World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
102
Citations
54937
World Ranking
695
National Ranking
102

John C. Marioni 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 John C. Marioni 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: 234 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

John C. Marioni 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 John C. Marioni 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: 102 D-Index — 84th percentile

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

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

Research.com Recognitions

  • Member of the European Molecular Biology Organization (EMBO)
  • Member of the European Molecular Biology Organization (EMBO)

Overview

John C. Marioni is affiliated with the European Bioinformatics Institute in the United Kingdom. Their research primarily focuses on biochemistry, genetics, and molecular biology, with a total of 238 publications in this field. Within this broad domain, Marioni's work spans several subfields including molecular biology, immunology, biophysics, surgery, and pulmonary and respiratory medicine.

Their scientific contributions emphasize key topics such as single-cell and spatial transcriptomics, cell image analysis techniques, gene regulatory network analysis, congenital heart defects research, neonatal respiratory health research, gene expression and cancer classification, and immune cell function and interaction.

Marioni's frequent collaborators include Sarah A. Teichmann, Berthold Göttgens, Emma Dann, Kerstin B. Meyer, and Krzysztof Polański. These partnerships have supported a diverse publication record across various high-impact journals and platforms.

The scientist's notable publication venues include bioRxiv (Cold Spring Harbor Laboratory) with 45 publications, Nature with 9 publications, Genome biology with 8, Nature Communications with 7, and Nature Biotechnology with 5 publications.

Some of Marioni's recent papers are:

  • "Eleven grand challenges in single-cell data science," 2020, Genome biology
  • "MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data," 2020, Genome biology
  • "Single-cell multi-omics analysis of the immune response in COVID-19," 2021, Nature Medicine
  • "Differential abundance testing on single-cell data using k-nearest neighbor graphs," 2021, Nature Biotechnology
  • "Cells of the human intestinal tract mapped across space and time," 2021, Nature

Marioni has been recognized as a member of the European Molecular Biology Organization (EMBO), acknowledging their participation in the broader molecular biology research community.

Best Publications

  • RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

    John C. Marioni;Christopher E. Mason;Shrikant M. Mane;Matthew Stephens

  • Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.

    Laleh Haghverdi;Aaron T L Lun;Michael D Morgan;John C Marioni;John C Marioni;John C Marioni

  • Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics

    Andrea Sottoriva;Andrea Sottoriva;Andrea Sottoriva;Inmaculada Spiteri;Sara G. M. Piccirillo;Anestis Touloumis

  • The Human Cell Atlas

    Aviv Regev;Aviv Regev;Aviv Regev;Sarah A Teichmann;Sarah A Teichmann;Sarah A Teichmann;Eric S Lander;Eric S Lander;Eric S Lander;Ido Amit

  • Understanding mechanisms underlying human gene expression variation with RNA sequencing

    Joseph K. Pickrell;John C. Marioni;Athma A. Pai;Jacob F. Degner

  • A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

    Aaron T.L. Lun;Davis J. McCarthy;John C. Marioni

  • The technology and biology of single-cell RNA sequencing.

    Aleksandra A. Kolodziejczyk;Aleksandra A. Kolodziejczyk;Jong Kyoung Kim;Valentine Svensson;John C. Marioni;John C. Marioni

  • Eleven grand challenges in single-cell data science

    David Lähnemann;David Lähnemann;Johannes Köster;Johannes Köster;Ewa Szczurek;Davis J. McCarthy;Davis J. McCarthy

  • Computational and analytical challenges in single-cell transcriptomics

    Oliver Stegle;Sarah A. Teichmann;John C. Marioni

  • Resolving the fibrotic niche of human liver cirrhosis at single cell level

    P Ramachandran;R Dobie;J R Wilson-Kanamori;E F Dora

  • Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

    Florian Buettner;Kedar N Natarajan;Kedar N Natarajan;F Paolo Casale;Valentina Proserpio;Valentina Proserpio

  • Pooling across cells to normalize single-cell RNA sequencing data with many zero counts

    Aaron T. L. Lun;Karsten Bach;John C. Marioni;John C. Marioni;John C. Marioni

  • Accounting for technical noise in single-cell RNA-seq experiments

    Philip Brennecke;Simon Anders;Jong Kyoung Kim;Aleksandra A Kołodziejczyk;Aleksandra A Kołodziejczyk

  • Multi-Omics Factor Analysis—a framework for unsupervised integration of multi-omics data sets

    Ricard Argelaguet;Britta Velten;Damien Arnol;Sascha Dietrich

  • EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data

    Aaron T. L. Lun;Samantha Riesenfeld;Tallulah Andrews

  • A single-cell molecular map of mouse gastrulation and early organogenesis.

    Blanca Pijuan-Sala;Jonathan A. Griffiths;Carolina Guibentif;Tom W. Hiscock

  • A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis

    Thomas A. Down;Vardhman K. Rakyan;Daniel J. Turner;Paul Flicek

  • Classification of low quality cells from single-cell RNA-seq data

    Tomislav Ilicic;Tomislav Ilicic;Jong Kyoung Kim;Aleksandra A. Kolodziejczyk;Aleksandra A. Kolodziejczyk;Frederik Otzen Bagger;Frederik Otzen Bagger;Frederik Otzen Bagger

  • Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data

    Jacob F. Degner;John C. Marioni;Athma A. Pai;Joseph K. Pickrell

  • scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells.

    Stephen James Clark;Ricardo Argelaguet;Chantriolnt-Andreas Kapourani;Thomas M Stubbs

Frequent Co-Authors

Sarah A. Teichmann
Sarah A. Teichmann University of Cambridge
Oliver Stegle
Oliver Stegle German Cancer Research Center
Wolf Reik
Wolf Reik Babraham Institute
Duncan T. Odom
Duncan T. Odom University of Cambridge
Simon Tavaré
Simon Tavaré Columbia University
Paul Flicek
Paul Flicek The Jackson Laboratory
Berthold Göttgens
Berthold Göttgens University of Cambridge
Benjamin D. Simons
Benjamin D. Simons University of Cambridge
Alvis Brazma
Alvis Brazma European Bioinformatics Institute
Aviv Regev
Aviv Regev Genentech

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