World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
93
Citations
60889
World Ranking
950
National Ranking
469

Medicine

D-Index
96
Citations
62535
World Ranking
9459
National Ranking
4880

Mingyao Li 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 Mingyao Li 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: 269 publications — 70th percentile

70% of scientists in this discipline score the same or lower.

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

Mingyao Li 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 Mingyao Li 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: 93 D-Index — 78th percentile

78% 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

  • 2018 - Fellow of the American Statistical Association (ASA)

Overview

Mingyao Li is affiliated with the University of Pennsylvania in the United States. Their research spans several areas within biochemistry, genetics, molecular biology, and medicine, with a substantial focus on molecular biology, immunology, cancer research, biophysics, and genetics.

Their work is published across various venues, with a notable number of publications in bioRxiv (Cold Spring Harbor Laboratory), UNC Libraries, Cancer Research, Circulation, and Cancer Discovery. These venues reflect a concentration on both foundational biological research and its applications in disease contexts.

Mingyao Li's recent papers include:

  • "SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network" (2021, Nature Methods)
  • "Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human" (2020, Circulation)
  • "Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis" (2020, Nature Communications)
  • "APOE and TREM2 regulate amyloid-responsive microglia in Alzheimer's disease" (2020, Acta Neuropathologica)
  • "Adeno-Associated Virus-Induced Dorsal Root Ganglion Pathology" (2020, Human Gene Therapy)

The major topics addressed in their research involve:

  • Single-cell and spatial transcriptomics
  • Cell image analysis techniques
  • Molecular biology techniques and applications
  • Gene expression and cancer classification
  • Atherosclerosis and cardiovascular diseases
  • Cancer-related molecular mechanisms research
  • Cancer genomics and diagnostics

The scientist's frequent co-authors include:

  • Muredach P. Reilly
  • Jian Hu
  • Kyle Coleman
  • Hanying Yan
  • Edward B. Lee

The research fields Mingyao Li is actively involved in focus on:

  • Biochemistry, genetics, and molecular biology
  • Medicine

An award associated with Mingyao Li is the Fellow of the American Statistical Association (ASA), received in 2018. This recognition points to a professional engagement with the statistical community relevant to their scientific work.

Best Publications

  • ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

    Kai Wang;Mingyao Li;Hakon Hakonarson

  • Biological, clinical and population relevance of 95 loci for blood lipids

    Tanya M. Teslovich;Kiran Musunuru;Albert V. Smith;Andrew C. Edmondson

  • 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

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

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

  • PennCNV: An integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data

    Kai Wang;Mingyao Li;Dexter Hadley;Rui Liu

  • A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants

    Lars G. Fritsche;Wilmar Igl;Jessica N.Cooke Bailey;Felix Grassmann

  • 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

  • Pathway-Based Approaches for Analysis of Genomewide Association Studies

    Kai Wang;Mingyao Li;Maja Bucan

  • Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease

    Jihwan Park;Rojesh Shrestha;Chengxiang Qiu;Ayano Kondo

  • Analysing biological pathways in genome-wide association studies

    Kai Wang;Kai Wang;Mingyao Li;Hakon Hakonarson;Hakon Hakonarson

  • 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

  • Meta-analysis and imputation refines the association of 15q25 with smoking quantity

    Jason Z. Liu;Federica Tozzi;Dawn M. Waterworth;Sreekumar G. Pillai

  • Bulk tissue cell type deconvolution with multi-subject single-cell expression reference

    Xuran Wang;Jihwan Park;Katalin Susztak;Nancy R. Zhang

  • Identification of ADAMTS7 as a novel locus for coronary atherosclerosis and association of ABO with myocardial infarction in the presence of coronary atherosclerosis: two genome-wide association studies

    Muredach P Reilly;Mingyao Li;Jing He;Jane F Ferguson

  • SAVER: gene expression recovery for single-cell RNA sequencing.

    Mo Huang;Jingshu Wang;Eduardo Torre;Hannah Dueck

  • Widespread RNA and DNA sequence differences in the human transcriptome.

    Mingyao Li;Isabel X. Wang;Yun Li;Alan Bruzel

  • A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium

    Nicole Soranzo;Nicole Soranzo;Tim D Spector;Massimo Mangino;Brigitte Kühnel

  • Novel Loci for Adiponectin Levels and Their Influence on Type 2 Diabetes and Metabolic Traits: A Multi-Ethnic Meta-Analysis of 45,891 Individuals

    Z Dastani;Hivert M-F.;Hivert M-F.;N Timpson;Perry Jrb.;Perry Jrb.

  • Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

    Cristian Pattaro;Alexander Teumer;Mathias Gorski;Audrey Y. Chu

  • SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network.

    Jian Hu;Xiangjie Li;Kyle Coleman;Amelia Schroeder

Frequent Co-Authors

Muredach P. Reilly
Muredach P. Reilly Columbia University
Hakon Hakonarson
Hakon Hakonarson Children's Hospital of Philadelphia
Daniel J. Rader
Daniel J. Rader University of Pennsylvania
Struan F.A. Grant
Struan F.A. Grant University of Pennsylvania
Nilesh J. Samani
Nilesh J. Samani University of Leicester
Sekar Kathiresan
Sekar Kathiresan Harvard University
Benjamin F. Voight
Benjamin F. Voight University of Pennsylvania
L. Adrienne Cupples
L. Adrienne Cupples Boston University
Jonathan P. Bradfield
Jonathan P. Bradfield Children's Hospital of Philadelphia
Joseph T. Glessner
Joseph T. Glessner Children's Hospital of Philadelphia

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