World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
58
Citations
49286
World Ranking
3277
National Ranking
1427

Ron Do 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 Ron Do 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: 175 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

Ron Do 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 Ron Do 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: 58 D-Index — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Overview

Ron Do is affiliated with the Icahn School of Medicine at Mount Sinai in the United States. They have a significant research presence in the fields of Medicine and Biochemistry, Genetics and Molecular Biology.

Their work frequently appears in prominent venues including bioRxiv (Cold Spring Harbor Laboratory), UNC Libraries, Journal of the American College of Cardiology, Nature Communications, and Nature Genetics.

Ron Do's research spans several subfields, with a major focus on Genetics, Molecular Biology, Cardiology and Cardiovascular Medicine, Ophthalmology, and Nephrology.

The main topics of their publications include Genetic Associations and Epidemiology, Genomics and Rare Diseases, Glaucoma and retinal disorders, Bioinformatics and Genomic Networks, Liver Disease Diagnosis and Treatment, Cardiovascular Function and Risk Factors, and Retinal Diseases and Treatments.

Recent papers authored or co-authored by Ron Do include:

  • Large-scale genome-wide association study of coronary artery disease in genetically diverse populations, 2022, Nature Medicine
  • Exploiting the GTEx resources to decipher the mechanisms at GWAS loci, 2021, Genome biology
  • Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts, 2022, The Lancet
  • Limitations of Contemporary Guidelines for Managing Patients at High Genetic Risk of Coronary Artery Disease, 2020, Journal of the American College of Cardiology
  • Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure, 2022, Nature Communications

Frequent co-authors with whom Ron Do has collaborated include:

  • Girish N. Nadkarni
  • Ha My T. Vy
  • Ghislain Rocheleau
  • Iain S. Forrest
  • Daniel M. Jordan

Best Publications

  • Analysis of protein-coding genetic variation in 60,706 humans

    Monkol Lek;Konrad J. Karczewski;Konrad J. Karczewski;Eric V. Minikel;Eric V. Minikel;Kaitlin E. Samocha

  • Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases.

    Marie Verbanck;Chia-Yen Chen;Benjamin Neale;Benjamin Neale;Ron Do

  • Discovery and refinement of loci associated with lipid levels

    Cristen J. Willer;Ellen M. Schmidt;Sebanti Sengupta;Gina M. Peloso;Gina M. Peloso;Gina M. Peloso

  • Plasma HDL cholesterol and risk of myocardial infarction: A mendelian randomisation study

    Benjamin F. Voight;Benjamin F. Voight;Benjamin F. Voight;Gina M. Peloso;Gina M. Peloso;Marju Orho-Melander;Ruth Frikke-Schmidt

  • A high-coverage genome sequence from an archaic Denisovan individual

    Matthias Meyer;Martin Kircher;Marie Theres Gansauge;Heng Li

  • Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease

    Heribert Schunkert;Inke R. König;Sekar Kathiresan;Muredach P. Reilly

  • Evolution and functional impact of rare coding variation from deep sequencing of human exomes

    Jacob A. Tennessen;Abigail W. Bigham;Timothy D. O'Connor;Wenqing Fu

  • Large-scale association analysis identifies new risk loci for coronary artery disease

    Panos Deloukas;Stavroula Kanoni;Christina Willenborg;Martin Farrall

  • Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

    Bjarni J. Vilhjálmsson;Jian Yang;Hilary K. Finucane;Alexander Gusev

  • Genome-wide association of early-onset myocardial infarction with single nucleotide polymorphisms and copy number variants.

    Sekar Kathiresan;Benjamin F Voight;Shaun Purcell;Kiran Musunuru

  • Common variants associated with plasma triglycerides and risk for coronary artery disease

    Ron Do;Cristen J. Willer;Ellen M. Schmidt;Sebanti Sengupta

  • Genetic analyses of diverse populations improves discovery for complex traits

    Genevieve L. Wojcik;Mariaelisa Graff;Katherine K. Nishimura;Ran Tao

  • Loss-of-function mutations in APOC3, triglycerides, and coronary disease

    Jacy Crosby;Gina M. Peloso;Gina M. Peloso;Paul L. Auer;David R. Crosslin

  • Exome sequencing, ANGPTL3 mutations, and familial combined hypolipidemia.

    Kiran Musunuru;James P. Pirruccello;James P. Pirruccello;James P. Pirruccello;Ron Do;Ron Do;Ron Do;Gina M. Peloso;Gina M. Peloso

  • Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction

    Ron Do;Ron Do;Nathan O. Stitziel;Hong Hee Won;Hong Hee Won;Anders Berg Jørgensen

  • Searching for missing heritability: Designing rare variant association studies

    Or Zuk;Or Zuk;Stephen F. Schaffner;Kaitlin Samocha;Ron Do

  • Inactivating mutations in NPC1L1 and protection from coronary heart disease

    Nathan O. Stitziel;Hong Hee Won;Alanna C. Morrison;Gina M. Peloso

  • Exome sequencing and the genetic basis of complex traits

    Adam Kiezun;Kiran Garimella;Ron Do;Ron Do;Nathan O Stitziel;Nathan O Stitziel

  • Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease

    Nathan O. Stitziel;Kathleen E. Stirrups;Nicholas G. D. Masca;Jeanette Erdmann

  • Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis

    Eli A Stahl;Daniel Wegmann;Gosia Trynka;Javier Gutierrez-Achury

Frequent Co-Authors

Sekar Kathiresan
Sekar Kathiresan Harvard University
Daniel J. Rader
Daniel J. Rader University of Pennsylvania
Nilesh J. Samani
Nilesh J. Samani University of Leicester
Gina M. Peloso
Gina M. Peloso Boston University
Ruth J. F. Loos
Ruth J. F. Loos University of Copenhagen
Panos Deloukas
Panos Deloukas Queen Mary University of London
Danish Saleheen
Danish Saleheen Columbia University
Muredach P. Reilly
Muredach P. Reilly Columbia University
Jeanette Erdmann
Jeanette Erdmann University of Lübeck
David Altshuler
David Altshuler Harvard University

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