioritization of Candidate Disease Genes

    Sebastian Köhler;Sebastian Bauer;Denise Horn;Peter N. Robinson

  • The Human Phenotype Ontology in 2021

    Sebastian Köhler;Michael Gargano;Nicolas Matentzoglu;Leigh C. Carmody

  • The Human Phenotype Ontology: A Tool for Annotating and Analyzing Human Hereditary Disease

    Peter N. Robinson;Sebastian Köhler;Sebastian Bauer;Dominik Seelow

  • The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

    Sebastian Köhler;Sandra C. Doelken;Christopher J. Mungall;Sebastian Bauer

  • The Human Phenotype Ontology in 2017

    Sebastian Köhler;Nicole A. Vasilevsky;Mark Engelstad;Erin D. Foster

  • Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

    Sebastian Köhler;Leigh Carmody;Nicole A. Vasilevsky;Julius O. B. Jacobsen

  • Effect of mutation type and location on clinical outcome in 1,013 probands with marfan syndrome or related phenotypes and FBN1 mutations : An international study

    L. Faivre;G. Collod-Beroud;G. Collod-Beroud;B.L. Loeys;A. Child

  • Ontologizer 2.0—a multifunctional tool for GO term enrichment analysis and data exploration

    Sebastian Bauer;Steffen Grossmann;Martin Vingron;Peter N. Robinson

  • The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment.

    Melissa A Haendel;Melissa A Haendel;Christopher G Chute;Tellen D Bennett;David A Eichmann

  • Clinical Diagnostics in Human Genetics with Semantic Similarity Searches in Ontologies

    Sebastian Köhler;Marcel H. Schulz;Marcel H. Schulz;Peter Krawitz;Sebastian Bauer

  • The Matchmaker Exchange: a platform for rare disease gene discovery

    Anthony A. Philippakis;Anthony A. Philippakis;Anthony A. Philippakis;Danielle R. Azzariti;Sergi Beltran;Anthony J. Brookes

  • The molecular genetics of Marfan syndrome and related disorders

    Peter N. Robinson;E. Arteaga-Solis;C. Baldock;G. Collod-Béroud

  • Deep phenotyping for precision medicine

    Peter N. Robinson

  • The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species.

    Christopher J. Mungall;Julie A. McMurry;Sebastian Köhler;James P. Balhoff

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • Improved detection of overrepresentation of Gene-Ontology annotations with parent–child analysis

    Steffen Grossmann;Sebastian Bauer;Peter N. Robinson;Martin Vingron

  • The molecular genetics of Marfan syndrome and related microfibrillopathies

    Peter N. Robinson;Maurice Godfrey

  • Update of the UMD-FBN1 mutation database and creation of an FBN1 polymorphism database.

    Gwenaëlle Collod-Béroud;Saga Le Bourdelles;Lesley Ades;Lesley Ades;Leena Ala-Kokko;Leena Ala-Kokko

  • The human phenotype ontology.

    PN Robinson;S Mundlos

  • The Monarch Initiative: An integrative data and analytic platform connecting phenotypes to genotypes across species

    Christopher J Mungall;Julie A McMurry;Sebastian Köhler;James P. Balhoff

Frequent Co-Authors

Stefan Mundlos
Stefan Mundlos Max Planck Society
Melissa A. Haendel
Melissa A. Haendel University of Colorado Anschutz Medical Campus
Christopher J. Mungall
Christopher J. Mungall Lawrence Berkeley National Laboratory
Damian Smedley
Damian Smedley Queen Mary University of London
Suzanna E. Lewis
Suzanna E. Lewis Lawrence Berkeley National Laboratory
Giorgio Valentini
Giorgio Valentini University of Milan
Uwe Kornak
Uwe Kornak University of Göttingen
Michael Brudno
Michael Brudno University of Toronto
Christophe Béroud
Christophe Béroud Aix-Marseille University
Jochen Hecht
Jochen Hecht Centre for Genomic Regulation

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