World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
96
Citations
152802
World Ranking
847
National Ranking
427

Matthew Stephens 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 Matthew Stephens 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: 178 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Matthew Stephens 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 Matthew Stephens 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: 96 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Overview

Matthew Stephens is a researcher affiliated with the University of Chicago in the United States, specializing in the fields of Biochemistry, Genetics, and Molecular Biology. Their work spans multiple subfields including Molecular Biology, Genetics, Statistics and Probability, Cancer Research, and Artificial Intelligence.

Their research focuses on a range of topics related to genetics and molecular biology. Key topics covered in their publications include:

  • Single-cell and spatial transcriptomics
  • Genetic Associations and Epidemiology
  • Gene expression and cancer classification
  • Genetic Mapping and Diversity in Plants and Animals
  • Genetic and phenotypic traits in livestock
  • RNA modifications and cancer
  • RNA Research and Splicing

Among their recent papers are:

  • A Simple New Approach to Variable Selection in Regression, with Application to Genetic Fine Mapping (2020) published in the Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • The impact of sex on gene expression across human tissues (2020) published in Science
  • Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics (2020) published in Nature Genetics
  • Cell type-specific genetic regulation of gene expression across human tissues (2020) published in Science
  • A Quantitative Proteome Map of the Human Body (2020) published in Cell

Frequent co-authors collaborating with Matthew Stephens include:

  • Peter Carbonetto (31 publications together)
  • Gao Wang (17 publications together)
  • Yuxin Zou (15 publications together)
  • François Aguet (11 publications together)
  • Ayellet V. Segrè (10 publications together)

Matthew Stephens has contributed numerous publications to a range of scientific venues. Among the most frequent are:

  • bioRxiv (Cold Spring Harbor Laboratory) with 12 publications
  • arXiv (Cornell University) with 10 publications
  • Nature Genetics with 6 publications
  • Zenodo (CERN European Organization for Nuclear Research) with 4 publications
  • Genome Biology with 3 publications

Best Publications

  • Inference of population structure using multilocus genotype data

    Jonathan K. Pritchard;Matthew Stephens;Peter Donnelly

  • Inference of Population Structure Using Multilocus Genotype Data: Linked Loci and Correlated Allele Frequencies

    Daniel Falush;Matthew Stephens;Jonathan K. Pritchard

  • A new statistical method for haplotype reconstruction from population data.

    Matthew Stephens;Nicholas J. Smith;Peter Donnelly

  • The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

    Kristin G. Ardlie;David S. Deluca;Ayellet V. Segrè

  • The GTEx Consortium atlas of genetic regulatory effects across human tissues

    F Aguet;AN Barbeira;R Bonazzola;A Brown

  • A haplotype map of the human genome

    John W. Belmont;Andrew Boudreau;Suzanne M. Leal;Paul Hardenbol

  • A second generation human haplotype map of over 3.1 million SNPs

    Kelly A. Frazer;Dennis G. Ballinger;David R. Cox;David A. Hinds

  • Genetic effects on gene expression across human tissues.

    Enhancing GTEx (eGTEx) groups

  • A Comparison of Bayesian Methods for Haplotype Reconstruction from Population Genotype Data

    Matthew Stephens;Peter Donnelly

  • Inferring weak population structure with the assistance of sample group information.

    Melissa J. Hubisz;Daniel Falush;Matthew Stephens;Jonathan K. Pritchard

  • Inference of population structure using multilocus genotype data: dominant markers and null alleles

    Daniel Falush;Matthew Stephens;Jonathan K. Pritchard

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

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

  • Genome-wide efficient mixed-model analysis for association studies.

    Xiang Zhou;Matthew Stephens

  • Genome-wide detection and characterization of positive selection in human populations

    Pardis C. Sabeti;Pardis C. Sabeti;Patrick Varilly;Patrick Varilly;Ben Fry;Jason Lohmueller

  • Association Mapping in Structured Populations

    Jonathan K. Pritchard;Matthew Stephens;Noah A. Rosenberg;Peter Donnelly

  • A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.

    Paul A Scheet;Matthew Stephens

  • Fast and accurate genotype imputation in genome-wide association studies through pre-phasing

    Bryan Howie;Christian Fuchsberger;Matthew Stephens;Jonathan Marchini;Jonathan Marchini

  • Genes mirror geography within Europe.

    John Novembre;Toby Johnson;Toby Johnson;Katarzyna Bryc;Zoltán Kutalik

  • The GTEx Consortium atlas of genetic regulatory effects across human tissues

    François Aguet;Alvaro N Barbeira;Rodrigo Bonazzola;Andrew Brown

  • Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies.

    Daniel Falush;Matthew Stephens;Jonathan K. Pritchard;sebnem ozemri sag

Frequent Co-Authors

Jonathan K. Pritchard
Jonathan K. Pritchard Stanford University
Yoav Gilad
Yoav Gilad University of Chicago
Emmanouil T. Dermitzakis
Emmanouil T. Dermitzakis University of Geneva
Xiaoquan Wen
Xiaoquan Wen University of Michigan–Ann Arbor
John Novembre
John Novembre University of Chicago
Eric R. Gamazon
Eric R. Gamazon Vanderbilt University Medical Center
Tuuli Lappalainen
Tuuli Lappalainen Royal Institute of Technology
Gad Getz
Gad Getz Broad Institute
Peter Donnelly
Peter Donnelly University of Oxford
Stephen B. Montgomery
Stephen B. Montgomery Stanford University

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